Downloaded 399 times
![REFERENCES
1. Bentzen SM, Rosenthal DI, Weymuller E. Increasing toxicity in
non-operative head and neck cancer treatment: Investigations
and interventions. Int J Radiat Oncol Biol Phys 2007;69(2
Suppl):S79–82.
2. Center for Disease Control (USA). Cancer survivorship—
United States, 1971–2001. Available at http://www.cdc.gov/
mmwr/preview/mmwrhtml/mm5324a3.htm. Accessed Decem-
ber 1, 2005.
3. Bentzen SM, Trotti A. Evaluation of early and late toxicities in
chemoradiation trials. J Clin Oncol 2007;25:4096–4103.
4. Trotti A, Bentzen SM. The need for adverse effects reporting
standards in oncology clinical trials. J Clin Oncol 2004;22:
19–22.
5. Papanikolaou PN, Ioannidis JP. Availability of large-scale evi-
dence on specific harms from systematic reviews of randomized
trials. Am J Med 2004;117:582–589.
6. National Cancer Institute. Common Terminology Criteria for
Adverse Events v3.0. Available at http://ctep.cancer.gov/
protocolDevelopment/electronic_applications/docs/ctcaev3.pdf.
Accessed February 9, 2009.
7. Bentzen SM, Dorr W, Anscher MS, et al. Normal tissue effects:
Reporting and analysis. Semin Radiat Oncol 2003;13:189–202.
8. Peeters ST, Lebesque JV, Heemsbergen WD, et al. Localized
volume effects for late rectal and anal toxicity after radiotherapy
for prostate cancer. Int J Radiat Oncol Biol Phys 2006;64:1151–
1161.
9. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue
to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21:
109–122.
10. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue
tolerance data to an analytic function. Int J Radiat Oncol Biol
Phys 1991;21:123–135.
11. Lyman JT. Complication probability as assessed from dose-vol-
ume histograms. Rad Res 1985;104: S-13–S-19.
12. Kutcher GJ, Burman C, Brewster L, et al. Histogram reduction
method for calculating complication probabilities for three-di-
mensional treatment planning evaluations. Int J Radiat Oncol
Biol Phys 1991;21:137–146.
13. Schultheiss TE, Orton CG, Peck RA. Models in radiotherapy:
Volume effects. Med Phys 1983;10:410–415.
14. Withers HR, Taylor JM, Maciejewski B. Treatment volume and
tissue tolerance. Int J Radiat Oncol Biol Phys 1988;14:751–
759.
15. Ka¨llman P, Aagren A, Brahme A. Tumour and normal tissue re-
sponses to fractionated non-uniform dose delivery. Int J Radiat
Biol 1992;62:249–262.
16. Liao ZX, Travis EL, Tucker SL. Damage and morbidity from
pneumonitis after irradiation of partial volumes of mouse lung
[see comments]. Int J Radiat Oncol Biol Phys 1995;32:1359–
1370.
17. Tucker SL, Liao ZX, Travis EL. Estimation of the spatial distri-
bution of target cells for radiation pneumonitis in mouse lung.
Int J Radiat Oncol Biol Phys 1997;38:1055–1066.
18. Konings AW, Faber H, Cotteleer F, et al. Secondary radiation
damage as the main cause for unexpected volume effects: A his-
topathologic study of the parotid gland. Int J Radiat Oncol Biol
Phys 2006;64:98–105.
19. van Luijk P, Faber H, Meertens H, et al. The impact of heart ir-
radiation on dose-volume effects in the rat lung. Int J Radiat On-
col Biol Phys 2007;69:552–559.
20. Hopewell JW, Trott KR. Volume effects in radiobiology as ap-
plied to radiotherapy. Radiother Oncol 2000;56:283–288.
21. Trott KR, Tamou S, Sassy T, et al. The effect of irradiated vol-
ume on the chronic radiation damage of the rat large bowel.
Strahlenther Onkol 1995;171:326–331.
22. Peeters ST, Hoogeman MS, Heemsbergen WD, et al. Rectal
bleeding, fecal incontinence, and high stool frequency after con-
formal radiotherapy for prostate cancer: Normal tissue compli-
cation probability modeling. Int J Radiat Oncol Biol Phys 2006;
66:11–19.
23. Stewart FA, van der Kogel AJ. Volume effects in normal tis-
sues. In: Steel GG, editor. Basic clinical radiobiology. 3rd ed.
London: Arnold; 2002. p. 42–51.
24. van Luijk P, Bijl HP, Konings AW, et al. Data on dose-volume
effects in the rat spinal cord do not support existing NTCP
models. Int J Radiat Oncol Biol Phys 2005;61:892–900.
25. Fiorino C, Fellin G, Rancati T, et al. Clinical and dosimetric
predictors of late rectal syndrome after 3D-CRT for localized
prostate cancer: Preliminary results of a multicenter prospective
study. Int J Radiat Oncol Biol Phys 2008;70:1130–1137.
26. Bentzen SM. Preventing or reducing late side effects of radia-
tion therapy: Radiobiology meets molecular pathology. Nat
Rev Cancer 2006;6:702–813.
27. Dawson LA, Biersack M, Lockwood G, et al. Use of principal
component analysis to evaluate the partial organ tolerance of
normal tissues to radiation. Int J Radiat Oncol Biol Phys
2005;62:829–837.
28. Stavreva N, Niemierko A, Stavrev P, et al. Modelling the dose-
volume response of the spinal cord, based on the idea of damage
to contiguous functional subunits. Int J Radiat Biol 2001;77:
695–702.
29. El Naqa I, Bradley J, Blanco AI, et al. Multivariable modeling
of radiotherapy outcomes, including dose-volume and clinical
factors. Int J Radiat Oncol Biol Phys 2006;64:1275–1286.
30. Gulliford SL, Webb S, Rowbottom CG, et al. Use of artificial
neural networks to predict biological outcomes for patients re-
ceiving radical radiotherapy of the prostate. Radiother Oncol
2004;71:3–12.
31. Chen S, Zhou S, Yin FF, et al. Investigation of the support vec-
tor machine algorithm to predict lung radiation-induced pneu-
monitis. Med Phys 2007;34:3808–3814.
32. Khuntia D, Harris J, Bentzen SM, et al. Increased oral mucositis
after IMRT versus non-IMRT when combined with cetuximab
and cisplatin or docetaxel for head and neck cancer: Preliminary
results of RTOG 0234 [abstract]. Int J Radiat Oncol Biol Phys
2008;72:S33.
33. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of
the risk of postoperative pulmonary complications among
esophageal cancer patients treated with concurrent chemoradio-
therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006;
66:754–761.
34. Tucker SL, Dong L, Cheung R, et al. Comparison of rectal
dose-wall histogram versus dose-volume histogram for model-
ing the incidence of late rectal bleeding after radiotherapy. Int J
Radiat Oncol Biol Phys 2004;60:1589–1601.
35. De Ruysscher D, Dehing C, Bremer RH, et al. Maximal neutro-
penia during chemotherapy and radiotherapy is significantly as-
sociated with the development of acute radiation-induced
dysphagia in lung cancer patients. Ann Oncol 2007;18:909–
916.
36. Bradley JD, Hope A, El N, et al. A nomogram to predict radia-
tion pneumonitis, derived from a combined analysis of RTOG
93-11 and institutional data. Int J Radiat Oncol Biol Phys
2007;69:985–992.
37. Tsougos I, Nilsson P, Theodorou K, et al. NTCP modelling and
pulmonary function tests evaluation for the prediction of radia-
tion induced pneumonitis in non-small-cell lung cancer radio-
therapy. Phys Med Biol 2007;52:1055–1073.
38. Yorke ED, Kutcher GJ, Jackson A, et al. Probability of radia-
tion-induced complications in normal tissues with parallel
S8 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-8-320.jpg)
![steepest part of the response curve. For a patient cohort with
diverse radiosensitivities, the response curve is shallower
(larger m) than for a biologically similar population receiving
the same treatment (14). Various S-shaped functions are used
to fit dose-response data, including the probit function used
by Lyman (below).
To account for the dose heterogeneity typical of parallel
opposed beam irradiation (partial organ uniform irradiation),
Jolles (15) described tissue tolerance as a power law of the
fractional volume irradiated:
DðVirradiatedÞ ¼ D
À
Vreference
Á
À
Vreference
Á
ðVirradiatedÞ
n
; [1]
Here Vreference isthereferencevolumeandVirradiatedistheuni-
formly irradiated volume. D is the corresponding tolerance
doses, representing a chosen level on the dose–response curve,
such as TD50. The parameter n controls the volume effect.
Lyman (16) used this power law model to define the risks
associated with partial organ volume uniform irradiation.
From Eq. 1, decreasing the irradiated volume fraction shifts
the dose–response curve (TD50) to higher doses by a factor
of the irradiated fractional volume raised to the power ‘‘neg-
ative n’’. The effect of different n values on tolerance dose is
shown in Fig. 2.
For example, if the n parameter equals 1, then the TD50 of
irradiation for one half of the volume is expected to increase
by a factor of 2, whereas if the n parameter is 0.5, TD50 for
irradiation of one half the volume would increase by a factor
of the square root of 2.
To generalize this to clinically realistic, heterogeneous
dose distributions, a summary statistic—the generalized
equivalent uniform dose (gEUD)—is often introduced (17,
18). The gEUD is the dose that, if given uniformly to the en-
tire organ, is believed to yield the same complication rate as
the true dose distribution. The gEUD is computed by sum-
ming over all voxels in the organ:
gEUD ¼
1
Nvoxels
ðd
1=n
1 þ d
1=n
2 þ . þ d
1=n
NVoxels
Þ
!n
: [2]
Here NVoxelsis the number of equi-volume voxels, and di is
the dose to the ith
voxel. The gEUD equation is consistent
with the power-law assumption. Together, the gEUD equa-
tion and the Lyman assumptions are often referred to as the
Lyman-Kutcher-Burman (LKB) model (16, 18–20).
Note that some analyses use the parameter n, and some use
the parameter a, equal to 1/n. Both are shown in Fig. 2. When
n is small (and a is large), changes in irradiated volume make
only a modest change in relative tolerance whereas, as n gets
larger (and a gets smaller), the tolerance dose depends
strongly on the irradiated volume fraction.
Serial vs. parallel complication endpoints
There have been efforts to devise mechanistic models that
ascribe the volume dependence of some complications to dis-
ruption of the organ’s functional architecture by RT (21–23).
In so-called parallel complications, subvolumes of the or-
gan function relatively independently. Sufficiently small por-
tions of the organ can be damaged without clinical effect; the
complication is observed only after more than a critical vol-
ume is damaged. Parallel complications have large volume
effects, and for this reason they are often likened to LKB
models with n z 1 (as is found in analyses of liver, lung,
and kidney complications). More detailed models exist, in-
cluding models employing the concept of a functional re-
serve, representing a hypothesized fraction of organ
function that can be lost before a complication is likely (23).
In contrast, serial complications occur when even a small
portion of the organ suffers damage. Here, n is small (e.g.,
z 0.1 for late rectal bleeding). Serial complications are
most affected by the hottest portion of the DVH. More de-
tailed models exist for this type of endpoint as well, including
models that make explicit the size of small subunits, all of
which need to be preserved to avoid a complication (23).
Figure 3 shows how different parts of an example DVH
contributetotheoverall gEUDas nvaries. Notethat: (a) thelow-
est value of n results in the highest gEUD corresponding to the
hottest point on the DVH (more appropriate for serial-like end-
points), and (b) the lower dose bins contribute more when n ap-
proaches 1 (more appropriate for parallel-like endpoints).
Multimetric models
Clinicians frequently estimate complication risk via a sin-
gle DVH point based on a statistically significant dose/vol-
ume cut-point reported in one or more studies. An example
is the often-used V20 (percentage of lung receiving 20
Gy) as a predictor of radiation pneumonitis (24). However,
such single ‘‘volume threshold’’ rules are overly simple,
and often easily manipulated by the treatment planner, or
by the optimization software. Optimizing based on such
a threshold may introduce a ‘kink’ in one part of the DVH
to achieve a desired ‘‘threshold value,’’ while inadequately
constraining the rest. An infinite number of very different
dose distributions (some likely with very different risks)
can have the same V20. The same is true for any
Fig. 2. As the (idealized) irradiated organ fraction decreases, the tol-
erance dose (D) increases, more so for larger values of n or smaller
values of a (=1/n). VReferencerepresents the reference volume (usually
the full organ volume), and VIrradiated represents the volume irradiated.
Use of NTCP models in the clinic d L. B. MARKS et al. S13](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-13-320.jpg)
![3. CHALLENGES DEFINING VOLUMES
There is little disagreement regarding image segmentation
of the entire brain, and little intra- or interfraction movement
occurs. However, segmenting the brain subregions is
challenging (e.g., the superior boundary of the brain stem).
Currently the utility of subregion definition is unclear.
4. REVIEW OF DOSE–VOLUME DATA
Radiation necrosis
For radiosurgery, the incidence of necrosis depends on the
dose, volume, and region irradiated (1–10) (Table 1 and
Fig. 1). The Radiation Therapy Oncology Group conducted
a dose-escalation study that sought to define the maximal
dose for targets of different sizes; all subjects had previously
undergone whole brain irradiation. The maximal tolerated
dose for targets 31–40 mm in diameter was 15 Gy, and for
targets 21–30 mm in diameter, it was 18 Gy. For targets
20 mm, the maximal tolerated dose was 24 Gy (11). The
volume of brain receiving $12 Gy has been shown to corre-
late with both the incidence of radiation necrosis and asymp-
tomatic radiologic changes (Table 1).
The large variation in absolute complication rates among
studies (Fig. 1) is difficult to comprehend, but it might relate
to differences in the definitions of the volume and toxicity,
the avoidance of critical structures, and the type and length
of clinical follow-up.
For fractionated RT, the relationship between the radiation
dose and radiation necrosis for partial brain irradiation is pre-
sented in Table 2 (12–19) and Fig. 2, segregated by the frac-
tionation scheme. Different fractionation schemes were
compared using the biologically effective dose (BED) (20),
with an a/b ratio of 3. For standard fractionation, a dose–re-
sponse relationship exists, such that an incidence of side ef-
fects of 5% and 10% occur at a BED of 120 Gy (range,
100–140) and 150 Gy (range, 140–170), respectively (corre-
sponding to 72 Gy [range, 60–84] and 90 Gy [range, 84–102]
in 2-Gy fractions). For twice-daily fractionation, a steep in-
crease in toxicity appears to occur when the BED is 80
Gy. For daily large fraction sizes (2.5 Gy), the incidence
Table 1. Dose–volume predictors of radiation necrosis after stereotactic radiosurgery
Reference Diagnosis Technique
Patients
(n)
Dmin*
(Gy)
RN
incidence
(%)
Subgroup
(cm3
)
RN incidence
(%)
Primary
toxicity
predictor
Other risk
factors
1 AVM GK 823 ? 5 Average dose
in 20 cm3
2 Mixed LINAC 133 15.0 (7.0–25.0) 12.8 V10: 10 vs. 10 0 vs. 23.7 V10 Location
3 AVM GK 307 20.9 (12–30) 10.7 V12 Location
4 AVM LINAC 73 16 (10–22) 14 Tx volume:
1
1–3.9
4–13.9
14
0
15
14
27
Treatment
volume
Dose, previous
brain insult
5 Mixed GK 243 20 (10–30) 7 V10 Repeated
radiosurgery,
Glioma
6 Mixed GK 749 18 (16–19)y
? Prescription
volume:
0.05–0.66
0.67–3
3.1–8.6
8.7–95.1
0
3
7
9
Prescription
volume
7 AVM Proton
beam
1250 10.5 (4–65) 4.1 Dose and
volume
combined
Older age,
location
8 AVM ? 269 ? 4.7 V12
9 Brain
metastases
GK 137 16 (12–25) 11.4 Tx volume:
2
2
3.7
16
Volume
10 Tumor GK 129 17.3 (11–25) 30 V12:
0–5
5–10
10–15
15
23
20
54
57
V12 Location,
previous
WBRT, male
Abbreviations: Dmin = minimal dose; RN = radiation necrosis; AVM = arteriovenous malformation; GK = gamma knife; LINAC = linear
accelerator teletherapy machine; V10 = percentage of volume receiving $10 Gy; V12 = percentage of volume receiving $ 12 Gy; Tx = treat-
ment; WBRT = whole brain radiotherapy.
* Data presented as mean, with range in parentheses, unless otherwise noted.
y
Range refers to 25th to 75th quartile.
Radiation dose–volume effects in brain d Y. R. LAWRENCE et al. S21](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-21-320.jpg)
![For radiosurgery, a variety of models have been suggested.
All are highly simplified and ignore many relevant variables,
and none has been adequately validated.
7. SPECIAL SITUATIONS
Re-irradiation is frequently performed in the brain. A
meta-analysis of brain re-irradiation (interval between
courses, 3–55 months) found no cases of necrosis when the
total radiation dose was 100 Gy (normalized to 2 Gy/frac-
tion; a/b ratio, 2) (59).
Unlike other settings, in primary central nervous system
lymphoma, RT (to z40 Gy) has been associated with cogni-
tive decline, especially in those 60 years old (60, 61). The
heightened sensitivity of this population to irradiation might
be explained by the tumor’s highly diffuse, angiocentric
growth pattern and that most patients receive high-dose
methotrexate, a potent neurotoxin. As a result, upfront full-
dose RT is now often avoided in elderly patients with this dis-
ease. A lower radiation dose of 23.4 Gy might be safe even in
older patients (62).
8. RECOMMENDED DOSE–VOLUME LIMITS
The constraints presented in the following paragraphs are
the best estimates determined from the available data; how-
ever, high-level evidence is lacking. The constraints should
be used with appropriate caution and interpreted within the
clinical context.
Fractionated RT to partial brain
For standard fractionation, a 5% and 10% risk of symp-
tomatic radiation necrosis is predicted to occur at a BED of
120 Gy (range, 100–140) and 150 Gy (range, 140–170), re-
spectively (corresponding to 72 Gy [range, 60–84] and 90
Gy [range, 84–102] in 2-Gy fractions). The brain is especially
sensitive to fraction sizes 2 Gy and, surprisingly, twice-
daily RT.
Fig. 2. Relationship between biologically effective dose (BED) and radiation necrosis after fractionated radiotherapy. Fit
was done using nonlinear least-squares algorithm using Matlab software (The MathWorks, Natick, MA). Nonlinear func-
tion chosen was probit model (similar functional form to Lyman model). Dotted lines represent 95% confidence levels;
each dot represents data from specific study (Table 2), n = patient numbers as shown. (a) Fraction size 2.5 Gy; (b) fraction
size $2.5 Gy (data too scattered to allow plotting of ‘‘best-fit’’ line); and (c) twice-daily radiotherapy.
S24 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-24-320.jpg)
![gradients. Image segmentation uncertainties and distinctions
between the mean dose vs. Dmax, could be particularly
relevant for SRS. Tishler et al. (30) reviewed optic nerve
injury from the early radiosurgery experience. They proposed
8 Gy as a limit for optic tolerance from their analysis, which
cited the lowest dose for optic neuropathy as 9.7 Gy. Stafford
et al. (31) reported that optic neuropathy occurred in 4 of 215
patients receiving a median dose of 10 Gy to the optic chi-
asm, with chiasm/optic nerve Dmax of 0.4–16 Gy. The risk
of RION was estimated at 1.7%, 1.8%, 0%, and 6.9% for
a Dmax of 8, 8–10, 10–12, and 12 Gy, respectively. Of
the 4 patients, 3 had undergone previous external beam RT
with doses in the range of 45–58.8 Gy. Pollock et al. (32)
observed no cases of RION in 62 patients undergoing gamma
knife SRS for nonfunctioning pituitary adenomas. The
median Dmax to the optic apparatus was 9.5 Æ 1.7 Gy.
They reported using 12 Gy as an optic structure dose con-
straint. Leber et al. (33) analyzed optic neuropathy risks in
50 patients 24–60 months (median follow-up, 40 months)
after gamma knife SRS for benign skull base tumors. They
reported optic neuropathy risks of 0% with 10 Gy, 27%
with 10 to 15 Gy, and 78% with $15 Gy, respectively.
5. FACTORS AFFECTING RISK
Parsons et al. (4) reported an increased risk of RION with
increasing age. None of the 38 patients in the 20–50-year
range developed RION, even though the reported optic nerve
doses were 60 Gy for 58% and 70 Gy for 26% of patients.
In contrast, RION was noted in older patients. For patients
with doses 60 Gy, the incidence was 26% vs. 56% for the
50–70 vs. 70-year age groups. Similarly, Bhandare et al.
(20) noted RION in 0%, 4%, 13%, and 14% of patients
aged 20, 20–50, 51–70, and 70 years, respectively.
Data on other clinical factors such as chemotherapy, diabe-
tes mellitus, and hypertension have been inconsistent. Mini-
mal data are available on re-irradiation of the optic apparatus
and the effect of the interval between courses on RT
tolerance. Flickinger et al. (34) found that 1 of 10 patients
studied after repeat irradiation developed RION (they had
received an initial 40 Gy, with a 7.5-year interval, and then
received 46 Gy; both at 2 Gy/fraction).
6. MATHEMATICAL/BIOLOGIC MODELS
The original Lyman-Kutcher-Burman normal tissue
complication probability volumetric modeling parameters
were estimated (35) as TD50= 65 Gy, n = 0.25, and m =
0.14. The dose–response data from Jiang et al. (15) (z1.5–
2.2 Gy/fraction) suggested TD50 z72–75 Gy. Martel et al.
(14) and Brizel et al. (36) estimated TD50 at 72 and 70 Gy,
respectively. The Parsons’ dose response extrapolated
TD50 to 70 Gy.
Isoeffect models have been used to estimate the threshold
Dmax values. In linear quadratic modeling, the a/b can be
very small. Jiang et al. (15) estimated the a/b at 1.6 for the
optic nerves, but the lower 95% confidence interval value
was À7. For the optic chiasm, they found an a/b of 0. Flick-
inger et al. (37) also found an a/b of 0 in their modeling.
The inadequacies of the linear-quadratic model for SRS
have recently been discussed by Kirkpatrick et al. (38). Al-
ternative biologically effective dose models that incorporate
the number of fractions (Optic Ret) or number of fractions
and overall treatment time (Neuret) have been explored.
Flickinger et al. (39) examined complications vs. the normal-
ized total dose (NTD) calculated from the Neuret formula
(NTD 1.8 [Neuret]). This formulation is designed to repre-
sent the equivalent dose delivered in 1.8-Gy fractions, 5 d/
wk. They found the actuarial risk of optic neuropathy was
Table 1. Selected studies documenting dose to optic structures without radiation-induced optic neuropathy
Investigator(ref)/
#Patients Disease/technique
Prescription dose
(range)/fraction (range) Dmax Mean/median dose
Daly (17)/36 Paranasal sinus, nasal cavity/photon
IMRT
70 (63–72) Gy
CTV 1.8 Gy/fx
GTV 2.12 Gy/fx
Chiasm 52.3 Æ 5.1 Gy
Nerve 59.1 Æ 7.7 Gy
Chiasm 39.5 Æ 4.2 Gy
Nerve 48.1 Æ 3.7 Gy
Hoppe (21)/85 Paranasal sinus, nasal
cavity/photon mixed
63 (50–70) Gy
(1.8–2.0) Gy/fx
Chiasm 52 (4–105) Gy
Nerve 54 (4–105) Gy
Chiasm 45 (5–51) Gy
Nerve 35 (6–81) Gy
Weber (27)/29 Chordoma, chondrosarcoma/proton C: 74 (67–74) CGE
(1.8–2.0) CGE/fx
CS:68(64–74) CGE
(1.8–2.0) CGE/fx
Chiasm 58.1
(12.2–68.6) CGE
Nerve 51.7
(9.0 –74.9) CGE
Chiasm 47.0 (3.9–60.7) CGE
Nerve 16.5 (0.6–60.2) CGE
Nishimura (28)/14 Olfactory neuroblastoma/proton 65 CGE
2.5 CGE/fx
67.7 (35.1–68.9) CGE 27.3 (6.5–53.3) CGE
Lee (47)/11 Craniopharyngioma/CyberKnife 25 (18–38) Gy
5 (3.8–6.7) Gy/fx
5 Gy/fx NR
Pollock (32)/62 Nonfunctioning pituitary
adenoma/gamma knife
16.3 (11–20) Gy
Single fraction
9.5 Gy Æ 1.7 (5.0–12.6) Gy NR
Abbreviations: Dmax = maximum dose; IMRT = intensity-modulated radiotherapy; CTV = clinical target volume; GTV = gross tumor
volume; fx = fraction; CGE = Cobalt Gray Equivalent; NR = not reported; RION = radiation-induced optic neuropathy.
Average reported mean follow-up was 38 months (range, 15–60) for all studies not reporting RION.
Some of data were estimated from text, tables, and figures of the published articles.
S30 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-30-320.jpg)
![31. Eichhorn HJ, Lessel A, Rotte KH. Einfuss verschiedener
Bestrahlungsrhythmen auf Tumor-und Normalgewebe in
vivo. Strahlentheraphie 1972;146:614–629.
32. Scruggs H, El-Mahdi A, Marks RD, Jr., et al. The results of
split-course radiation therapy in cancer of the lung. Am J Roent-
genol Radium Ther Nucl Med 1974;121:754–760.
33. Macbeth FR, Bolger JJ, Hopwood P, et al. Randomized trial of
palliative two-fraction versus more intensive 13-fraction radio-
therapy for patients with inoperable non-small cell lung cancer
and good performance status. Medical Research Council Lung
Cancer Working Party [see comment]. Clin Oncol (R Coll
Radiol) 1996;8:167–175.
34. Macbeth FR, Wheldon TE, Girling DJ, et al. Radiation myelop-
athy: Estimates of risk in 1048 patients in three randomized
trials of palliative radiotherapy for non-small cell lung cancer.
The Medical Research Council Lung Cancer Working Party.
Clin Oncol (R Coll Radiol) 1996;8:176–181.
35. Nieder C, Grosu AL, Andratschke NH, et al. Proposal of human
spinal cord reirradiation dose based on collection of data from
40 patients. Int J Radiat Oncol Biol Phys 2005;61:851–855.
36. Wright JL, Lovelock DM, Bilsky MH, et al. Clinical outcomes
after reirradiation of paraspinal tumors. Am J Clin Oncol 2006;
29:495–502.
37. Langendijk JA, Kasperts N, Leemans CR, et al. A phase II study
of primary reirradiation in squamous cell carcinoma of head and
neck. Radiother Oncol 2006;78:306–312.
38. Grosu AL, Andratschke N, Nieder C, et al. Retreatment of the
spinal cord with palliative radiotherapy. Int J Radiat Oncol
Biol Phys 2002;52:1288–1292.
39. Nieder C, Grosu AL, Andratschke NH, et al. Update of human
spinal cord reirradiation tolerance based on additional data
from 38 patients. Int J Radiat Oncol Biol Phys 2006;66:
1446–1449.
40. Schiff D, Shaw EG, Cascino TL. Outcome after spinal reirradia-
tion for malignant epidural spinal cord compression. Ann Neu-
rol 1995;37:583–5899.
41. Ryu S, Gorty S, Kazee AM, et al. Reirradiation of human cer-
vical spinal cord. Am J Clin Oncol 2000;23:29–31.
42. Kuo JV, Cabebe E, Al-Ghazi M, et al. Intensity-modulated
radiation therapy for the spine at the University of California,
Irvine. Med Dosim 2002;27:137–145.
43. Bauman GS, Sneed PK, Wara WM, et al. Reirradiation of pri-
mary CNS tumors. Int J Radiat Oncol Biol Phys 1996;36:
433–441.
44. Sminia P, Oldenburger F, Slotman BJ, et al. Re-irradiation of
the human spinal cord. Strahlenther Onkol 2002;178:
453–456.
45. Magrini SM, Biti GP, de Scisciolo G, et al. Neurological dam-
age in patients irradiated twice on the spinal cord: A morpho-
logic and electrophysiological study. Radiother Oncol 1990;
17:209–218.
46. Rades D, Stalpers LJA, Veninga T, et al. Evaluation of five ra-
diation schedules and prognostic factors for metastatic spinal
cord compression. J Clin Oncol 2005;23:3366–3375.
47. Jackson MA, Ball DL. Palliative retreatment of locally recurrent
lung cancer after radical radiotherapy. Med J Aust 1987;147:
391–394.
48. Wong CS, Van Dyk J, Milosevic M, et al. Radiation myelopa-
thy following single courses of radiotherapy and retreatment. Int
J Radiat Oncol Biol Phys 1994;30:575–581.
49. Gwak H-S, Yoo H-J, Youn S-M, et al. Hypofractionated stereo-
tactic radiotherapy for skull base and upper cervical chordoma
and chondrosarcoma: Preliminary results. Stereotact Funct
Neurosurg 2005;83:233–243.
50. Gibbs IC, Patil I, Gerszten PC, et al. Delayed radiation-induced
myelopathy after spinal radiosurgery. Neurosurg 2009;64(2
Suppl):A67–A72.
51. Benzil DL, Saboori M, Mogilner AY, et al. Safety and efficacy
of stereotactic radiosurgery for tumors of the spine. J Neurosurg
2004;101(Suppl 3):413–418.
52. Sahgal A, Choua D, Amesa C, et al. Proximity of spinous/para-
spinous radiosurgery metastatic targets to the spinal cord versus
risk of local failure. Int J Radiat Oncol Biol Phys 2007;69:S243.
53. Sahgal A, Chou D, Ames C, et al. Image-guided robotic stereo-
tactic body radiotherapy for benign spinal tumors: The Univer-
sity of California San Francisco preliminary experience.
Technol Cancer Res Treat 2007;6:595–604.
54. Chang EL, Shiu AS, Mendel E, et al. Phase I/II study of stereo-
tactic body radiotherapy for spinal metastasis and its pattern of
failure. J Neurosurg Spine 2007;7:151–160.
55. Gerszten PC, Burton SA, Welch WC, et al. Single-fraction
radiosurgery for the treatment of spinal breast metastases. Can-
cer 2005;104:2244–2254.
56. Nelson JW, Yoo DS, Wang Z, et al. Stereotactic body radiother-
apy for lesions of the spine and paraspinal regions. Int J Radiat
Oncol Biol Phys 2009;73:1369–1375.
57. Ruifrok AC, Kleiboer BJ, van der Kogel AJ. Radiation toler-
ance of the immature rat spinal cord. Radiother Oncol 1992;
23:249–256.
58. Ruifrok AC, Kleiboer BJ, van der Kogel AJ. Radiation toler-
ance and fractionation sensitivity of the developing rat cervical
spinal cord. Int J Radiat Oncol Biol Phys 1992;24:505–510.
59. Ruifrok AC, Stephens LC, van der Kogel AJ. Radiation
response of the rat cervical spinal cord after irradiation at differ-
ent ages: Tolerance, latency and pathology. Int J Radiat Oncol
Biol Phys 1994;29:73–79.
60. Friedman DL, Constine LS. Late effects of cancer treatment. In:
Halperin EC, Constine LS, Tarbell NJ, Kun LE, editors. Pediat-
ric radiation oncology. Philadelphia: Lippincott, Williams
Wilkins; 2005.
61. Ruifrok AC, van der Kogel AJ. The effect of intraspinal cyto-
sine arabinoside on the re-irradiation tolerance of the cervical
spinal cord of young and adult rats. Eur J Cancer 1993;29A:
1766–1770.
62. Gre´goire V, Ruifrok AC, Price RE, et al. Effect of intra-perito-
neal fludarabine on rat spinal cord tolerance to fractionated irra-
diation. Radiother Oncol 1995;36:50–55.
63. Ruckdeschel JC, Baxter DH, McKneally MF, et al. Sequential
radiotherapy and Adriamycin in the management of broncho-
genic carcinoma: The question of additive toxicity. Int J Radiat
Oncol Biol Phys 1979;5:1323–1328.
64. Bloss JD, DiSaia PJ, Mannel RS, et al. Radiation myelitis:
A complication of concurrent cisplatin and 5-fluorouracil
chemotherapy with extended field radiotherapy for carcinoma
of the uterine cervix. Gynecol Oncol 1991;43:305–308.
65. Chao MW, Wirth A, Ryan G, et al. Radiation myelopathy
following transplantation and radiotherapy for non-Hodgkin’s
lymphoma. Int J Radiat Oncol Biol Phys 1998;41:1057–1061.
66. Seddon BM, Cassoni AM, Galloway MJ, et al. Fatal radiation
myelopathy after high-dose busulfan and melphalan chemother-
apy and radiotherapy for Ewing’s sarcoma: A review of the
literature and implications for practice. Clin Oncol (R Coll Ra-
diol) 2005;17:385–390.
67. Lee YY, Nauert C, Glass JP. Treatment-related white matter
changes in cancer patients. Cancer 1986;57:1473–1482.
68. Schultheiss TE, Kun LE, Ang KK, et al. Radiation response of
the central nervous system. Int J Radiat Oncol Biol Phys 1995;
31:1093–1112.
69. Schultheiss TE, Thames HD, Peters LJ, et al. Effect of latency
on calculated complication rates. Int J Radiat Oncol Biol Phys
1986;12:1861–1865.
70. Kirkpatrick JP, Meyer JJ, Marks LB. The linear-quadratic
model is inappropriate to model high-dose per fraction effects.
Semin Radiat Oncol 2008;18:240–243.
Radiation dose-volume effects in the spinal cord d J. P. KIRKPATRICK et al. S49](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-49-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Central Nervous System: Ear
RADIATION THERAPY AND HEARING LOSS
NIRANJAN BHANDARE, M.S.,* ANDREW JACKSON, PH.D.,y
AVRAHAM EISBRUCH, M.D.,z
CHARLIE C. PAN, M.D.,z
JOHN C. FLICKINGER, M.D.,x
PATRICK ANTONELLI, M.D.,jj
AND WILLIAM M. MENDENHALL, M.D.*
From the *Departments of Radiation Oncology and jj
Otolaryngology, University of Florida College of Medicine, Gainesville, Florida;
y
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY; z
Department of Radiation Oncology,
University of Michigan; and x
Department of Radiation Oncology, University of Pittsburgh Medical Center
A review of literature on the development of sensorineural hearing loss after high-dose radiation therapy for head-
and-neck tumors and stereotactic radiosurgery or fractionated stereotactic radiotherapy for the treatment of
vestibular schwannoma is presented. Because of the small volume of the cochlea a dose–volume analysis is not fea-
sible. Instead, the current literature on the effect of the mean dose received by the cochlea and other treatment- and
patient-related factors on outcome are evaluated. Based on the data, a specific threshold dose to cochlea for sen-
sorineural hearing loss cannot be determined; therefore, dose–prescription limits are suggested. A standard for
evaluating radiation therapy–associated ototoxicity as well as a detailed approach for scoring toxicity is
presented. Ó 2010 Elsevier Inc.
Radiotherapy, Sensorineural hearing loss, Ototoxicity, Auditory, Ear, QUANTEC.
1. CLINICAL SIGNIFICANCE
Radiation therapy (RT) may damage the cochlea and/or acous-
tic nerve, leading to sensorineural hearing loss (SNHL) (1–4),
with resultant long-lasting compromise in the quality of life.
This report focuses on RT-induced SNHL in adults who
have received fractionated RT, stereotactic radiosurgery
(SRS), and fractionated stereotactic RT (FSRT) for head-
and-neck cancers and vestibular schwannomas (VS).
2. ENDPOINTS
SNHL is traditionally defined as a clinically significant in-
crease in bone conduction threshold (BCT) at the key human
speech frequencies (0.5–4.0 kHz), as seen in pure-tone audi-
ometry. However, reports of SNHL after fractionated RT
vary in terms of: (a) the frequencies evaluated (e.g., 2 or
4 kHz alone (5,6) and/or pure tone average [PTA] of frequen-
cies between 0.5–3.0 kHz) (7–9); (b) the control/standard used
for comparison (e.g., pre-RT BCT of same ear (10) or post-RT
BCT of the contralateral ear (5), or age-specific standard (4));
and (c) the change in BCT (DBCT) that is defined as clinically
significant (e.g., 20 dB (5, 6), 15 dB (7, 8), 10 dB (5)). The de-
gree ofhearing lossafterRTforhead-and-neckcancerisworse
at higher frequencies, as presented in Figures 1a–c (5–8, 10–
12). Although early changes in hearing can be reversible, per-
sistent hearing loss (HL) continues to increase with time (11).
Selected studies on SNHL after head-and-neck radiation ther-
apy are shown in Table 1.
Hearing status after SRS for VS is evaluated using the
Gardner-Robertson hearing grade (GRHG) scale, which in-
cludes both PTA and speech discrimination scores (SDS)
(13). HL after SRS for VS is commonly presented as pre-
RT to post-RT variation in GRHG as: (a) pretreatment hearing
preservation (HP) in terms of (i) serviceable hearing (SH), as
hearing that is useful with or without a hearing aid, or (ii) mea-
surable hearing (MH), as any hearing with detectable audio-
metric responses; and (b) improvement or loss in hearing
expressed as change in GRHG. Selected studies on the treat-
ment of vestibular schwannomas are shown in Table 2.
Acute SNHL has been reported after SRS (14), but not
after fractionated RT. Hearing impairment has been reported
within 3 to 24 months after single-fraction SRS (13, 15), with
a median time to onset of 4 months (15, 16). Although it can
occur as early as 3 months after completing fractionated RT,
the median latency is 1.5–2.0 years (10, 11).
3. CHALLENGES DEFINING VOLUMES
Computed tomography (CT)-magnetic resonance imaging
fusion is helpful in defining the inner ear. Its small size and
location (embedded deep in the temporal bone) make it chal-
lenging to delineate on CT scans and requires the appropriate
bone window, level, and image thickness (preferably
Reprint requests to: William M. Mendenhall, M.D., PO Box
100385, Gainesville, FL 32610. Tel: (352) 265-0287; Fax: (352)
265-7045; E-mail: mendwm@shands.ufl.edu
Conflict of interest: None.
Received March 18, 2009, and in revised form April 23, 2009.
Accepted for publication April 27, 2009.
S50
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S50–S57, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.04.096](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-50-320.jpg)
![5. FACTORS AFFECTING RISK
Non-dose–volume factors could affect the risk of xerosto-
mia. Nondosimetric patient factors (e.g., gender and age) and
the use of chemotherapy have typically not correlated with
xerostomia risk. However, pretreatment salivary function
and medications affecting salivary function can affect the
risk of xerostomia.
6. MATHEMATICAL MODELING
Several investigators have tried to fit dose, volume, and
complication risk data to a sigmoidal response function.
This mirrors the local function curve derived from imaging
measurements (Fig. 4). The Lyman-Kutcher-Burman volume
effect parameter, n, is typically set to 1, although the best-fit
value of n has sometimes been reported to be either less (6) or
greater (14) than 1. Chao et al. (4) fit stimulated whole mouth
salivary function to a sum of two exponentials, representing
contributions from both glands. Single gland function at 6
months was approximately given by exp(À0.054 Â mean
gland dose) (2). This model neglects the known submandib-
ular gland contributions, however, which might cause it to
overestimate the reduction at low mean doses (mean dose,
15 Gy). More complicated models have shown only minor
improvements (6). Consistent with this, patient-specific flow
predictions using mean gland doses have significant uncer-
tainties (21). The function of the parotid glands should be
modeled separately, because the glands seem to respond in-
dependently (Fig. 1).
Fraction size effects on salivary function
Detailed studies addressing fractionation have been lim-
ited, with conflicting results. In rats, Franzen et al. (22) esti-
mated the a/b ratio for early effects to be high, z20 Gy. The
clinical Continuous hyperfractionated accelerated radiother-
apy (CHART) experience has suggested that hyperfractiona-
tion has a protective effect on late function, consistent with
a low a/b ratio (23). However, in rhesus monkeys, acini
cell number reduction at 16 weeks after RT was worse for
CHART hyperfractionation than for conventional fraction-
ation to a similar dose (24), consistent with a relatively
high a/b ratio. Thus, it might be that acute effects have
a high a/b ratio and late damage (dependent on stem cell
recovery [25]) has a low a/b ratio.
Possible intragland sensitivity variations
Function and response are typically assumed to be uniform
throughout the parotid gland. However, this might not be ac-
curate. In rats (26), RT to the cranial half produced more
functional loss than RT to the caudal half. This finding relates
to the specific anatomy of the rat parotid gland, in which the
saliva from the caudal part flows through the cranial part and
is therefore affected by damage to the cranial ductules.
Although human parotid gland anatomy is more complex,
Fig. 1. Stimulated whole mouth salivary measurements vs. mean parotid gland dose. Summary of Washington University
stimulated salivary results at 6 and 12 months of follow-up. Data showed that when either gland was spared (20 Gy mean
dose), ratio of post-radiotherapy (RT) to pre-RT flow is usually 0.25. Note, if either gland was highly spared (10–15 Gy),
resulting salivary function will usually be high, regardless of irradiation level of the other parotid gland (data originally
presented in Blanco et al. [6], but redrawn here).
Fig. 2. Mean percentage of reduction in stimulated salivary flow
rate vs. mean parotid gland dose for different follow-up durations
(8, 10, 12, 14, 15, 16). Follow-up durations of 1, 6, and 12 months
represent ranges of 1–1.5, 6–7, and 12 months, respectively. Linear
fits of data from different follow-up intervals shown. Dose–response
effect appears present at all times, with shift of data to right with
time, suggesting functional repair or regeneration.
S60 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-60-320.jpg)
![it is possible that similar phenomena occur in humans, and
this might be the cause of some of the variation in the
reported mean dose TD50 values.
7. SPECIAL SITUATIONS
Submandibular gland sparing can reduce the risk of both
stimulated and unstimulated xerostomia (27). Jellema et al.
(28) reported that the mean dose to the parotid glands and
the mean dose to the submandibular glands were both se-
lected on multivariate analysis for patient-reported xerosto-
mia. A hypothetical patient receiving a mean dose of 30 Gy
to the parotid glands was estimated to have the risk of xero-
stomia decrease by z20% if the mean dose to the subman-
dibular gland was 0 Gy compared with 50 Gy. Similarly,
surgical transfer of the submandibular gland out of the
high-dose radiation field was reported to spare z30% of pre-
treatment stimulated salivary function (29). Regarding the
dose response, Murdoch-Kinch et al. (30) reported that sub-
mandibular gland-stimulated salivary function decreased sig-
nificantly after a mean dose of 40 Gy. It is, therefore, not
clear whether the parotid and submandibular glands have
the same dose–volume response characteristics.
The mean dose to the oral cavity (containing minor sali-
vary glands) has been found to be an independent risk factor
in some data sets (7) but not others (25), probably because of
technique differences.
The chemical modifier amifostine, is a radioprotector and
has recently been shown to reduce the rates of xerostomia.
Although quantitative data are sparse, Munter et al. (31)
noted that amifostine significantly increased the combined
parotid and submandibular gland tolerance dose for scinti-
graphically measured clearance dysfunction, by a mean
dose of approximately 9 Gy.
8. RECOMMENDED DOSE–VOLUME LIMITS
Sparing at least one parotid gland appears to eliminate xe-
rostomia (Fig. 1), and sparing at least one submandibular
gland also appears to reduce xerostomia risk and increase
stimulated and unstimulated salivary function. Some of the
reduction in stimulated salivary function in Fig. 1 also re-
sulted from consistently irradiated submandibular glands. Se-
vere xerostomia (long-term salivary function 25% of
baseline) can usually be avoided if at least one parotid gland
has been spared to a mean dose of less than z20 Gy or if both
glands have been spared to a mean dose of less than z25 Gy.
For complex partial volume RT patterns (e.g., intensity-
modulated RT), the mean dose to each parotid gland should
be kept as low as possible, consistent with the desired clinical
Fig. 4. Population-based dose vs. local function response (salivary
function at rest) from imaging study by Buus et al. (2). Local func-
tional decline in metabolic clearance of parotid salivary glands vs.
local dose, according to voxel-by-voxel estimated time-activity
curves of intravenously injected C11-methionine. Data points
from 12 patients shown, along with best-fit curve and 95% confi-
dence intervals of curve fit. Individual gland curves reported by
Buus et al. (2) deviated significantly from this population average
curve (reproduced from Buus et al. [2], used with permission.)
This population curve demonstrated functional decline in salivary
function even at low doses.
Fig. 3. Reported tissue dose required for 50% response for loss of
stimulated saliva flow after radiotherapy (RT) (2, 6, 10, 14–20)
for single parotid gland. Endpoint considered in reports was salivary
flow reduction to 25% (black symbols) or 50% (gray symbols) of
pretreatment value. Tissue dose required for 50% response defined
as dose at which 50% of patients developed complications. Error
bars (if shown) indicate 95% confidence intervals; refer to original
publications for exact meaning. 95% Confidence intervals for stud-
ies by Munter et al. (19, 20) were estimated from standard errors
provided. Lines connect points from data sets with measurements
taken at more than one interval after radiotherapy. Most studies
used salivary gland scintigraphy. Some studies measured physical
production (ipsilateral salivary flow or whole salivary flow; marked
with ‘‘I’’ or ‘‘W’’, respectively). Data from Buus et al. (2) (which
did not include preradiotherapy assessments) derived by comparing
different regions of parotid gland that had received different doses.
Each label gives number of patients. Note, most imaging-derived
endpoint data had greater values for tissue dose required for 50% re-
sponse (TD50) than measured salivary data. CRT = conformal ra-
diotherapy; IMRT = intensity-modulated radiotherapy.
Radiation-induced xerostomia d J. O. DEASY et al. S61](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-61-320.jpg)
![target volume coverage. A lower mean dose to the parotid
gland usually results in better function, even for relatively
low mean doses (10 Gy). Similarly, the mean dose to the
parotid gland should still be minimized, consistent with ade-
quate target coverage, even if one or both cannot be kept to
a threshold of 20 or 25 Gy. Published variations in re-
sponse among different patient cohorts were probably related
to the lack of an accurate model that correctly includes the ef-
fects of multiple salivary glands and intragland sensitivity
variations. When it can be deemed oncologically safe, sub-
mandibular gland sparing to modest mean doses (35 Gy
to see any effect) might reduce xerostomia symptoms.
9. FUTURE TOXICITY STUDIES
To improve patient-specific predictions, several questions
need additional research:
1. Whether partial sparing (achievable with intensity-modu-
lated RT) of the submandibular glands or minor glands
within the oral cavity will have a positive effect on pa-
tients’ QOL
2. Whether the (arbitrary) 25% salivary threshold is the best
quantitative measure with respect to the affects on patient
QOL
3. Whether spatial/anatomic variations exist in the local radi-
ation effect
4. Whether parotid gland shrinkage during RT should be
explicitly accounted for in functional predictions
5. How submandibular sparing should be incorporated into
predictive salivary function models
6. The quantitative effect on xerostomia of oral cavity
sparing
7. The effect of the radioprotector amifostine on whole
mouth salivary function
8. The reason imaging endpoints result in greater TD50
values than direct salivary measurements
An overarching goal is the validation of an accurate predic-
tive salivary function model. This will probably require com-
bining multiple institutional or cooperative group data sets.
10. TOXICITY SCORING
To best define xerostomia,we recommend that anobserver-
based system (e.g., the Common Terminology Criteria for
Adverse Events) be supplemented by a validated QOL mea-
surement device (e.g., the XQ (xerostomia questionnaire)
[7]) and/or salivary measurements (e.g., whole mouth-stimu-
lated measurements).
REFERENCES
1. Dawes C, Wood CM. The contribution of oral minor mucous
gland secretions to the volume of whole saliva in man. Arch
Oral Biol 1973;18:337–342.
2. Buus S, Grau C, Munk O, et al. Individual radiation response of
parotid glands investigated by dynamic 11C-methionine PET.
Radiother Oncol 2006;78:262–269.
3. Astreinidou E, Roesink JM, Raaijmakers CP, et al. 3D MR
sialography as a tool to investigate radiation-induced xerosto-
mia: Feasibility study. Int J Radiat Oncol Biol Phys 2007;68:
1310–1319.
4. Chao KSC, Deasy JO, Markman J, et al. A prospective study of
salivary function sparing in patients with head-and-neck cancers
receiving intensity-modulated or three-dimensional radiation
therapy: Initial results. Int J Radiat Oncol Biol Phys 2001;49:
907–916.
5. Meirovitz A, Murdoch-Kinch C, Schipper M, et al. Grading xe-
rostomia by physicians or by patients after intensity-modulated
radiotherapy of head-and-neck cancer. Int J Radiat Oncol Biol
Phys 2006;66:445–453.
6. Blanco AI, Chao KSC, El Naqa I, et al. Dose-volume modeling
of salivary function in patients with head-and-neck cancer re-
ceiving radiotherapy. Int J Radiat Oncol Biol Phys 2005;62:
1055–1069.
7. Eisbruch A, Kim KM, Terrell JE, et al. Xerostomia and its pre-
dictors following parotid-sparing irradiation of head-and-neck
cancer. Int J Radiat Oncol Biol Phys 2001;50:695–704.
8. Maes A, Weltens C, Flamen P, et al. Preservation of parotid
function with uncomplicated conformal radiotherapy. Radio-
ther Oncol 2002;63:203–211.
9. Li Y, Taylor J, Ten Haken R, et al. The impact of dose on pa-
rotid salivary recovery in head and neck cancer patients treated
with radiation therapy. Int J Radiat Oncol Biol Phys 2007;67:
660–669.
10. Braam PM, Roesink JM, Raaijmakers CP, et al. Quality of life
and salivary output in patients with head-and-neck cancer five
years after radiotherapy. Radiat Oncol 2007;2:3.
11. Robar JL, Day A, Clancey J, et al. Spatial and dosimetric
variability of organs at risk in head-and-neck intensity-modulated
radiotherapy. Int J Radiat Oncol Biol Phys 2007;68:1121–1130.
12. Saarilahti K, Kouri M, Collan J, et al. Sparing of the submandib-
ular glands by intensity modulated radiotherapy in the treatment
of head and neck cancer. Radiother Oncol 2006;78:270–275.
13. Portaluri M, Fucilli F, Castagna R, et al. Three-dimensional
conformal radiotherapy for locally advanced (stage II and
worse) head-and-neck cancer: Dosimetric and clinical evalua-
tion. Int J Radiat Oncol Biol Phys 2006;66:1036–1043.
14. Roesink JM, Moerland MA, Battermann JJ, et al. Quantitative
dose–volume response analysis of changes in parotid gland
function after radiotherapy in the head-and-neck region. Int J
Radiat Oncol Biol Phys 2001;51:938–946.
15. Roesink JM, Moerland MA, Hoekstra A. Scintigraphic assess-
ment of early and late parotid gland function after radiotherapy
for head-and-neck cancer: A prospective study of dose–volume
response relationships. Int J Radiat Oncol Biol Phys 2004;58:
1451–1460.
16. Bussels B, Maes A, Flamen P, et al. Dose–response relation-
ships within the parotid gland after radiotherapy for head and
neck cancer. Radiother Oncol 2004;73:297–306.
17. Eisbruch A, Ten Haken R, Kim H, et al. Dose, volume, and
function relationships in parotid salivary glands following con-
formal and intensity-modulated irradiation of head and neck
cancer. Int J Radiat Oncol Biol Phys 1999;45:577–587.
18. Munter MW, Karger CP, Hoffner SG, et al. Evaluation of sali-
vary gland function after treatment of head-and-neck tumors
with intensity-modulated radiotherapy by quantitative pertechne-
tate scintigraphy. Int J Radiat Oncol Biol Phys 2007;58:175–184.
19. Munter MW, Hoffner S, Hof H, et al. Changes in salivary gland
function after radiotherapy of head and neck tumors measured
by quantitative pertechnetate scintigraphy: Comparison of in-
tensity-modulated radiotherapy and conventional radiation ther-
apy with and without amifostine. Int J Radiat Oncol Biol Phys
2007;67:651–659.
S62 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-62-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Head and Neck: Larynx/Pharynx
RADIATION DOSE–VOLUME EFFECTS IN THE LARYNX AND PHARYNX
TIZIANA RANCATI, PH.D.,* MARCO SCHWARZ, PH.D.,y
AARON M. ALLEN, M.D.,z
FELIX FENG, M.D.,x
ARON POPOVTZER, M.D.,z
BHARAT MITTAL, M.D.,{
AND AVRAHAM EISBRUCH, M.D.x
*Fondazione IRCCS-Istituto Nazionale dei Tumori, Milan, Italy; y
Agenzia Provinciale per la Protonterapia, Trento, Italy; z
Rabin
Medical Center, Petah Tikvah, Israel; x
University of Michigan, Ann Arbor, MI; {
Northwestern University, Chicago, IL
The dose–volume outcome data for RT-associated laryngeal edema, laryngeal dysfunction, and dysphagia, have
only recently been addressed, and are summarized. For late dysphagia, a major issue is accurate definition and
uncertainty of the relevant anatomical structures. These and other issues are discussed. Ó 2010 Elsevier Inc.
Larynx, pharynx, dysphagia, radiotherapy, dose effect.
1. CLINICAL SIGNIFICANCE
Radiotherapy (RT) is the primary modality allowing larynx
preservation in patients with tumors in the upper aerodiges-
tive tract. RT-induced laryngeal edema (due to inflammation
and lymphatic disruption) is a common and expected side
effect. Progressive edema and associated fibrosis can lead
to long-term problems with phonation and swallowing (1).
Since the primary goal of larynx preservation is speech and
swallowing retention, RT-induced laryngeal dysfunction
could undermine this therapeutic approach. In many in-
stances, the larynx and pharynx are target structures and pur-
posefully receive high radiation doses.
Dysphagia is common after chemoradiotherapy of head-
and-neck (HN) cancer. For example, patients included in
the Radiation Therapy Oncology Group (RTOG) 91-11 trial
were randomized to receive RT with or without concurrent
cisplatin. The combined modality arm demonstrated im-
proved tumor control rates (2). However, 1 year after therapy,
23% of the patients in the chemo-RT arm were unable to eat
solid food compared with 9% who had undergone RT alone.
Aspiration pneumonia associated with dysphagia after inten-
sive chemo-RT has recently been reported (3). The topics
reviewed in the present report are the subjects of current
intensive research. This review examined key studies
published through June 2008.
A. LARYNX
A2. Endpoints
Larynx edema. Edema can be assessed using flexible
fiberoptic examination. The grade of larynx edema can be
scored according to the RTOG scale as follows: 0, no edema;
1, slight edema; 2, moderate edema; 3, severe edema; and 4,
necrosis. Some degree of uncertainty is intrinsic to the sub-
jectivity in the interpretation of ‘‘slight’’ and ‘‘moderate’’
in the RTOG scale. Grade 1 edema would correspond to
‘‘minimal’’ thickening of the epiglottis, aryepiglottic folds,
arytenoids, and false cords. Grade 2 is a more diffuse and
evident edema, although still without significant or symp-
tomatic airway obstruction.
Vocal function. Vocal function can be assessed objec-
tively using instruments (e.g., videostroboscopy for direct
visualization to assess supraglottic activity, vocal fold edge,
amplitude, mucosal wave, phase symmetry, and glottic
closure [4]; aerodynamic measurements of phonation time
[5], or human observation [6]). Subjective assessments can
be made with validated patient-focused questionnaires to
assess various combinations of voice, eating, speech, and
social function.
A3. Challenges defining volumes
The identification of the most important anatomic sites
whose dose–volume parameters would primarily affect vocal
function remains controversial. Dornfeld et al. (7) considered
the dose points in various structures (e.g., base of tongue,
epiglottis, lateral pharyngeal walls, pre-epiglottic space,
aryepiglottic folds, false vocal cords, and upper esophageal
sphincter) to be related to vocal injury. Sanguineti et al. (8)
considered the larynx from the tip of the epiglottis superiorly
to the bottom of the cricoid inferiorly; the external cartilage
framework was excluded from the laryngeal volume.
Because of the small size and close proximity of these
structures, high-resolution, contrast-enhanced computed
Reprint requests to: Avraham Eisbruch, M.D., Department of Ra-
diation Oncology, University of Michigan Hospital, Ann Arbor MI
48109. Tel: (734) 936-9337; Fax: (734) 936-7370; E-mail:
eisbruch@umich.edu
Conflict of interest: none.
Received Jan 13, 2009, and in revised form March 26, 2009.
Accepted for publication March 27, 2009.
S64
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S64–S69, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.03.079](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-64-320.jpg)
![acute dysphagia would lead to improvements in late swallow-
ing abnormalities.
Validation of assessors of dysphagia
The most commonly used observer-rated dysphagia grad-
ing tool is the CTCAE dysphagia item, which has not been
validated formally. Similarly, multiple patient-reported
QOL instruments have been used, as detailed in the present
report, and few have formally been validated regarding their
dysphagia components.
The issue of what are the most important anatomic
structures and substructures whose damage is the likely cause
of dysphagia is the subject of current research by many inves-
tigators. An important aspect of this research is the effects of
the tumor on pretherapy swallowing and on the functional re-
sults after therapy. To capture these effects, prospective stud-
ies that have included pretherapy evaluations are essential.
B10. Toxicity scoring
As detailed, prospective evaluation is critical because of
tumor-related dysphagia and aspiration, particularly in
patients with advanced cancer. Although CTCAE-based
scoring is simple and commonly applied, the evidence of
‘‘silent aspiration’’ after RT (aspiration not eliciting a cough
owing to a laryngeal sensory deficit) requires objective mea-
surement using imaging and interpretation by professional
speech/language pathologists. In addition, an objective
swallow assessment might help quantify the swallowing
assessments. Correlating observer-rated scores such as the
CTCAE system, patient-reported scores, and objective swal-
lowing dysfunction is recommended for future focused stud-
ies. Until more data regarding this issue are available, we
recommend the use of the CTCAE system, as well as
a patient-reported QOL instrument, for large-scale clinical
studies of chemo-RT for HN cancer.
REFERENCES
1. Fung K, Yoo J, Leeper HA, et al. Effects of head and neck ra-
diation therapy on vocal function. J Otolaryngol 2001;30:
133–139.
2. Forastiere AA, Goepfert H, Maor M, et al. Concurrent chemo-
therapy and radiotherapy for organ preservation in advanced la-
ryngeal cancer. N Engl J Med 2003;349:2091–2098.
3. Eisbruch A, Lyden T, Bradford CR, et al. Objective assessment
of swallowing dysfunction and aspiration after radiation concur-
rent with chemotherapy for head and neck cancer. Int J Radiat
Oncol Biol Phys 2002;53:23–28.
4. Hirano M. Clinical examination of voice. In: Arnold GE,
Winkel F, Wyke BD, editors. Disorders of human communica-
tion. New York: Springer-Verlag; 1981. p. 81–84.
5. Fung K, Yoo J, Leeper A, et al. Vocal function following radi-
ation for non-laryngeal versus laryngeal tumors of the head and
neck. Laryngoscope 2001;111:1920–1924.
6. Hocevar-Boltezar I, Zargi M, Strojan P. Risk factors for voice
quality after radiotherapy for early glottic cancer. Radiother
Oncol 2009;93:524–529.
7. Dornfeld K, Simmons JR, Karnell L, et al. Radiation doses to
structures within and adjacent to the larynx are correlated with
long-term diet and speech-related quality of life. Int J Radiat
Oncol Biol Phys 2007;68:750–757.
8. Sanguineti G, Adapala P, Endres EJ, et al. Dosimetric predictors of
laryngeal edema. Int J Radiat Oncol Biol Phys 2007;68:741–749.
9. Fu KK, Woofhouse RJ, Quivey JM, et al. The significance of
laryngeal edema following radiotherapy of carcinoma of the
vocal cord. Cancer 1982;49:6555–6558.
10. Rancati T, Sanguineti G, Fiorino C. NTCP modeling of sub-
acute/late laryngeal edema scored by fiberoptic examination:
evidence of a large volume effect. Int J Radiat Oncol Biol
Phys 2007;69(Suppl. 3):S409–S410.
11. Kendall KA, McKenzie SW, Leonard RJ, et al. Timing of
events in normal swallowing: A videofluroscopic study. Dys-
phagia 2000;15:74–84.
12. Logemann J. Mechanism of normal and abnormal swallowing. In:
Cummings JW, Flint PW, Haughey BA, et al., editors. Otolaryn-
gology: head and neck surgery. 5th ed. St. Louis: Mosby; 2008.
13. Eisbruch A, Schwartz M, Rasch C, et al. Dysphagia and aspira-
tion after chemoradiotherapy for head and neck cancer: Which
anatomic structures are affected and can they be spared by
IMRT? Int J Radiat Oncol Biol Phys 2004;60:1425–1439.
14. Feng FY, Kim HM, Lyden TH, et al. Intensity-modulated radio-
therapy of head and neck cancer aiming to reduce dysphagia:
Early dose–effect relationships for the swallowing structures.
Int J Radiat Oncol Biol Phys 2007;68:1289–1298.
15. Levandag PC, Teguh DN, Voet P, et al. Dysphagia disorders in
patients with cancer of the oropharynx are significantly affected
by the radiation therapy dose to the superior and middle
constrictor muscle: A dose–effect relationship. Radiother Oncol
2007;85:64–73.
16. Jensen K, Lambertsen K, Grau C. Late swallowing dysfunction
and dysphagia after radiotherapy for pharynx cancer: Fre-
quency, intensity, and correlation with dose and volume param-
eters. Radiother Oncol 2007;85:74–82.
17. Fua TF, Corry J, Milner AD, et al. Intensity-modulated radio-
therapy for nasopharyngeal carcinoma: Clinical correlation of
dose to the pharyngoesophageal axis and dysphagia. Int J
Radiat Oncol Biol Phys 2007;67:976–981.
18. Doornaert P, Slotman BJ, Rietveld DHF, et al. The mean radi-
ation dose in pharyngeal structures is a strong predictor of acute
and persistent swallowing dysfunction and quality of life in
head and neck radiotherapy [Abstract]. Int J Radiat Oncol
Biol Phys 2007;69(Suppl):55.
19. Caglar HB, Allen AM, Othus M, et al. Dose to the larynx pre-
dicts for swallowing complications following IMRT and che-
motherapy. Int J Radiat Oncol Biol Phys 2008;72:1110–1118.
20. O’Meara EA, Machtay M, Moughan J, et al. Association
between radiation doses to pharyngeal regions and severe late
toxicity in head and neck cancer patients treated with concurrent
chemoradiotherapy—An RTOG analysis [Abstract]. Int J
Radiat Oncol Biol Phys 2007;69(Suppl):54.
21. Laurell G, Kraepelien T, Mavroidis P, et al. Stricture of the
proximal esophagus in head and neck carcinoma patients after
radiotherapy. Cancer 2003;97:1693–1700.
22. Rosenthal DI, Lewin JS, Eisbruch A. Prevention and treatment
of dysphagia and aspiration after chemoradiation for head and
neck cancer. J Clin Oncol 2006;24:2636–2643.
23. Mekhail TM, Adelstein DJ, Rybicki LA, et al. Enteral nutrition
during the treatment of head and neck carcinoma: Is percutane-
ous endoscopic gastrostomy tube preferable to a nasogastric
tube? Cancer 2001;91:1785–1790.
24. Brizel DM, Wasserman TH, Henke M, et al. Phase 3 random-
ized trial of amifostine as a radioprotector in head and neck
cancer. J Clin Oncol 2000;18:3339–3345.
25. Langerman A, MacCracken E, Kasza K, et al. Aspiration in
chemoradiated patients with head and neck cancer. Arch Oto-
laryngol Head Neck Surg 2007;133:1289–1295.
Dose–volume effects in larynx and pharynx d T. RANCATI et al. S69](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-69-320.jpg)
![ambiguity in defining its dose–volume histogram (DVH)-
based parameters. In the articles herein reviewed, dosimetric
information was mostly based on CT images obtained during
free breathing. The dosimetric parameters would change had
these scans been obtained at specific phases of the respiratory
cycle. Segmentation of a thoracic scan can be challenging.
There is uncertainty regarding how much of the bronchus
should be defined as ‘‘lung,’’ and the lung edges may vary
with the window/level setting. Thus, volume-based parame-
ters will vary between investigators. The accuracy of any au-
tosegmenting tools should be carefully assessed, especially to
ensure that portions of atelectatic lung or tumor at soft-tissue
interfaces are not inadvertently omitted from the lung.
During RT planning, the total lung volume is usually de-
fined to exclude the gross tumor volume (GTV). Excluding
the planning target volume (PTV) rather than the GTV
from the lung volume may reduce the apparent lung exposure
(because normal lung within the PTV but outside the GTV
will be excluded) and may increase interinstitutional varia-
tions (because PTV margins may vary).
During treatment there may be changes in GTV, with cor-
responding changes in normal tissue anatomy. Thus, plans
defined on the basis of pre-RT imaging may not accurately
reflect the degree of normal lung exposure. Although this
effect has not been widely considered, presumably tumor
shrinkage (with movement of normal lung into space previ-
ously occupied GTV) will increase normal lung exposure rel-
ative to pre-RT plans. Similarly, changes in pleural effusions
and re-aeration of lung regions can cause anatomic and func-
tional changes. Indeed, the ability to predict changes in lung
function according to pre-RT dosimetric data is reduced in
patients with tumor-associated airway obstruction (i.e., those
most likely to experience re-aeration during therapy) (4).
4. REVIEW OF DOSE–VOLUME DATA
The literature on dose–volume parameters and pneumoni-
tis is extensive: for this review we identified 70 published
articles. The results are inconsistent, both for the best predic-
tive metrics and significant comorbid factors.
Lyman-Kutcher-Burman DVH reduction scheme and mean
lung dose
The most widely used normal tissue complication proba-
bility model for RP is the Lyman-Kutcher-Burman (LKB)
model. This model has three parameters: a position parame-
ter, TD50, a steepness parameter, m, and the volume expo-
nent, n (where n = 1 the model reverts to mean lung dose
[MLD]). Although TD50 is strongly dependent on the grade
of RP being considered, n is often regarded as a tissue char-
acteristic. Figure 1 shows a meta-analysis of reported n
values; it does not include the study by Rancati et al. (5),
which used only the ipsilateral lung. The best estimate for
n is 1.03 with standard deviation 0.17 (95% confidence inter-
val [CI], 0.67, 1.39), the test for heterogeneity of the datasets
is not significant, and I2
is zero. The TD50 values cannot be
pooled in a meaningful way, because the various reports an-
alyzed considered varying grades of RP.
The MLD model is widely considered owing to its simplic-
ity and effectiveness. It was the metric used by the large
multi-institutional analysis of Kwa et al. (6) and often per-
forms as well as more complex models. Figure 2A shows a lo-
gistic regression fitted to RP vs. MLD data from all published
studies of a significant size that had extractable complication
rates binned by mean dose. Some of the variation around the
fitted curve is possibly explained by differences in patient se-
lection, as well as differences in the grade of RP reported in
the various studies. Nevertheless, there is a relatively small
68% confidence interval (stippled lines). A similar fit using
the probit model (equivalent to fitting the Lyman model
with n fixed at 1) gives an essentially identical response func-
tion in the region of the data. The gradual increase in dose re-
sponse suggests that there is no absolute ‘‘safe’’ MLD below
which there is no pneumonitis. The clinically acceptable risk
of RP—and therefore the associated planning constraint on
MLD—will depend on the risk/benefit ratio in the individual
case. A number of non–DVH-based factors may affect the
risk of RP (see ‘‘Factors Affecting Risk’’). Finally, it is likely
Table 1. Example endpoints for radiotherapy-induced lung
injury (and approximate incidence)
Regional Global
Clinical Bronchial stricture
(3%*)
Shortness of breath
(5–50%)
Subclinical Radiologic abnormalities
(e.g. computed tomography,
perfusion/ventilation scans)
(20–80%)
Pulmonary function
tests, 6-min walk
test, blood
gases, exercise
capacityy
Example endpoints used to study radiotherapy-induced lung in-
jury can be broadly segregated as shown.
* Uncommon with conventional fractionation and doses. More
common with brachytherapy, high total doses, and/or hypofractio-
nation.
y
Many patients experience declines in functional assessments,
but the magnitude of the decline is variable.
Fig. 1. Meta-analysis of reported n values (volume parameter) for
the Lyman-Kutcher-Burman (LKB) model using an inverse-vari-
ance (IV) weighting method. Recovery of variance estimates from
the 95% confidence interval (CI) and use of approximately
Æ2*sigma instead of 1.96*sigma gave rise to small deviations in
the derived 95% CI as compared with the literature reported values.
Data estimated from references 47–49. Fixed = fixed effect model.
The n value reflects the manner in which dose–volume parameters
lead to complications. A lower value of n suggests that the tissue
is sensitive to hot spots (e.g., an organ structured in ‘‘series’’),
whereas a higher value of n (closer to 1.0), suggests that the risk
is more related to the volume of an organ irradiated (e.g., ‘‘parallel’’
structure).
Radiation effects in lung d L. B. MARKS et al. S71](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-71-320.jpg)
![that the MLD–RP relationship may have lower predictive
power for ‘‘nonstandard’’ dose distributions not included
in these analyses, for example after stereotactic body radio-
therapy (SBRT), Intensity-Modulated Radiation Therapy
(IMRT), or proton therapy.
Dose–volume threshold analyses
Various Vx values (percentage lung volume receiving $x
Gy) are associated with RP risk (Fig. 2B). The observation
that a variety of dose levels are predictive suggests that there
is no sharp dose threshold below which there is no risk.
Within individual datasets there are usually strong correla-
tions between the different dosimetric parameters (e.g., V5
and V20), and thus this may partly obscure any ‘‘optimal’’
threshold. Furthermore, the correlations between dosimetric
parameters are technique dependent, and readers should care-
fully assess the similarity of their treatment technique to the
historical reports before using any of these limits as clinical
constraints.
Radiotherapy-induced dyspnea appears more commonly
in patients with lower- vs. upper-lobe tumors and may be bet-
ter correlated with RT doses to the lower vs. upper lung (7–
11). An analysis that combined institutional data with RTOG
93-11 (n = 324) concluded that RP is much better predicted
(at least for that dataset) according to MLD and positional de-
pendence of the high-dose region as opposed to MLD alone
(12).
5. FACTORS AFFECTING RISK
Several patient- and treatment-related factors have been in-
consistently reported to correlate with the risk of developing
RP. Vogelius and Bentzen (unpublished data) applied stan-
dard meta-analysis methodology to eight factors with mean-
ingful data. In summary, there was no significant evidence for
an association between RP and GTV laterality (left vs. right
lung), comorbidity, or gender. Younger patients, typically
defined as 60 or 70 years of age, had a lower risk of RP
than older patients. Surgery had a just-significant p value,
but the test for heterogeneity was significant (p = 0.03), sug-
gesting that the variation among studies cannot be explained
by chance alone. Thus, at present, the reduced rate of RP in
patients undergoing surgery remains controversial. Interest-
ingly, current smokers had a significantly reduced risk of de-
veloping RP.
Chemotherapy
Many systemic agents have known pulmonary toxicities
(13) and may exacerbate RT-induced injury. The varying
drugs, doses, and schedules (e.g., sequential or concurrent)
make any synthesis of data from multiple studies generally
not feasible. On the basis of general experience, adding chemo-
therapy might be expected to increase the risk of RP.
Fig. 2. Rate of radiation pneumonitis after fractionated partial lung
radiotherapy (RT) related to (a) mean lung dose and (b) different
values of Vx. (a) Mean lung dose. Confidence intervals shown are
Æ1 standard deviation. Mean dose–response data from: Memorial
Sloan-Kettering Cancer Center (MSKCC) (10 [Fig. 4a]; Radiation
Therapy Oncology Group [RTOG] Grade $3, 6 months); Duke,
(15 [Table 4]; Common Toxicity Criteria [CTC] Grade $1, 6
months); Michigan (50 [Table 4 and Fig. 2a]; Southwest Oncology
Group [SWOG] Grade $2, 6 months)—bin location and time from
authors; M. D. Anderson Cancer Center (51 [Fig. 2]; CTC Grade
$3, 1 year actuarial—includes concurrent chemo patients); Nether-
lands Cancer Institute (NKI) (9 [Fig. 3a]; SWOG Grade $2, 6
months); Washington University (WU) (11 [Fig. 9c]; SWOG Grade
$2—no time limit), with bin locations from authors, increased by
11% to approximately account for inhomogeneity corrections;
Michigan (52 [Table 1]; SWOG Grade $1) with mean doses calcu-
lated from relationship between equivalent uniform dose (n = 0.87)
and mean dose from Kwa et al. (53 [Fig. 2a]); Heidelberg (54 [Fig 2.
and text]; RTOG acute Grade $1); Milan (55 [Fig. 3]; SWOG Grade
$2—no time limit, patients without chronic obstructive pulmonary
disease—includes induction chemotherapy patients); Gyeonggi (56
[Table 5]; RTOG Grade $3, 6 months—includes concurrent che-
motherapy patients), median values of mean dose in each bin pro-
vided by the authors. Dashed line is logistic fit: data fit to the
form [f/(1 + f)], where f = exp(b0 + b1 Â dmean). Best-fit values
(95% confidence intervals) are b0 = À3.87 (À3.33, À4.49), b1 =
0.126 (0.100, 0.153), corresponding to TD50 = 30.75 (28.7, 33.9)
Gy and g50 = 0.969 (0.833, 1.122), where g50 represents the increase
in response (measured as percentage) per 1% increase in dose, near
the 50% dose–response level. (b) Rates of radiation pneumonitis for
different values of Vx. Vx response data from: Yorke V13, V40, (10
[Fig. 4d]); Willner V40, (57 [Fig. 4]); Hernando V30 (15 [Table 6]);
Tsujino V20 (58 [Fig. 3]); Kong V13, V20, (50 [Table 4]); Armstrong
V25 (59 [Fig. 3]); Kim V20, V30 (56 [Table 5]; Graham V20 (7 [Table
4]); Seppenwoolde V13 48([Fig. 2]); and Wang V5 (51; and Schal-
lenkamp V13 (60 [Fig. 2b]). Some data estimated from published re-
ports.
S72 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-72-320.jpg)
![Nevertheless,theagentsmostcommonlyusedwithRTforlung
cancer, such as cisplatin, carboplatin, paclitaxel, and etoposide,
have not been consistently shown to increase the risk of pneu-
monitis (7, 11, 14–16). More modern agents have been associ-
ated with high rates of pulmonary toxicity when used
concurrently with thoracic RT (e.g., docetaxel and gemcita-
bine) (1, 17, 18).
Radiation dose, time, and fractionation
Radiation pneumonitis has a relatively high fractionation
sensitivity (19, 20); the best current estimate (Æ1 standard er-
ror of the estimate) of the a/b ratio of the linear-quadratic
model is 4.0 Æ 0.9 Gy (21). For comparison, the upper bound
of the 95% CI for a/b for pulmonary fibrosis is 3.5 Gy. There is
also a significant time factor for pneumonitis, with an overall
best estimate of the dose recovered per day, Dp, of 0.54 Æ
0.21 Gy/day. Several investigators have suggested methods
to adjust the DVH to reflect the impact of fraction size (22, 23).
6. MATHEMATIC/BIOLOGIC MODELS
The association between RP risk and MLD (logistic fit to
the data in Fig. 2(a) can be expressed as
p ¼
expðb0 þ b1,MLDÞ
1 þ expðb0 þ b1,MLDÞ
:
Best-fit parameters (95% CI) are b0 = À3.87 (À3.33, À4.49)
and b1 = 0.126 (0.100, 0.153) GyÀ1
. These estimates yield
a predicted TD50 = 30.8 (28.7, 33.9) Gy and g50 = 0.97
(0.83, 1.12) (this parameter represents the increase in response
[measured as percentage] per 1% increase in dose, at the 50%
dose–response level). A fit using the probit response function
(equivalent to a fit of the Lyman model with n = 1) yields TD50
= 31.4 Gy (95% CI, 29.0, 34.7 Gy) and m = 0.45 (0.39, 0.51).
The resultant response function is essentially identical to that
of the logistic fit in the region occupied by the data. The cur-
vature is slightly smaller, resulting in the slightly larger
TD50 value. Both fits assumed heterogeneity corrected dose
distributions (an approximate correction of 11% was applied
to doses from studies using homogeneous calculations).
7. SPECIAL SITUATIONS
The data reviewed here are largely derived from patients
who received partial-lung irradiation using conformal
three-dimensionally planned external-beam RT with conven-
tional fractionation (e.g., 1.8–2.0 Gy per fraction). Several
special situations are discussed here.
Whole-lung irradiation
Near-uniform irradiation of both lungs occurs during total-
body irradiation as conditioning for stem cell transplants,
hemibody RT for diffuse metastases, and whole-lung irradi-
ation for prophylaxis or treatment of pulmonary metastases
from various malignancies. The risk of RP depends on total
dose and fraction size (Fig. 3). The development of RP in
these settings is an ominous sign, proving fatal in up to
80% of patients (24). The pathogenesis of RP, in particular
after total-body irradiation, is relatively complex and de-
pends on multiple patient- and treatment-related factors
(25). There are consistent data supporting a protective effect
of low dose rate and low dose per fraction. For a recent com-
prehensive review, see Sampath et al. (26).
Hypofractionation
Stereotactic body radiotherapy generally involves 1–5
large fractions (e.g., 14–30 Gy) given over 5–20 days (27,
28). The high-dose volumes are small, and dose gradients
are typically uniformly steep, minimizing dose to surround-
ing critical structures. However, because numerous beams
are used, there are large areas of lung receiving low to me-
dium doses (28). Thus, the dose–volume characteristics of
SBRT are quite different from those of conventional lung
RT and deserve special consideration. Radiation pneumonitis
is relatively uncommon after SBRT, usually 10% (28–30)
but as high as 25% (31). Bronchial injury/stenosis, an un-
usual complication with conventional doses (32), has been
associated with SBRT of perihilar/central tumors (28).
Intensity-modulated radiotherapy for lung cancer
The M. D. Anderson Cancer Center reported a lower rate
of symptomatic Grade $3 pneumonitis in 68 patients treated
with intensity-modulated radiotherapy (IMRT) compared
with a historical control group of 222 receiving conventional
three-dimensional conformal RT (33). The Memorial Sloan-
Kettering Cancer Center recently noted an acceptable 11%
rate of Grade $3 pneumonitis in 55 patients treated with
IMRT (34). Postoperative IMRT for mesothelioma has
been associated with a high rate of lethal pneumonitis (8–
46%) (35–37), and extreme care should be used to limit
lung irradiation in these cases (see next section).
8. RECOMMENDED DOSE/VOLUME LIMITS
Recommending dose/volume limits is challenging because
there are no clear and consistent ‘‘thresholds’’ for candidate
metrics (i.e., the response function is often gradual), and
baR 1 679
xf/yGc051
kyDnaV 1891
esoDelgniS
)yG(esoD
63 219 8151 4212 0372
IncidenceofPneumonitis
8791razalaS
esoDelgniS
)4/1(
)04/0(
)3/3(
9691notweN
003 xf/yGc
051 xf/yGc
)62/0(
ruerB 8791
xf/yGc571
)44/0(
8891sregruB
xf/yGc002
)65/8(
1
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0
kyDnaVottiF d ata
Fig. 3. Rate of pneumonitis after whole-lung irradiation for diffuse
lung or bone metastases, or prophylaxis for occult metastatic disease
(24, 61–67). Numbers in parentheses give the incidence of pneumo-
nitis divided by the population at risk for each fractionation scheme
in each study. Some data estimated from published reports.
Radiation effects in lung d L. B. MARKS et al. S73](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-73-320.jpg)
![the ‘‘acceptable’’ risk level varies with the clinic scenario.
Radiotherapy fields for lung cancer may be appropriately
large for target coverage; physicians and patients often
need to accept the significant pulmonary risks. Furthermore,
there are marked interpatient variations in pre-RT lung func-
tion that may impact symptom development, and tumor-re-
lated dysfunction may improve after RT.
Despite these caveats, it is prudent to limit V20 to #30–35
% and MLD to #20–23 Gy (with conventional fractionation)
if one wants to limit the risk of RP to #20% in definitively
treated patients with non–small-cell lung cancer. Similar
guidelines for other parameters can be extracted from the fig-
ures. Limiting the dose to the central airways to #80 Gy may
reduce the risk of bronchial stricture (30). In patients treated
after pneumonectomy for mesothelioma, it is prudent to limit
the V5 to 60%, the V20 to 4–10%, and the MLD to 8 Gy
(see Miles et al. [37] for detailed review).
9. FUTURE TOXICITY STUDIES
Progress regarding the predictors of RT-induced lung in-
jury requires further understanding of the following.
Endpoint interaction
The study of RT-induced lung injury is confounded by the
use of ambiguous endpoints. Many scoring systems combine
radiologic, functional, and symptomatic criteria to define
a ‘‘global score.’’ Because each endpoint may have different
dose–volume dependence, this approach may be counterpro-
ductive. Therefore, we recommend that further study of lung
injury explicitly consider symptomatic, functional, and radio-
graphic endpoints separately.
Impact of clinical factors
The impact of clinical factors (e.g., pre-RT functional sta-
tus, tobacco use) and systemic agents (e.g., chemotherapy) on
the risk of RP needs further study.
Organ interactions
Some pre-clinical data suggest that there may be interac-
tions between the lung and heart in the development of RT-
associated dyspnea. In rats, the respiratory rate after thoracic
RT was related to the volume of lung and heart irradiated
(38–40).
Impact of an in situ lung cancer on the risk of radiation-
induced lung injury
The data for whole-lung radiation is derived essentially
from patients without primary lung cancers (e.g., elective
lung RT for sarcoma), vs. fractionated partial lung radiation,
often derived from patients with gross lung cancers. The con-
founding effect of tumor in the lung makes the study of RT-
induced lung injury extremely challenging. Indeed, in several
studies, the ability to predict for RT-induced lung injury is
improved in patients without large central or occluding tu-
mors. Thus, it might be relevant to develop separate predic-
tive models in patients with intact intraparenchymal lung
tumors vs. those without such a lesion (i.e., postresection
RT for lung cancer, or RT for other thoracic tumors).
Radiation response modifiers
Amifostine is a thio-organic prodrug believed to scavenge
harmful free radicals mediating RT-induced injury. Several
randomized studies in patients receiving RT for lung cancer
note a reduction in RP in the amifostine arm (41–43), although
the largest study (from RTOG) was negative (44). However,
this study has been criticized because the drug was adminis-
tered once daily (4 days/week) whereas the RT was delivered
twice daily (5 days/week), and thus 60% of the RT fractions
were delivered without the protector. Such mixed results,
combined withthe acutetoxicities of amifostine (nausea/vom-
iting, hypotension, infection, and rash), have dissuaded many
from using it in routine practice. One small randomized study
demonstrated a protective effect of pentoxifylline, but pentox-
ifylline is not currently used in routine clinical practice (45).
Biomarkers
Additional work is needed to assess the predictive ability
offered by biomarkers (see Bentzen et al. in this issue),
such as transforming growth factor b (measured before
and/or during RT) (46).
10. TOXICITY SCORING
A Late Effects of Normal Tissue–Subjective, Objective,
Management, and Analytic (LENT-SOMA)-type scoring
system is recommended because it explicitly considers symp-
tomatic, functional, and radiographic endpoints individually.
A global score can be generated, but the granular data can be
maintained.
REFERENCES
1. Mehta V. Radiation pneumonitis and pulmonary fibrosis in non-
small-cell lung cancer: Pulmonary function, prediction, and pre-
vention. Int J Radiat Oncol Biol Phys 2005;63:5–24.
2. Marks LB, Yu X, Vujaskovic Z, et al. Radiation-induced lung
injury. Semin Radiother Oncol 2003;13:333–345.
3. Kocak Z, Evans ES, Zhou SM, et al. Challenges in defining ra-
diation pneumonitis in patients with lung cancer. Int J Radiat
Oncol Biol Phys 2005;62:635–638.
4. Marks LB, Hollis D, Munley M, et al. The role of lung perfu-
sion imaging in predicting the direction of radiation-induced
changes in pulmonary function tests. Cancer 2000;88:2135–
2141.
5. Rancati T, Wennberg B, Lind P, et al. Early clinical and radio-
logical pulmonary complications following breast cancer radia-
tion therapy: NTCP fit with four different models. Radiother
Oncol 2007;82:308–316.
6. Kwa SL, Lebesque JV, Theuws JC, et al. Radiation pneumo-
nitis as a function of mean lung dose: An analysis of pooled
data of 540 patients. Int J Radiat Oncol Biol Phys 1998;42:
1–9.
S74 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-74-320.jpg)
![44. Movsas B, Scott C, Langer C, et al. Randomized trial of amifos-
tine in locally advanced non-small-cell lung cancer patients re-
ceiving chemotherapy and hyperfractionated radiation:
Radiation Therapy Oncology Group trial 98-01. J Clin Oncol
2005;23:2145–2154.
45. Ozturk B, Egehan I, Atavci S, et al. Pentoxifylline in prevention
of radiation-induced lung toxicity in patients with breast and
lung cancer: A double-blind randomized trial. Int J Radiat On-
col Biol Phys 2004;58:213–219.
46. Fu X-L, Huang H, Bentel G, et al. Predicting the risk of symp-
tomatic radiation-induced lung injury using both the physical
and biologic parameters V30 and transforming growth factor
[beta]. Int J Radiat Oncol Biol Phys 2001;50:899–908.
47. Moiseenko V, Deasy JO, Dyk JV. Radiobiological modeling for
treatment planning. In: Van Dyk J, editor. The modern technol-
ogy of radiation oncology: A compendium for medical physi-
cists and radiation oncologists. Vol. 2. Madison, WI: Medical
Physics; 2005.
48. Seppenwoolde Y, Lebesque JV, de Jaeger K, et al. Comparing
different NTCP models that predict the incidence of radiation
pneumonitis. Normal tissue complication probability. Int J Ra-
diat Oncol Biol Phys 2003;55:724–735.
49. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of
the risk of postoperative pulmonary complications among
esophageal cancer patients treated with concurrent chemoradio-
therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006;
66:754–761.
50. Kong FM, Hayman JA, Griffith KA, et al. Final toxicity
results of a radiation-dose escalation study in patients with
non-small-cell lung cancer (NSCLC): Predictors for radiation
pneumonitis and fibrosis. Int J Radiat Oncol Biol Phys
2006;65:1075–1086.
51. Wang S, Liao Z, Wei X, et al. Analysis of clinical and dosimet-
ric factors associated with treatment-related pneumonitis (TRP)
in patients with non-small-cell lung cancer (NSCLC) treated
with concurrent chemotherapy and three-dimensional confor-
mal radiotherapy (3D-CRT). Int J Radiat Oncol Biol Phys
2006;66:1399–1407.
52. Martel MK, Ten Haken RK, Hazuka MB, et al. Dose-volume
histogram and 3-D treatment planning evaluation of patients
with pneumonitis. Int J Radiat Oncol Biol Phys 1994;28:575–
581.
53. Kwa SL, Theuws JC, Wagenaar A, et al. Evaluation of two
dose-volume histogram reduction models for the prediction of
radiation pneumonitis. Radiother Oncol 1998;48:61–69.
54. Oetzel D, Schraube P, Hensley F, et al. Estimation of pneumo-
nitis risk in three-dimensional treatment planning using dose-
volume histogram analysis. Int J Radiat Oncol Biol Phys
1995;33:455–460.
55. Rancati T, Ceresoli GL, Gagliardi G, et al. Factors predicting
radiation pneumonitis in lung cancer patients: A retrospective
study. Radiother Oncol 2003;67:275–283.
56. Kim TH, Cho KH, Pyo HR, et al. Dose-volumetric parameters
for predicting severe radiation pneumonitis after three-dimen-
sional conformal radiation therapy for lung cancer. Radiology
2005;235:208–215.
57. Willner J, Jost A, Baier K, et al. A little to a lot or a lot to a little?
An analysis of pneumonitis risk from dose-volume histogram
parameters of the lung in patients with lung cancer treated
with 3-D conformal radiotherapy. Strahlenther Onkol 2003;
179:548–556.
58. Tsujino K, Hirota S, Endo M, et al. Predictive value of dose-vol-
ume histogram parameters for predicting radiation pneumonitis
after concurrent chemoradiation for lung cancer. Int J Radiat
Oncol Biol Phys 2003;55:110–115.
59. Armstrong JG, Zelefsky MJ, Leibel SA, et al. Strategy for dose
escalation using 3-dimensional conformal radiation therapy for
lung cancer. Ann Oncol 1995;6:693–697.
60. Schallenkamp JM, Miller RC, Brinkmann DH, et al. Incidence
of radiation pneumonitis after thoracic irradiation: Dose-
volume correlates. Int J Radiat Oncol Biol Phys 2007;67:
410–416.
61. Newton KA. Total thoracic irradiation combined with intrave-
nous injection of autogenous marrow. Clin Radiol 1960;11:
14–21.
62. Newton KA, Spittle MF. An analysis of 40 cases treated by total
thoracic irradiation. Clin Radiol 1969;20:19–22.
63. Salazar OM, Rubin P, Keller B, et al. Systemic (half-body) ra-
diation therapy: Response and toxicity. Int J Radiat Oncol Biol
Phys 1978;4:937–950.
64. Van Dyk J, Keane TJ, Kan S. Radiation pneumonitis following
large single dose irradiation: A re-evaluation based on absolute
dose to lung. Int J Radiat Oncol Biol Phys 1981;7:461–467.
65. Rab GT, Ivins JC, Childs J, Donald S, et al. Elective whole lung
irradiation in the treatment of osteogenic sarcoma. Cancer
1976;38:939–942.
66. Breur K, Cohen P, Schweisguth O, et al. Irradiation of the lungs
as an adjuvant therapy in the treatment of osteosarcoma of the
limbs. An E.O.R.T.C. randomized study. European Journal
of Cancer 1978;14:461–471.
67. Burgers JM, van Glabbeke V, Busson A, et al. Osteosarcoma of
the limbs. Report of the EORTC-SIOP 03 trial 20781 investigat-
ing the value of adjuvant treatment with chemotherapy and/or
prophylactic lung irradiation. Cancer 1988;61:1024–1031.
S76 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-76-320.jpg)
![QUANTEC: ORGAN SPECIFIC PAPER Thorax: Heart
RADIATION DOSE–VOLUME EFFECTS IN THE HEART
GIOVANNA GAGLIARDI, PH.D.,* LOUIS S. CONSTINE, M.D.,y
VITALI MOISEENKO, PH.D.,z
CANDACE CORREA, M.D.,x
LORI J. PIERCE, M.D.,x
AARON M. ALLEN, M.D.,k
AND LAWRENCE B. MARKS, M.D.{
* Department of Medical Physics, Karolinska University Hospital and Karolinska Institute, Stockholm, Sweden; y
Department of
Radiation Oncology, University of Rochester Cancer Center, Rochester, NY; z
Vancouver Cancer Centre, British Columbia Cancer
Agency, Vancouver, BC, Canada; x
Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; k
Department of
Radiation Oncology, Dana- Farber Cancer Institute, Boston, MA; Rabin Medical Center Petach Tikvah, Israel ; and {
Department of
Radiation Oncology, University of North Carolina, Chapel Hill, NC
The literature is reviewed to identify the main clinical and dose–volume predictors for acute and late radiation-
induced heart disease. A clear quantitative dose and/or volume dependence for most cardiac toxicity has not yet
been shown, primarily because of the scarcity of the data. Several clinical factors, such as age, comorbidities
and doxorubicin use, appear to increase the risk of injury. The existing dose-volume data is presented, as well
as suggestions for future investigations to better define radiation-induced cardiac injury. Ó 2010 Elsevier Inc.
Radiation heart disease, Dose–volume predictors, NTCP, Breast cancer, Lymphoma, Esophagus cancer.
1. CLINICAL SIGINIFICANCE
Radiation-associated cardiac disease is seen in patients
treated for lymphoma, breast cancer, seminoma, peptic ulcer
disease, and lung cancer, as well as in atomic bomb survivors.
Acute injury, often manifest as pericarditis, is usually
transient but can be chronic. Late injury, often manifest as
congestive heart failure (CHF), ischemia, coronary artery
disease (CAD), or myocardial infarction (MI) several months
to years post-radiation treatment (RT), is more clinically
significant. In some disease settings, RT-induced heart dis-
ease has offset the improvements in cancer-specific survival
provided by adjuvant RT (1). For example, the leading cause
of noncancer mortality among long-term RT-treated survi-
vors of Hodgkin’s lymphoma is cardiovascular death (2).
2. ENDPOINTS
Both clinical and subclinical endpoints describe the spec-
trum of RT-induced heart disease (Table 1). The latency of
RT-associated cardiac effects ranges from months (pericardi-
tis) to decades (CAD, MI). The most clinically significant
endpoints analyzed are morbidity (e.g., CHF and ischemic
events such as MI) and cardiac deaths. Since these events
occur at a relatively high rate in patients who have not
undergone irradiation, the best data are derived from rando-
mised clinical trials, or population-based studies with or
without RT. Overall, the relative risks (RR) of these clinically
significant cardiac events are within a range of 1.2 to 3.5 after
RT. Subclinical abnormalities are more common, and are
noted in up to 50% of patients, depending on the sensitivity
of the endpoint considered and the associated comorbidities.
Pericardial disease
Acute pericarditis during RT is uncommon and usually
associated with pericardiac mediastinal tumours. Delayed
pericardial disease can occur from months to years after
RT; it includes pericarditis and chronic pericardial effusion
(usually asymptomatic). Although most cases resolve sponta-
neously, approximately 20% develop into chronic and/or con-
strictive pericarditis that may necessitate pericardectomy (3).
Ischemic heart disease
Evidence that ischemic heart disease correlates with RT
comes from the Early Breast Cancer Trialists’ Collaborative
Group meta-analyses of randomized clinical trials. The most
recent update showed an increased RR of mortality from
heart disease among women treated with RT vs. no RT
([RR] = 1.27) (1).
Long-term cardiac outcomes from randomized clinical
trials of postmastectomy RT (4, 5) usually reveal an
Reprint requests to: Giovanna Gagliardi, Ph.D., Department of
Medical Physics, Karolinska University Hospital and Karolinska In-
stitute, 17176 Stockholm, Sweden. Tel: +46-8-517 75025; E-mail:
giovanna.gagliardi@karolinska.se
Conflict of interest: none.
Acknowledgment—Supported in part by grants from the NIH
(CA69579) and the Lance Armstrong Foundation (LBM).
Received Sept 3, 2008, and in revised form April 16, 2009.
Accepted for publication April 16, 2009.
S77
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S77–S85, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.04.093](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-77-320.jpg)
![increased cardiac mortality risk (RR = $2.5) associated
with left-sided and internal mammary nodal (IMN) RT. Ret-
rospective population-based investigations have compared
mortality endpoints by laterality of RT vs. surgical controls
(6–8). Some investigations have shown an increased risk of
cardiac mortality (hazard ratio [HR] = $ 1.5) for left-sided
vs. right-sided cancers treated with RT in the 1970s, but not
with more modern RT techniques (7, 9, 12).
For cardiac morbidity endpoints there is an increase in
CAD and/or non-fatal MI with left-sided RT compared
with either right-sided RT or no RT (6, 9–13). In two pro-
spective studies and one retrospective study subclinical end-
points of perfusion defects have been assessed, but their
clinical significance is still uncertain (11, 14, 15). At Stan-
ford, children and adolescents with Hodgkin’s lymphoma
(HL) who underwent mediastinal RT had an increased RR
for death from heart disease (RR = 28–37) (16). In the ex-
tended analysis including 2,232 patients of all age groups,
the RR for death from acute MI was 3.2 (17). The elevated
risk, already significant in the first 5 years, remained elevated
throughout the follow-up period (20 years); the average in-
terval to MI was 10.3 years. In a recent study with 7,033 pa-
tients, the RR for lethal MI was 2.5 (18). In another analysis,
mediastinal RT for HL had a greater likelihood of causing
right coronary or left main or left anterior descending coro-
nary artery lesions compared with circumflex lesions, possi-
bly because of the location of the former (19). These studies
generally included patients treated with doses $30 Gy. In the
Stanford data, CAD risk was much reduced at doses #30 Gy.
Congestive heart failure
Two retrospective studies evaluating CHF among irradi-
ated breast cancer patients yielded conflicting results
(10, 12). In the Stanford data on 2,232 HL patients, the RR
of death from cardiac causes other than MI decreased with
use of subcarinal blocking from 5.3 to 1.4 (17). Adams
et al. reported findings suggesting a greater impact on
diastolic than systolic dysfunction in their investigation of
48 long-term survivors of childhood HL treated with mantle
irradiation (median, 40 Gy) (20).
Valvular disease
For breast cancer patients, data are conflicting regarding
the association of RT with valvular dysfunction. In a large
study in the Netherlands the risk of valvular dysfunction
was higher in the group receiving IMN RT vs. the group
with no RT (HR = 3.17) (12), but this was not demonstrated
in a smaller study (10).
In HL patients, valvular abnormalities include both insuf-
ficiency and stenosis, the former being more common and
less clinically relevant. Incidence of left-sided valvular re-
gurgitation ranges from 16% to 40% (vs. 2% in controls)
(21, 22). Data from Stanford on 294 asymptomatic HL survi-
vors treated with a mantle technique at a mean dose of 43 Gy
showed a 34-fold increased risk of aortic regurgitation (abso-
lute incidence, 26.1%) (23).
3. CHALLENGES IN DEFINING VOLUMES
Delineation of the clinically relevant subregions of the
heart is challenging because their structural definition
through the current devices used in treatment planning
(e.g., computed tomography [CT]) is imprecise. No imaging
modality clearly shows these structures. The heart border
may be difficult to differentiate from liver and diaphragm,
but the segmenting of the superior border with the large
vessels can be more challenging. The heart moves with the
respiratory and cardiac cycles: the degree of motion, mainly
in the superior–inferior direction, is modest with free breath-
ing (24). Furthermore, the anatomy of the great vessels as
they intersect the heart is complex. Newer imaging tools,
such as magnetic resonance imaging, may be able to better
identify cardiac subregions, but their application to RT
planning is still limited.
Cardiac structures can be defined anatomically and/or
based on functionality; this can be problematic because of
the anatomic/functional complexities, the interactions of the
various structures such as the ventricles, valves, vasculature
and their overlying anatomy. Uncertainties remain regarding
which region of the heart is functionally most important for
RT-induced toxicities.
Three main clinical endpoints have been considered in the
study of specific dose–volume response relationships: mor-
tality from ischemic heart disease, pericarditis, and decreased
myocardial perfusion. For these analyses, the volumes con-
sidered were either the entire heart (25), pericardium (26,
27), or the left ventricle alone (28) (Tables 2–4). Because cor-
onary/ischemic events are a major concern, several investiga-
tors have calculated doses to potentially relevant
Table 1. Endpoints related to radiation-induced heart disease
Regional endpoints Global endpoints
Subclinical Localized imaging abnormality (e.g., perfusion defect or
regional wall motion abnormality)
Myocardial fibrosis
Global imaging abnormality (e.g., diffuse hypocontractility)
Asymptomatic decline in ejection fraction
Clinical Coronary artery disease
Myocardial infarction
Valvular disease
Congestive heart failure
Pericarditis/pericardial effusion
Arrhythmia
Autonomic dysfunction (monotonous heart beat responding to
changes in hemodynamic requirements)
S78 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-78-320.jpg)
![dependence. A joint analysis of the breast cancer and Hodg-
kin’s material (50, 51) yielded higher D50 (i.e., dose giving
50% of complication probability) and a lower g (steepness)
values than in the breast analysis (Fig. 1); note that different
parts of heart are irradiated in the two situations.
Carr et al. examined the long-term outcomes of patients
treated for peptic ulcer disease between 1937 and 1965 using
(typically) orthovoltage RT, with the field including a portion
of the cardiac apex (estimated 5% of heart volume) but only
a small part of the coronary vessels (52). The RR of coronary
artery disease was increased in patients in whom the (in-field)
cardiac apex dose exceeded $12 Gy, corresponding to an
estimated mean heart dose 2.6 Gy. Similarly, in 4,414 breast
cancer survivors with a minimum of 10 years of follow-up
treated between 1970 and 1986, the risk of cardiovascular dis-
ease was found to increase with mean cardiac doses (12). The
maximum heart distance (MHD), that is, the maximum dis-
tance from the posterior edge of the tangent field to the heart
contour, has been proposed as a surrogate for the irradiated
heart volume in the high-dose region in patients treated with
tangential fields (53). However, in 1,601 breast patients with
0 to 24 years (median, 16 years) of follow-up, there was no
clear association between the MHD and cardiovascular disease
risk; the potential role of low heart doses was discussed (13).
Cardiac perfusion defects
Extensive analysis of perfusion defects induced by radio-
therapy in the left ventricle have been prospectively carried
out in a group of 73 breast cancer patients (Table 4). Subclin-
ical injury, inferred from abnormalities on regional myocar-
dial perfusion imaging tests, occurred in a volume-
dependent manner: an incidence of 20% was found for tan-
gential fields including 5% of the LV vs. 50% with 5%
LV volume (54). Two NTCP models (LKB and relative
seriality[RS]) were fitted to the data (28). A serial behavior
of the LV is suggested by the fit with the RS model; however,
the D50 values obtained from the two fits were mutually
inconsistent. The clinical siginificance of these perfusion
defects has not been clearly established (54).
7. SPECIAL SITUATIONS
Several aspects, both general and heart specific, have to be
considered when applying NTCP models and dose–volume
constraints to clinical treatment planning.
First, there are anatomical and functional considerations in
defining the organ or parts of the organ at risk, e.g., heart vs.
pericardium vs. coronary vessels. For example, applying peri-
carditis NTCP parameters obtained from the pericardium dose
distribution to the whole heart is more acceptable in a calcula-
tion and/or comparison exercise than in clinical situations. The
recent study by Wei et al. suggests that clinical data on pericar-
dial effusions are better correlated with parameters derived
from the dose–volume histograms (DVHs) of the pericardium
than with those of the whole heart (27).
Second, the irradiated heart in patients with breast cancer is
at or beyond the field edges. In these volumes, the accuracy of
the dose calculations varies between different treatment plan-
ning systems (TPS) (55) and influences NTCP modelling,
due to the differences in heart dose calculated; even small dif-
ferences might be relevant if NTCP should be kept low.
Third, if inhomogeneity corrections for the low density of
lung tissue are not made in the treatment plan, the heart dose
is underestimated, thus affecting the evaluation of the dosi-
metric predictors (56).
Fourth, because of differences in setup accuracy, the
planned and actual cardiac exposures can vary, with implica-
tions for the estimated NTCP (57).
Fifth,theparametersderivedforthevariousmodelsarebased
on limited clinical data in a reduced number of diseases and
which generally do not involve a wide range of fraction sizes.
Therefore, these models may not be applicable in the evolving
era of hypofractionation and in a broader range of diseases.
Finally, concerning the applicability of the results obtained,
the main criterion remains diagnosis. Dosimetric modeling
data may be most applicable in the disease setting from which
they were derived. For example it may be questionable to ap-
ply results based on Hodgkin’sdisease studies to breast cancer
cases, considering the different irradiated volumes.
8. RECOMMENDED DOSE/VOLUME LIMITS
Radiation-induced cardiac complications have different
significance and implications depending on the clinical
scenario. As such constraints/NTCP values can be used
only for guidance; they must always be considered in relation
to probability of tumor control and the specific patient
Fig. 1. Dose–response curves for long-term cardiac mortality based
on Hodgkin’s disease (HD) and breast cancer data sets. From Eriks-
son et al. (51), with permission. Curves were obtained by fitting, re-
spectively, Stockholm and Oslo breast cancer trials data (25)
(denoted ‘‘Breast’’ in the figure); data from a patient cohort treated
for HD (denoted ‘‘Hodgkin’’), the joint material (denoted ‘‘Hodgkin
+ Breast’’). Plotted curve corresponds to a uniform irradiation of one
third of the heart volume, in the interval of the clinical data. Param-
eter values are also reported. Note that in the interval of the clinical
and dosimetric data of interest, the curve from breast data only is
much steeper than the other curves.
S82 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-82-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Thorax: Esophagus
RADIATION DOSE-VOLUME EFFECTS IN THE ESOPHAGUS
MARIA WERNER-WASIK, M.D.,* ELLEN YORKE, PH.D.,y
JOSEPH DEASY, PH.D.,z
JIHO NAM, M.D.,x
AND LAWRENCE B. MARKS, M.D.x
*Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA; y
Department of Radiation Oncology,
Memorial Sloan-Kettering Cancer Center, New York, NY; z
Department of Radiation Oncology, Washington University School of
Medicine, St. Louis, MO; x
Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC
Publications relating esophageal radiation toxicity to clinical variables and to quantitative dose and dose–volume
measures derived from three-dimensional conformal radiotherapy for non–small-cell lung cancer are reviewed. A
variety of clinical and dosimetric parameters have been associated with acute and late toxicity. Suggestions for fu-
ture studies are presented. Ó 2010 Elsevier Inc.
Esophagitis, Lung cancer, Radiotherapy, Esophagus, Toxicity.
1. CLINICAL SIGNIFICANCE
Acute esophagitis (occurring #90 days after treatment in-
itiation) is a common side effect of patients undergoing
radiotherapy (RT) for thoracic tumors. Concurrent chemora-
diotherapy (CCT) or hyperfractionation results in a 15–25%
rate of severe (Radiation Therapy Oncology Group [RTOG]
Grade 3 or greater) acute esophagitis (1–3) that can require
hospitalization, invasive diagnostic tests (e.g., endoscopy),
surgical intervention (e.g., percutaneous endoscopic gastro-
stomy tube) or RT breaks that could lower local tumor
control.
Late injury is less commonly reported, perhaps because the
patients might not live long enough to manifest toxicity (e.g.,
the disease-specific survival is relatively short for many tho-
racic cancers). Dose escalation of standard fractionated RT
and hypofractionated RT regimens (4, 5) can increase the
risk of late esophageal toxicity, especially if the survival rates
improve. Esophageal stricture often requires periodic dila-
tion, usually with good results (6). Death related to late
esophageal injury (e.g., tracheoesophageal fistula or esop-
hageal perforation) has been reported in only 0.4–1% of
patients (7, 8).
2. ENDPOINTS
The assigned toxicity grade varies with the scoring system
used, making interstudy comparisons challenging. In general,
Grade 1 toxicities cause minor changes in a patient’s lifestyle,
and Grade 2 or greater toxicities might require medical inter-
vention. The currently accepted grading system is the Com-
mon Terminology Criteria for Adverse Events, version 3
(9); however, the studies cited in the present report mostly
used the RTOG scoring system. In the present review, Grade
2 or greater acute esophagitis (because it constituted the end-
point of many studies) and any late esophagitis (Grade 1 or
greater), independent of the duration of the late symptoms,
were considered clinically significant.
Acute esophagitis occurs during RT and often persists for
several weeks after RT. The symptoms of severe esophagitis
(Grade 3 or greater) typically peak 4–8 weeks from the begin-
ning of RT (10). Late esophageal damage, typically stricture
and associated dysphagia, develops $3–8 months (range, 5–
40) after RT (11). Abnormal esophageal motility can be
noted within 3–4 weeks from RT alone and as early as 1
week after starting concurrent chemoradiotherapy (12).
Some of the pitfalls in assigning the acute esophagitis
grade are as follows:
1. Esophageal infection can mimic treatment (RT or concur-
rent chemoradiotherapy)-related esophagitis. Candidiasis
(usually suggested by co-existing oral candidiasis) or,
rarely, herpes simplex esophagitis are the main culprits.
2. Pre-existing gastroesophageal reflux can worsen the
symptoms of esophagitis and should be treated. Constant
burning, unrelated to the act of swallowing, and localized
in the lower part of the esophagus is more likely related to
the reflux than to the treatment-related esophagitis.
Reprint requests to: Maria Werner-Wasik, M.D., Department of
Radiation Oncology, Thomas Jefferson University Hospital,
111 S. 11th St., Philadelphia, PA 19107-5097. Tel: (215) 955-
6702; Fax: (215) 955-0412; E-mail: maria.werner-wasik@
jeffersonhospital.org
Conflict of interest: none.
Received Nov 10, 2008, and in revised form April 30, 2009.
Accepted for publication May 2, 2009.
S86
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S86–S93, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.05.070](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-86-320.jpg)
![3. Incidental irradiation of the stomach, and associated gas-
tritis symptoms, can occur when a lower lobe lung mass
has been treated.
4. The assignment of Grade 2 (brief intravenous fluid for
#24 hours) vs. Grade 3 (hospitalization) esophagitis
might be physician-dependent.
3. CHALLENGES DEFINING VOLUMES
The adult esophagus length is z25 cm and is defined by its
external contour on axial computed tomography (CT) im-
ages. The esophagus remains closed when not involved in
swallowing, and its lumen is often not easily identifiable
throughout its entire length, particularly in the middle and
caudal levels. Administration of a thick barium paste can
help localize the esophagus, but the swallowing times are
short (10 seconds), and the barium paste might not fully opa-
cify the entire organ. In addition, high-contrast barium can af-
fect the heterogeneity-corrected dose calculations. It is
recommended that the entire length of the esophagus, from
the cricoid cartilage to the gastroesophageal junction, be
identified, requiring that a portion of the neck and upper ab-
domen be included in the planning CT scan. In some of the
studies (8, 11, 13), the cephalad (‘‘cervical’’) esophagus
was not included, causing the absolute esophageal volume
to be $20% smaller than if its entirety had been contoured.
The esophagus is slightly mobile. In a study of 29 patients
undergoing four-dimensional CT scans three times during
RT, the cephalad, middle, and caudal esophagus can move
#5, 7, and 9 mm in the combined anteroposterior and cranio-
caudal directions, respectively (14). Thus, dose–volume
analyses using the planning CT scan (as was done in the stud-
ies we reviewed), could have some inaccuracies, although no
specific margin recommendations can be given at this time.
The esophageal circumference varies markedly on sequen-
tial axial CT images, a reflection of the swallowing act. This
appearance does not reflect the anatomic reality of a relatively
uniform circumference (15). Thus, conventional dose–vol-
ume histograms (DVHs) might not accurately reflect the par-
tial volume doses. In the single study to consider this issue, the
predictive value of metrics that were ‘‘corrected’’ for this an-
atomic reality were slightly better predictors of outcome than
were the ‘‘traditional’’ DVH-based metrics (15). Neverthe-
less, the use of alternative three-dimensional dosimetric pa-
rameters (e.g., dose–surface-area, dose–circumference
histograms, ‘‘anatomically corrected’’ DVHs) as improved
predictors of outcome is of unclear utility (11, 15, 16).
4. REVIEW OF DOSE–VOLUME PUBLISHED DATA
A total 12 studies published between 1999 and January
2009 that assessed the dose–volume outcome in $90 patients
treated for non–small cell lung cancer were reviewed (7, 8,
11, 13, 16–19, 20–23) (Table 1). All but one study (17)
used three-dimensional planning. The endpoint was usually
RTOG Grade 2 or greater or Grade 3 or greater. Two studies
(7, 8) combined acute and late toxicities in a single analysis.
The others either analyzed only acute (13, 16, 17, 19, 20, 22,
23) or analyzed acute and late toxicity separately (11, 18).
The studies found a correlation with these endpoints for a va-
riety of dose–volume factors.
The maximal esophagus dose had significant univariate
correlation (p # .05), with severe esophagitis in all the stud-
ies that included it as a variable (7, 8, 11, 13, 20). However, it
only remained significant in multivariate analyses in some of
them (7, 8, 11).
Ten studies (8, 13, 16, 18, 19–24) searched for correlations
between severe acute esophagitis and either the absolute vol-
ume (aVdose), absolute area (aAdose), or percentage of a refer-
ence volume (Vdose), or reference area (Adose) receiving more
than a specified dose. Eight of these studies (13, 16, 19–24)
found significant univariate correlations with exposure over
a wide dose range (10–80 Gy; Table 1 and Fig. 1). Multivar-
iate analysis (16, 19, 20, 22, 24) identified fewer dose–vol-
ume combinations. Because of the diverse reporting
metrics, we could not find a consensus for the dose–volume
thresholds. For example, one study (19) found V35 was the
only dosimetric predictor of RTOG Grade 2 or greater acute
esophagitis on multivariate analysis, both with and without
CCT, and another study (22) found V20 to be the only multi-
variate significant factor for 215 patients receiving CCT.
However, a third study (16) found a much greater dose region
(aA55 and aA80 or aV60 and aV80) to be significant.
Some studies found circumferential metrics (e.g., esopha-
geal length receiving full circumference dose 40–66 Gy
[19] or 50–65 Gy [11]) to be significant, although not supe-
rior to simpler volume or area metrics.
Four studies (7, 8, 11, 22) found a univariate correlation
with the mean dose greater than levels ranging from 34 Gy
(7) to 40 Gy (8). A 34-Gy mean dose recommendation was
adopted in the RTOG Phase III comparison of 60 Gy vs.
74 Gy with CCT in Grade III non–small-cell lung cancer
(RTOG 0617).
Dose–volume histogram parameters describing cumula-
tive dose 50 Gy have been identified as highly statistically
significantly correlated with acute esophagitis in several stud-
ies. Some studies (Fig. 1), however, have shown the strongest
statistically significant correlations with esophagitis at lower
doses (as low as V30), perhaps owing to technique differ-
ences. V30 was also implicated in a multivariate modeling
study by El Naqa (21). Overall, the data are consistent with
some risk of acute esophagitis at intermediate doses (30–50
Gy) and an increasing effect for greater doses.
A main obstacle to obtaining definitive dosimetric recom-
mendations from the published data is the variety of volumet-
ric metrics—the absolute volume or area, relative volume or
area, and circumferential measures—all have been analyzed.
Reports describing relative metrics might have used different
reference volumes (9, 13). Differences in the way other tech-
nical factors were handled have less effect. For example, ad-
justing DVHs for conventional fraction size and the type of
tissue heterogeneity correction used are likely to have only
minor effect, the latter because the esophagus is embedded
in bulky soft tissue and anteroposterior/posteroanterior
Dose–volume effects in esophagus d M. WERNER-WASIK et al. S87](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-87-320.jpg)
![Table 1. Summary of large published series investigating treatment-related esophagitis in patients with NSCLC
Series/investigator Patients (n)
Prescription dose (Gy)
range [median]*
(special
fractionations) CCT (%) Endpointy
(rate)
Univariate
significant
factors
Multivariate
significant
factors
Duke/Maguire et al.
(18), 1999
91 64–86 [79]z
(64%
twice daily, 1.25–1.6
Gy/fx)
47 Acute G $3 (G3,
11%; G4-5, 0%)
None None
Any late,x
18% (G1,
9%; G2, 6%; G3,
3%)
V50, A50, length of
100%
circumference 50
Gy
Gender, pre-RT
dysphagia, V50,
maximum
percentage of
circumference 80
Gy
Thomas Jefferson/
Werner-Wasik et al.
(17), 2000{
105 45–70 [60] (7% twice
daily)jj
,#
55 Acute G $3 (G3,
12%; G4, 1%)
CCT, twice-daily
treatment, female
gender
CCT, twice-daily
treatment
Washington
University/Singh
et al. (7), 2003
207 60–74 [70]** 25.6 Acute G $3 (G3,
4.3% G4, 0.5%)
and/oryy
late G $3
(G3, 4.8%; G4,
0.5%; G5, 0.5%)zz
CCT, Dmax $58 Gy,
mean dose 34 Gy,
subcarinal nodes,
race
CCT, Dmax $58 Gy
Washington
University/Bradley
et al. (16), 2004xx
166 60–74 [70]{{
24.7 Acute G $2 (G2,
22.3%; G3, 4.2%;
G4, 0.6%)
CCT, aA range
(aA5–aA70),
aA55
jjjj
, aV range
(aV5–aV70), aV60
jjjj
CCT and aV60; CCT,
aV60, and aV80;
CCT and aA55;
CCT, aA55, and
aA80 ‘‘volume and
area equally
predictive’’
Duke/Ahn et al. (11),
2005##
254 30–86 [66]xx
(39%
twice daily, 1.25–1.6
Gy/fx)
12.6 Acute G $3 (G3,
8.7%; G4, 0.4%)
Twice daily; nodal
stage; pretreatment
dysphagia; Dmax;
mean dose; V50;
length of 50%,
75%, or 100%;
circumference $50
Gy; maximal
percentage
circumference $50,
60, 70 Gy
Twice daily RT, nodal
stage, pretreatment
dysphagia
Any latex
(G2, 2%;
G3, 2%; G4, 1%)
Length with 75%
circumference $70
Gy, length with
100%
circumference $50,
55 Gy; maximal
percentage
circumference
$60–80 Gy
Previous acute
toxicity dominated
all dosimetric
factors
NKI/Belderbos et al.
(19), 2005
156 Group 1 (n = 88), 50–
95 at 2.25/fx#,***,yyy
Group 2 (n = 68), 66
at 2.75/fx#,***
23.7zzz
Acute G $2 (G2,
20%; G3, 6%; G4,
0.6%)
Lyman NTCPxxx
,V
range (V20–V60);
V35
jjjj
, percentage
of length, 100%;
circumference $40
Gy or $66 Gy;
treatment group
(column 3); CCT
worse than
sequential C/RT or
RT only; sequential
C/RT worse than
RT alone; T stage
and nodal stage;
age{{{
V35, CCT
(Continued)
S88 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-88-320.jpg)
![beams are the main component in many treatment plans. Sev-
eral studies have provide enough information to estimate the
incidence of esophagitis to dosimetric parameters (Fig. 2).
There does appear to be a dose–response relationship, al-
though the interstudy variations have been large. Neverthe-
less, the data are somewhat consistent, with rates of acute
Grade 2 or greater esophagitis increasing to 30% as V70 ex-
ceeds 20%, V50 exceeds 40%, and V35 exceeds 50%.
Table 1. Summary of large published series investigating treatment-related esophagitis in patients with NSCLC (Continued)
Series/investigator Patients (n)
Prescription dose (Gy)
range [median]*
(special
fractionations) CCT (%) Endpointy
(rate)
Univariate
significant
factors
Multivariate
significant
factors
University of
Michigan/Chapet
et al. (13), 2005
101 65–103#,***,yyy
0 Acute G $2 (G2,
13%; G3, 3%)
Nodal stage, V range
(V40–V70), Dose-
percentage volume
range (D5–D60),
D30
jjjj
, D1 cc, 2.5
cc, 5 cc
Lyman model NTCP
with study-specific
parameters
Goyang/Kim et al.
(20), 2005
124 54–66 [60]#,***
60 Acute G $3-4 (G3,
12%; G4, 0.8%)
CCT, V range (V58–
V63), Dmax,
Lyman model
NTCP (Burman
et al. [24]
parameters)
CCT, V60 (in patients
with CCT)
Harbin University/
Qiao et al. (8), 2005
208 60–72 [70]** 26 Acute G $3 (G3, 5%;
G4, 0.5%; G5, 1%)
and/or late G $3
(G3, 5%; G4, 0.5%)
CCT, Dmax $60 Gy,
mean dose $40 Gy,
subcarinal lymph
nodes
CCT, Dmax $60 Gy
MDACC/Wei et al.
(22), 2006
215 60–70 [63]***
(16% twice daily,
1.2 Gy/fx)
100 Acute G $3jjjjjj
(G3,
20%; G4, 0.5%)
aV range (aV15–V45);
V range (V10–V45);
mean dose $34.5
Gy
V20
Barcelona/Rodriquez
et al. (23), 2009
100 55–65 [62] 100 Acute G $1 (G2,
29%; G3, 4%)
esophagitis
index###
V50–V55 NA
Abbreviations: NSCLC = non–small-cell lung cancer; CCT = concurrent chemotherapy; fx = fraction; G = grade; Vdose (e.g., V20) = relative
volume receiving specified dose or more (e.g., $ 20 Gy); RT = radiotherapy; Dmax = maximal dose; Adose = relative surface area receiving
specified dose or greater; aVdose, aAdose = absolute volume (V) or area (A) receiving specified dose or greater; D# = dose encompassing hottest
percentage of esophagus. D #cc = dose encompassing hottest cubic centimeters of esophagus; NTCP = normal tissue complication probability;
RTOG = Radiation Therapy Oncology Group.
* All doses at standard fractionation of 1.8–2.2 Gy/d, 5 d/wk, unless otherwise stated.
y
Unless otherwise specified, RTOG grading was used; RTOG Grade 2, moderate dysphagia or odynophagia, requiring narcotic agents or
liquid diet; RTOG Grade 3, severe dysphagia or odynophagia with dehydration or weight loss, requiring nasogastric feeding.
z
Clinical calculations and prescriptions done without inhomogeneity correction; doses for study retrospectively corrected for inhomogeneity
and tabulated above.
x
Late complications determined from fraction of patients assessable for late toxicity.
{
No three-dimensional conformal RT but correlation with irradiated esophagus length inferred from length of spine in field was investigated.
jj
All twice-daily patients also underwent CCT.
#
Doses were fraction size-corrected using linear-quadratic model and a/b = 10 Gy.
** Doses reported without tissue heterogeneity correction.
yy
Acute and Late complications analyzed together.
zz
Percentage of late complications from raw numbers (e.g., 4.8% = 10 patients of 207 patients).
xx
Same patients analyzed by El Naqa et al. (21).
{{
Various treatment techniques and fractionation schedules used; most common was standard fractionation for 45 Gy to clinical target vol-
ume with cone-down to 66 Gy total to gross target volume; dose range quoted was overall dose to isocenter, corrected for tissue heterogeneity.
jjjj
Lowest p value.
##
Some patients analyzed by Ahn et al. (10) were also analyzed by Maguire et al. (18).
*** Doses were heterogeneity corrected.
yyy
Esophagus constraint on treatment plan.
zzz
All CCT patients were in 66-Gy group, a randomized trial of concurrent vs. sequential chemotherapy; they constituted 54% of that group
but only 23.7% of total.
xxx
Found Lyman NTCP model parameters that gave visually good fit to data; significance not stated.
{{{
Not specified whether toxicity was more likely at older age.
jjjjjj
Grading by institutional modification of RTOG.
###
See Rodriguez et al. (23) for definition.
Dose–volume effects in esophagus d M. WERNER-WASIK et al. S89](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-89-320.jpg)
![5. FACTORS AFFECTING RISK
Greater acute esophagitis rates are seen with increased RT
aggressiveness (e.g., hyperfractionation, concurrent boost),
the addition of CCT, and several clinical factors (e.g., pre-ex-
isting dysphagia and increasing nodal stage, with the latter
likely a surrogate for larger tumors; Table 1). The incidence
of Grade 3 or greater acute esophagitis is z1% for patients
treated with once-daily RT alone. It is markedly increased
with the addition of CCT (incidence, 6–24%) and is as great
as 49% with concurrent gemcitabine. The Continuous Hyper-
fractionated Accelerated Radiation Therapy regimen (25) re-
ported a 19% rate of severe (Grade 3 or greater) esophagitis.
Older patients (70 years of age) were more likely than youn-
ger patients to experience high-grade esophagitis in a second-
ary analysis of the RTOG 94-10 study (26).
Several studies have assessed the putative radioprotector
amifostine. Three single-institution Phase III studies (27–
29) suggested a significant benefit (27, 28) or a trend (29)
for amifostine in lowering Grade 2 or greater esophagitis.
However, the findings are difficult to interpret because of
the small patient numbers and low (28) or unknown (27) in-
cidence of Grade 3 or greater esophagitis. These results were
not confirmed in a large cooperative group Phase III random-
ized study of 243 patients (RTOG trial 98-01) (30).
6. MATHEMATICAL/BIOLOGIC MODELS
Statistical models
The statistical level of correlation between a complication
and a set of variables is inadequate for treatment planning
purposes. Statistical models aim to supply the missing link.
They use the most significant dose–volume or dose–area var-
iable and medical factors (e.g., CCT) as variables in a sigmoi-
dal function. The typical functional form is
%NTCP ¼ 100 exp½c0 þ ccctCCT þ SiðciVdoseiÞŠ=
½1 þ expðc0 þ ccctCCT þ Si½ciVdoseiŠÞ :Š
The summation (symbolized by Si) represents a weighted
combination of the patient-specific values of the significant
dose–volume variables, Vdosei. CCT can be handled by an
extra term or by having different sets of coefficients for pa-
tients with and without CCT. The model coefficients, ci,
are chosen to best match the observed complication rates,
and coefficient values are given in the cited studies. The sim-
plest models (probably too simple) use a single dose–volume
variable (e.g., V35 [19], V20, or mean dose [22]). Others use
several DVH-based variables (e.g., a four-variable model
[21] selected absolute area points with doses from 30 to 85
Gy). Such statistical models are more sensitive to the DVH
shape than those based on a single Vdose point.
Lyman-Kutcher-Burman model
Two recent studies (13, 19) used the maximum likelihood
method to find the Lyman-Kutcher-Burman model parame-
ters that correlated well with the incidence of Grade 2 or
greater acute esophagitis in their respective populations of
Fig. 1. Correlations between acute esophagitis and Vx values (vol-
ume greater than x Gy). p Values correlated with relative or absolute
volumes (in cubic centimeters); relative volumes used except as
noted for 2006 data from Wei et al. (22). Lower values indicate bet-
ter correlations with outcomes. As the wide variety of correlation
shapes suggests, there does not appear to be any singular ‘‘thresh-
old’’ dose above which a toxic effect is observed.
Fig. 2. Incidence of acute esophagitis according to Vx (volume re-
ceiving more than x Gy). x-Axis values estimated according to range
of doses reported. Each curve annotated as follows: Vdose (investiga-
tor, number of patients, percentage with concurrent chemotherapy
[CCT]. Percentage of patients who received sequential chemother-
apy in studies by Ahn et al. (11), Belderbos et al. (19), and Kim
et al. (20) was 44%, 38%, and 15%, respectively. Data for V50
(Ahn et al. [11]) at 15, 45, and 75 Gy represent reported rates of
Grade 2 or greater acute esophagitis plotted in dose bins at 30%,
30–60%, and 60%, respectively. Similarly, for V70 (Ahn et al.
[11]), V50 (Rodriguez et al. [23]), and V60 (Kim et al. [20]), each
symbol represents rates of acute esophagitis at 10% vs. 11–30%
vs. 31–64%, and #30% vs. $30%, and #30 vs. 30%, respec-
tively. Dashed horizontal lines reflect dose ranges ascribed to each
data point. Upper x-axis range of greatest data point for V50 (Rodri-
guez et al. [23]), V50 (Ahn et al. [11]), and V60 (Kim et al. [20]), are
indefinite according to data (light-gray dotted bars). Solid and open
symbols represent reported rates of Grade 2 or greater acute esoph-
agitis and Grade 3 or greater acute esophagitis, respectively. Thicker
and thinner solid lines represent higher and lower doses of Vx, re-
spectively (i.e., thicker line for V70 and thinner line for V20).
S90 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-90-320.jpg)
![therapy, usually well before the total dose has been delivered.
Complication models could potentially be constructed on the
basis of the dose accumulated each week and the total dose.
Thus, the data analysis would not be a continual cycle of hy-
pothesis/model generation, such as is commonly the case to-
day.
Peer-reviewed treatment planning and outcomes data
should be pooled and made permanently available. This
might enable a single analysis to confidently uncover the fac-
tors that lead to such an array of dose–volume correlations,
such as seen in Fig. 1, to derive robust parameter sets for
the Lyman or relative seriality models or to derive new semi-
mechanistic models.
The exclusion of the entire esophageal length/volume from
the high-dose radiation region is extremely difficult; how-
ever, reducing the radiation dose delivered to a part of esoph-
ageal circumference might be feasible. Intensity-modulated
RT seems well suited for that purpose, with its ability to de-
liver concave-shaped RT dose distributions around organs at
risk (39). Studies to better understand the importance of the
spatial distribution of the dose (and hence the utility of partial
circumferential sparing) would be useful.
Additional study is needed to understand the utility of ra-
dioprotectors.
A prospective assessment of the dose and volume and
other factors relating to esophageal injury after hypofractio-
nation is needed, given the growing interest in this approach.
The identification of biologic markers of radiation sensitiv-
ity will be important to explain individual variations in pa-
tients’ reactions.
10. TOXICITY SCORING
We recommend that the Common Terminology Criteria
for Adverse Events, version 3, be used to score both acute
and late injury. It is simple and consistent, and its use has
been mandated by the National Cancer Institute in the coop-
erative group trials since October 2003 (40). Late injury
might be scored under several endpoints, including necrosis,
obstruction, perforation, or stricture, depending on the pa-
tient’s symptoms.
REFERENCES
1. Curran W Jr., Scott C, Langer C, et al. Phase III comparison of
sequential vs. concurrent chemoradiation for patients with unre-
sected stage III non-small cell lung cancer: Initial report of
RTOG 9410. Proc ASCO 2000;19:484a.
2. Furuse K, Fukuoka M, Kawahara M, et al. Phase III study of
concurrent vs. sequential thoracic radiotherapy in combination
with mitomycin, vindesine, and cisplatin in unresectable stage
III non-small cell lung cancer. J Clin Oncol 1999;17:2692–
2699.
3. Cox JD, Pajak TF, Asbell S, et al. Interruptions of high-dose ra-
diation therapy decrease long-term survival of favorable pa-
tients with unresectable non-small cell carcinoma of the lung:
Analysis of 1244 cases from 3 RTOG trials. Int J Radiat Oncol
Biol Phys 1993;27:493–498.
4. Timmerman R, McGarry R, Yiannoutsos C, et al. Excessive
toxicity when treating central tumors in a phase II study of ste-
reotactic body radiation therapy for medically inoperable early-
stage lung cancers. J Clin Oncol 2006;24:4833–4839.
5. Onishi H, Shirato H, Nagata Y, et al. Hypofractionated stereo-
tactic radiotherapy (HypoFXSRT) for stage I non-small cell
lung cancer: Updated results of 257 patients in a Japanese
multi-institutional study. J Thoracic Oncol 2007;2(7 Suppl.
3):S94–S100.
6. Choi GB, Shin JH, Song HY, et al. Fluoroscopically guided bal-
loon dilation for patients with esophageal stricture after radia-
tion treatment. J Vascular Intervent Radiol 2005;16:1705–1710.
7. Singh AK, Lockett MA, Bradley JD. Predictors of radiation-in-
duced esophageal toxicity in patients with non-small cell lung
cancer treated with three-dimensional conformal radiotherapy.
Int J Radiat Oncol Biol Phys 2003;55:337–341.
8. Qiao W-B, Zhao Y-H, Zhao Y-B, et al. Clinical and dosimetric
factors of radiation-induced esophageal injury: Radiation-in-
duced esophageal toxicity. World J Gastroenterol 2005;11:
2626–2629.
9. CTC/CTCAE Codes. Available from: www.ctep.info.nih.gov/
reporting/ctc.html. Last accessed December 15, 2009.
10. Werner-Wasik M, Scott C, Curran WJ Jr., et al. Correlation be-
tween acute esophagitis and late pneumonitis in patients (pts)
with locally advanced non-small cell lung cancer (LA-NSCLC)
receiving concurrent thoracic radiotherapy (RT) and chemo-
therapy: A multivariate analysis of the Radiation Therapy On-
cology Group (RTOG) database [Abstract]. Proc ASCO 2002;
21:299a.
11. Ahn S-J, Kahn D, Zhou S, et al. Dosimetric and clinical predic-
tors for radiation- induced esophageal injury. Int J Radiat Oncol
Biol Phys 2005;61:335–347.
12. Goldstein HM, Rogers LF, Fletcher GH, et al. Radiological
manifestations of radiation-induced injury to the normal upper
gastrointestinal tract. Radiology 1975;117:135–140.
13. Chapet O, Kong F-M, Lee JS, et al. Normal tissue complication
probability modeling for acute esophagitis in patients treated
with conformal radiation therapy for non-small cell lung cancer.
Radiother Oncol 2005;77:176–181.
14. Dieleman EMT, Senan S, Vincent A, et al. Four-dimensional com-
puted tomographic analysis of esophageal mobility during normal
respiration. Int J Radiat Oncol Biol Phys 2007;67:775–780.
15. Kahn D, Zhou S, Ahn S-J, et al. Anatomically correct dosimet-
ric parameters may be better predictors for esophageal toxicity
than are traditional CT-based metrics. Int J Radiat Oncol Biol
Phys 2005;62:645–651.
16. Bradley J, Deasy JO, Bentzen S, et al. Dosimetric correlates for
acute esophagitis in patients treated with radiotherapy for lung
carcinoma. Int J Radiat Oncol Biol Phys 2004;58:1108–1113.
17. Werner-Wasik M, Pequignot E, Leeper D, et al. Predictors of
severe esophagitis include use of concurrent chemotherapy,
but not the length of irradiated esophagus: A multivariate anal-
ysis of patients with lung cancer treated with non-operative ther-
apy. Int J Radiat Oncol Biol Phys 2000;48:689–696.
18. Maguire, Sibley GS, Zhou SM, et al. Clinical and dosimetric
predictors of radiation-induced esophageal toxicity. Int J Radiat
Oncol Biol Phys 1999;45:97–103.
19. Belderbos J, Heemsbergen W, Hoogeman M, et al. Acute esoph-
ageal toxicity in non-small cell lung cancer patients after high
dose conformal radiotherapy. Radiother Oncol 2005;75:157–164.
20. Kim TH, Cho KH, Pyo HR, et al. Dose–volumetric parameters
of acute esophageal toxicity in patients with lung cancer treated
with three-dimensional conformal radiotherapy. Int J Radiat
Oncol Biol Phys 2005;62:995–1002.
S92 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-92-320.jpg)
![three-dimensional conformal RT, and concurrent hepatic ar-
terial chemotherapy, demonstrated that small portions of the
liver can be irradiated to a very high dose (up to 90 Gy) if the
Veff was low (8). Mean liver dose was also a strong predictor
of RILD in the UM series (see ‘‘Mathematical/Biological
Models’’).
Dose–volume limit recommendations are discussed in the
Recommended Dose–volume Limits section. Regarding risk,
in general, the risks reported in the studies cited within this
review are realistic estimates, as the follow-up durations in
the studies are greater than the 3–4 months within which
RILD typically occurs.
5. FACTORS AFFECTING RISK
Preexisting liver dysfunction may render patients more
susceptible to RT-induced liver injury (Table 2). Patients
with Child-Pugh B or C scores have a higher risk of RT-re-
lated problems than those with Child-Pugh A scores (3,
18–20). Additional factors reportedly associated with a higher
risk of RILD include hepatitis B carrier status (21), prior
transcatheter arterial chemoembolization (18), concurrent
chemotherapy (8), portal vein tumor thrombosis (4, 18, 22),
tumor stage (18), male sex (8), and Cancer of the Liver Italian
Program staging system (18, 22).
Although it is likely that the risk of liver injury relates to
the dose per fraction received by portions of the liver, it is dif-
ficult to characterize the magnitude of any effect because
most series include patients treated within a narrow range
of dose per fraction. Furthermore, with any size fraction
given to the tumor, the adjacent normal liver receives a broad
range of doses because of beam entrance/exit zones and pen-
umbra, further complicating the analysis. The topic of dose
modeling is discussed further in Mathematical/Biological
Models, and the topic of hypofractionation is discussed fur-
ther in the Special Situations section.
6. MATHEMATICAL/BIOLOGICAL MODELS
The Lyman NTCP model has been applied by numerous
groups. From the series referenced in Table 2, the range of
estimates of the parameters generated among patients with
Child-Pugh A or better liver function and no HBV infection
are as follows: n, 0.86–1.1; m, 0.12–0.31; and TD50, 39.8–
46.1 Gy (8, 21). For patients with HBV or Child-Pugh B dys-
function, the ranges are: n = 0.26–0.7, m = 0.4–0.43, TD50 =
23–50 Gy (3, 21). These patients with worse liver dysfunc-
tion likely have lower TD50 values within the previous
range, though this needs to be clarified in future studies.
Analysis of UM patients treated for primary hepatobiliary
cancer or 98 metastases with concurrent continuous hepatic
arterial floxuridine (FUdR) or bromodeoxyuridine (BUdR)
and RT in twice daily 1.5 Gy fractions revealed a strong cor-
relation of RILD with the mean liver dose. No classic RILD
was observed when the mean liver dose was 31 Gy, with or
without chemotherapy. For patients treated with FUdR, the
mean liver doses associated with 5% risk of classic RILD
was 28 Gy for primary and 32 Gy for metastatic liver cancer
(corrected to 2 Gy fraction equivalent doses using the linear-
quadratic [LQ] model, assuming an a/b = 2 Gy). Based on
these observations and derived Lyman model parameter esti-
mates, the partial volume tolerance of the liver for a defined
allowable risk of RILD can be graphed (Figure 1) for a 5%
risk of RILD. With ‘‘n’’ of approximately 1 in the Lyman
NTCP model, a large volume effect is seen and a strong cor-
relation of NTCP with mean liver dose is revealed. Again
Table 2. Series of fractionated partial liver irradiation and rates of RILD
Study group n Diagnosis
Baseline
Child-Pugh score
Prescription dose
fractionation
Crude percent
RILD
Mean normal
liver dose in
patients with vs.
without RILD
Factors associated
with RILD
Michigan (8, 23) 203* PLC + LMC 203 A 1.5 Gy twice daily 9.4% (19/203) 37 Gy vs. 31.3 Gy PLC vs. LMC
mean liver dose
Taipei (20) 89y
HCC 68 A
21 B
1.8–3.0 Gy 19% (17/89) 23 Gy vs. 19 Gy HBV, liver
cirrhosis
Shanghai (3, 18) 109y
PLC 93 A
16 B
4–6 Gy 15.6% (17/109) 24.9 Gy vs. 19.9
Gy
Liver cirrhosis
Guangdong (20) 94** HCC 43 A
51 B
4–8 Gy 17% (16/94)
Note: 4 fatal
Not stated Liver cirrhosis
S. Korea (Seong,
Park) (21)
158y
HCC 117 A
41 B
1.8 Gy 7% (11/158) Not stated Dose
S. Korea (Kim) (4) 105y
HCC 85 A
20 B
2.0 Gy 12.3% (13/105) 25.4 Gy vs. 19.1
Gy
Total liver volume
receiving 30 Gy
or more above
60%
Abbreviations: HBV = hepatitis B viral infection; HCC = hepatocellular carcinoma; PLC = primary liver cancer; LMC = liver metastatic
disease; RILD = radiation-induced liver damage.
* Patients also received FUdR or BUdR; in this series the mean normal liver dose was calculated as corrected for 1.5 Gy twice-daily equiv-
alent dose, and the comparison of patients with vs. without RILD refers to the median value of mean normal liver dose, whereas for other series
the comparison is between the average (mean) of mean normal liver dose in each group.
y
At least 77% of patients in these series also received transarterial chemoembolization (TACE).
S96 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-96-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Abdomen: Kidney
RADIATION-ASSOCIATED KIDNEY INJURY
LAURA A. DAWSON, M.D.,* BRIAN D. KAVANAGH, M.D.,y
ARNOLD C. PAULINO, M.D.,z
SHIVA K. DAS, PH.D.,x
MOYED MIFTEN, PH.D.,y
X. ALLEN LI, PH.D.,jj
CHARLIE PAN, M.D.,#
RANDALL K. TEN HAKEN, PH.D.,#
AND TIMOTHY E. SCHULTHEISS, PH.D.**
*Department of Radiation Oncology, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada; y
Department of
Radiation Oncology, University of Colorado, Denver, CO; z
Department of Radiology, Division of Radiation Oncology, Baylor College
of Medicine and Methodist Hospital, Houston, TX; x
Department of Radiation Oncology, Duke University Medical Center, Durham, NC;
jj
Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI; #
Department of Radiation Oncology, University
of Michigan Medical School, Ann Arbor, MI; **Department of Radiation Oncology, City of Hope Medical Center and Beckman
Research Institute, Duarte, CA
The kidneys are the dose-limiting organs for radiotherapy to upper abdominal cancers and during total body ir-
radiation. The incidence of radiotherapy-associated kidney injury is likely underreported owing to its long latency
and because the toxicity is often attributed to more common causes of kidney injury. The pathophysiology of
radiation injury is poorly understood. Its presentation can be acute and irreversible or subtle, with a gradual
progressive dysfunction over years. A variety of dose and volume parameters have been associated with renal
toxicity and are reviewed to provide treatment guidelines. The available predictive models are suboptimal and re-
quire validation. Mitigation of radiation nephropathy with angiotensin-converting enzyme inhibitors and other
compounds has been shown in animal models and, more recently, in patients. Ó 2010 Elsevier Inc.
Kidney injury, Radiation toxicity, Radiotherapy.
1. CLINICAL SIGNIFICANCE
The kidneys are the dose-limiting organs for radiotherapy
(RT) to gastrointestinal cancers, gynecologic cancers, lym-
phomas, and sarcomas of the upper abdomen and during total
body irradiation (TBI). The kidneys are vitally important, re-
sponsible for filtering waste metabolites and electrolytes
from the blood, producing erythropoietin to stimulate red
blood cell production, and modulating blood pressure by
fluid/electrolyte balance. The incidence of RT-associated
kidney injury is likely underreported owing to its long la-
tency and because dysfunction is likely often attributed to
more common causes.
2. ENDPOINTS
The findings associated with RT-induced kidney injury
can be segregated into subclinical and clinical (Table 1). Af-
ter TBI, RT-induced kidney injury often includes features of
hemolytic-uremic syndrome (e.g., microangiopathic hemo-
lytic anemia, and thrombocytopenia) (1).
Acute (within 3 months) RT-induced kidney injury is gen-
erally subclinical. The signs and symptoms (e.g., decreased
glomerular filtration rate [GFR], increased serum b2-micro-
globulin) usually develop during the subacute period (3–18
months). Chronic injury (18 months) is characterized by be-
nign or malignant hypertension, elevated creatinine levels,
anemia, and renal failure (2, 3). If no changes in renal blood
perfusion or GFR are observed within 2 years after RT, sub-
sequent chronic injury is unlikely (4). RT-induced kidney in-
jury can also reduce a patient’s reserve against future renal
insults.
The long latency for clinical kidney toxicity was high-
lighted in a study of 67 patients with peptic ulcer disease,
without pre-existing hypertension, who were treated with
$20 Gy within 3 weeks (encompassing the left kidney) (5).
Of the 67 patients, 31 (46%) developed kidney toxicity within
8–19 years after RT, including 7 patients with fatal uremia (n
= 5) or malignant hypertension (n = 2). At autopsy, atrophy of
the left kidney with degenerative changes of the small and me-
dium arteries were observed. The long latency for RT-induced
kidney injury and the high prevalence of confounding non–
RT-related factors (see the section ‘‘Patient- and Treatment-
Related Factors’’) that can injury the kidneys have hindered
our ability to understand the effects of partial kidney RT.
Reprint requests to: Laura A. Dawson, M.D., Department of Ra-
diation Oncology, Princess Margaret Hospital, University of Tor-
onto, 610 University Ave., Toronto, ON M5G 2M9, Canada. Tel:
(416) 946-2124; Fax: (416) 946-6566; E-mail: laura.dawson@
rmp.uhn.on.ca
Conflict of interest: none.
Received Aug 20, 2008, and in revised form Feb 1, 2009.
Accepted for publication Feb 3, 2009.
S108
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S108–S115, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.02.089](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-108-320.jpg)
![3. DEFINING THE KIDNEYS
The kidneys are relatively easy to identify on the planning
computed tomography (CT) scan, even without intravenous
contrast. Typically, the doses delivered to each kidney alone
and combined should be evaluated. Ideally, the kidney paren-
chyma should be segmented, because this is the ‘‘functional’’
component. The magnitude of errors introduced by including
the collecting system in the ‘‘kidney volume’’ is unclear.
The existing published data were largely derived from pa-
tients treated without computed tomography-based planning,
and with delivery techniques associated with substantial do-
simetric uncertainty (e.g., the moving strip technique). Even
with modern planning, kidney breathing motion or shifts in
kidney position are not usually accounted for, introducing
uncertainty in the delivered vs. the planned kidney doses
(6). The kidneys move inferiorly (by #7 cm) and change
shape in the upright vs. supine position (7); thus, if kidney
blocks were designed using supine CT scans for patients
treated in the upright position (e.g., with TBI), the actual kid-
ney doses would be far greater than planned.
4. REVIEW OF DOSE–VOLUME DATA
The risk of RT-induced kidney injury largely depends on
the use of whole-volume or partial-volume RT to one or
both kidneys. In the present report, whole kidney tolerance
refers to bilateral, uniform kidney RT, segregated by the
use of TBI or not, and partial kidney tolerance includes
any partial-volume RT experience, including uniform RT
to one kidney.
Whole kidney tolerance
The dose–response data for whole kidney irradiation in pa-
tients undergoing TBI is summarized in Table 2 and Fig. 1.
Patients undergoing TBI typically have substantial co-mor-
bidities and also receive potentially nephrotoxic chemother-
apy. Cheng et al. (8) conducted a comprehensive review of
12 studies reporting kidney toxicity (increased creatinine or
hemolytic uremic syndrome) after TBI (Table 2 and
Fig. 1). On multivariate analysis, for those reports describing
adult-only experience (n = 479 patients), the dose was the
only significant factor associated with increased kidney tox-
icity. Neither the dose rate nor the number of fractions were
significant in their model. For the studies that included adult
and pediatric populations (n = 437 patients), significant fac-
tors included the dose, dose rate (#6 vs. 6.1–9.9 vs. $10
cGy/min) and the use of fludarabine. Considering all the stud-
ies, except for those with pediatric populations only (n = 916
patients), the number of fractions became a significant factor,
in addition to the total dose and dose rate. The dose associ-
ated with a 5% risk of kidney toxicity, without nephrotoxic
drugs, was 9.8 Gy, regardless of the fractionation scheme
used (median dose, 12 Gy; range, 7.5–14; median fractions,
6; range 1–11, delivered once or twice daily).
The whole kidney dose–response data, excluding TBI, is
summarized in Table 3 and Figs. 2 and 3. The dose–response
data are consistent with previous reviews (e.g., Emami et al.
[9] in 1991 and Cassady [10] in 1995; Fig. 1) that suggested
a total dose associated with a 5% and 50% risk of injury at 5
years of 18–23 Gy and 28 Gy, in 0.5–1.25 Gy/fraction,
respectively. Increases in creatinine clearance have been
observed after 10–20 Gy to both kidneys, at 0.8–1.25 Gy/
fraction (11).
Partial kidney tolerance
Nephrectomy is more often associated with subclinical
elevations in creatinine and late chronic kidney injury than
is ‘‘nephron-sparing’’ partial nephrectomy (12). Thus, the
global function/reserve appears related to the nephron vol-
ume, and tolerance to RT is likely reduced in patients with
one (vs. two) kidneys.
Table 4 summarizes the key studies describing partial kid-
ney tolerance to RT. Unilateral kidney RT is not risk free, as
Table 1. Radiation-associated kidney toxicity endpoints
Category Physiologic Biochemical Imaging
Subclinical Elevated blood pressure
Increased weight
Elevated serum b2-microglobulin
Elevated urine beta2 microglobulin
Elevated serum blood urea nitrogen
Elevated serum creatinine
Elevated serum renin
Reduced glomerular filtration rate
Decreased creatinine clearance*
Proteinuria
Urine casts
Hematuria
Anemia
Reduced glomerular function, GFR
99m
Tc-DTPA renography
Reduced tubular function
99m
Tc-DMSA scintigraphy
Perfusion deficits on scintigraphy
131
Iodine radiohippurate
Asymmetric uptake of intraenous contrast on
computed tomography
Kidney atrophy
Clinical Malignant hypertension
Headache, Edema, Dyspnea
Fatigue, Nausea, Vomiting
Confusion, Coma, Death
Abbreviations: 99m
Tc-DTPA = 99m
Technetium-diethylene-triamine-penta-acetic acid; GFR = glomerular filtration rate; 99m
Tc-DMSA =
99m
Technetium-dimercaptosuccinyl acid.
* Often used to estimate GFR.
Radiation-induced kidney injury d L. A. DAWSON et al. S109](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-109-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Pelvis: Bladder
RADIATION DOSE–VOLUME EFFECTS OF THE URINARY BLADDER
AKILA N. VISWANATHAN, M.D., M.P.H.,* ELLEN D. YORKE, PH.D.,y
LAWRENCE B. MARKS, M.D.,z
PATRICIA J. EIFEL, M.D.,x
AND WILLIAM U. SHIPLEY, M.D.{
*Department of Radiation Oncology, Brigham and Women’s Hospital/Dana-Farber Cancer Institute and Harvard Medical School,
Boston, MA; y
Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY; z
Department of Radiation
Oncology, University of North Carolina, Chapel Hill, NC; x
Department of Radiation Oncology, M. D. Anderson Cancer Center,
Houston, TX; {
Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA
An in-depth overview of the normal-tissue radiation tolerance of the urinary bladder is presented. The most in-
formative studies consider whole-organ irradiation. The data on partial-organ/nonuniform irradiation are suspect
because the bladder motion is not accounted for, and many studies lack long enough follow-up data. Future studies
are needed. Ó 2010 Elsevier Inc.
Bladder dose, toxicity.
1. CLINICAL SIGNIFICANCE
Radiotherapy (RT) with or without chemotherapy for pelvic
malignancies may result in genitourinary (GU) complica-
tions. Overall, severe late effects occur in #10% of patients
with prostate, bladder, or cervical cancer (1). However, given
a possible latency period of several decades between treat-
ment and the clinical manifestation of sequelae (2, 3), reports
may have underestimated the late GU toxicity rates. The re-
ported rates of acute side effects might be more accurate.
2. ENDPOINTS
Many endpoints may be used to score bladder injury. In the
present report, we focus on clinical symptoms. The symp-
toms attributed to RT-related injury can also occur as a conse-
quence of other medical co-morbidities, such as infection or
aging, particularly for incontinence. The toxicity profile will
depend on the treatment regimen of RT with or without sur-
gery or chemotherapy, and the origin, extent, and location of
cancer. When discussing bladder toxicities in relation to dose
and/or volume, a significant heterogeneity of dose can exist,
depending on whether the patient has undergone brachyther-
apy, teletherapy, or both, and on bladder motion.
Acute side effects that occur during RT usually resolve
within a few months. Long-term symptoms attributable to
global injury include dysuria, frequency, urgency, contracture,
spasm, reduced flow, and incontinence. In contrast, symptoms
thought to arise fromfocal injury include hematuria,fistula, ob-
struction, ulceration, and necrosis. The grading of toxicities ac-
cording to treatment given is subjective. One physician might
prescribe an intervention sooner than another, leading to a rela-
tive ‘‘upgrading.’’ Furthermore, symptoms attributable to the
bladder might be urethral in origin. Several scoring systems
have been proposed to standardize the reporting of bladder tox-
icity, each with a slightly different approach. Some systems
have separately considered objective vs. subjective endpoints
(e.g., Late Effects of Normal Tissues-Subjective, Objective,
Management and Analytic system [LENT-SOMA]), and
others have not differentiated between acute and late effects
(e.g., Common Terminology Criteria for Adverse Events
[CTCAE]) or have ambiguities (e.g., ‘‘spontaneous, pads indi-
cated’’ is considered Grade 2 incontinence using the CTCAE).
Interstudy comparisons are challenging, because the scoring
system used was not always clearly stated. Furthermore, crude,
rather than actuarial, rates have often been reported. In general,
patient-reported data have been shown to be superior to physi-
cian-reporteddata,althoughthecollectionismorecomplex(4).
3. CHALLENGES DEFINING VOLUMES
The bladder is a highly distensible organ. Its volume
continuously changes with filling, and the post-void residual
volume can vary. Furthermore, the bladder can move with
positioning, respiration, or bowel filling. Therefore, we
Reprint requests to: Akila N. Viswanathan, M.D., M.P.H., De-
partment of Radiation Oncology, Brigham and Women’s Hospi-
tal/Dana-Farber Cancer Institute, Harvard Medical School, 75
Francis St., L2, Boston, MA 02115. Tel: (617) 732-6331; Fax:
(617) 278-6988; E-mail: aviswanathan@lroc.harvard.edu
Conflict of interest: none.
Acknowledgments—Thank you to Barbara Silver and Christian Kir-
isits, ScD for reading the manuscript.
Received Aug 28, 2008, and in revised form Feb 6, 2009.
Accepted for publication Feb 28, 2009.
S116
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S116–S122, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.02.090](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-116-320.jpg)
![EBRT 50 Gy (hazard ratio [HR], 3.34; p = .002), black race
(HR, 1.89; p = .003), smoking history (HR, 1.81; p = .006),
and body mass index 30 kg/m2
(HR, 1.55; p = .05) were sig-
nificantly associated with bladder complications (49). Age,
diabetes, hypertension, or a history of pelvic inflammatory
disease were not significantly related to bladder toxicity
(49). From the experience of the senior investigators of the
present report, patients taking anticoagulation medications
might develop hematuria.
Surgery
TURBP, prostatectomy, hysterectomy, biopsy or any kind
of procedure before RT may potentially increase morbidity.
The site of TURBT might heal slowly. Hysterectomy or pros-
tatectomy can denervate the bladder, which causes urinary
hesitancy or retention, resulting in overflow incontinence.
Approximately 5% of patients who undergo radical hysterec-
tomy require chronic suprapubic catheterization; 38–50%
develop detrusor instability, impairment of bladder sensation,
alteration in bladder compliance or capacity, or a reduction
in the maximal urethral pressure (50, 51). In one study
(52), transurethral prostate resection (TURP) before defini-
tive RT resulted in incontinence in 5% of patients compared
with 1% who had not undergone TURP. After EBRT for
prostate cancer, the rate of urethral stricture has been reported
to range from 2% to 5% in patients without previous TURP
vs. 6–16% in patients with previous TURP (1).
Chemotherapy
Changes in bladder function can occur with chemotherapy
alone or with concurrent chemoradiotherapy. Cytoxan is
independently associated with chronic hemorrhagic cystitis,
incontinence, contractions, vesicoureteral reflux, and urothe-
lial malignancies (53). In one study with 8 years of follow-up
of cervical-cancer patients treated with chemoradiotherapy,
3% developed late bladder side effects (54). During the
past one to two decades, selective bladder-preserving
approaches for patients with muscle-invasive bladder cancer
have included EBRT with concurrent cisplatin-containing
chemotherapy. Tumor doses of 64–65 Gy have been well
tolerated (19). Chemotherapy administered concurrently
with RT can sensitize the normal tissue, although this has
not been shown to increase the risk of long-term bladder
complications in patients with cervical cancer or bladder
cancer.
Fractionation
Some evidence has supported the association of a high
dose per fraction with a greater complication rate (1). Pros-
tate-cancer patients treated with 5.17 Gy/fraction twice
a week through anteroposterior/posteroanterior fields for 9
weeks with a 3-week break mid-way through therapy had
a 19% rate of serious bladder injury (55). These included
both global (cystitis and contracture) and focal (fistula) in-
jury. Treatment timing could also be a factor. One study of
Dose (Gray)
IncidenceofGrade3latebladdertoxicity(%)
0
5
10
15
20
25
30
35
40
45
7060504030
Physical Dose
Equivalent Dose
J,123
A,24
I, 186
F,24
L,330
E,96
B,60
K,154
A, 20
A, 8
A,58
H, 889
D, 34
M,121
G, 62
ytliuQ.A
02
nacnuD.B
12
uY.C
22
narocroC.D
32
laicraM.E
42
notnioP.F
52
namdooG.G
62
2nacnuD.H
9
ledöR.I
11
J netlohcS.
21
ragnaM.K
51
nahgemaM.L
13
anodreP.M
41
A
A
A
B
G
A
F
J
L
E
M
D
C,309
H
Fig. 1. Incidence of Radiation Therapy Oncology Group Grade 3 or greater late bladder toxicity in relation to average dose
(squares) or linear-quadratic model equivalent dose (triangles) in 2-Gy fractions (assuming a/b = 6 Gy) for studies treating
whole bladder only (listed in Table 1 and reviewed by Marks, et al. [1]). Letter in each square denotes data source: pub-
lication specified in key as first author followed by superscript reference number. Note, Quilty and Duncan (20) had four
dose groups. Number of patients italicized inside each square. No significant correlation was found between complication
rate and either dose or equivalent dose. (Courtesy of E.D. Yorke.)
Radiation-associated bladder injury d A. N. VISWANATHAN et al. S119](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-119-320.jpg)
![6. MATHEMATIC/BIOLOGIC MODELS
The published literature includes at least five fits of the
Lyman-Kutcher-Burman (LKB) normal tissue complication
probability (NTCP) model to rectal toxicity data (7, 10,
23–27) (Table 1). With one exception (10) the published
parameter estimates have been remarkably consistent, even
though the endpoint has varied somewhat among these stud-
ies. The volume parameter, n, has usually, but not always,
been found to be quite small (0.15). Small values of n indi-
cate that high-dose regions play a predominant role in deter-
mining the risk of late rectal toxicity (i.e., series architecture),
in accordance with the analyses of the DVH cut-points
(Fig. 1). An advantage of the LKB model over DVH con-
straints is that it yields NTCP values for patient-specific treat-
ment plans.
7. SPECIAL SITUATIONS
Given the large numbers of patients included in published
studies of rectal toxicity, and the relative consistency of their
results for rectal bleeding, existing estimates of toxicity from
the LKB model are probably better than for most organs.
In the Dutch randomized trial, bleeding, high stool fre-
quency, and fecal incontinence were scored and modeled
separately. Not only were the parameter estimates markedly
different for each endpoint, but the organ at risk also differed
(27). For rectal bleeding and high stool frequency, modeling
based on the DVH of the anorectal wall was best, whereas for
fecal incontinence, that of the distal 3 cm of the anal canal
wall was most relevant. Furthermore, they estimated the
dose-modifying factors for patients with increased risk of rec-
tal injury due to prior abdominal surgery.
Model-based predictions for treatments with prescribed
doses 79.2 Gy and diseases other than prostate cancer, for
which there is little data, should be viewed as tentative and
require validation. Model predictions may not be representa-
tive of settings where intensity modulation or image-guided
practices are in place. In the prostate cancer dose escalation
trial, RTOG 9406, larger planning target volumes (PTVs)
were associated with increased toxicity (28). Image guidance
should reduce the volume of rectum that overlaps with the
high-dose PTV and yield a planned rectal DVH that more
closely approximates the volume of rectum irradiated daily.
The NTCP estimates are population-based: a low risk esti-
mate does not preclude the occurrence of rectal injury, possi-
bly severe, in any individual patient.
8. RECOMMENDED DOSE/VOLUME LIMITS
Organ segmentation
The rectum should be segmented from above the anal
verge to the turn into the sigmoid colon, including the rectal
contents. Although there can be variation in defining these
landmarks, the superior limit is where the bowel moves ante-
riorly, close to the inferior level of the sacroiliac joints, and
the inferior limit is commonly at the bottom of the ischial
tuberosities. In prostate cancer therapy, an empty rectum at
simulation is advised to avoid introducing a systematic error
in PTV coverage. A supine position is associated with less
variability in daily organ positioning. These conditions are
less critical with image-guided RT.
Dose–volume constraints for conventional fractionation up
to 78 Gy
The following dose–volume constraints are provided as
a conservative starting point for 3D treatment planning:
V50 50%, V60 35%, V65 25%, V70 20%, and V75
15%. However, they have yet to be validated as ‘‘rela-
tively-safe.’’ For typical DVHs, the NTCP models predict
that following these constraints should limit Grade $2 late
rectal toxicity to 15% and the probability of Grade $3
late rectal toxicity to 10% for prescriptions up to 79.2 Gy
in standard 1.8- to 2-Gy fractions.
Higher doses in the VDose parameter have more impact on
the complication probability. Clinicians should strive to min-
imize the V70 and V75 volumes below the recommended con-
straints without compromising tumor coverage. Reducing the
V75 by just 5% from 15% to 10% has a significant impact in
the predicted complication probability, whereas reducing the
V50 from 50% to 45% makes relatively little difference.
Intensity-modulated RT (IMRT) planning yields distinctly
different shaped DVH curves than forward-planned 3D con-
formal RT (3D-CRT), with considerably decreased rectal
volume receiving low to intermediate radiation doses.
Although the parameters above provide a safe starting point
for both 3D-CRT and IMRT, it is likely that because IMRT
can achieve better low to intermediate dose–volume con-
straints, the observed rectal toxicity will be lower (20). The
Memorial Sloan-Kettering IMRT experience suggests that
doses in the intermediate range of 40–60 Gy may become im-
portant in patients who are receiving radiation prescriptions
in excess of 78 Gy.
NTCP models
All series from which LKB parameters are reported used
3D-CRT prescribed to doses #79.2 Gy for localized prostate
cancer. Depending on the patient geometry, dose prescribed,
treatment technique, and other clinical variables, the pro-
posed dose–volume constraints might be unachievable
(e.g., for doses 79.2 Gy), but every effort should be made
to be as close as possible to the constraints especially in the
high doses. In situations similar to those from which the
model parameters were derived, the LKB model can estimate
the complication probability.
A meta-analysis of the results from the four studies (10, 24–
26) of Grade $2 late toxicity or rectal bleeding gavethe overall
best estimates of the LKB parameters (95% confidence
interval) as n = 0.09 (0.04–0.14); m = 0.13 (0.10–0.17); and
TD50 = 76.9 (73.7–80.1) Gy. Estimates of TD50 were found
to be heterogeneous (the null hypothesis that estimates for
a model parameter were drawn from the same distribution
was rejected, p 0.01; the inconsistency index [I2
] was
79%). Although heterogeneity could not be established for es-
timates of n (p 0.1), the inconsistency index was substantial
Rectal Radiation Dose-Volume Effects d J. M. MICHALSKI et al. S125](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-125-320.jpg)
![Table 1. Description of endpoints, study details, and Lyman-Kutcher-Burman parameters for published analyses
Authors (reference) Endpoint
No. of centers/time period
studied/RT technique Incidence, % (n)
Total prescribed
dose (Gy)/fraction
size (Gy)
Parameters
(68% CI) [95% CI] Rectal DVH
Tucker et al. (26) Grade $2 RTOG* 42
1994–2000
Mostly 4–7 field
3D-CRT
13.5 (138/1023) 68.4, 73.2, 79.2/1.8
74, 78/2
n = 0.08 [0.04–0.26]
m = 0.14 [0.10–0.25]
TD50 = 78 [72–84] Gy
Rectum plus contents
So¨hn et al. (25) Grade $2 CTCAE v3.0y
1
1999–2002
4-field 3D-CRT
16 (51/319) 70.2, 72, 73.8, 75.6,
77.4, 79.2/1.8
a = 11.9 Æ 3.8
n = 1/a = 0.08
m = 0.108 Æ 0.027
TD50/not reported = 78.4 Æ 2.1 Gy
Median follow-up: 2.8 y;
range, 0.1–6.4 y
Rectum plus contents
Rancati et al. (24) Grade $2 bleedingz
5
1994–2001
3–4-field 3D-CRT
7.0 (38/547)
intact and
postprostatectomy
64–79.2/1.8–2 n = 0.23 (0.14–0.42)
m = 0.19 (0.15–0.25)
TD50/1.5 = 81.9
(76.8–91.2) Gy
Rectum plus contents
6.9 (22/321)
intact only
70–79.2/1.8–2 n = 0.24 (0.14–0.50)
m = 0.14 (0.11–0.19)
TD50/1.5 = 75.7
(72.1–81.8) Gy
Grade $3 bleedingx
1.6 (9/547) 64–79.2/1.8–2 n = 0.06 Æ 0.01?
m = 0.06 Æ 0.005?
TD50/1.5 = 78.6 Æ 3.7?
Gy
Peeters et al.(27) Bleedingk
4
1997–2003
2–4-field 3D-CRT{
4.9 (23/468) 68 (n = 234),
78 (n = 234)/2
n = 0.13 (0.04–0.25)
m = 0.14 (0.11–0.19)
TD50/3 = 81 (75–90) Gy
Anorectal wall; method
of Meijer et al. (35)
Frequency 6.4 (30/468) n = 0.39 (0.19–1.11)
m = 0.24 (0.18–0.35)
TD50/3 = 84 (75–103) Gy
Anorectal wall; method
of Meijer et al. (35)
Fecal incontinence 6.8 (32/468) n = 7.48 (0.56–N)
m = 0.46 (0.39–0.52)
TD50/3 = 105 (88–138) Gy
Anal wall; method of
Meijer et al. (35)
Cheung et al. (10) Grade $2 toxicity,
modified scale#
1
1992–1999
3D-CRT
4-field to 46 Gy
6-field to 78 Gy
22.7 (29/128) 78/2 n = 3.91 [0.031–N]
m = 0.156 [0.036–0.271]
TD50 = 53.6 [50–75.1] Gy
External rectal wall
plus contents
Without hemorrhoids
16.7 (14/ 84)
n = 0.746 [0.026–N]
m = 0.092 [0.019–0.189]
TD50 = 56.7 [49.9–75.2] Gy
(Continued)
S126I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-126-320.jpg)
![(I2
= 40%). Estimates of m showed no indications of heteroge-
neity (p 0.1, I2
= 0). The source of heterogeneity in both n and
TD50 was the study from the M. D. Anderson Cancer Center
(10). If that data set was excluded, the best estimate of TD50 be-
came 78.5 (75.2–81.8) Gy. Other parameters remained the
same to 10% in the confidence intervals; however, all indica-
tions of heterogeneity disappeared (p 0.1,I2
= 0 for all param-
eters). Excluding prostatectomy patients (24) from the analysis
resulted in essentially no change in the overall best estimates of
parameter values or in measure of heterogeneity.
It is notable that the LKB parameters from studies of Grade
$3 late rectal bleeding (24, 27) (Table 1) are broadly similar
to those above. It might be expected that the dose response
for Grade 3 complications should be shifted to higher doses,
but this was not seen. However, Rancati et al. (24) showed
a decrease in n (to 0.06) for Grade $3 complications, indicat-
ing an increased dependence on the highest doses. Daily
deviations of rectal position probably result in some patients
receiving higher cumulative rectal DVHs than planned. Such
patients may skew the corresponding NTCP modeling anal-
ysis, making the resulting parameters overestimate the com-
plication risk. For this reason, the model predictions have
some uncertainty regarding their applicability depending on
the immobilization, treatment, and localization techniques
used. In the presence of daily localization and IMRT, these
models may tend to overestimate the risk of toxicity because
the model parameters were based on patients treated mostly
without IMRT or daily localization. Patients treated with
IMRT have been reported to have lower complication rates
than those treated with standard 3D-CRT (20).
Hypofractionation
Until more clinical data are available for the various hypo-
fractionated schedules, DVH dose bins should be adjusted to
conventional 1.8- or 2-Gy fractions using the linear-quadratic
model with an a/b ratio of 3 for the rectum. Whereas some
have proposed a rectal a/b ratio of 5.4 Gy, the choice of
a/b ratio of 3 is a reasonably conservative estimate (29).
The LKB model could then be used on a linear-quadratic–
adjusted DVH to estimate the rectal complication probability.
An interim report of a prospective robotic radiosurgery Phase
II trial of 36.25 Gy in 5 fractions observed a reduced rate of
severe rectal toxicities with an every-other-day vs. consecu-
tive-day treatment schedule (30). This observation warrants
further exploration.
3D-CRT vs. IMRT
Most of the mature published clinical data on dose-related
rectal toxicity come from 3D-CRT. Increasingly, IMRT is
being used to treat pelvic malignancies, especially localized
prostate cancer, often leading to a much lower volume of rec-
tal tissue receiving intermediate to high doses. Modeling
derived from 3D-CRT treatments may need to be modified
to predict complications from IMRT treatments. As dis-
cussed in ‘‘Review of Dose–Volume Data,’’ intermediate
dose levels are often correlated to the specific 3D treatment
techniques used, and rectal volumes exposed to these doses
Table1.Descriptionofendpoints,studydetails,andLyman-Kutcher-Burmanparametersforpublishedanalyses(Continued)
Authors(reference)Endpoint
No.ofcenters/timeperiod
studied/RTtechniqueIncidence,%(n)
Totalprescribed
dose(Gy)/fraction
size(Gy)
Parameters
(68%CI)[95%CI]RectalDVH
Burmanetal.(23)Severeproctitis,necrosis,
fistula,andstenosis**
n=0.12
m=0.15
TD50/5=80Gy
*Grade2isdefinedas‘‘moderatediarrheaandcolic;bowelmovement5timesdaily;excessiverectalmucusorintermittentbleeding’’(2),startingorpersisting120daysafterstartoftherapy.
y
ChronicrectalbleedingthatexcludesGrade1bleedingdefinedas‘‘mildhemorrhage/bleeding;intervention(otherthanironsupplements)notindicated.’’
z
ExcludesGrade1or‘‘slight’’bleeding(#2weeks).Latecomplicationsweredefinedasthosedeveloping3monthsafterthecompletionofthetherapy,orthosestartingbeforeandpersisting
for3monthsafterthecompletionoftherapy.
x
Grade3definedasasinglecoagulationprocedureand/ortransfusion.Latecomplicationsweredefinedasthosedeveloping3monthsafterthecompletionofthetherapyorthosestarting
beforeandpersistingfor3monthsafterthecompletionoftherapy.
k
Bleedingrequiringlasertreatmentortransfusionofpackedcellsandstarting120daysafterthestartoftherapy.
{
Twopatientsreceivedintensity-modulatedradiotherapy.
#
ExcludesGrade1toxicitydefinedasexcessbowelmovementstwicebaselineand/orslightrectaldischargeorblood.
**BasedontheEmamietal.rectaltoleranceestimatesin1991(36)andprovidedforhistoricalpurposesonly.
Abbreviations:RT=radiotherapy;CI=confidenceinterval;DVH=dose–volumehistogram;RTOG=RadiationTherapyOncologyGroup;3D-CRT=three-dimensionalconformalradio-
therapy;TD50/t=radiationdosethatwouldresultina50%riskofseverecomplicationswithintyearsafterirradiation;CTCAE=CommonTerminologyCriteriaforAdverseEvents;?
=deduced
usingamethodthatyieldssmalleruncertaintiesthanthoseoftheotherstudies.
AllstudiesareprospectiveexceptRancatietal.
Rectal Radiation Dose-Volume Effects d J. M. MICHALSKI et al. S127](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-127-320.jpg)
![QUANTEC: ORGAN-SPECIFIC PAPER Pelvis: Penile Bulb
RADIATION DOSE–VOLUME EFFECTS AND THE PENILE BULB
MACK ROACH, III, M.D., FACR,* JIHO NAM, M.D.,y
GIOVANNA GAGLIARDI, PH.D.,z
ISSAM EL NAQA, PH.D.,x
JOSEPH O. DEASY, PH.D.,x
AND LAWRENCE B. MARKS, M.D.y
*Department of Radiation Oncology, University of California-San Francisco, San Francisco, CA; y
Department of Radiation Oncology,
University of North Carolina at Chapel Hill, Chapel Hill, NC; z
Department of Medical Physics, Karolinska University Hospital and
Karolinska Institutet, Stockholm, Sweden; and x
Department of Radiation Oncology, School of Medicine, Washington University in St.
Louis, St. Louis, MO
The dose, volume, and clinical outcome data for penile bulb are reviewed for patients treated with external-beam
radiotherapy. Most, but not all, studies find an association between impotence and dosimetric parameters (e.g.,
threshold doses) and clinical factors (e.g., age, comorbid diseases). According to the data available, it is prudent
to keep the mean dose to 95% of the penile bulb volume to 50 Gy. It may also be prudent to limit the D70 and
D90 to 70 Gy and 50 Gy, respectively, but coverage of the planning target volume should not be compromised.
It is acknowledged that the penile bulb may not be the critical component of the erectile apparatus, but it
seems to be a surrogate for yet to be determined structure(s) critical for erectile function for at least some
techniques. Ó 2010 Elsevier Inc.
Erectile dysfunction, Penile bulb, Radiation.
1. CLINICAL SIGNIFICANCE
Erectile dysfunction (ED), the consistent inability to attain or
maintain an erection of sufficient quality to permit satisfac-
tory sexual intercourse, is a common complication resulting
from radiotherapy (RT) for prostate cancer (1). Many patients
choose RT for their clinically localized prostate cancer
because they believe there may be a lower risk of ED com-
pared with radical prostatectomy (RP); however, this remains
controversial. Posttreatment ED rates have been reported to
be approximately 24% (brachytherapy alone), 40% (brachy-
therapy plus external RT), 45% (external RT alone), 66%
(nerve-sparing RP), 75% (non–nerve-sparing RP), and 87%
for cryosurgery, but physician-reported rates are known to
be less reliable than patient-reported outcomes, so the
optimal comparison studies have yet to be done (2).
2. ENDPOINTS
The time course for RT-associated ED is variable (reported
as days to years) and often evolves gradually. Ascribing ED to
RT alone is difficult because men lose some erectile function
with age, and other common diseases (e.g., diabetes,
hypertension) may contribute. Various self-administered
questionnaires have been used to assess erectile function in
clinical studies (e.g., the International Index of Erectile Func-
tion [IIEF]) (3). Additional objective diagnostic tests can be
performed (e.g., nocturnal penile tumescence, somatosensory
evoked potentials, bulbocavernous reflex latency, penile elec-
tromyography, color duplex Doppler ultrasound, dynamic in-
fusion cavernosometry, and pharmacotesting), but these are
generally applied to establish the etiology of ED (4).
3. CHALLENGES DEFINING VOLUME
The anatomy of the pelvic floor is challenging to visualize
on CT or MRI, and hence definition of the penile bulb (PB)
varies. This may contribute to inconsistent reports (5–15).
The PB appears as an oval-shaped, hyperintense midline
structure on T2-weighted MR images; on axial CT imaging
it is bounded by the crura, corpora spongiosum, and the leva-
tor ani muscle (Fig. 1; see ref. 16 for details). At University of
California-San Francisco, the bulb is defined as the most prox-
imal portion of the penis sitting immediately caudal to the
prostate. We also recognize that the bulb itself is not part of
Reprint requests to: Mack Roach III, M.D., F.A.C.R., Department
of Radiation Oncology, University of California-San Francisco,
1600 Divisadero Street, San Francisco, CA 94143-1708. Tel:
(415) 353-7181; Fax: (415) 353-9883; E-mail: mroach@radonc.
ucsf.edu
Conflict of interest: M.R. has received recent funding from GSK,
Siemens, CareCore National, the National Cancer Institute, Molec-
ular Insight, TROFEX, General Electric, Novartis, CPAC (Tomo-
therapy, Inc.), and has acted as a consultant (Proton and Carbon
Accelerator development). L.B.M. has received honoraria from Var-
ian Medical Systems, as well as grant support from the National In-
stitutes of Health (NIH), the Lance Armstrong Foundation, and the
U.S. Department of Defense. J.O.D. receives funding from the NIH,
Varian Medical Systems, and Tomotherapy, Inc. I.E.-N. receives
funding from the NIH, Varian Medical Systems, and Tomotherapy,
Inc. All other authors have no conflict of interest.
Received Feb 3, 2009, and in revised form April 7, 2009.
Accepted for publication April 10, 2009.
S130
Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S130–S134, 2010
Copyright Ó 2010 Elsevier Inc.
Printed in the USA. All rights reserved
0360-3016/10/$–see front matter
doi:10.1016/j.ijrobp.2009.04.094](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-130-320.jpg)
![In the 1999 report the authors found that 21 was the optimal
cutoff score. Thus, whenever possible investigators are en-
couraged to use this cutoff to define ED instead of the
mild, moderate, and severe categories (unless independently
validated). Thus for example, in the case of the report by Se-
lek et al. (11) it is likely than only assigning patients with
a score ‘‘0’’ as being impotent underestimated the true base-
line level of ED in their study population (see recommenda-
tions in ‘‘Toxicity Scoring’’).
In addition, several of these studies included a sizable frac-
tion of patients who received phosphodiesterase type 5 inhib-
itors that might attenuate the effects of RT on sexual function
(18, 19). Earlier studies were less likely to be contaminated
by this issue because these agents were not available when
most of these patients were treated (7, 10).
Brown et al. (5) studied 32 patients and noted no dose–
response association for ED. However, they used intensity-
modulated RT and attempted to spare the PB, resulting in
a mean dose to the bulb of only 25 Gy. Thus, their data do
not explicitly refute the presence of a dose–response associ-
ation at higher doses.
Several studies reported a significant dose–volume effect
correlatedwithriskofED using the metrics of Dx (i.e.,the min-
imum dose received by x% volume of the PB). For example,
Fisch et al. (7) noted ED in 0, 80%, or 100% of patients with
a D70 of 0–40, 40–70, and 70 Gy, respectively. Similarly,
Mangar et al. (8) reported that a D90 $50 Gy is associated
with a significant risk of ED. Wernicke et al. (14) reported
that D30, D45, D60, and D75 correlated with an increased
risk of ED. Roach et al. (10) reported a significant correlation
between a median PB dose of 52.5 Gy and an increase in ED.
Brachytherapy studies are mixed in their support for an as-
sociation between PB doses and ED. Merrick et al. (20) used
a matched-pair study of ED after brachytherapy and related
PB dose–volume metrics to patient-reported questionnaire
data. The rate of ED was associated with doses to the PB (par-
ticularly median dose [D50]) and to a lesser degree the crura.
On the other hand, the Macdonald et al. (21) review of 342
patients after brachytherapy failed to show an association
between median PB dose and ED.
5. FACTORS AFFECTING RISK
Patient-related factors for ED have not been emphasized,
except for a few reports. Post-RT ED rates have been
reported to be higher with baseline pretreatment ED, diabe-
tes, smoking history, or a history of hypertension (5, 7, 20,
22). The data, however, are somewhat conflicting (Table 1).
6. MATHEMATIC/BIOLOGIC MODELS
Penile bulb dose–volume parameters may be associated
with the incidence of ED, although the results are conflicting
to prove a clear correlation between those parameters (Fig. 2).
For example, van der Wielen et al. (23) reviewed the litera-
ture and concluded that ‘‘sparing of the penile bulb to im-
prove potency-preservation is not sufficiently supported by
the current literature.’’ and questioned whether the poten-
tial ‘‘oncological risk’’ was justified given the uncertainty
of potency sparing. It is possible that the key anatomic struc-
tures involved in ED pathophysiology have not been defined.
Moreover, dosimetric accuracy of the true accumulated dose
distribution has seldom been examined in detail. The data are
sparse. Overall, the data plotted in Fig. 2 may be consistent
with either a causal or surrogate relationship.
7. SPECIAL SITUATIONS
Hormonal therapy itself is associated with the ED. Several
studies reported the deleterious impact of hormonal therapy on
erectilefunction(3, 17,23–27).However,theassociation of hor-
monal therapy with RT dose/volume of the PB is unknown.
8. RECOMMENDED DOSE/VOLUME LIMITS
On the basis of the data available, it is prudent to keep the
mean dose to 95% of the PB volume to 50 Gy. It may also be
prudent to limit the D70 and D90 to 70 Gy and 50 Gy, respec-
tively. It is acknowledged that the PB may not be the critical
component of the erectile apparatus, but it seems to be a sur-
rogate for yet to be determined structure(s) critical for erectile
function for at least some techniques.
Fig. 2. Incidence of erectile dysfunction according to the radiation
dose to the penile bulb. The x axis values are estimated according to
the range of doses reported. The data for Fisch et al. (7) at 20, 55,
and 80 Gy represent the reported rates of erectile dysfunction at
40, 40–70, and 70 Gy, respectively. Similarly, for Wernicke
et al. (14) and Roach et al. (10), each symbol represents the rates
of erectile dysfunction at #42 vs. 42 and 52.5 vs. $52.5 Gy, re-
spectively. The dashed horizontal lines reflect the dose ranges as-
cribed to each data point. The upper x-axis range of the highest
data point for Fisch et al. (7) and Roach et al. (10) are unknown.
The mean doses of van der Wielen et al. (13) and Mangar et al.
(8) are estimated from the subgroup data. The x-axis values for Wer-
nicke et al. (14) are D60 and for Fisch et al. (7) are D70 (i.e., min-
imum dose received by 60% or 70% volume of the penile bulb). A
thick solid line represents the fitted model with sample size correc-
tion, with 95% confidence intervals (dotted curves).
Radiation effects in penile bulb d M. ROACH III et al. S133](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-133-320.jpg)
![TOWARD ACCURATE DOSE ESTIMATION
The necessary elements to achieve routine determination
of DA include: (1) a time-dependent description of the patient
anatomy and treatment parameters over the course of therapy,
(2) a method to calculate the dose applied at each of those
time points, and (3) the ability to generate a cumulative deliv-
ered dose distribution over the course of therapy for each
small (few mm3
) subvolume of tissue. It should be noted
that these elements set aside the additional complexity asso-
ciated with iatrogenic cell or fluid loss over the course of ther-
apy - a largely ignored complexity in this context.
Time-dependent descriptors of the patient anatomy and
treatment
Volumetric imaging (computed tomography [CT], mag-
netic resonance [MR], positron emission tomography) and
three-dimensional treatment planning are now elements of
routine care in radiation oncology. The adoption of inverse
planning techniques for intensity-modulated radiation ther-
apy has also driven the creation of standard protocols for con-
touring and segmentation (9), as well as the continuing
development of automated segmentation tools in the treat-
ment planning domain (10). The development of time-depen-
dent associations of anatomical structures is also being
pursued to assist in the segmentation of time-course studies
(11, 12). In addition to advances in imaging and segmenta-
tion for simulation, image-guidance technologies at the
time of treatment are being employed for directing therapy.
Current systems, such as kV and megavoltage cone-beam
CT, megavoltage CT, and, in the future, MR imaging, while
assuring geometric targeting of the tumor, also provide a po-
tential wealth of valuable information about the patient’s nor-
mal anatomy. Thus, it is now possible to have an image-based
record of the relevant anatomy at each fraction of the
treatment.
However, this valuable imaging information will only con-
tribute to dose record activities if effective, automated seg-
mentation methods are developed to address the laborious
nature of manual segmentation. The development of
model-based approaches to segmentation is congruent with
an important trend toward the adoption of structured descrip-
tions or atlases of patient anatomy. Further efforts in this area
do not need to be overly complex, but, rather, rigorous and
unifying (13, 14). For example, the failure to develop stan-
dards for contouring of relevant anatomy (e.g., inner and
outer wall of rectum, or superior/inferior extent of rectum)
continues to confound inter-institutional comparisons as
well as intra-institutional standardization.
In addition to image-based descriptions of the patient anat-
omy, developments in intensity-modulated radiation therapy
have required the use of electronic descriptions of the de-
tailed treatment parameters (e.g., DICOM-radiation therapy
control points) that are stored within the electronic medical
record and verified at each treatment fraction. In combination
with the guidance images, the records provide a highly
descriptive account of the treatment from which DA could
be accurately determined, provided image-guidance adjust-
ments are recorded, the machine is operating within specified
tolerances, and accurate dose calculation methods are
available.
Improvements in the accuracy of dose calculation
Accurately accounting for tissue heterogeneities is funda-
mental to improving the modeling and prediction of dose–
volume effects in radiation therapy. The accuracy of a calcu-
lated dose distribution is strongly dependent on the algorithm
used to account for heterogeneities (15, 16). Monte Carlo
methods, which can model the transport of radiation through
all the components of the treatment unit head, as well as
through the CT-based patient geometry, represent the gold
standard of dose calculations (17, 18). The use of Monte
Carlo dose calculations for research studies prospectively
and even retrospectively is growing (19, 20). The benefits
of which are expected to be realized in regions of substantial
tissue heterogeneity (e.g., for lung or head-and-neck treat-
ments), as well as in low dose (21) or out-of-field regions
(22). Despite calculation advances, currently used dose–vol-
ume constraints are typically based on data largely calculated
either without any accounting for tissue heterogeneities, or
using very simple methods (23–25). The impact of heteroge-
neity corrections, or the type of heterogeneity corrections, on
the dose–volume analysis of treatment outcomes is poorly
studied. Recent work shows that tumor control probability
modeling was affected by the underlying dose calculation ac-
curacy (retrospective Monte Carlo–based corrections vs.
path-length based corrections) (26). As its use propagates,
proton therapy will not only alter the dose to normal tissues
and contribute to our understanding of dose–volume effects,
but also highlight the dose computation challenges that re-
main for this technology (27).
Development of tissue deformation and tracking tools
The development and validation of deformable registration
algorithms has enabled tracking of mobile tissues over the
treatment course and, in some cases, during the treatment frac-
tion. Tissue deformation tracking can improve the accuracy of
DA for both the target volume and the critical normal tissues.
Validation of these methods is typically achieved using intrin-
sic features (e.g., bifurcations in blood vessels) or fiducials
(e.g., gold markers) that can be confidently localized and com-
pared with the deformation estimate of displacement (28, 29).
The lung presents a unique challenge as the volume changes
substantially between inhale and exhale. Studies have inves-
tigated the effect of different interpolation methods on the
accumulation of dose with changes in volumes (30). Using
four-dimensional cone beam CT images (31) or, in the future,
dynamic MR imaging (32), obtained at each treatment frac-
tion should improve the accuracy of the DA distribution by
modeling the breathing motion and the residual setup uncer-
tainties that cannot be accounted for with simple couch
corrections. Geometric tracking of tissue over the course of
treatment becomes increasingly difficult in the presence of
large changes in tissue volume (33, 34). Ultimately, the
S136 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-136-320.jpg)
![fully benefiting from genomic and proteomic studies of nor-
mal tissue radiosensitivity. Hence, these records need to be of
sufficient flexibility to allow complex volume (alternative
structures [e.g., portions of the lung]) and time dependent ef-
fects (e.g., variations in dose rate across intensity-modulated
radiation therapy practice) to be integrated into the analysis.
SUMMARY
The goal of generating accurate DA distributions to target
and normal tissues as a part of routine radiotherapy practice
is feasible. However, key research and development areas
need to be accelerated, including: auto-segmentation, defor-
mation modeling, dose accumulation, dose calculation in
complex environments, and methods of estimating the uncer-
tainty in the accumulated dose distribution over the course of
therapy. In addition to these research initiatives, informatics
developments are necessary to make the tracking of dose
a feasible and viable activity, including, support for workflow
tools that allow automated image segmentation and dose ac-
cumulation with efficient review and validation. Finally, the
efforts will not succeed without a corresponding level of in-
vestment in the leadership required to formulate standardized
methods and nomenclature to allow the volumetric results to
be compared in a direct and productive fashion. It should go
without saying that accomplishing the goal of accurate nor-
mal tissue dose response would also assist in tumor dose-re-
sponse characterization, provide methods for adaptive
approaches, and eliminate a confounding variable in studies
of individualized normal tissue radiosensitivity. Accurately
estimating DA is a critical element in the drive to maximize
the performance and safe application of radiation therapy
for the individual patient.
REFERENCES
1. Kutcher GJ, Mageras GS, Leibel SA. Control, correction, and
modeling of setup errors and organ motion. Seminars in Radia-
tion Oncology 1996;5:134.
2. Langen KM, Jones DT. Organ motion and its management. Int J
Radiat Oncol Biol Phys 2001;50:265–278.
3. Keall PJ, Beckham WA, Booth JT, et al. A method to predict the
effect of organ motion and set-up variations on treatment plans.
Australas Phys Eng Sci Med 1999;22:48–52.
4. Yan D, Jaffray DA, Wong JW. A model to accumulate fraction-
ated dose in a deforming organ. Med Phys 1999;44:665.
5. Bos LJ, van der Geer J, van Herk M, et al. The sensitivity of
dose distributions for organ motion and set-up uncertainties in
prostate IMRT. Radiother Oncol 2005;76:18–26.
6. O’Daniel JC, Garden AS, Schwartz DL, et al. Parotid gland
dose in intensity-modulated radiotherapy for head and neck can-
cer: is what you plan what you get? Int J Radiat Oncol Biol Phys
2007;69:1290–1296.
7. ICRU50. ICRU report 50: Prescribing, recording, and reporting
photon beam therapy. Bethesda, Maryland: International Com-
mission on Radiation Units and Measurements; 1993.
8. ICRU62. ICRU report 62: Prescribing, recording, and reporting
photon beam therapy (Supplement to ICRU Report 50). Be-
thesda, MD, USA: International Commission on Radiation
Units and Measurements; 1999.
9. Gregoire V, De Neve W, Eisbruch A, et al. Intensity-modulated
radiation therapy for head and neck carcinoma. Oncologist
2007;12:555–564.
10. Pekar V, McNutt TR, Kaus MR. Automated model-based organ
delineation for radiotherapy planning in prostatic region. Int J
Radiat Oncol Biol Phys. 2004;60:973–980.
11. Ezhil M, Starkschall G, Mohan R, et al. Validation of a model-
based segmentation approach to propagating normal anatomic
regions of interest through the 10 phases of respiration. Int J Ra-
diat Oncol Biol Phys 2008;71:900–906.
12. Wang H, Garden AS, Zhang L, et al. Performance evaluation of
automatic anatomy segmentation algorithm on repeat or four-di-
mensional computed tomography images using deformable im-
age registration method. Int J Radiat Oncol Biol Phys 2008;72:
210–219.
13. Kim JJ, Breen SL, Aj Waldron, et al. A Standardized Nomen-
clature System for Head and Neck (HN) IMRT Contouring,
Planning and Quality Assurance. Int J Radiat Oncol Biol
Phys 2007;70. S473.
14. Gregoire V, Coche E, Cosnard G, et al. Selection and delinea-
tion of lymph node target volumes in head and neck conformal
radiotherapy. Proposal for standardizing terminology and pro-
cedure based on the surgical experience. Radiother Oncol
2000;56:135–150.
15. Papanikolaou N, Battista J, Boyer A, et al. AAPM Report No.
85: Tissue inhomogeneity corrections for megavoltage photon
beams. Madison, WI: Medical Physics Publishing; 2004.
16. Ahnesjo A, Aspradakis MM. Dose calculations for external pho-
ton beams in radiotherapy. Phys Med Biol 1999;44:R99–155.
17. Verhaegen F, Seuntjens J. Monte Carlo modelling of external
radiotherapy photon beams. Phys Med Biol 2003;48:R107–
R164.
18. Chetty IJ, Curran B, Cygler JE, et al. Report of the AAPM Task
Group No. 105: Issues associated with clinical implementation
of Monte Carlo-based photon and electron external beam treat-
ment planning. Med Phys 2007;34:4818–4853.
19. Lindsay PE, El Naqa I, Hope AJ, et al. Retrospective monte
carlo dose calculations with limited beam weight information.
Med Phys 2007;34:334–346.
20. Stroian G, Martens C, Souhami L, et al. Local Correlation Be-
tween Monte-Carlo Dose and Radiation-Induced Fibrosis in
Lung Cancer Patients. Int J Radiat Oncol Biol Phys 2008;70:
921–930.
21. Jang SY, Liu HH, Mohan R. Underestimation of low-dose radi-
ation in treatment planning of intensity-modulated radiother-
apy. Int J Radiat Oncol Biol Phys 2008;71:1537–1546.
22. Kry SF, Titt U, Followill D, et al. A Monte Carlo model for out-
of-field dose calculation from high-energy photon therapy. Med
Phys 2007;34:3489–3499.
23. Bradley J, Graham MV, Winter K, et al. Toxicity and outcome
results of RTOG 9311: A phase I-II dose-escalation study using
three-dimensional conformal radiotherapy in patients with inop-
erable non-small-cell lung carcinoma. Int J Radiat Oncol Biol
Phys 2005;61:318–328.
24. Kwa SLS, Lebesque JV, Theuws JCM, et al. Radiation
pneumonitis as a function of mean lung dose: an analysis of
pooled data of 540 patients. Int J Radiat Oncol Biol Phys
1998;42:1–9.
25. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue
to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21:
109–122.
26. Mu Y, Hope A, Lindsay P, et al. Statistical Modelling of Tumor
Control Probability for Non-small-cell Lung Cancer Radiother-
apy. Int J Radiat Oncol Biol Phys 2008;72. S448.
27. Goitein M. Magical protons? Int J Radiat Oncol Biol Phys
2008;70:654–656.
S138 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-138-320.jpg)
![for regional portal venous perfusion dysfunction 1 month
post-RT (14). Furthermore, it has been demonstrated that
the regional liver venous perfusion dysfunction is associated
with overall liver function (30). An alternative reoptimization
strategy could be reoptimization of irradiation geometry
based on local normal tissue damage (31); however, it is
questionable whether the changes would be detectable early
enough to allow modification of already started treatment
regimen.
Imaging as a biomarker
Imaging biomarkers are characteristics that can be objec-
tively imaged as indicators of normal biological processes,
pathogenic processes, or pharmacologic responses to thera-
peutic interventions. Imaging biomarkers as surrogate end-
points are imaging biomarkers that are intended to
substitute for clinical endpoints. Surrogate endpoints are
expected to predict clinical benefit (or harm or lack of benefit
or harm) based on epidemiologic, therapeutic, pathophysio-
logic, or other scientific evidence.
Imaging biomarkers should be discussed in the context of
molecular biomarkers, which are described in detail else-
where (see Bentzen et al., this issue). Molecular biomarkers
have biophysical properties, which allow their measurements
in biological samples, such as plasma, serum, cerebrospinal
fluid, or biopsy samples. Molecular biomarkers can detect
molecular and cellular changes with high sensitivity but might
not be very specific. For example, the hematocrit or other
blood counts can be a sensitive measure of marrow function.
However, they can also be affected by dysfunction caused by
other conditions (e.g., bowel disease or malnutrition affecting
hematocrit). Further, molecular markers lack spatial informa-
tion. Thus, they may be useful in the realm of whole organ
irradiation (e.g., blood counts for total body irradiation or liver
function tests for whole liver irradiation) but may not be
sensitive for regional organ effects. Similar limitations hold
for molecular biomarkers obtained from biopsy samples,
which sample only few points in the organ, thus being unable
to assess the regional organ response heterogeneity. On the
contrary, imaging has the unique potential for detecting the
spatial distribution of the tissue damage that can lead to organ
dysfunction. Common to imaging and molecular biomarkers
(32) is that they may beused to identify patients at increased or
decreased risk for radiation treatment-related injury. In some
settings, imaging and molecular biomarkers may be synergis-
tic, and their combined use may overcome inherent limita-
tions of each single approach, thereby increasing overall
sensitivity and specificity of the assessment.
Multiple obstacles lie in the path toward establishment of
imaging biomarkers as surrogate endpoints for assessment
and prediction of clinical injury. Challenges for quantitative
imaging are discussed in the next section. Other obstacles in-
clude unknown temporal dynamics of RT-induced injury, un-
derstanding of normal biology, and the relationship between
early normal tissue damage and late symptomatic organ dys-
function. In addition, RT is often combined with chemother-
apy and molecular targeted therapies; normal tissue toxicity
can result from either modality separately or through a syner-
gistic effect of combined therapies. New knowledge about
the mechanisms of normal tissue toxicity and potential inhi-
bition of the effects, for example, with anti-inflammatory
compounds (e.g., inhibitors of prostaglandin and leukotriene
formation, NFkB and interleukin [IL]-1 signaling) might sig-
nificantly affect RT-induced toxicity management. Monitor-
ing induction, resolution, and mitigation of radiation-induced
toxicity will be essential in the development of clinically suc-
cessful normal tissue preserving strategies. Molecular imag-
ing might be particularly useful to study and monitor these
changes. However, much work still needs to be done before
relevant molecular probes are developed to explore fully the
potential that molecular imaging offers for questions relevant
to human clinical imaging.
Need for quantitative imaging of normal tissue toxicity
Imaging modalities and techniques, primarily developed
with clinical diagnostic application in mind, are often not
quantitative enough to raise imaging to the level of a bio-
marker. Imaging, although it has a quantitative physical ba-
sis, is often burdened with significant uncertainties,
preventing characterization of small changes that are charac-
teristic of moderate normal tissue injury. It is important that
quantification is ensured through the whole procedure—
from image acquisition and image reconstruction to image
analysis. The assessment of imaging as either a biomarker
or surrogate endpoint also requires quantitative clinical end-
points. However, whereas imaging endpoints are usually
continuous, most clinical endpoints are dichotic. Using a con-
tinuous variable for measurement of an organ function or
stage of injury could improve statistical power for correlative
analysis relating imaging to clinical events, thereby reducing
the number of patients required for studies. Although qualita-
tive diagnostic imaging does not carry the same value as
quantitative imaging, it can be useful in the diagnosis of nor-
mal tissue effects (e.g., esophageal stricture seen on barium
swallow, cerebral edema, on CT/MRI).
Clearly, these problems call for a wide cooperative effort
among various governmental, professional, and industrial en-
tities. Some of these efforts have already begun. Initial efforts
started within individual professional societies: Radiological
Society of North America, American College of Radiology,
American Association of Physicists in Medicine, Society of
Nuclear Medicine, International Society for Magnetic Reso-
nance in Medicine; however, it was soon realized that the
problems are too significant to be solved by a single profes-
sional society. The first organized effort was initiated by Na-
tional Cancer Institute (NCI) and Association of American
Cancer Institutes in 2003. It lead to the formation of Image
Response Assessment Teams (IRAT) with the purpose to fa-
cilitate development of multidisciplinary teams in NCI-des-
ignated comprehensive cancer centers to advance the role
of imaging in assessment of response to therapy. The IRAT
project’s primary objective was to increase collaboration be-
tween imaging scientists and oncology investigators to en-
hance the use of quantitative anatomic, functional, and
S142 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-142-320.jpg)
![12. Marks LB, Prosnitz RG, Hardenbergh PH. Functional conse-
quences of radiation (RT)-induced perfusion changes in patients
with left-sided breast cancer. Int J Radiat Oncol Biol Phys 2002;
54:3–4.
13. Prosnitz RG, Hubbs JL, Evans ES, et al. Prospective assessment
of radiotherapy-associated cardiac toxicity in breast cancer pa-
tients: Analysis of data 3 to 6 years after treatment. Cancer
2007;110:1840–1850.
14. Cao Y, Platt JF, Francis IR, et al. The prediction of radiation-
induced liver dysfunction using a local dose and regional
venous perfusion model. Med Phys 2007;34:604–612.
15. Munden RF, Erasmus JJ, Smythe WR, et al. Radiation injury to
the liver after intensity-modulated radiation therapy in patients
with mesothelioma: An unusual CT appearance. AJR Am J
Roentgenol 2005;184:1091–1095.
16. Hahn CA, Zhou SM, Dunn RH, et al. Dose-dependent effects of
radiation therapy on cerebral blood flow, metabolism and neu-
rocognitive dysfunction. Int J Radiat Biol Phys 2005;62(Suppl.
1):S67.
17. Rutkowski T, Tarnawski R, Sokol M, et al. 1H-MR spectros-
copy of normal brain tissue before and after postoperative radio-
therapy because of primary brain tumors. Int J Radiat Oncol
Biol Phys 2003;56:1381–1389.
18. Usenius T, Usenius JP, Tenhunen M, et al. Radiation-induced
changes in human brain metabolites as studied by 1H nuclear
magnetic resonance spectroscopy in vivo. Int J Radiat Oncol
Biol Phys 1995;33:719–724.
19. Waldrop SM, Davis PC, Padgett CA, et al. Treatment of brain
tumors in children is associated with abnormal MR spectro-
scopic ratios in brain tissue remote from the tumor site. AJNR
Am J Neuroradiol 1998;19:963–970.
20. Buus S, Grau C, Munk OL, et al. 11C-methionine PET, a novel
method for measuring regional salivary gland function after ra-
diotherapy of head and neck cancer. Radiother Oncol 2004;73:
289–296.
21. Zhang L, Murata Y, Ishida R, et al. Functional evaluation with
intravoxel incoherent motion echo-planar MRI in irradiated sal-
ivary glands: A correlative study with salivary gland scintigra-
phy. J Magn Reson Imaging 2001;14:223–229.
22. Brush J, Lipnick SL, Phillips T, et al. Molecular mechanisms of
late normal tissue injury. Semin Radiat Oncol 2007;17:121–
130.
23. Atwood T, Payne VS, Zhao W, et al. Quantitative magnetic res-
onance spectroscopy reveals a potential relationship between ra-
diation-induced changes in rat brain metabolites and cognitive
impairment. Radiat Res 2007;168:574–581.
24. Atwood T, Robbins ME, Zhu JM. Quantitative in vivo proton
MR spectroscopic evaluation of the irradiated rat brain.
J Magn Reson Imaging 2007;26:1590–1595.
25. Darby SC, McGale P, Taylor CW, et al. Long-term mortality
from heart disease and lung cancer after radiotherapy for early
breast cancer: Prospective cohort study of about 300,000
women in US SEER cancer registries. Lancet Oncol 2005;6:
557–565.
26. Muryama S, Akamine T, Sakai S, et al. Risk factor of radiation
pneumonitis: Assessment with velocity-encoded cine magnetic
resonance imaging of pulmonary artery. J Comput Assist
Tomogr 2004;28:204–208.
27. Guerrero T, Johnson V, Hart J, et al. Radiation pneumonitis:
Local dose versus [18F]-fluorodeoxyglucose uptake response
in irradiated lung. Int J Radiat Oncol Biol Phys 2007;68:
1030–1035.
28. Hart JP, McCurdy MR, Ezhil M, et al. Radiation pneumonitis:
Correlation of toxicity with pulmonary metabolic radiation
response. Int J Radiat Oncol Biol Phys 2008;71:967–971.
29. Hassaballa HA, Cohen ES, Khan AJ, et al. Positron emission
tomography demonstrates radiation-induced changes to nonir-
radiated lungs in lung cancer patients treated with radiation
and chemotherapy. Chest 2005;128:1448–1452.
30. Cao Y, Pan C, Balter JM, et al. Liver function after irradiation
based on computed tomographic portal vein perfusion imaging.
Int J Radiat Oncol Biol Phys 2008;70:154–160.
31. Zhang G, Dilling TJ, Stevens CW, et al. Functional lung imag-
ing in thoracic cancer radiotherapy. Cancer Control 2008;15:
112–119.
32. Fleckenstein K, Gauter-Fleckenstein B, Jackson IL, et al. Using
biological markers to predict risk of radiation injury. Semin
Radiat Oncol 2007;17:89–98.
S144 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-144-320.jpg)
![endpoints are required for the success of such projects.
Studies of this kind, together with the recent explosion in
radiotherapy planning and delivery tools, leading to more
diversity in dose distributions, may provide an exciting
time when the complex responses of normal tissues to
radiation can be better understood.
REFERENCES
1. Bentzen S. Towards evidence based radiation oncology:
Improving the design, analysis, and reporting of clinical out-
come studies in radiotherapy. Radiother Oncol 1998;46:5–18.
2. Trotti A, Bentzen S. The need for adverse effects reporting stan-
dards in oncology clinical trials. J Clin Oncol 2004;22:19–22.
3. Wong C, Van Dyk J, Milosevic M, et al. Radiation myelopathy
following single courses of radiotherapy and retreatment. Int J
Radiat Oncol Biol Phys 1994;30:575–581.
4. Jackson A, Yorke E, Rosenzweig K. The atlas of complication
incidence: A proposal for a new standard for reporting the
results of radiotherapy protocols. Semin Radiat Oncol 2006;
16:260–268.
5. Schultheiss TE. Spinal cord radiation tolerance. Int J Radiat
Oncol Biol Phys 1994;30:735–736.
6. Hope AJ, Lindsay PE, Naqa IE, et al. Modeling radiation pneu-
monitis risk with clinical, dosimetric, and spatial parameters. Int
J Radiat Oncol Biol Phys 2006;65:112–124.
7. Hernando ML, Marks LB, Bentel GC, et al. Radiation-induced
pulmonary toxicity: A dose-volume histogram analysis in 201
patients with lung cancer. Int J Radiat Oncol Biol Phys 2001;
51:650–659.
8. Kong F-M, Hayman J, Griffith K, et al. Final toxicity results of
a radiation-dose escalation study in patients with non-small-cell
lung cancer (NSCLC): Predictors for radiation pneumonitis and
fibrosis. Int J Radiat Oncol Biol Phys 2006;65:1075–1086.
9. Pan CC, Eisbruch A, Lee JS, et al. Prospective study of inner ear
radiation dose and hearing loss in head-and-neck cancer
patients. Int J Radiat Oncol Biol Phys 2005;61:1393–1402.
10. Jackson A, Skwaarchuk MW, Zelefsky MJ, et al. Late rectal
bleeding after conformal radiotherapy of prostate cancer (II):
Volume effects and dose-volume histograms. Int J Rad Oncol
Biol Phys 2001;49:685–698.
11. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of
the risk of postoperative pulmonary complications among
esophageal cancer patients treated with concurrent chemoradio-
therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006;
66:754–761.
12. Jackson A. Partial organ irradiation of the rectum. Seminars
Radiat Oncol 2001;11:215–223.
13. Jackson A, Yorke ED, Rosenzweig KE, et al. EUD and dose-
volume based atlases of complication incidence: A proposal
for new standards in reporting results of treatment protocols
[abstract]. ASTRO 2006 Philadelphia, PA; 2006., Int J Radiat
Oncol Biol Phys 2006;66(S3):S124-125
14. Jackson A, Ten Haken RK, Robertson JM, et al. Analysis of
clinical complication data for radiation hepatitis using a parallel
architecture model. Int J Radiat Oncol Biol Phys 1995;31:883–
891.
15. Wei LJ. Testing goodness of fit for proportional hazards model
with censored observations. J Am Stat Assoc 1984;79:649–652.
16. Hae H, Lee S. Comparison of goodness of fit tests for the cox
proportional hazards model. Comm Stat Simulat Comput
2000;29:187–206.
17. Le C, Zelterman D, Le C. Goodness of fit tests for proportional
hazards regression models. Biometrical J 1992;34:557–566.
18. Schoenfeld D. Chi-squared goodness-of-fit tests for the propor-
tional hazards regression model. Biometrika 1980;67:145–153.
19. Skwarchuk M, Jackson A, Zelefsky M, et al. Late rectal toxicity
after conformal radiotherapy of prostate cancer (I): Multivariate
analysis and dose-response. Int J Radiat Oncol Biol Phy 2000;
47:103–113.
20. Storey MR, Pollack A, Zagars G, et al. Complications from
radiotherapy dose escalation in prostate cancer: Preliminary
results of a randomized trial. Int J Radiat Oncol Biol Phys
2000;48:635–642.
21. Kupelian P, Reddy C, Carlson T, et al. Dose/volume relation-
ship of late rectal bleeding after external beam radiotherapy
for localized prostate cancer: Absolute or relative rectal
volume? Cancer J Sci Am 2002;8:62–66.
22. Fenwick JD, Khoo VS, Nahum AE, et al. Correlations between
dose-surface histograms and the incidence of long-term rectal
bleeding following conformal or conventional radiotherapy
treatment of prostate cancer. Int J Radiat Oncol Biol Phys
2001;49:473–480.
23. Koper PC, Heemsbergen WD, Hoogeman MS. Impact of
volume and location of irradiated rectum wall on rectal blood
loss after radiotherapy of prostate cancer. Int J Radiat Oncol
Biol Phys 2004;58:1072–1082.
24. Garcia-Vincente F, Zapatero A, Floriano A, et al. Statistical
analysis of dose-volume and dose-wall histograms for rectal
toxicity following 3D-CRT in prostate cancer. Med Phys
2005;32:2503–2509.
25. Yorke ED, Jackson A, Rosenzweig KE, et al. Correlation of
dosimetric factors and radiation pneumonitis for non-small-
cell lung cancer patients in a recently completed dose escalation
study. Int J Radiat Oncol Biol Phys 2005;63:672–682.
26. Levegrun S, Jackson A, Zelefsky M, et al. Risk group
dependence of dose response for biopsy outcome after three-
dimensional conformal radiation therapy of prostate cancer.
Radiother Oncol 2002;63:11–26.
27. Bradley J, Hope A, Naqa IE, et al. A nomogram to predict radi-
ation pneumonitis, derived from a combined analysis of RTOG
9311 and institutional data. Int J Radiat Oncol Biol Phys 2007;
69:985–992.
28. Tucker S, Liu H, Liao Z, et al. Analysis of radiation pneumoni-
tis risk using a generalized Lyman model. Int J Radiat Oncol
Biol Phys 2008;72:568–574.
29. Heemsbergen WD, Hoogeman MS, Hart GA, et al. Gastrointes-
tinal toxicity and its relation to dose distributions in the anorec-
tal region of prostate cancer patients treated with radiotherapy.
Int J Radiat Oncol Biol Phys 2005;61:1011–1018.
30. Peeters ST, Lebesque JV, Heemsbergen WD. Localized volume
effects for late rectal and anal toxicity after radiotherapy for
prostate cancer. Int J Radiat Oncol Biol Phys 2006;64:1151–
1161.
31. Eisbruch A, Ten Haken RK, Kim HM, et al. Dose, volume, and
function relationships in parotid salivary glands following con-
formal and intensity-modulated irradiation of head and neck
cancer. Int J Radiat Oncol Biol Phys 1999;45:577–587.
32. Schilstra C, Meertens H. Calculation of the uncertainty in com-
plication probability for various dose-response models, applied
to the parotid gland. Int J Radiat Oncol Biol Phys 2001;50:147–
158.
33. Blanco AI, Chao KS, Naqa IE. Dose-volume modeling of
salivary function in patients with head-and-neck cancer receiv-
ing radiotherapy. Int J Radiat Oncol Biol Phys 2005;62:1055–
1069.
34. Chao KS, Deasy JO, Markman J, et al. A prospective study of
salivary function sparing in patients with head-and-neck
cancers receiving intensity-modulated or three-dimensional
radiation therapy: Initial results. Int J Radiat Oncol Biol Phys
2001;49:907–916.
The lessons of QUANTEC d A. JACKSON et al. S159](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-159-320.jpg)
![35. Eisbruch A, Ship JA, Kim HM, et al. Partial irradiation of the
parotid gland. Semin Radiat Oncol 2001;11:234–239.
36. Jellema AP, Doornaert P, Slotman BJ, et al. Does radiation dose
to the salivary glands and oral cavity predict patient-rated xero-
stomia and sticky saliva in head and neck cancer patients treated
with curative radiotherapy? Radiother Oncol 2005;77:164–171.
37. Saarilahti K, Kouri M, Collan J, et al. Erratum to ‘‘sparing of the
submandibular glands by intensity modulated radiotherapy in
the treatment of head and neck cancer’’ [Radiother. Oncol. 78
(2006) 270–275]. Radiother Oncol 2006;80:107–108.
38. Saarilahti K, Kouri M, Collan J, et al. Sparing of the submandib-
ular glands by intensity modulated radiotherapy in the treatment
of head and neck cancer. Radiother Oncol 2006;78:270–275.
39. LENT SOMA Tables: Table of contents 1995. Radiother Oncol
1995;35:17–60.
40. Overgaard J, Bartelink H. About tolerance and quality. An im-
portant notice to all radiation oncologists. Radiother Oncol
1995;35:1–3.
41. Pavy J-J, Denekamp J, Letschert J, et al. EORTC late effects
working group. Late effect toxicity scoring: The SOMA scales.
Radiother Oncol 1995;35:11–15.
42. Rubin P, Constine LS, Fajardo LF, et al. RTOG late effects
working group: Overview of late effects normal tissues
(LENT) scoring system. Radiother Oncol 1995;35:9–10.
43. Denekamp J, Bartelink H, Rubin P, et al. Correction for the use
of the SOMA LENT tables. Radiother Oncol 1996;39:191.
S160 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010](https://image.slidesharecdn.com/emamiupdate-quantec-130930130141-phpapp02/85/QUANTEC-160-320.jpg)
Uploaded byTeresa Muñoz Migueláñez
QUANTEC
This introductory paper presents a special issue of the International Journal of Radiation Oncology, Biology, Physics focused on the QUANTEC initiative, aimed at improving the quantitative analysis of normal tissue effects in radiation therapy. The issue includes various organ-specific reviews, highlighting the evolution of dose/volume/outcome data since the classic Emami paper, and emphasizing the need for ongoing research to address current limitations in predictive models. Overall, QUANTEC serves as a vital resource for clinicians to inform treatment planning and reduce normal tissue toxicity risks while providing insights for future investigations.
More Related Content
QUANTEC
- 1. INTRODUCTORY PAPER GUEST EDITOR’SINTRODUCTION TO QUANTEC: A USERS GUIDE LAWRENCE B. MARKS, M.D.,* RANDALL K. TEN HAKEN, PH.D.,y GUEST EDITORS, AND MARY K. MARTEL, PH.D.,z ASSOCIATE GUEST EDITOR *University of North Carolina, Chapel Hill, North Carolina; y University of Michigan, Ann Arbor, Michigan; and z M. D. Anderson Cancer Center, Houston, Texas We are pleased to present this special issue of the International Journal of Radiation Oncology$Biology$Physics, dedicated to the Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC). This work is the result of the diligent ef- forts of numerous investigators, authors, reviewers, and support personnel. We are particularly indebted to the comembers of the QUANTEC Steering Committee1 , for their dedication. This is an exciting time in the field of radiation oncology. Sophisticated treatment-planning tools and delivery systems remarkably increase our ability to steer the dose where we want it. An increased knowledge of how dose distributions af- fect normal tissue outcomes is critically needed to know how best to exploit these new planning/delivery tools. In 1991, Emami et al. (1) published a comprehensive review of the available dose/volume/outcome data, along with expert opin- ion where data were lacking. Since the publication of the clas- sic paper by Emami et al. (1), there have been numerous additional studies providing dose/volume/outcome data. The QUANTEC reviews provide focused summaries of the dose/volume/outcome information for many organs. The re- views will be excellent resources to assist physicians and treatment planners in determining acceptable dose/volume constraints. In addition, the QUANTEC papers point out the shortcomings of current predictive models and suggest areas for future research. Despite the limitations of the data, the new information presented should be of substantial use in the treat- ment planning process. We are particularly pleased with the many summary tables and figures that, we hope, will adorn the walls of treatment planning areas. This special issue is organized into three sections. There are two introductory papers: the first paper is an overview/history with some scientific issues related to the QUANTEC effort, and the second paper contains suggestions on how to ratio- nally incorporate the QUANTEC metrics/models into clinical practice. The latter paper includes a large summary table of dose/volume/outcome data. The bulk of this issue is 16 organ- specific clinical papers. To assist the reader, each article is organized in a consistent format that includes 10 sections (Fig. 1). The organs discussed were selected because the authors believed that there were meaningful data to review, and a clinical need to better summarize the available dose/vol- ume data for these organs. We conclude with a series of vision papers outlining interesting issues that merit further study. Dr. Philip Rubin, at the University of Rochester, the found- ing Editor of this journal, was an early leader in the field of radiation-induced normal tissue injury. He conducted many of the classic studies of normal tissue response and provided some of the earliest summaries of normal tissue dose/volume/ outcome estimates. It is particularly fitting that an entire issue of the International Journal of Radiation Oncology$ Biology$Physics be devoted to a topic so very dear to our founding editor. QUANTEC represents an evolution from the early sum- mary tables presented by Dr. Rubin, to the more recent re- views by investigators such as Emami et al. (1). All those involved in the QUANTEC effort recognize that much work remains to be done. For example, most of the available data relate to conventionally fractionated conformal irradia- tion, i.e., not hypofractionated or intensity-modulated ap- proaches. We anticipate regular updates of the information and believe these will help our field continue to provide qual- ity care to our patients. We hope to be able to provide updated Reprint requests to: Dr. Lawrence B. Marks, M.D., University of North Carolina, Department of Radiation Oncology, CB 7512, Chapel Hill, NC 27514. Tel: (919) 966-0400; Fax: (919) 966- 7681; E-mail: marks@med.unc.edu The QUANTEC effort was made possible, in part, by generous financial support from the American Society for Radiation Oncol- ogy (ASTRO) and the American Association of Physicists in Medicine (AAPM). This special supplement to the Red Journal was supported by ASTRO. Acknowledgments—We thank the leaders of ASTRO’s Research Council and Health Services Research Committee (Drs. David Morris and Carol Hahn) and the AAPM Science Council. Special thanks to Beth Notzon and Deborah Williams at the International Journal of Radiation Oncology$Biology$Physics and Jessica Hubbs at University of North Carolina for oversight and patience with the review/editing process. Members of the 1 QUANTEC steering com- mittee: Drs. Søren M. Bentzen, Louis S. Constine, Joseph O. Deasy, Avi Eisbruch, Andrew Jackson, Lawrence B. Marks, Randy Ten Haken, and Ellen D. Yorke. Received Aug 27, 2009. Accepted for publication Aug 28, 2009. S1 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S1–S2, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.08.075
- 2. QUANTEC reviews onan ASTRO-sponsored web site, as well as perhaps on a bulletin board or blog where readers can provide comments/data for consideration for future re- views. Attempts to limit normal tissue risks should be taken in the context of the competing need to deliver a ‘‘therapeutic dose distribution.’’ Target coverage may trump normal tissue spar- ing: recurrent tumor can be morbid/lethal, and the normal tis- sue risks considered in the QUANTEC reviews are often not life threatening. Furthermore, QUANTEC’s focus on three-di- mensional dose/volume parameters reinforces the reliance on dose-volume histogram-based optimization systems to mini- mize normal tissue risk. It is important to remember that rela- tively simple measures (e.g., careful attention to patient positioning) can reduce normal tissue exposure and comple- ment our newer planning/delivery/optimization tools. It is humbling to have helped lead this QUANTEC effort, and it was a privilege to work with so many talented and ded- icated people. The information presented here was inspired by our mentors and teachers and relies almost entirely on the published work of others. We hope that current and future generations of investigators—physicians, physicists, biolo- gists, imagers, and others—will continue this area of study. Exploiting the rapidly evolving advances outlined in the vision papers (e.g., imaging, dose monitoring, genetics, and other biologic factors) will facilitate the development of bet- ter tools to understand and reduce the risks of radiation- induced normal tissue injury. REFERENCE 1. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeuticradiation.IntJRadiatOncolBiolPhys1991;21:109–122. Fig. 1. Outline of the issue: the first section consists of Introductory Papers; the second section consists of Organ-Specific Papers, each containing 10 topic sections; and the third section consists of Vision Papers. S2 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 3. INTRODUCTORY PAPER QUANTITATIVE ANALYSESOF NORMAL TISSUE EFFECTS IN THE CLINIC (QUANTEC): AN INTRODUCTION TO THE SCIENTIFIC ISSUES SØREN M. BENTZEN, PH.D., D.SC.,* LOUIS S. CONSTINE, M.D.,y JOSEPH O. DEASY, PH.D.,z AVI EISBRUCH, M.D.,x ANDREW JACKSON, PH.D.,k LAWRENCE B. MARKS, M.D.,{ RANDALL K. TEN HAKEN, PH.D.,x AND ELLEN D. YORKE, PH.D.k From the *Departments of Human Oncology, Medical Physics, Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, WI; y Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY; z Department of Radiation Oncology, Washington University, St. Louis, MO; x Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; k Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY; { Department of Radiation Oncology, University of North Carolina at Chapel Hill, NC Advances in dose–volume/outcome (or normal tissue complication probability, NTCP) modeling since the seminal Emami paper from 1991 are reviewed. There has been some progress with an increasing number of studies on large patient samples with three-dimensional dosimetry. Nevertheless, NTCP models are not ideal. Issues related to the grading of side effects, selection of appropriate statistical methods, testing of internal and external model validity, and quantification of predictive power and statistical uncertainty, all limit the usefulness of much of the published literature. Synthesis (meta-analysis) of data from multiple studies is often impossible because of suboptimal pri- mary analysis, insufficient reporting and variations in the models and predictors analyzed. Clinical limitations to the current knowledge base include the need for more data on the effect of patient-related cofactors, interactions between dose distribution and cytotoxic or molecular targeted agents, and the effect of dose fractions and overall treatment time in relation to nonuniform dose distributions. Research priorities for the next 5–10 years are proposed. Ó 2010 Elsevier Inc. QUANTEC, Normal tissue complications, Overview, Modeling. WHY QUANTEC? Modern radiation therapy (RT) techniques generally yield nonuniform dose distributions in nontarget tissues. The intro- duction of external beam megavoltage RT in the 1950s shifted the most important side effects from the skin and sub- cutaneous tissues to the deeper seated tissues. The ensuing wide adoption of parallel opposing field techniques led to im- provements in target dose homogeneity, but typically led to whole or partial organ irradiation of the neighboring non-tar- get tissues: a fractional volume of an organ at risk would es- sentially receive the prescribed target dose. Because of the limited capabilities to image the tumor extent, most RT fields included liberal margins. Computed tomography–based diagnosis and RT planning in the 1980s and 1990s revolutionized target volume visual- ization and facilitated multiple-field and three-dimensional (3D) conformal RT. Conceptual and technological advances have led to new RT technologies (e.g., intensity-modulated radiation therapy, rotational or helical delivery, robotic delivery, and proton therapy). These technologies typically deliver near-uniform doses to the target volume. However, the dose distribution in the surrounding normal tissues is more variable. Therefore, these new technologies provide the treatment planner with increased flexibility in determining which re- gions of normal tissue are to be incidentally irradiated. The treatment planner needs information to predict the risk of a normal tissue injury for competing 3D dose distributions, such that the therapeutic ratio can be optimized. One of the goals of QUANTEC is to summarize the available 3D dose–volume/outcome data. At the same time, increasing use of combined modality therapy has often increased the burden of early and late tox- icities (1). Understanding the tradeoff between an expected decrease in toxicity resulting from an improved dose distribu- tion, and the possible increase in toxicity with systemic agents, is an increasingly pertinent, yet poorly researched, area. Reprint requests to: Søren M. Bentzen, Ph.D., D.Sc., University of Wisconsin School of Medicine and Public Health, Department of Human Oncology, K4/316 Clinical Science Center, 600 Highland Avenue, Madison, WI 53792. Tel: (608) 265-8572; Fax: (608) 263- 9947; E-mail: bentzen@humonc.wisc.edu Acknowledgment—This work was partially supported by NIH grants CA014520 (S.M.B.), CA85181 (J.O.D.), and CA69579 (L.B.M.), and a grant from the Lance Armstrong Foundation (L.B.M.). Received April 8, 2009, and in revised form Sept 1, 2009. Accepted for publication Sept 2, 2009. S3 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S3–S9, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.09.040
- 4. ANALYZING RT-RELATED TOXICITY Cancersurvivorship issues have been gaining prominence, partly because of the increasing number of cancer survivors; a tripling in the United States (2) between 1970 and 2001. This increase is the result of early diagnosis, screening ef- forts, improved treatments, and an increased incidence of many cancers. Radiation oncologists have pioneered record- ing and analysis of late treatment sequelae and the available literature on late effects is much richer for this modality than for cytotoxic or surgical treatments. However, toxicity is of- ten underreported, and probably underrecorded, even in the more rigorous framework of prospective clinical trials (3– 5). Clearly, this is a special concern in NTCP (normal tissue complication probability) modeling studies where the data analyzed often are retrospectively extracted from charts or databases. The US National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v3.0 is a comprehen- sive dictionary for recording and grading of side effects of all major cancer therapies (6). Widespread adoption of a com- mon grading system for adverse events, such as CTCAE, would improve between-study comparability and is encour- aged. However, CTCAE still combines multiple signs and symptoms into a single grade. Although this may be conve- nient for routine studies and comparisons of therapies across studies, it is associated with a loss of specificity in toxicity- specific studies (7). For such studies, including NTCP mod- eling studies, grades should be atomized (i.e., broken down to specific signs and symptoms that are likely to reflect specific radiation pathophysiologies). The SOMA (Subjective, Ob- jective, Management, Analytic) scale explicitly distinguishes between objective signs and subjective symptoms. For toxic- ity-specific studies, a ‘‘SOMAtized’’ scale—that is, a scale where these components of toxicity are kept separate—is preferable. Grouping several specific toxicities into a single composite endpoint is likely associated with a loss of statis- tical resolution (3, 8). THE EMAMI PAPER AND EARLY NTCP MODELING The paper by Emami et al. (9) is the most frequently cited paper ever published in the International Journal of Radia- tion Oncology Biology Physics, with 1,062 citations accord- ing to the ISI Web of Science (accessed February 3, 2009). This paper published the tolerance doses for irradiation of one third, two thirds, or the whole of various organs. Because high-quality clinical data were scarce, the task force took the bold approach to establish these doses by a simple consensus of clinical experience or opinions. In an accompanying paper, Burman et al. (10) fitted a Lyman model (11) to the Emami consensus dose–volume data thereby facilitating the use of Emami’s constraints for an arbitrary fraction of a whole organ uniformly irradiated. Further, Kutcher et al. (12) proposed a method, a so-called dose–volume histogram (DVH) reduc- tion algorithm, for reducing an arbitrary nonuniform dose distribution into a partial volume receiving the maximum dose, effectively allowing the extrapolation of Emami’s con- straints to any dose distribution. The mathematical method amounted to a common formula for taking a ‘‘generalized mean,’’ although this was not recognized at the time. This Lyman-Kutcher-Burman model, combining Lyman’s model with the Kutcher-Burman DVH reduction scheme, remains the most widely used NTCP model. Although the model claims no deep mechanistic validity, its mathematical form is sufficiently flexible to allow representation of various dose–volume dependencies. Within the structural resolution of current datasets, the Lyman-Kutcher-Burman model can typically not be rejected as a good fit of the data, although it is not always the best model considered. Probabilistic models, studied in groundbreaking papers in the 1980s by Schultheiss (13) and Withers (14), introduced concepts like serial and parallel tissue organization and functional sub- units and became conceptually influential but have played a relatively modest role in actual data analyses except for The Relative Seriality Model (15), that has found some use in analyzing clinical data. SMALL ANIMAL MODELS AND LIMITATIONS TO A DVH-BASED APPROACH DVH-based analyses inherently assume that organ func- tion is uniformly distributed within an organ. Experimental animal studies of the volume effect have produced important proof-of-principle insights that question this assumption. However, these have had relatively little impact on clinical NTCP modeling so far. In 1995, Travis et al. (16, 17) re- ported that partial organ irradiation of a volume of the mouse lung base was more likely to cause radiation pneumonitis than irradiating an identical volume of the apex or, even more pronounced, the middle regions of the lung. Because the histological damage in the lung did not vary with loca- tion, this finding has been interpreted as a result of variation in the functional importance of different lung regions. How- ever, some of the demonstrated effect may have also resulted from inadvertent inclusion of the central airways/vessels within the computed tomography–defined lung. Attempts at modeling location effects in human lung have only been tried relatively recently, with mixed results (see the paper by Marks et al. in this issue). Location effects have also been demonstrated in partial volume irradiation of the parotid gland (18), probably reflecting damage to the excretory ducts, blood vessels, and nerves. Another example where DVH- based analysis for the organ at risk may not be adequate is lung, where irradiation of the heart in addition to the lung has been shown in experimental animals to affect the risk of radiation induced pneumonitis as assessed by respiratory rate (19). Hopewell and Trott (20) analyzed experimental dose–vol- ume data and concluded that ‘‘Volume, as such, is not the rel- evant criterion, since critical, radiosensitive structures are not homogeneously distributed within organs.’’ Work by Trott et al. (21) in 1995 documented a volume effect for functional damage after irradiation of the rat rectum but found no S4 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 5. significant influence ofvolume on structural damage to the rectal wall. The theme of different radiation pathogenesis for different rectal side effects, and therefore varying radiobi- ological properties, has only relatively recently been system- atically analyzed in patients by the group at the Netherlands Kanker Instituut (22). Extensive studies by van der Kogel in the late 1980s show- ing that the probabilistic model did not correctly predict the probability of spinal cord injury after irradiation of two geo- metrically separated 4-mm segments of rat cervical spinal cord undoubtedly discouraged further exploration of this model in the analysis of clinical datasets (23). Van der Ko- gel’s studies were subsequently expanded into an elegant, systematic study of dose–volume effects in the rat spinal cord, ending with the sobering conclusion that not any of the 14 mathematical models, tried by the authors, could fit all the data (24). PROGRESS ON ALL FRONTS SINCE 1991 Much has changed since 1991 (Table 1). Many, mainly ret- rospective, clinical studies have been published on dose–vol- ume-outcome analysis of clinical data. The QUANTEC review identified >70 papers on radiation pneumonitis alone. Some of these studies are very large (e.g., a study of rectal ef- fects in 1,132 patients by Fiorini et al.) (25). There are quan- titative analyses of dose–volume-outcome relationships for >30 organs and tissues. More than a dozen mathematical dose volume models have been proposed. One class of NTCP models reduces the 3D dose matrix to a scalar, often thought of as an effective volume or an effec- tive dose received by a defined reference volume. This scalar is subsequently related to the incidence or risk of normal tis- sue toxicity through a sigmoid link function, typically a logis- tic or probit relationship. This model building strategy is similar to the one used originally by Lyman (11) and it may be reasonable classifying these as generalized Lyman models. The push from cell-killing based models towards heuristic models has been strengthened by novel insights into radiation pathogenesis of late effects (26) and an in- creased appreciation of the role of anatomical and physiolog- ical factors in normal tissue dysfunction. Other modeling approaches have been used such as princi- pal component analysis (27), contiguous (or cluster) damage model (28), and data mining to build multivariate models (29). Further approaches include the use of artificial neural networks (30) and support vector machines (31) as classifiers of patients with respect to the development of side effects. These methods are complementary to more traditional mod- eling and will undoubtedly be further explored in the coming years. THE QUANTEC INITIATIVE It was on this background that the QUANTEC Steering Committee was formed. Stimulated by a proposal from the Science Council of the American Association of Physicists in Medicine to revise and update the Emami guidelines, the QUANTEC group was formed from a loose network of re- searchers with a longstanding interest in dose–volume mod- eling. The Steering Committee defined three aims for QUANTEC. (1) To provide a critical overview of the current state of knowledge on quantitative dose–response and dose–vol- ume relationships for clinically relevant normal-tissue endpoints (2) To produce practical guidance allowing the clinician to reasonably (though not necessarily precisely) categorize toxicity risk based on dose–volume parameters or model results (3) To identify future research avenues that would help im- prove risk estimation or mitigation of early and late side effects of radiation therapy A kickoff workshop with 57 invited participants from North America and Europe was held in Madison, Wisconsin, in October 2007 with generous financial support from the American Association of Physicists in Medicine and the Board of the American Society for Therapeutic Radiation Oncology. The main deliverable from the workshop was the formation of a number of working groups charged with producing organ site-specific overviews of quantitative dose–volume relationships as well as groups producing vision papers on future research avenues in the field. The re- sults of these efforts are partly presented in this issue of the International Journal of Radiation Biology and Physics, again made possible with generous support from American Society for Therapeutic Radiation Oncology. Although overall progress has been real and substantial, research in the past two decades has also defined limitations to our current methods and the resulting knowledge. One of the main lessons from the literature overviews is that more uniform and comprehensive reporting would be a huge help when trying to combine data from multiple studies (see the paper by Jackson in this issue). Current best esti- mates of dose–volume parameters can in many situations be based on empirical data, in contrast to the consensus values proposed by Emami et al. However, there is still a lack of proper estimation of the uncertainty in these param- eters in most cases. Clinically, the literature on patient-related risk factors is scattered and often inconsistent from one study to the next. When patient- or treatment-related risk factors pa- rameters are not listed as significant in a given paper, it is of- ten not clear whether the factor has been tested or not. Therapeutically, RT is combined with drugs in more and more indications. Although calculating the risk associated with the RT dose distribution alone may provide some guid- ance, it cannot generally be assumed that giving a drug to- gether with radiation will even preserve the ranking of competing radiotherapy RT plans (32). The increased use of hypofractionation, and the use of an increasing number of beam orientations (e.g., rotational delivery), results in a rel- atively large volume of normal tissue receiving a low total dose and dose per fraction. The available dose–volume/out- come data may not be applicable in this setting. There has QUANTEC: scientific issues d S. M. BENTZEN et al. S5
- 6. been little discussion—andno consensus—on how models or dose–volume constraints should be adjusted if the fraction- ation scheme changes significantly. One study did adjust the individual bins in the dose–volume histogram for dose per fraction (33), but the fits obtained with a/b = 3 Gy, 10 Gy, or infinity ( = physical dose) were not statistically differ- ent for that given treatment fractionation scheme. However, the model may not be valid without correction if a signifi- cantly different fractionation scheme is used. MODEL VALIDATION AND DATA ANALYSIS On the model side, there is a need for improved data ana- lytical methods and a more critical appraisal of the various di- mensions of model validity. Face validity The first screen when judging a model fit to a set of data is face validity. Is the probability of a side effect a nondecreas- ing function of dose, dose per fraction, and volume, given that two of these three variables are held constant? If the model includes patient characteristics, such as age, smoking history, or comorbidity, is the effect estimated using the model consistent with published clinical data? Are confi- dence intervals or standard errors of the estimates reasonable in view of the analyzed sample size and the number of events actually recorded? Internal validity Internal validity relates to whether the model actually pro- vides a reasonable representation of the data to which it is fit- ted. To this end, a graphical representation of the fit to the data may be informative. This may be supplemented with a formal goodness of fit statistics, such as the chi-square test. The null hypothesis being tested is that the discrepancy between the observed toxicity incidence data and the data ex- pected under the fitted model can be explained by chance alone. A test p value <0.05 means that the null hypothesis can be rejected at the 5% significance level (i.e., the model ‘‘does not fit the data’’). A nonsignificant p value, however, may not be very informative as typical NTCP model fits to clinical data sets yield a relatively low statistical power of goodness of fit statistics. In other words, two alternative mathematical models may be quite divergent without either one of them being rejected based on the goodness of fit test. The log-likelihood may also be used for comparing the fit of competing models to a data set; again, studies have shown that competing models tend to produce very similar log-like- lihood values for a given data set (34). For nested models (i.e., models that differ by the inclusion of one additional pa- rameter), the difference in log-likelihood forms the basis for the likelihood ratio test, a robust test for the statistical signif- icance of adding this parameter. For non-nested models the Akaike Information Criterion has been used by some authors, see for example Tucker (34). Some authors look at NTCP models as classifiers (i.e., as a way to separate patients who do or do not develop a given toxicity). This leads to a standard predictive testing frame- work, where sensitivity, specificity, and negative and posi- tive predictive values can be estimated. The area under the curve of the receiver operating characteristic curve can be used as a figure of merit for comparing alternative models. Note, however, that a model reliably identifying subgroups of patients with, say, a 10% and a 40% risk of toxicity would Table 1. Dose-volume relationships ca. 1990 and 2009+ ca. 1990 2009+ Treatment usually with parallel opposing fields or ‘‘box’’ techniques—three-dimensional conformal radiation therapy gaining ground clinically in some centers Widespread use of conformal techniques, including intensity- modulated radiation therapy, often resulting in highly nonuniform dose distribution in organs at risk with large volumes receiving low doses Radiation therapy typically delivered as single modality— spectrum of toxicities relatively well-characterized Many curative cases receiving combined modality therapy—many regimens are very toxic leading to problems with compliance Conventional fractionation dominates—clinical trials of hyperfractionation and accelerated fractionation Conventional fractionation dominates—clinical trials of hypofractionation in progress Authors search for a ‘‘safe’’ dose–volume constraint Increasing appreciation of the risk-benefit tradeoff in an individual patient—a monotonic increase in toxicity risk with increasing dose/increasing volume Early interest in normal tissue complication probability modeling— Lyman model most widely used Change from ‘‘more models’’ to ‘‘more data’’—Lyman model still widely used, but new modeling strategies are being pursued Analysis often based on groups of patients Analysis of individual patient level data Lack of consistency in contouring organs at risk among investigators Lack of consistency in contouring organs at risk among investigators Models often applied with parameters from the literature—no adjustment for patient or treatment characteristics Statistical estimation of model parameters—often with adjustment for significant patient or treatment characteristics Toxicity underscored and underreported in most studies Toxicity underscored and underreported in most studies—despite attempts to define dictionaries for toxicity reporting such as Common Terminology Criteria for Adverse Events A lack of quantitative, evidence-based dose–volume constraints— Emami et al. develops a ground-breaking set of consensus constraints for partial organ irradiation A lack of quantitative, evidence-based dose-volume constraints— the QUANTEC group initiates a series of systematic literature reviews S6 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 7. most likely beclinically useful, but if the latter group is la- beled as ‘‘responders’’ there would still be a 60% false-pos- itive rate. In this case a binned comparison of observed and expected toxicity may be more informative (35). Cross-vali- dation techniques have been suggested for NTCP modeling (29), but have so far not been widely applied. External validity External validity addresses how well the model explains the variability in response seen in an independent dataset, preferably from another institution. Multivariate NTCP models are often overfitted in the sense that they include too many parameters relative to the number of events ana- lyzed. This may result in strongly correlated parameter esti- mates and, although such a model may pass the test for internal validity with flying colors, it often has poor external validity. Differences between institutions in the scoring of re- actions, in patient demographics, in the burden of comorbid- ities as well as in treatment characteristics may all contribute to a reduced predictive power of a model when tested in an independent dataset. Relatively little research has been per- formed on external validity of NTCP models. Bradley et al. (36) applied a radiation pneumonitis model fitted to data from 219 Washington University patients to an independent series of radiation pneumonitis data from 129 patients en- rolled in the Radiation Therapy Oncology Group 93-11 trial and concluded that the model ‘‘performed poorly’’ in the new dataset. A model fitted to the two datasets combined was found to give an odds ratio of approximately two between the 33% of all patients with the riskiest plans and the 33% of patients with the safest plans, but much of the variability is still unexplained. Similar problems with generalizabilty are seen in studies applying different models on the same da- taset: as an example, Tsougos et al. (37) found that six pub- lished models predicted an incidence of Grade 3+ radiation pneumonitis ranging from 4% to 21% in a group of 47 pa- tients. One issue is that various dose–volume metrics often are strongly correlated within a given dataset (38). This may lead to problems with multicollinearity, which, although it may not affect the internal validity of the model, can lead to reduced generalizability. This becomes particularly rele- vant for extrapolation in dose–volume space (i.e., if a model derived on basis of ‘‘similar’’ dose plans is applied to a very different dose distribution) (39). Clinical utility Dose–volume constraints are used in routine dose planning as an integral part of the informal optimization of therapeutic ratio that inverse planning entails. Acceptable dose distribu- tions are identified from a assessment of the risk:benefit ratio in an individual patient—often on the basis of clinical expe- rience rather than on numerical estimates from dose–volume models. Population constraints are very important in this con- text but can obviously not stand alone. Careful consideration should be given not only to the numerical value of these con- straints but also to their statistical uncertainty. Using these values directly in dose–plan optimization should be done with great caution. The fact that dose–volume constraints or NTCP models are used in clinical practice does not in itself prove that they im- prove cancer care from an evidence-based medicine perspec- tive. Ultimately, the clinical utility of NTCP modeling should be tested in randomized controlled trials. Phase I/II dose es- calation trials in patients with non–small-cell lung cancer, where the individual patient is assigned a dose based on an NTCP estimate (40), have been completed or are in progress for example at University of Wisconsin (41), University of Michigan (42), and the Maastricht Radiation Oncology clinic in the Netherlands (43). The goal is to test these strategies in randomized Phase III trials. This could potentially provide an evidence base for risk adaptive radiotherapy for non–small- cell lung cancer based on NTCP modeling. RESEARCH PRIORITIES: BEYOND QUANTEC Important research priorities, identified above as well as in the QUANTEC thematic and organ-site reviews, include the following. A. Development of tools and strategies for prospective recording of specific pathologies after RT alone or com- bined with drugs B. Wider application of methods adjusting for censoring when analyzing late effects C. Quantification of the influence of physiologic factors and comorbidities on the expression of toxicities D. The continued development of robust normal tissue end- points including patient reported outcomes to further our understanding of the relationship between toxicity and quality of life E. Development of methods for synthesizing results across studies with appropriate estimation of prediction uncer- tainty F. Establishment of large continually growing data bases with full access to the 3D dose matrix and linkage with biomarkers and clinical outcome G. Prospective testing of model performance in independent datasets, preferably from clinical trials H. Improved understanding of the interaction between dose distribution on one hand and dose per fraction or admin- istration of other modalities on the other I. Developing strategies for testing the clinical utility of NTCP models. J. Development of methods for recording actual delivered dose in an individual patient after fractionated radiother- apy. K. Additional studies that use molecular and functional im- aging as an intermediary between local damage and organ-level signs and symptoms. Adjustment for dose distribution remains a major chal- lenge in clinical radiation research. A systematic effort, capa- ble of winning competitive research funding, is required to take this field to the next stage. QUANTEC: scientific issues d S. M. BENTZEN et al. S7
- 8. REFERENCES 1. Bentzen SM,Rosenthal DI, Weymuller E. Increasing toxicity in non-operative head and neck cancer treatment: Investigations and interventions. Int J Radiat Oncol Biol Phys 2007;69(2 Suppl):S79–82. 2. Center for Disease Control (USA). Cancer survivorship— United States, 1971–2001. Available at http://www.cdc.gov/ mmwr/preview/mmwrhtml/mm5324a3.htm. Accessed Decem- ber 1, 2005. 3. Bentzen SM, Trotti A. Evaluation of early and late toxicities in chemoradiation trials. J Clin Oncol 2007;25:4096–4103. 4. Trotti A, Bentzen SM. The need for adverse effects reporting standards in oncology clinical trials. J Clin Oncol 2004;22: 19–22. 5. Papanikolaou PN, Ioannidis JP. Availability of large-scale evi- dence on specific harms from systematic reviews of randomized trials. Am J Med 2004;117:582–589. 6. National Cancer Institute. Common Terminology Criteria for Adverse Events v3.0. Available at http://ctep.cancer.gov/ protocolDevelopment/electronic_applications/docs/ctcaev3.pdf. Accessed February 9, 2009. 7. Bentzen SM, Dorr W, Anscher MS, et al. Normal tissue effects: Reporting and analysis. Semin Radiat Oncol 2003;13:189–202. 8. Peeters ST, Lebesque JV, Heemsbergen WD, et al. Localized volume effects for late rectal and anal toxicity after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2006;64:1151– 1161. 9. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 10. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 11. Lyman JT. Complication probability as assessed from dose-vol- ume histograms. Rad Res 1985;104: S-13–S-19. 12. Kutcher GJ, Burman C, Brewster L, et al. Histogram reduction method for calculating complication probabilities for three-di- mensional treatment planning evaluations. Int J Radiat Oncol Biol Phys 1991;21:137–146. 13. Schultheiss TE, Orton CG, Peck RA. Models in radiotherapy: Volume effects. Med Phys 1983;10:410–415. 14. Withers HR, Taylor JM, Maciejewski B. Treatment volume and tissue tolerance. Int J Radiat Oncol Biol Phys 1988;14:751– 759. 15. Ka¨llman P, Aagren A, Brahme A. Tumour and normal tissue re- sponses to fractionated non-uniform dose delivery. Int J Radiat Biol 1992;62:249–262. 16. Liao ZX, Travis EL, Tucker SL. Damage and morbidity from pneumonitis after irradiation of partial volumes of mouse lung [see comments]. Int J Radiat Oncol Biol Phys 1995;32:1359– 1370. 17. Tucker SL, Liao ZX, Travis EL. Estimation of the spatial distri- bution of target cells for radiation pneumonitis in mouse lung. Int J Radiat Oncol Biol Phys 1997;38:1055–1066. 18. Konings AW, Faber H, Cotteleer F, et al. Secondary radiation damage as the main cause for unexpected volume effects: A his- topathologic study of the parotid gland. Int J Radiat Oncol Biol Phys 2006;64:98–105. 19. van Luijk P, Faber H, Meertens H, et al. The impact of heart ir- radiation on dose-volume effects in the rat lung. Int J Radiat On- col Biol Phys 2007;69:552–559. 20. Hopewell JW, Trott KR. Volume effects in radiobiology as ap- plied to radiotherapy. Radiother Oncol 2000;56:283–288. 21. Trott KR, Tamou S, Sassy T, et al. The effect of irradiated vol- ume on the chronic radiation damage of the rat large bowel. Strahlenther Onkol 1995;171:326–331. 22. Peeters ST, Hoogeman MS, Heemsbergen WD, et al. Rectal bleeding, fecal incontinence, and high stool frequency after con- formal radiotherapy for prostate cancer: Normal tissue compli- cation probability modeling. Int J Radiat Oncol Biol Phys 2006; 66:11–19. 23. Stewart FA, van der Kogel AJ. Volume effects in normal tis- sues. In: Steel GG, editor. Basic clinical radiobiology. 3rd ed. London: Arnold; 2002. p. 42–51. 24. van Luijk P, Bijl HP, Konings AW, et al. Data on dose-volume effects in the rat spinal cord do not support existing NTCP models. Int J Radiat Oncol Biol Phys 2005;61:892–900. 25. Fiorino C, Fellin G, Rancati T, et al. Clinical and dosimetric predictors of late rectal syndrome after 3D-CRT for localized prostate cancer: Preliminary results of a multicenter prospective study. Int J Radiat Oncol Biol Phys 2008;70:1130–1137. 26. Bentzen SM. Preventing or reducing late side effects of radia- tion therapy: Radiobiology meets molecular pathology. Nat Rev Cancer 2006;6:702–813. 27. Dawson LA, Biersack M, Lockwood G, et al. Use of principal component analysis to evaluate the partial organ tolerance of normal tissues to radiation. Int J Radiat Oncol Biol Phys 2005;62:829–837. 28. Stavreva N, Niemierko A, Stavrev P, et al. Modelling the dose- volume response of the spinal cord, based on the idea of damage to contiguous functional subunits. Int J Radiat Biol 2001;77: 695–702. 29. El Naqa I, Bradley J, Blanco AI, et al. Multivariable modeling of radiotherapy outcomes, including dose-volume and clinical factors. Int J Radiat Oncol Biol Phys 2006;64:1275–1286. 30. Gulliford SL, Webb S, Rowbottom CG, et al. Use of artificial neural networks to predict biological outcomes for patients re- ceiving radical radiotherapy of the prostate. Radiother Oncol 2004;71:3–12. 31. Chen S, Zhou S, Yin FF, et al. Investigation of the support vec- tor machine algorithm to predict lung radiation-induced pneu- monitis. Med Phys 2007;34:3808–3814. 32. Khuntia D, Harris J, Bentzen SM, et al. Increased oral mucositis after IMRT versus non-IMRT when combined with cetuximab and cisplatin or docetaxel for head and neck cancer: Preliminary results of RTOG 0234 [abstract]. Int J Radiat Oncol Biol Phys 2008;72:S33. 33. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of the risk of postoperative pulmonary complications among esophageal cancer patients treated with concurrent chemoradio- therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006; 66:754–761. 34. Tucker SL, Dong L, Cheung R, et al. Comparison of rectal dose-wall histogram versus dose-volume histogram for model- ing the incidence of late rectal bleeding after radiotherapy. Int J Radiat Oncol Biol Phys 2004;60:1589–1601. 35. De Ruysscher D, Dehing C, Bremer RH, et al. Maximal neutro- penia during chemotherapy and radiotherapy is significantly as- sociated with the development of acute radiation-induced dysphagia in lung cancer patients. Ann Oncol 2007;18:909– 916. 36. Bradley JD, Hope A, El N, et al. A nomogram to predict radia- tion pneumonitis, derived from a combined analysis of RTOG 93-11 and institutional data. Int J Radiat Oncol Biol Phys 2007;69:985–992. 37. Tsougos I, Nilsson P, Theodorou K, et al. NTCP modelling and pulmonary function tests evaluation for the prediction of radia- tion induced pneumonitis in non-small-cell lung cancer radio- therapy. Phys Med Biol 2007;52:1055–1073. 38. Yorke ED, Kutcher GJ, Jackson A, et al. Probability of radia- tion-induced complications in normal tissues with parallel S8 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 9. architecture under conditionsof uniform whole or partial organ irradiation. Radiother Oncol 1993;26:226–237. 39. Deasy JO, Niemierko A, Herbert D, et al. Methodological is- sues in radiation dose-volume outcome analyses: summary of a joint AAPM/NIH workshop. Med Phys 2002;29:2109–2127. 40. Lawrence TS, Kessler ML, Robertson JM. 3-D conformal radi- ation therapy in upper gastrointestinal cancer. The University of Michigan experience. Front Radiat Ther Oncol 1996;29:221– 228. 41. Adkison JB, Khuntia D, Bentzen SM, et al. Dose escalated, hypofractionated radiotherapy using helical tomotherapy for inoperable non-small cell lung cancer: Preliminary results of a risk-stratified phase I dose escalation study. Technol Cancer Res Treat 2008;7:441–448. 42. Kong FM, Hayman JA, Griffith KA, et al. Final toxicity results of a radiation-dose escalation study in patients with non-small- cell lung cancer (NSCLC): Predictors for radiation pneumonitis and fibrosis. Int J Radiat Oncol Biol Phys 2006;65:1075–1086. 43. van Baardwijk A, Bosmans G, Boersma L, et al. Individualized radical radiotherapy of non-small-cell lung cancer based on nor- mal tissue dose constraints: A feasibility study. Int J Radiat Oncol Biol Phys 2008;71:1394–1401. QUANTEC: scientific issues d S. M. BENTZEN et al. S9
- 10. INTRODUCTORY PAPER USE OFNORMAL TISSUE COMPLICATION PROBABILITY MODELS IN THE CLINIC LAWRENCE B. MARKS, M.D.,* ELLEN D. YORKE, PH.D.,y ANDREW JACKSON, PH.D.,y RANDALL K. TEN HAKEN, PH.D.,z LOUIS S. CONSTINE, M.D.,x AVRAHAM EISBRUCH, M.D.,z SØREN M. BENTZEN, PH.D.,k JIHO NAM, M.D.,* AND JOSEPH O. DEASY, PH.D.{ *Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC; y Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY; z Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; x Department of Radiation Oncology, University of Rochester Cancer Center, Rochester, NY; k Department of Human Oncology, University of Wisconsin School of Medicine, Madison, WI; and { Department of Radiation Oncology, Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO The Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) review summarizes the currently available three-dimensional dose/volume/outcome data to update and refine the normal tissue dose/volume toler- ance guidelines provided by the classic Emami et al. paper published in 1991. A ‘‘clinician’s view’’ on using the QUANTEC information in a responsible manner is presented along with a description of the most commonly used normal tissue complication probability (NTCP) models. A summary of organ-specific dose/volume/outcome data, based on the QUANTEC reviews, is included. Ó 2010 Elsevier Inc. QUANTEC, NTCP. INTRODUCTION Historically, radiation therapy (RT) fields/doses were selected empirically, based largely on experience. Physicians relied on clinical intuition to select field sizes/doses. They understood that these empiric guidelines were imprecise and did not fully reflect the underlying anatomy, physiology, and dosimetry. A great promise of three-dimensional (3D) treatment plan- ning was quantitative correlates of doses/volumes with clin- ical outcomes. This promise was partly delivered. When 3D dosimetric information became widely available, guidelines were needed to help physicians predict the relative safety of proposed treatment plans, although only limited data were available. In 1991, investigators pooled their clinical experience, judgment, and information regarding partial or- gan tolerance doses, and produced the ‘‘Emami paper’’ (1). While ‘‘Emami’’ is often criticized, the paper clearly stated the uncertainties and limitations in its recommendations, and it is widely admired for addressing a clinical need. During the last 18 years, numerous studies reported asso- ciations between dosimetric parameters and normal tissue outcomes. The QUANTEC (quantitative analysis of normal tissue effects in the clinic) articles summarize the available data to update/refine the estimates provided by Emami et al. A central goal of QUANTEC is to summarize this infor- mation in a clinically useful manner. We hope the information will improve patient care by pro- viding clinicians and treatment planners with tools to esti- mate ‘‘optimal/acceptable’’ 3D dose distributions. We hope that at least some of the summary tables, graphs, and models presented will be reproduced and posted in resident work- rooms, dosimetry planning areas, and physician offices, as is currently done with the Emami et al. tables. The information provided by QUANTEC is not ideal, and care must be taken to apply it correctly in the clinic. We herein present a ‘‘clinician’s view’’ on using the QUANTEC information in a responsible manner, highlighting the diverse type of limitations of the presented data. LIMITATIONS INHERENT IN EXTRACTING DATA FROM THE LITERATURE The information presented is largely extracted from publi- cations. Because different investigators often present infor- mation differently (e.g., actuarial vs. crude complication rates), pooling data from multiple studies may be inaccurate. Reprint requests to: Lawrence B. Marks, M.D., Department of Radiation Oncology, Box 7512 University of North Carolina, Chapel Hill, NC 27514. Tel: (919) 966-0400; Fax: (919) 966- 7681; E-mail: marks@med.unc.edu Conflict of interest: none. Acknowledgments—The authors express special thanks to Jessica Hubbs and Janet Bailey for their assistance in the preparation of this manuscript. Partially supported by National Institutes of Health grants CA85181 (J.O.D.) and CA69579 (L.B.M.) and by a grant from the Lance Armstrong Foundation (L.B.M.). Received Jan 6, 2009, and in revised form July 1, 2009. Accepted for publication July 2, 2009. S10 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S10–S19, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.07.1754
- 11. Summary tables areoften included to help the reader better understand the primary data. LIMITATIONS OF PREDICTIVE MODELS Some studies use models to estimate the complication risk. Care should be taken when applying models, especially when clinical dose/volume parameters are beyond the range of data used to generate the model/parameters. Models and dose/vol- ume recommendations are only as good as the data available. Typically, they are based on dose–volume histograms (DVHs). DVHs are not ideal representations of the 3D doses as they discard all organ-specific spatial information (and hence assume all regions are of equal functional importance), and often do not consider fraction size variations. They are usually based on a single planning computed tomography (CT) scan that does not account for anatomic variations during therapy (Fig. 1). Interinstitutional/physician differences in image segmentation, dose calculation, patient populations, and preferred beam arrangements may limit model exportabil- ity. Before introducing a predictive model into a clinical prac- tice, it is prudent to assess if its predictions ‘‘make sense’’ in regard to that clinic’s treatment plans and experience. EVOLVING FRACTIONATION SCHEDULES RT-induced normal tissue responses are fraction size de- pendent. Throughout the QUANTEC reviews, this variable is acknowledged and, where possible, considered by making adjustments for fraction size based on the linear quadratic (LQ) model. Nevertheless, a/b ratios are uncertain. Particular care must be taken when QUANTEC information is applied to stereotactic RT, where the fraction size is much different than that in the cited literature. For very novel fractionations, even the validity of the LQ model is questioned (2). Even when the prescribed tumor dose is ‘‘conventionally’’ fractionated, the fraction size seen by the normal tissue may have varied over time. When ‘‘Emami’’ was published, most external RT was delivered with opposing fields, and shrink- ing field techniques—the normal tissue was irradiated with a fairly uniform fraction size. Modern techniques often use multiple beams (with or without concurrent boosts); the vol- ume of normal tissue exposed to low doses is often increased and the dose is delivered at fraction sizes ranging from z0 to the prescribed fraction size. COMBINED MODALITY THERAPY Use of sequential/concurrent chemotherapy/RT is increas- ing for many tumors. Concurrent chemotherapy is typically believed to exacerbate the severity of normal tissue reactions, but data quantifying this is often lacking. Even when such data are available, the chemotherapy doses, schedules and agents—which may influence outcomes—are in evolution. HOST FACTORS Host factors (e.g., chronic liver disease, genetic, lifestyle) may affect dose–response relationships and are partly respon- sible for the shallowness of these relationships in the patient population. It is likely that incorporating these factors, when they are known, will produce better models/correlations/pre- dictors of toxicity. BALANCING THE RISKS TO DIFFERENT ORGANS Different morbidities vary in their clinical significance. Grade 2 toxicity has a different clinical meaning for the esophagus than for the rectum. Furthermore, different pa- tients may have different levels of acceptance for injuries. When comparing competing treatment plans, there is usually a tradeoff; for example, should we accept a certain dose to the lung or to the esophagus? For most cases, modern treatments will redistribute, not eliminate, the dose to normal tissue. The fundamental problem of treatment planning is how to balance exposure of one organ against that of another. Unfortunately, there is no objective way to do this. Investigators have considered the risks to multiple organs, and computed the probability of uncomplicated tumor con- trol (3–5). Others have attempted to incorporate the relative importance of different toxicities by considering their impact on patients’ quality of life. This approach generates a global figure of merit such as the ‘‘quality of life adjusted tumor con- trol probability’’ (6, 7). The utility of this approach, although conceptually attractive, is not clear. FOLLOW-UP DURATION If dose–effect relationships for a late complication are de- rived from a patient population with very poor prognosis, they may be limited by lack of long-term follow-up, and not applicable to patients with a better prognosis (e.g., apply- ing brain toxicity from patients with high-grade glioma to pa- tients with low-grade tumors). The risk of normal tissue complication occurs in the con- text of a patient’s expected longevity. Radiation therapy is an effective anti-cancer therapy and can provide good Fig. 1. A three-dimensional dose distribution is reduced to a two-di- mensional (2D) dose–volume histogram (DVH) by discarding all spatial, anatomic and physiologic data. The 2D graph is then further reduced to a single value of merit, such as the mean dose, the percent of the organ receiving $20 Gy (V20), or a model-based normal tis- sue complication probability (NTCP). Use of NTCP models in the clinic d L. B. MARKS et al. S11
- 12. palliation for patientswith recurrent/metastatic/incurable dis- ease. In these settings, concern for late normal tissue reac- tions often should not limit the application of RT. For example, reirradiation of the whole brain for recurrent brain metastases to cumulative doses well above tolerance can pro- vide palliation for these challenging cases (8–10) for which concern about late toxicity may be unnecessary. Similarly, RT for locally advanced lung cancers may routinely exceed the normal dose limits for lung and heart. In these instances, there typically are no good alternative therapies available. Withholding thoracic RT because of the risk of pericarditis or pneumonitis may not be therapeutically rational. These concerns are most applicable to recently trained ra- diation oncologists who are accustomed to using 3D dosimet- ric information for most of their clinical decision making. They may be uncomfortable in clinical settings where large RT fields need to be applied without 3D dosimetry in order to provide palliative effect. It is the physician’s responsibility to tell dosimetrists/physicists when it is appropriate to pro- ceed with treatment without a formal 3D dose/volume assess- ment and/or suspend the conventional departmental dose/ volume guidelines. RELATING ‘‘WHOLE TREATMENT’’ DVHS WITH ACUTE TOXICITIES For some organs, a relevant acute toxicity may occur dur- ing the course of RT (i.e., before the delivery of the entire RT course). Relating the incidence of such acute events to a DVH that reflects the whole treatment course may be somewhat il- logical. It might be preferable to try to relate acute events to the dose delivered before symptom onset (or even to doses received a number of days before symptom onset, if there is a known latency time). If a consistent set of treatment fields is used throughout the entirecourseoftreatment(e.g.,nofieldreductions),the‘‘whole course’’ DVH might bea reasonable surrogate for the 3D doses delivered before acute symptom onset. Therefore, in these sit- uations, it still might be a reasonable to relate the risk of acute events to a DVH that reflects the whole treatment course. However, field arrangements often change during therapy, thus altering the dose/volume parameters for the target organ (e.g., initial AP-PA fields plus a subsequent off-cord boost). In these situations, the ‘‘whole-course’’ DVH is less likely to be a reasonable surrogate for the 3D doses delivered prior to the acute toxicity. Thus, some dose/volume/outcomes analy- ses for acute endpoints that consider the so-called whole- course DVH may be suspect. Further complicating the issue is the fact that the duration of symptoms (that may also influence the scoring of toxicity), may be affected by RT dose delivered after the onset of symptoms. In this regard, the whole-course DVH may indeed be reasonable to consider in dose/volume/outcomes analyses. A similar concern may apply for analyses of late effects. If a late toxicity results from a severe acute toxicity occurring during the course of RT, relating that late event to the whole-course DVH may also be suboptimal. TUMOR COVERAGE VS. NORMAL TISSUE RISK For most curative patients, a marginal miss is more serious than a normal tissue complication. For many tumors, recur- rences are difficult to manage, cause severe morbidity, and usually result in mortality. Target coverage should generally not be compromised to reduce the normal tissue risks. This is exemplified by the experience from Israel in treating orbital lymphomas. In 24 tumors treated in 23 patients, intraorbital recurrence was seen in four of 12 (33%) of the tumors treated with conformal fields (including the radiographically defined gross tumor with margin), vs. none of the 12 tumors treated with conventional whole-orbit techniques (11). Similarly, in- vestigators at Washington University noted a higher relapse rate in lung cancers closer to the spinal cord; perhaps reflect- ing compromised GTV coverage because of spinal cord pro- tection (Ref. 12 and personal communication from J. Deasy, 2008). Engels et al. noted a reduction in 5-year biochemical disease-free survival rate (from 91% to 58%) in patients irra- diated for prostate cancer with the addition of implanted seeds for localization, and tighter ‘‘PTV margins,’’ with the intent of reducing exposure to surrounding normal tissues (13). The use of improved diagnostic imaging, and improved immobi- lization and image guidance during RT, may facilitate a more realistic PTV margin to be applied safely. APPLICABILITY TO CHILDREN In the young, a mosaic of tissues develop at different rates and temporal sequences. In adults, the same tissues are in a steady state with relatively slow cell renewal kinetics. The vulnerability of tissues to RT typically increases during the periods of rapid proliferation. Consequently, generalizing data from adult to pediatric populations is problematic and re- quires caution. Ideally, specific data from investigations on children should be used to predict risks in this population. UNDERSTANDING THE BASICS OF NTCP MODELS Despite these caveats, model-based risk estimates are a re- ality. Physicians routinely use models, in their broadest sense, to make treatment decisions. Use of metrics such as the mean lung dose, and cord maximum dose to estimate risks are models, albeit simple ones. We present a primer re- garding the basic principles of NTCP models. Generally, NTCP models attempt to reduce complicated dosimetric and anatomic information to a single risk measure. Most models fall into one of three categories: DVH-reduction models, tissue architecture models, and multiple-metric (i.e. multimetric) models. DVH-reduction models Although most applications of DVH reduction models are to nonuniform dose distributions, they are based on estimated complication probability under uniform irradiation. A dose- response for uniform irradiation is described by a mathemat- ical function with at least two parameters: for example TD50, which denotes the dose for 50% complication probability, and m, which is inversely proportional to the slope at the S12 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 13. steepest part ofthe response curve. For a patient cohort with diverse radiosensitivities, the response curve is shallower (larger m) than for a biologically similar population receiving the same treatment (14). Various S-shaped functions are used to fit dose-response data, including the probit function used by Lyman (below). To account for the dose heterogeneity typical of parallel opposed beam irradiation (partial organ uniform irradiation), Jolles (15) described tissue tolerance as a power law of the fractional volume irradiated: DðVirradiatedÞ ¼ D À Vreference Á À Vreference Á ðVirradiatedÞ n ; [1] Here Vreference isthereferencevolumeandVirradiatedistheuni- formly irradiated volume. D is the corresponding tolerance doses, representing a chosen level on the dose–response curve, such as TD50. The parameter n controls the volume effect. Lyman (16) used this power law model to define the risks associated with partial organ volume uniform irradiation. From Eq. 1, decreasing the irradiated volume fraction shifts the dose–response curve (TD50) to higher doses by a factor of the irradiated fractional volume raised to the power ‘‘neg- ative n’’. The effect of different n values on tolerance dose is shown in Fig. 2. For example, if the n parameter equals 1, then the TD50 of irradiation for one half of the volume is expected to increase by a factor of 2, whereas if the n parameter is 0.5, TD50 for irradiation of one half the volume would increase by a factor of the square root of 2. To generalize this to clinically realistic, heterogeneous dose distributions, a summary statistic—the generalized equivalent uniform dose (gEUD)—is often introduced (17, 18). The gEUD is the dose that, if given uniformly to the en- tire organ, is believed to yield the same complication rate as the true dose distribution. The gEUD is computed by sum- ming over all voxels in the organ: gEUD ¼ 1 Nvoxels ðd 1=n 1 þ d 1=n 2 þ . þ d 1=n NVoxels Þ !n : [2] Here NVoxelsis the number of equi-volume voxels, and di is the dose to the ith voxel. The gEUD equation is consistent with the power-law assumption. Together, the gEUD equa- tion and the Lyman assumptions are often referred to as the Lyman-Kutcher-Burman (LKB) model (16, 18–20). Note that some analyses use the parameter n, and some use the parameter a, equal to 1/n. Both are shown in Fig. 2. When n is small (and a is large), changes in irradiated volume make only a modest change in relative tolerance whereas, as n gets larger (and a gets smaller), the tolerance dose depends strongly on the irradiated volume fraction. Serial vs. parallel complication endpoints There have been efforts to devise mechanistic models that ascribe the volume dependence of some complications to dis- ruption of the organ’s functional architecture by RT (21–23). In so-called parallel complications, subvolumes of the or- gan function relatively independently. Sufficiently small por- tions of the organ can be damaged without clinical effect; the complication is observed only after more than a critical vol- ume is damaged. Parallel complications have large volume effects, and for this reason they are often likened to LKB models with n z 1 (as is found in analyses of liver, lung, and kidney complications). More detailed models exist, in- cluding models employing the concept of a functional re- serve, representing a hypothesized fraction of organ function that can be lost before a complication is likely (23). In contrast, serial complications occur when even a small portion of the organ suffers damage. Here, n is small (e.g., z 0.1 for late rectal bleeding). Serial complications are most affected by the hottest portion of the DVH. More de- tailed models exist for this type of endpoint as well, including models that make explicit the size of small subunits, all of which need to be preserved to avoid a complication (23). Figure 3 shows how different parts of an example DVH contributetotheoverall gEUDas nvaries. Notethat: (a) thelow- est value of n results in the highest gEUD corresponding to the hottest point on the DVH (more appropriate for serial-like end- points), and (b) the lower dose bins contribute more when n ap- proaches 1 (more appropriate for parallel-like endpoints). Multimetric models Clinicians frequently estimate complication risk via a sin- gle DVH point based on a statistically significant dose/vol- ume cut-point reported in one or more studies. An example is the often-used V20 (percentage of lung receiving 20 Gy) as a predictor of radiation pneumonitis (24). However, such single ‘‘volume threshold’’ rules are overly simple, and often easily manipulated by the treatment planner, or by the optimization software. Optimizing based on such a threshold may introduce a ‘kink’ in one part of the DVH to achieve a desired ‘‘threshold value,’’ while inadequately constraining the rest. An infinite number of very different dose distributions (some likely with very different risks) can have the same V20. The same is true for any Fig. 2. As the (idealized) irradiated organ fraction decreases, the tol- erance dose (D) increases, more so for larger values of n or smaller values of a (=1/n). VReferencerepresents the reference volume (usually the full organ volume), and VIrradiated represents the volume irradiated. Use of NTCP models in the clinic d L. B. MARKS et al. S13
- 14. DVH-reduction scheme, includingthe LKB models; mark- edly different-looking DVHs can yield the same NTCP. However, models that consider a larger fraction of the DVH are less easily manipulated (and may be more radiobi- ologically logical) than are the threshold models that consider only one point on the DVH. Nonetheless, reports correlating single DVH point thresholds to toxicity are common and are often included in the QUANTEC reviews. The more robust multimetric approach selects several uni- variate-significant dosimetric features of the dose distribution (e.g., multiple Vdose values) as well as medical variables and use multivariate analysis together with sophisticated statisti- cal methods or ‘‘machine learning’’ algorithms to pick out the most significant combinations (25). In-depth discussions of this topic can be found in reviews elsewhere (26–29). SUMMARY A major goal of this issue of the Journal is to provide prac- tical clinical guidance for physicians and treatment planners. The information presented is not perfect, as evidenced by the multiple caveats above. The lack of good predictors is some- what unsettling. Nevertheless, the QUANTEC papers present a valuable review. Over time, with the help of new studies guided by new physical, statistical and biological technolo- gies, we hope to be able to update this information so that pa- tient care can be continually improved. With the multiple caveats outlined above in mind, a limited summary of available organ-specific dose/volume/outcome data is provided in Table 1. This is not meant to replace the detailed information provided in the individual organ-spe- cific reviews. Treatment planners and physicians are encour- aged to read the individual papers to understand the origin, certainty, and nuances that apply to the dose/volume/out- come data provided in the summary table. In general, the dose/volume/outcome data provided in the summary table are associated with generally-regarded clinically acceptable rates of injury; for example, low rates for severe injury (e.g., brain necrosis), and higher rates of less severe end- points (e.g., erectile dysfunction). Thus, these are dose/vol- ume parameters that might be widely applied in clinical practice. Obviously many clinical situations require treat- ments that exceed the dose/volume values shown. Where practical, some dose response data are included as well. Fur- thermore, most of the data in the table is based on convention- ally fractionated radiation using conventional techniques, and may or may not be applicable in other settings. Fig. 3. Volume–effect parameter. The effect of changing the n parameter (= 1/a) in the Lyman model with the generalized equivalent uniform dose equation to compute normal tissue complication probability (NTCP) is shown. Starting with a (real) rectal dose–volume histogram (DVH) computed for an intensity-modulated radiation therapy (IMRT) prostate pa- tient plan (upper left), the DVH is first transformed into a single number by the generalized equivalent uniform dose (gEUD) equation that weights dose values exponentially. Lower figure shows the cumulative contribution of each part of the DVH to the overall gEUD for all bins below the given dose value. As one can see, if a is set to 1 (rightmost curve), gEUD would equal the mean dose (e.g., for parallel organs), and many voxels with doses as low as 20 to 30 Gy contribute significantly to the gEUD and therefore may increase the final NTCP value (although contributions are proportional to dose, so higher dose still does contribute more for the same volume). As n decreases, the value of gEUD is a determined mainly by the highest dose voxels (e.g., for series organs). Typical clinical values for late rectal bleeding are n z 0.1. Un- fortunately, investigators sometimes report a (especially when discussing the gEUD) and other-times use n, where n =1/a. S14 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 15. Table 1. QUANTECSummary: Approximate Dose/Volume/Outcome Data for Several Organs Following Conventional Fractionation (Unless Otherwise Noted)* Organ Volume segmented Irradiation type (partial organ unless otherwise stated)y Endpoint Dose (Gy), or dose/volume parametersy Rate (%) Notes on dose/volume parameters Brain Whole organ 3D-CRT Symptomatic necrosis Dmax 60 3 Data at 72 and 90 Gy, extrapolated from BED modelsWhole organ 3D-CRT Symptomatic necrosis Dmax = 72 5 Whole organ 3D-CRT Symptomatic necrosis Dmax = 90 10 Whole organ SRS (single fraction) Symptomatic necrosis V12 5–10 cc 20 Rapid rise when V12 5–10 cc Brain stem Whole organ Whole organ Permanent cranial neuropathy or necrosis Dmax 54 5 Whole organ 3D-CRT Permanent cranial neuropathy or necrosis D1–10 cck #59 5 Whole organ 3D-CRT Permanent cranial neuropathy or necrosis Dmax 64 5 Point dose 1 cc Whole organ SRS (single fraction) Permanent cranial neuropathy or necrosis Dmax 12.5 5 For patients with acoustic tumors Optic nerve / chiasm Whole organ 3D-CRT Optic neuropathy Dmax 55 3 Given the small size, 3D CRT is often whole organzz Whole organ 3D-CRT Optic neuropathy Dmax 55–60 3–7 Whole organ 3D-CRT Optic neuropathy Dmax 60 7-20 Whole organ SRS (single fraction) Optic neuropathy Dmax 12 10 Spinal cord Partial organ 3D-CRT Myelopathy Dmax = 50 0.2 Including full cord cross-section Partial organ 3D-CRT Myelopathy Dmax = 60 6 Partial organ 3D-CRT Myelopathy Dmax = 69 50 Partial organ SRS (single fraction) Myelopathy Dmax = 13 1 Partial cord cross-section irradiated Partial organ SRS (hypofraction) Myelopathy Dmax = 20 1 3 fractions, partial cord cross-section irradiated Cochlea Whole organ 3D-CRT Sensory neural hearing loss Mean dose #45 30 Mean dose to cochlear, hearing at 4 kHz Whole organ SRS (single fraction) Sensory neural hearing loss Prescription dose #14 25 Serviceable hearing Parotid Bilateral whole parotid glands 3D-CRT Long term parotid salivary function reduced to 25% of pre-RT level Mean dose 25 20 For combined parotid glands{ Unilateral whole parotid gland 3D-CRT Long term parotid salivary function reduced to 25% of pre-RT level Mean dose 20 20 For single parotid gland. At least one parotid gland spared to 20 Gy{ (Continued) UseofNTCPmodelsintheclinicdL.B.MARKSetal.S15
- 16. Table 1. QUANTECSummary: Approximate Dose/Volume/Outcome Data for Several Organs Following Conventional Fractionation (Unless Otherwise Noted)* (Continued) Organ Volume segmented Irradiation type (partial organ unless otherwise stated)y Endpoint Dose (Gy), or dose/volume parametersy Rate (%) Notes on dose/volume parameters Bilateral whole parotid glands 3D-CRT Long term parotid salivary function reduced to 25% of pre-RT level Mean dose 39 50 For combined parotid glands (per Fig. 3 in paper) { Pharynx Pharyngeal constrictors Whole organ Symptomatic dysphagia and aspiration Mean dose 50 20 Based on Section B4 in paper Larynx Whole organ 3D-CRT Vocal dysfunction Dmax 66 20 With chemotherapy, based on single study (see Section A4.2 in paper) Whole organ 3D-CRT Aspiration Mean dose 50 30 With chemotherapy, based on single study (see Fig. 1 in paper) Whole organ 3D-CRT Edema Mean dose 44 20 Without chemotherapy, based on single study in patients without larynx cancer**Whole organ 3D-CRT Edema V50 27% 20 Lung Whole organ 3D-CRT Symptomatic pneumonitis V20 # 30% 20 For combined lung. Gradual dose response Whole organ 3D-CRT Symptomatic pneumonitis Mean dose = 7 5 Excludes purposeful whole lung irradiationWhole organ 3D-CRT Symptomatic pneumonitis Mean dose = 13 10 Whole organ 3D-CRT Symptomatic pneumonitis Mean dose = 20 20 Whole organ 3D-CRT Symptomatic pneumonitis Mean dose = 24 30 Whole organ 3D-CRT Symptomatic pneumonitis Mean dose = 27 40 Esophagus Whole organ 3D-CRT Grade $3 acute esophagitis Mean dose 34 5–20 Based on RTOG and several studies Whole organ 3D-CRT Grade $2 acute esophagitis V35 50% 30 A variety of alternate threshold doses have been implicated. Appears to be a dose/volume responseWhole organ 3D-CRT Grade $2 acute esophagitis V50 40% 30 Whole organ 3D-CRT Grade $2 acute esophagitis V70 20% 30 Heart Pericardium 3D-CRT Pericarditis Mean dose 26 15 Based on single study Pericardium 3D-CRT Pericarditis V30 46% 15 Whole organ 3D-CRT Long-term cardiac mortality V25 10% 1 Overly safe risk estimate based on model predictions (Continued) S16I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010
- 17. Table 1. QUANTECSummary: Approximate Dose/Volume/Outcome Data for Several Organs Following Conventional Fractionation (Unless Otherwise Noted)* (Continued) Organ Volume segmented Irradiation type (partial organ unless otherwise stated)y Endpoint Dose (Gy), or dose/volume parametersy Rate (%) Notes on dose/volume parameters Liver Whole liver – GTV 3D-CRT or Whole organ Classic RILDyy Mean dose 30-32 5 Excluding patients with pre-existing liver disease or hepatocellular carcinoma, as tolerance doses are lower in these patients Whole liver – GTV 3D-CRT Classic RILD Mean dose 42 50 Whole liver – GTV 3D-CRT or Whole organ Classic RILD Mean dose 28 5 In patients with Child-Pugh A preexisting liver disease or hepatocellular carcinoma, excluding hepatitis B reactivation as an endpointWhole liver – GTV 3D-CRT Classic RILD Mean dose 36 50 Whole liver –GTV SBRT (hypofraction) Classic RILD Mean dose 13 18 5 5 3 fractions, for primary liver cancer 6 fractions, for primary liver cancer Whole liver – GTV SBRT (hypofraction) Classic RILD Mean dose 15 20 5 5 3 fractions, for liver metastases 6 fractions, for liver metastases 700 cc of normal liver SBRT (hypofraction) Classic RILD Dmax 15 5 Critical volume based, in 3–5 fractions Kidney Bilateral whole kidneyz Bilateral whole organ or 3D-CRT Clinically relevant renal dysfunction Mean dose 15–18 5 Bilateral whole kidneyz Bilateral whole organ Clinically relevant renal dysfunction Mean dose 28 50 Bilateral whole kidneyz 3D-CRT Clinically relevant renal dysfuntction V12 55% 5 For combined kidney V20 32% V23 30% V28 20% Stomach Whole organ Whole organ Ulceration D100k 45 7 Small bowel Individual small bowel loops 3D-CRT Grade $ 3 acute toxicityx V15 120 cc 10 Volume based on segmentation of the individual loops of bowel, not the entire potential peritoneal space Entire potential space within peritoneal cavity 3D-CRT Grade $ 3 acute toxicityx V45 195 cc 10 Volume based on the entire potential space within the peritoneal cavity (Continued) UseofNTCPmodelsintheclinicdL.B.MARKSetal.S17
- 18. Table 1. QUANTECSummary: Approximate Dose/Volume/Outcome Data for Several Organs Following Conventional Fractionation (Unless Otherwise Noted)* (Continued) Organ Volume segmented Irradiation type (partial organ unless otherwise stated)y Endpoint Dose (Gy), or dose/volume parametersy Rate (%) Notes on dose/volume parameters Rectum Whole organ 3D-CRT Grade $ 2 late rectal toxicity, Grade $ 3 late rectal toxicity V50 50% 15 10 Prostate cancer treatment Whole organ 3D-CRT Grade $ 2 late rectal toxicity, Grade $ 3 late rectal toxicity V60 35% 15 10 Whole organ 3D-CRT Grade $ 2 late rectal toxicity, Grade $ 3 late rectal toxicity V65 25% 15 10 Whole organ 3D-CRT Grade $ 2 late rectal toxicity, Grade $ 3 late rectal toxicity V70 20% 15 10 Whole organ 3D-CRT Grade $ 2 late rectal toxicity, Grade $ 3 late rectal toxicity V75 15% 15 10 Bladder Whole organ 3D-CRT Grade $ 3 late RTOG Dmax 65 6 Bladder cancer treatment. Variations in bladder size/shape/ location during RT hamper ability to generate accurate data Whole organ 3D-CRT Grade $3 late RTOG V65 #50 % Prostate cancer treatment Based on current RTOG 0415 recommendation V70 #35 % V75 #25 % V80 #15 % Penile bulb Whole organ 3D-CRT Severe erectile dysfunction Mean dose to 95% of gland 50 35 Whole organ 3D-CRT Severe erectile dysfunction D90k 50 35 Whole organ 3D-CRT Severe erectile dysfunction D60-70 70 55 Abbreviations: 3D-CRT = 3-dimensional conformal radiotherapy, SRS = stereotactic radiosurgery, BED = Biologically effective dose, SBRT = stereotactic body radiotherapy, RILD = radi- ation-induced liver disease, RTOG = Radiation Therapy Oncology Group. * All data are estimated from the literature summarized in the QUANTEC reviews unless otherwise noted. Clinically, these data should be applied with caution. Clinicians are strongly advised to use the individual QUANTEC articles to check the applicability of these limits to the clinical situation at hand. They largely do not reflect modern IMRT. y All at standard fractionation (i.e., 1.8–2.0 Gy per daily fraction) unless otherwise noted. Vx is the volume of the organ receiving $ x Gy. Dmax = Maximum radiation dose. z Non-TBI. x With combined chemotherapy. k Dx = minimum dose received by the ‘‘hottest’’ x% (or x cc’s) of the organ. { Severe xerostomia is related to additional factors including the doses to the submandibular glands. ** Estimated by Dr. Eisbruch. yy Classic Radiation induced liver disease (RILD) involves anicteric hepatomegaly and ascites, typically occurring between 2 weeks and 3 months after therapy. Classic RILD also involves elevated alkaline phosphatase (more than twice the upper limit of normal or baseline value). zz For optic nerve, the cases of neuropathy in the 55 to 60 Gy range received z59 Gy (see optic nerve paper for details). Excludes patients with pituitary tumors where the tolerance may be reduced. S18I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010
- 19. REFERENCES 1. Emami B,Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 2. Kirkpatrick J, Meyer J, Marks L. The linear-quadratic model is inappropriate to model high-dose per fraction effects. Semin Ra- diat Oncol 2008;18:240–243. 3. Trotti A, Colevas AD, Setser A, et al. CTCAE v3.0: Develop- ment of a comprehensive grading system for the adverse effects of cancer treatment. Semin Radiat Oncol 2003;13:176–181. 4. Langer M, Morrill SS, Lane R. A test of the claim that plan rank- ings are determined by relative complication and tumor-control probabilities. Int J Radiat Oncol Biol Phys 1998;41:451–457. 5. Agren A, Brahme A, Turesson I. Optimization of uncompli- cated control for head and neck tumors. Int J Radiat Oncol Biol Phys 1990;19:1077–1085. 6. MiftenMGO,PardaDS,ProsnitzRG,MarksLM.Usingqualityof life information to rationally incorporate normal tissue effects into treatment plan evaluation and scoring. In: Rubin PCL, Marks LB, Okunieff P, editors.Cured I—lent.Lateeffectsof cancer treatment on normal tissue. 1st ed. New York: Springer; 2007. 7. Amols HI, Zaider M, Hayes MK, et al. Physician/patient-driven risk assignment in radiation oncology: Reality or fancy? Int J Radiat Oncol Biol Phys 1997;38:455–461. 8. Morris DE. Clinical experience with retreatment for palliation. Semin Radiat Oncol 2000;10:210–221. 9. Sadikov E, Bezjak A, Yi QL, et al. Value of whole brain re-ir- radiation for brain metastases—single centre experience. Clin Oncol 2007;19:532–538. 10. Kurup P, Reddy S, Hendrickson FR. Results of re-irradiation for cerebral metastases. Cancer 1980;46:2587–2589. 11. Pfeffer MR, Rabin T, Tsvang L, et al. Orbital lymphoma: Is it necessary to treat the entire orbit? Int J Radiat Oncol Biol Phys 2004;60:527–530. 12. Hope AJ, Lindsay PE, El Naqa I, et al. Clinical, dosimetric, and location-related factors to predict local control in non-small cell lung cancer. Int J Radiat Oncol Biol Phys 2005;63. S231–S231. 13. Engels B, Soete G, Verellen D, et al. Conformal Arc Radiotherapy for Prostate Cancer: Increased Biochemical Failure in Patients With Distended Rectum on the Planning Computed Tomogram Despite Image Guidance by Implanted Markers. Int J Radiat Oncol Biol Phys 2009;74:388–391. 14. Zagars GK, Schultheiss TE, Peters LJ. Inter-tumor heterogene- ity and radiation dose-control curves. Radiother Oncol 1987;8: 353–361. 15. Jolles B. Area factor in skin reaction. Br Emp Cancer Campaign Rep 1939;16. 16. Lyman JT. Complication probability as assessed from dose-vol- ume histograms. Radiat Res Suppl 1985;8:S13–S19. 17. Mohan R, Mageras GS, Baldwin B, et al. Clinically relevant op- timization of 3-D conformal treatments. AAPM 1992;19:933– 944. 18. Niemierko A. A generalized concept of equivalent uniform dose (EUD). Med Phys 1999;26:1100. 19. Kutcher GJ, Burman C, Brewster L, et al. Histogram reduction method for calculating complication probabilities for three-di- mensional treatment planning evaluations. Int J Radiat Oncol Biol Phys 1991;21:137–146. 20. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 21. Withers HR, Tayor JMG, Maciejewski B. Treatment volume and tissue tolerance. Int J Radiat Oncol Biol Phys 1988;15: 751–759. 22. Jackson A, Ten Haken RK, Robertson JM, et al. Analysis of clinical complication data for radiation hepatitis using a paral- lel architecture model. Int J Radiat Oncol Biol Phys 1995;31: 883–891. 23. Niemierko A, Goitein M. Calculation of normal tissue compli- cation probability and dose-volume histogram reduction schemes for tissues with a critical element architecture. Radio- ther Oncol 1991;20:166–176. 24. Graham MV, Purdy JA, Emami B, et al. Clinical dose-volume histogram analysis for pneumonitis after 3D treatment for non- small cell lung cancer (NSCLC). Int J Radiat Oncol Biol Phys 1999;45:323–329. 25. El Naqa I, Bradley J, Blanco AI, et al. Multivariable modeling of radiotherapy outcomes including dose-volume and clinical factors. Int J Radiat Oncol Biol Phys 2006;64:1275–1286. 26. Jackson A, Yorke E. NTCP and TCP for treatment planning. In: Memorial Sloan-Kettering Cancer Center, editor. A practical guide to intensity-modulated radiation therapy. Madison, WI: Medical Physics Pubishers; 2003; pp. 185–220. 27. Deasy JO, Niemierko A, Herbert D, et al. Methodological is- sues in radiation dose-volume outcome analyses: Summary of a joint AAPM/NIH workshop. Med Phys 2002;29:2109–2127. 28. YorkeED.Modelingtheeffectsofinhomogeneous dose distribu- tions in normal tissues. Semin Radiat Oncol 2001;11:197–209. 29. Moiseenko J, Deasy O, Van Dyk J. Radiobiological modeling for treatment planning. In: Van Dyk J, editor. The modern tech- nology of radiation oncology: A compendium for medical phys- icists and radiation oncologists, vol. 2. Madison, WI: Medical Physics Publishing; 2005, pp. 185–220. Use of NTCP models in the clinic d L. B. MARKS et al. S19
- 20. QUANTEC: ORGAN SPECIFICPAPER Central Nervous System: Brain RADIATION DOSE–VOLUME EFFECTS IN THE BRAIN YAACOV RICHARD LAWRENCE, M.R.C.P.,* X. ALLEN LI, PH.D.,y ISSAM EL NAQA, PH.D.,z CAROL A. HAHN, M.D.,x LAWRENCE B. MARKS, M.D.,{ THOMAS E. MERCHANT, D.O. PH.D.,k AND ADAM P. DICKER, M.D. PH.D.* *Department of Radiation Oncology, Thomas Jefferson University, Philadelphia, PA; y Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI; z Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO; x Department of Radiation Oncology, Duke University Medical Center, Durham, NC; { Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC; k Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN We have reviewed the published data regarding radiotherapy (RT)-induced brain injury. Radiation necrosis ap- pears a median of 1–2 years after RT; however, cognitive decline develops over many years. The incidence and se- verity is dose and volume dependent and can also be increased by chemotherapy, age, diabetes, and spatial factors. For fractionated RTwith a fraction size of 2.5 Gy, an incidence of radiation necrosis of 5% and 10% is predicted to occur at a biologically effective dose of 120 Gy (range, 100–140) and 150 Gy (range, 140–170), respectively. For twice-daily fractionation, a steep increase in toxicity appears to occur when the biologically effective dose is 80 Gy. For large fraction sizes ($2.5 Gy), the incidence and severity of toxicity is unpredictable. For single fraction radiosurgery, a clear correlation has been demonstrated between the target size and the risk of adverse events. Sub- stantial variation among different centers’ reported outcomes have prevented us from making toxicity–risk predic- tions. Cognitive dysfunction in children is largely seen for whole brain doses of $18 Gy. No substantial evidence has shown that RT induces irreversible cognitive decline in adults within 4 years of RT. Ó 2010 Elsevier Inc. Radiotherapy, stereotactic radiosurgery, brain, tolerance, side effects. 1. CLINICAL SIGNIFICANCE Radiotherapy (RT) plays an important role in the curative and palliative treatment of patients with primary and metastatic brain tumors. Primary brain tumors account for 22% of tumors in those 18 years of age. Brain metastases occur in z30% of patients diagnosed with solid tumors, afflicting z170,000 Americans annually. The acute and late effects of RT on the brainarecommonandrepresentasignificantsourceofmorbid- ity. Such morbidity is particularly troubling in patients with baseline tumor-related dysfunction. In addition, the radiation fields used to treat the upper aerodigestive track (e.g., pharynx and nasal cavities) often include a portion of the brain. 2. ENDPOINTS The acute side effects of RT to the brain include nausea, vomiting, and headache; vertigo and seizures are less fre- quent. These symptoms are transient and generally respond to medication. The present report summarizes the dose–volume predictors for the principal late side effects of RT to the brain: radiation necrosis and cognitive deterioration. A biopsy is rarely per- formed to confirm suspected radiation necrosis. The working definition used by most of the studies listed in Tables 1 and 2 was ‘‘new symptoms with suggestive radiologic findings.’’ However, most investigators have reported their late toxic- ity rates as crude numbers according to the number of patients treated rather than the number at risk (i.e., the survivors). This method understates the risk, because some subjects will have died before the toxicity has had a chance to develop. The actuarial rates have rarely been discussed. Surgery, chemo- therapy, steroids, antiepileptic agents, and opioids impair neurologic and cognitive function, further confounding the interpretation of suspected RT toxicity. Reprint requests to: Yaacov Richard Lawrence, M.R.C.P., Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Bodine Cancer Center, 111 S. 11th St., Philadelphia, PA 19107. Tel: (215) 955-6700; Fax: (215) 955- 0412; E-mail: richard.lawrence@jefferson.edu Y. R. Lawrence is supported by The ASCO Cancer Foundation Young Investigator Award. Any opinions, findings, and conclusions expressed in this material are those of the author(s) and do not nec- essarily reflect those of the American Society of Clinical Oncology or The ASCO Cancer Foundation. L. B. Marks is supported by NIH R01 69579 and the Lance Armstrong Foundation. A. P. Dicker is supported by National Institutes of Health Grant CA10663, Tobacco Research Settlement Fund (State of Pennsylva- nia), and the Christine Baxter Fund. Conflict of interest: none. Received Nov 26, 2008, and in revised form Feb 24, 2009. Accepted for publication Feb 27, 2009. S20 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S20–S27, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.02.091
- 21. 3. CHALLENGES DEFININGVOLUMES There is little disagreement regarding image segmentation of the entire brain, and little intra- or interfraction movement occurs. However, segmenting the brain subregions is challenging (e.g., the superior boundary of the brain stem). Currently the utility of subregion definition is unclear. 4. REVIEW OF DOSE–VOLUME DATA Radiation necrosis For radiosurgery, the incidence of necrosis depends on the dose, volume, and region irradiated (1–10) (Table 1 and Fig. 1). The Radiation Therapy Oncology Group conducted a dose-escalation study that sought to define the maximal dose for targets of different sizes; all subjects had previously undergone whole brain irradiation. The maximal tolerated dose for targets 31–40 mm in diameter was 15 Gy, and for targets 21–30 mm in diameter, it was 18 Gy. For targets 20 mm, the maximal tolerated dose was 24 Gy (11). The volume of brain receiving $12 Gy has been shown to corre- late with both the incidence of radiation necrosis and asymp- tomatic radiologic changes (Table 1). The large variation in absolute complication rates among studies (Fig. 1) is difficult to comprehend, but it might relate to differences in the definitions of the volume and toxicity, the avoidance of critical structures, and the type and length of clinical follow-up. For fractionated RT, the relationship between the radiation dose and radiation necrosis for partial brain irradiation is pre- sented in Table 2 (12–19) and Fig. 2, segregated by the frac- tionation scheme. Different fractionation schemes were compared using the biologically effective dose (BED) (20), with an a/b ratio of 3. For standard fractionation, a dose–re- sponse relationship exists, such that an incidence of side ef- fects of 5% and 10% occur at a BED of 120 Gy (range, 100–140) and 150 Gy (range, 140–170), respectively (corre- sponding to 72 Gy [range, 60–84] and 90 Gy [range, 84–102] in 2-Gy fractions). For twice-daily fractionation, a steep in- crease in toxicity appears to occur when the BED is 80 Gy. For daily large fraction sizes (2.5 Gy), the incidence Table 1. Dose–volume predictors of radiation necrosis after stereotactic radiosurgery Reference Diagnosis Technique Patients (n) Dmin* (Gy) RN incidence (%) Subgroup (cm3 ) RN incidence (%) Primary toxicity predictor Other risk factors 1 AVM GK 823 ? 5 Average dose in 20 cm3 2 Mixed LINAC 133 15.0 (7.0–25.0) 12.8 V10: 10 vs. 10 0 vs. 23.7 V10 Location 3 AVM GK 307 20.9 (12–30) 10.7 V12 Location 4 AVM LINAC 73 16 (10–22) 14 Tx volume: 1 1–3.9 4–13.9 14 0 15 14 27 Treatment volume Dose, previous brain insult 5 Mixed GK 243 20 (10–30) 7 V10 Repeated radiosurgery, Glioma 6 Mixed GK 749 18 (16–19)y ? Prescription volume: 0.05–0.66 0.67–3 3.1–8.6 8.7–95.1 0 3 7 9 Prescription volume 7 AVM Proton beam 1250 10.5 (4–65) 4.1 Dose and volume combined Older age, location 8 AVM ? 269 ? 4.7 V12 9 Brain metastases GK 137 16 (12–25) 11.4 Tx volume: 2 2 3.7 16 Volume 10 Tumor GK 129 17.3 (11–25) 30 V12: 0–5 5–10 10–15 15 23 20 54 57 V12 Location, previous WBRT, male Abbreviations: Dmin = minimal dose; RN = radiation necrosis; AVM = arteriovenous malformation; GK = gamma knife; LINAC = linear accelerator teletherapy machine; V10 = percentage of volume receiving $10 Gy; V12 = percentage of volume receiving $ 12 Gy; Tx = treat- ment; WBRT = whole brain radiotherapy. * Data presented as mean, with range in parentheses, unless otherwise noted. y Range refers to 25th to 75th quartile. Radiation dose–volume effects in brain d Y. R. LAWRENCE et al. S21
- 22. and severity oftoxicity is unpredictable. The reader is cau- tioned against overinterpreting the data presented in Fig. 2, which was created from a heterogeneous data pool (i.e., dif- ferent target volumes, endpoints, sample sizes, and brain re- gions). No evidence has shown that children are especially at risk of radiation necrosis (21, 22). Table 2. Dose–volume predictors of radiation necrosis after fractionated radiotherapy Reference Patients (n) Disease Volume Fraction size* Prescribed dose (Gy) Fractions/ week* BED (Gy) RN incidence (%) Comment 12 141 NPC TL 2 66 5 110 0 5-y Actuarial rate 12 126 NPC TL 2.5 60 4 110 0 ’’ ’’ 12 89 NPC TL 2.5 60 5 110 1.4 ’’ ’’ 12 53 NPC TL 3.5 59.5 3 129 8.1 ’’ ’’ 12 218 NPC TL 2 62.5 5 108 1.5 ’’ ’’ 12 109 NPC TL 2 62.5 5 108 1.4 ’’ ’’ 12 212 NPC TL 2.5 61 4 119 0.6 ’’ ’’ 12 48 NPC TL 1.6 71.2 10 115 14 ’’ ’’ 13 56 NPC TL 3.8 45.6 2 103 4.8 10-y Actuarial rate 13 621 NPC TL 4.2 50.4 2 121 18.6 ’’ ’’ 13 320 NPC TL 2.5 60 2 110 4.6 ’’ ’’ 12 105 NPC TL 2 67 5 112 1 Data represent dose range and fractionation parameters; mean values given; time of evaluation not clearly stated 12 378 NPC TL 2 67 5 107 1.1 ’’ ’’ 12 86 NPC TL 2.1 54 5 92 1.2 ’’ ’’ 12 143 NPC TL 1.9 62 5 101 1.4 ’’ ’’ 12 152 NPC TL 3 60 5 120 3.3 ’’ ’’ 12 18 NPC TL 2.4 60 5 108 5.6 ’’ ’’ 12 82 NPC TL 2.5 60 5 110 19.5 Time of evaluation not clearly stated 12 23 NPC TL 1.6 67.2 10 103 34.8 ’’ ’’ 12 77 NPC TL 1.6 71.2 10 131 40.3 ’’ ’’ 14 60 HGG PB 1.6 51.2 10 79 1.6 Received nitrosourea; endpoint, possible RN on 18-mo imaging 14 66 HGG PB 1.2 68.4 10 96 6.1 ’’ ’’ 14 51 HGG PB 1.2 79.2 10 111 17.7 ’’ ’’ 15 291 HGG PB 2 ? 5 103 4 Assume a/b of 2, BED included initial and salvage RT; some patients received chemotherapy; range of fraction sizes used; time of evaluation not clearly stated 15 11 HGG PB 2 ? 5 138 9 ’’ ’’ 15 23 HGG PB 2 ? 5 173 17 ’’ ’’ 15 23 HGG PB 2 ? 5 208 22 ’’ ’’ 16 101 LGG PB 1.8 50.4 5 81 2.5 16 102 LGG PB 1.8 64.8 5 104 11 17 213 BM WB 3 30 5 60 0 Median survival only 6 mo; later events might have been missed; time of evaluation not clearly stated 17 216 BM WB+B 1.6 54.4 10 83 0.4 ’’ ’’ 18 63 BM WB+B 1.6 48 10 74 0.0 ’’ ’’ 18 121 BM WB+B 1.6 54.4 10 83.4 1.7 ’’ ’’ 18 105 BM WB+B 1.6 64 10 98.4 1.9 ’’ ’’ 18 56 BM WB+B 1.6 70.4 10 108 1.8 ’’ ’’ 19 11 NPC TL 1.6 64 10 98 27 Refers to dose received by temporal lobe; time of evaluation not clearly stated 19 70 NPC TL 1.2 70.8 10 99 0 ’’ ’’ Abbreviations: NPC = nasopharyngeal cancer; TL = temporal lobe; BM = brain metastases; LGG = low-grade glioma; HGG = high grade glioma; WB = whole brain; WB+B = whole brain 32 Gy plus boost; PB = partial brain; RN = radiation necrosis. * For most fractions. S22 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 23. Neurocognitive function inchildren The neurocognitive effects of cranial RT in children have been studied in several settings. With central nervous system prophylaxis for acute lymphoblastic leukemia, the addition of 24 Gy radiation to the whole brain (to a chemotherapy regi- men) has been associated with a median 13-point intelligence quotient reduction at 5 years after RT and poorer academic achievement and self-image, and greater psychological dis- tress (23) at 15 years after RT. The reported toxicities have been lower (or not detected) when 14–18 Gy was used (24–26). In medulloblastoma, the post-RT intelligence quotients were 10–15 points better after a whole brain dose of 23.4 Gy vs. 36 Gy (27, 28). Others (29), but not all (30, 31), have also noted a dose response in the 18–36-Gy range. Dif- ferences between the studies can be explained by the inability of small studies to overcome the complex interactions among dose, volume, patient age, and follow-up length. Merchant et al. (32) has suggested that different regions of the brain, particularly the supratentorial area, are important in the development of RT-associated cognitive decline. Neurocognitive functioning in adults The evidence for RT-induced neurocognitive injury in adults is weak. Irreversible cognitive side effects were first highlighted in survivors who had undergone whole brain RT in 3–6 Gy/fraction (33). Subsequently, cognitive dys- function was found to be frequently present even before RT (34). Multiple studies have demonstrated improved cog- nitive function after RT, because of its antitumor effects (35– 39). The results from randomized studies of ‘‘elective’’ whole brain RT (e.g., for lung small cell carcinoma) have been difficult to interpret because those not receiving RT have tended to develop more brain metastases. In one adult study, learning impairment did not develop until 5 years after RT (40); however, few studies have followed up patients for this long. Several studies have compared the cognitive function of patients who underwent RT with that of those who did not. Four studies with a follow-up of #2 years found no differ- ence (34, 41–43). However, the two studies with $5 years of follow-up noted negative cognitive effects of RT; most of these patients had undergone partial brain RT (44, 45). The total doses were 56 and 60 Gy; only those receiving frac- tion sizes 2 Gy showed cognitive decline. Two randomized studies of high- vs. low-dose partial brain irradiation failed to discern a difference in neurocognitive outcome (46, 47); however, an insensitive instrument was used. Two small studies suggested that whole brain RT is more detrimental than focal RT (48, 49). These findings were not confirmed by a randomized trial comparing radiosurgery and radiosurgery combined with whole brain RT, however this study used an insensitive instrument and had a short follow-up period (50). Thus, very limited evidence is available to show that brain RT in 2-Gy fractions causes irreversible cognitive decline in adults. 5. FACTORS AFFECTING RISK The radiation dose, fraction size, and volume are the major variables that influence the development of radiation necro- sis. Although location does not influence the susceptibility to radiation necrosis, necrosis is far more likely to be symp- tomatic in certain areas (e.g., corpus callosum and brain stem) (51). Other suggested risk factors for radiation necrosis in- clude chemotherapy use, lower conformality index, shorter overall treatment time, older age, and diabetes mellitus (12, 15, 30). Young age is the most important risk factor for neurocog- nitive decline in children undergoing cranial RT (29, 31, 52). Other risk factors include female gender, NF-1 mutation, extent of surgical resection, hydrocephalus, concomitant chemotherapy (especially methotrexate), location, and volume of brain irradiated (31, 53–57). An excellent review can be found in the report by Duffner (58). The risk factors for neurocognitive decline in adults might include the volume irradiated (48, 49), large fraction size (44), and longer interval after treatment (40). 6. MATHEMATICAL/BIOLOGIC MODELS The linear-quadratic model has been used to model radia- tion necrosis in the brain after fractionated RT (12, 13, 20). The a/b ratio for the normal brain has been estimated to be 2.9 (13). Fig. 1. Relationship between volume receiving high-dose irradia- tion and incidence of radiation necrosis in single-fraction stereotac- tic radiosurgery. Studies differed in their completeness of follow-up, definition of volume, and definition of radiation necrosis. Graph based on data presented in Table 1. Volume plotted as a point, representing mid-point of volume range. V10 = volume receiving 10 Gy; V12 = volume receiving 12 Gy; RxV = treatment volume. Flickinger data is shown for patients with either radiologic or symp- tomatic evidence of necrosis (marked as All), or only those with symptomatic necrosis (Symp). The other authors’ data refers to symptomatic necrosis. Radiation dose–volume effects in brain d Y. R. LAWRENCE et al. S23
- 24. For radiosurgery, avariety of models have been suggested. All are highly simplified and ignore many relevant variables, and none has been adequately validated. 7. SPECIAL SITUATIONS Re-irradiation is frequently performed in the brain. A meta-analysis of brain re-irradiation (interval between courses, 3–55 months) found no cases of necrosis when the total radiation dose was 100 Gy (normalized to 2 Gy/frac- tion; a/b ratio, 2) (59). Unlike other settings, in primary central nervous system lymphoma, RT (to z40 Gy) has been associated with cogni- tive decline, especially in those 60 years old (60, 61). The heightened sensitivity of this population to irradiation might be explained by the tumor’s highly diffuse, angiocentric growth pattern and that most patients receive high-dose methotrexate, a potent neurotoxin. As a result, upfront full- dose RT is now often avoided in elderly patients with this dis- ease. A lower radiation dose of 23.4 Gy might be safe even in older patients (62). 8. RECOMMENDED DOSE–VOLUME LIMITS The constraints presented in the following paragraphs are the best estimates determined from the available data; how- ever, high-level evidence is lacking. The constraints should be used with appropriate caution and interpreted within the clinical context. Fractionated RT to partial brain For standard fractionation, a 5% and 10% risk of symp- tomatic radiation necrosis is predicted to occur at a BED of 120 Gy (range, 100–140) and 150 Gy (range, 140–170), re- spectively (corresponding to 72 Gy [range, 60–84] and 90 Gy [range, 84–102] in 2-Gy fractions). The brain is especially sensitive to fraction sizes 2 Gy and, surprisingly, twice- daily RT. Fig. 2. Relationship between biologically effective dose (BED) and radiation necrosis after fractionated radiotherapy. Fit was done using nonlinear least-squares algorithm using Matlab software (The MathWorks, Natick, MA). Nonlinear func- tion chosen was probit model (similar functional form to Lyman model). Dotted lines represent 95% confidence levels; each dot represents data from specific study (Table 2), n = patient numbers as shown. (a) Fraction size 2.5 Gy; (b) fraction size $2.5 Gy (data too scattered to allow plotting of ‘‘best-fit’’ line); and (c) twice-daily radiotherapy. S24 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 25. Cognitive changes occurin children after $18 Gy to the entire brain. The effect of irradiation on the cognitive perfor- mance of adults is less well defined. Emami’s original estimate for fractionated partial brain RT (5% risk at 5 years for one-third brain, 60 Gy) appears to be overly conservative. We have concluded that the 5% risk at 5 years of the partial brain for normally fractionated RT is 72 Gy (range, 60–84). We emphasize that for most cancers, there is no clinical indication for giving fraction- ated RT 60 Gy and that, in some scenarios, an incidence of 1-5% radiation necrosis at 5 years would be unaccept- ably high. Radiosurgery The risk of complications increases with the size of the target volume. Toxicity increases rapidly once the volume of the brain exposed to 12 Gy is 5–10 cm3 . Eloquent areas of the brain (brain stem, corpus callosum) require more stringent limits. The substantial variation between the reported treatment parameters and outcomes from dif- ferent centers has prevented us from making precise toxicity risk predictions. 9. FUTURE TOXICITY STUDIES Modern imaging modalities (e.g., magnetic resonance imaging perfusion and spectroscopy, positron emission tomography) can detect damage before routine computed tomography or magnetic resonance imaging and symptom development (63–65). Hahn et al. (66) detected metabolic changes in normal brain that had undergone 40 Gy and cor- related these with neurocognitive effects. Future studies should aim to link early imaging changes with clinically rel- evant endpoints, facilitating rapid and quantitative estimates of treatment-induced toxicity. The effect of chemotherapy and newer targeted biologic agents on the incidence and severity of radiation necrosis and cognitive outcomes should be systematically addressed. Higher functions require input from spatially disparate brain regions, producing a complex interaction between the radiation dose distribution and neurologic outcomes. A re- cent study demonstrated the utility of diffusion-tensor trac- tography in assessing the tolerance thresholds for different neurologic tracts (67). The designation and avoidance of ‘‘key’’ areas of the brain is needed. For instance, the role of the hippocampus in memory formation has recently been emphasized, encouraging clinicians to limit the radiation dose to it (62). The efficacy of such approaches has not yet been proved. Also, a quick and sensitive test for neurocognitive function that can be included in clinical studies is needed. The best method to obtain quality long-term follow-up data would be the creation of an international registry to gather and relatedemographic factors,diagnoses,co-morbidities, baseline imaging findings, other treatment modalities, and the three-di- mensional isodose distribution (with or without biospecimens) to outcomes. A National Cancer Institute-sponsored institution such as the Radiation Therapy Oncology Group would be well suited for both data collection and analysis. 10. TOXICITY SCORING The Common Terminology Criteria for Adverse Events, version 4.0, is recommended as a tool for scoring neurocog- nitive dysfunction. Long-term follow-up (e.g., $5 years) might be necessary to detect neurologic/cognitive decline. Prospective RT studies should incorporate formal neurocog- nitive assessments. Future studies reporting RT brain toxicity should provide a clear definition of toxicity, detailed normal brain dose–volume information, the use of repeat RT and sys- temic treatments, and should report toxicity as an actuarial (as opposed to a crude) rate. We recommend adoption of the ‘‘volume receiving 12 Gy’’ as the standard method of report- ing the dose to the normal brain in radiosurgery procedures. The location should also be reported. REFERENCES 1. Lax I, Karlsson B. Prediction of complications in gamma knife radiosurgery of arteriovenous malformation. Acta Oncol 1996; 35:49–55. 2. Voges J, Treuer H, Sturm V, et al. Risk analysis of linear accel- erator radiosurgery. Int J Radiat Oncol Biol Phys 1996;36: 1055–1063. 3. Flickinger JC, Kondziolka D, Pollock BE, et al. Complications from arteriovenous malformation radiosurgery: Multivariate analysis and risk modeling. Int J Radiat Oncol Biol Phys 1997;38:485–490. 4. Miyawaki L, Dowd C, Wara W, et al. Five year results of LINAC radiosurgery for arteriovenous malformations: Out- come for large AVMS. Int J Radiat Oncol Biol Phys 1999;44: 1089–1106. 5. Chin LS, Ma L, DiBiase S. Radiation necrosis following gamma knife surgery: A case-controlled comparison of treatment pa- rameters and long-term clinical follow up. J Neurosurg 2001; 94:899–904. 6. Nakamura JL, Verhey LJ, Smith V, et al. Dose conformity of gamma knife radiosurgery and risk factors for complications. Int J Radiat Oncol Biol Phys 2001;51:1313–1319. 7. Barker FG II, Butler WE, Lyons S, et al. Dose-volume predic- tion of radiation-related complications after proton beam radio- surgery for cerebral arteriovenous malformations. J Neurosurg 2003;99:254–263. 8. Friedman WA, Bova FJ, Bollampally S, et al. Analysis of factors predictive of success or complications in arteriovenous malformation radiosurgery. Neurosurgery 2003;52:296–307. 9. Varlotto JM, Flickinger JC, Niranjan A, et al. Analysis of tumor control and toxicity in patients who have survived at least one year after radiosurgery for brain metastases. Int J Radiat Oncol Biol Phys 2003;57:452–464. 10. Korytko T, Radivoyevitch T, Colussi V, et al. 12 Gy gamma knife radiosurgical volume is a predictor for radiation necrosis in non-AVM intracranial tumors. Int J Radiat Oncol Biol Phys 2006;64:419–424. Radiation dose–volume effects in brain d Y. R. LAWRENCE et al. S25
- 26. 11. Shaw E,Scott C, Souhami L, et al. Single dose radiosurgical treatment of recurrent previously irradiated primary brain tumors and brain metastases: Final report of RTOG protocol 90-05. Int J Radiat Oncol Biol Phys 2000;47:291–298. 12. Lee AW, Kwong DL, Leung SF, et al. Factors affecting risk of symptomatic temporal lobe necrosis: Significance of fractional dose and treatment time. Int J Radiat Oncol Biol Phys 2002;53: 75–85. 13. Lee AW, Foo W, Chappell R, et al. Effect of time, dose, and fractionation on temporal lobe necrosis following radiotherapy for nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 1998;40:35–42. 14. Corn BW, Yousem DM, Scott CB, et al. White matter changes are correlated significantly with radiation dose: Observations from a randomized dose-escalation trial for malignant glioma (Radiation Therapy Oncology Group 83-02). Cancer 1994;74: 2828–2835. 15. Ruben JD, Dally M, Bailey M, et al. Cerebral radiation necrosis: Incidence, outcomes, and risk factors with emphasis on radia- tion parameters and chemotherapy. Int J Radiat Oncol Biol Phys 2006;65:499–508. 16. Shaw E, Arusell R, Scheithauer B, et al. Prospective random- ized trial of low- versus high-dose radiation therapy in adults with supratentorial low-grade glioma: Initial report of a North Central Cancer Treatment Group/Radiation Therapy Oncology Group/Eastern Cooperative Oncology Group study. J Clin Oncol 2002;20:2267–2276. 17. Murray KJ, Scott C, Greenberg HM, et al. A randomized phase III study of accelerated hyperfractionation versus standard in patients with unresected brain metastases: A report of the Radiation Therapy Oncology Group (RTOG) 9104. Int J Radiat Oncol Biol Phys 1997;39:571–574. 18. Sause WT, Scott C, Krisch R, et al. Phase I/II trial of accelerated fractionation in brain metastases RTOG 85-28. Int J Radiat Oncol Biol Phys 1993;26:653–657. 19. Jen YM, Hsu WL, Chen CY, et al. Different risks of symptom- atic brain necrosis in NPC patients treated with different altered fractionated radiotherapy techniques. Int J Radiat Oncol Biol Phys 2001;51:344–348. 20. Fowler JF. The linear-quadratic formula and progress in fractionated radiotherapy. Br J Radiol 1989;62:679–694. 21. Smyth MD, Sneed PK, Ciricillo SF, et al. Stereotactic radiosur- gery for pediatric intracranial arteriovenous malformations: The University of California at San Francisco experience. J Neuro- surg 2002;97:48–55. 22. Tanaka T, Kobayashi T, Kida Y, et al. Comparison between adult and pediatric arteriovenous malformations treated by gamma knife radiosurgery. Stereotact Funct Neurosurg 1996; 66(Suppl. 1):288–295. 23. Hill JM, Kornblith AB, Jones D, et al. A comparative study of the long term psychosocial functioning of childhood acute lym- phoblastic leukemia survivors treated by intrathecal methotrex- ate with or without cranial radiation. Cancer 1998;82:208–218. 24. Waber DP, Turek J, Catania L, et al. Neuropsychological out- comes from a randomized trial of triple intrathecal chemother- apy compared with 18 Gy cranial radiation as CNS treatment in acute lymphoblastic leukemia: Findings from Dana-Farber Cancer Institute ALL Consortium Protocol 95-01. J Clin Oncol 2007;25:4914–4921. 25. Moore IM, Kramer JH, Wara W, et al. Cognitive function in children with leukemia. Effect of radiation dose and time since irradiation. Cancer 1991;68:1913–1917. 26. Smibert E, Anderson V, Godber T, et al. Risk factors for in- tellectual and educational sequelae of cranial irradiation in childhood acute lymphoblastic leukaemia. Br J Cancer 1996;73:825–830. 27. Mulhern RK, Kepner JL, Thomas PR, et al. Neuropsychologic functioning of survivors of childhood medulloblastoma ran- domized to receive conventional or reduced-dose craniospinal irradiation: A Pediatric Oncology Group study. J Clin Oncol 1998;16:1723–1728. 28. Mulhern RK, Fairclough D, Ochs J. A prospective comparison of neuropsychologic performance of children surviving leuke- mia who received 18-Gy, 24-Gy, or no cranial irradiation. J Clin Oncol 1991;9:1348–1356. 29. Jannoun L, Bloom HJ. Long-term psychological effects in chil- dren treated for intracranial tumors. Int J Radiat Oncol Biol Phys 1990;18:747–753. 30. Smith MC, Ryken TC, Buatti JM. Radiotoxicity after conformal radiation therapy for benign intracranial tumors. Neurosurg Clin North Am 2006;17:169–180, vii. 31. Bleyer WA, Fallavollita J, Robison L, et al. Influence of age, sex, and concurrent intrathecal methotrexate therapy on intel- lectual function after cranial irradiation during childhood: A re- port from the Children’s Cancer Study Group. Pediatr Hematol Oncol 1990;7:329–338. 32. Merchant TE, Kiehna EN, Li C, et al. Modeling radiation do- simetry to predict cognitive outcomes in pediatric patients with CNS embryonal tumors including medulloblastoma. Int J Radiat Oncol Biol Phys 2006;65:210–221. 33. DeAngelis LM, Delattre JY, Posner JB. Radiation-induced de- mentia in patients cured of brain metastases. Neurology 1989; 39:789–796. 34. Gregor A, Cull A, Stephens RJ, et al., for theUnited Kingdom Coordinating Committee for Cancer Research (UKCCCR) and the European Organization for Research and Treatment of Cancer (EORTC). Prophylactic cranial irradiation is indicated following complete response to induction therapy in small cell lung cancer: Results of a multicentre randomised trial. Eur J Cancer 1997;33:1752–1758. 35. Steinvorth S, Wenz F, Wildermuth S, et al. Cognitive function in patients with cerebral arteriovenous malformations after radiosurgery: Prospective long-term follow-up. Int J Radiat Oncol Biol Phys 2002;54:1430–1437. 36. Steinvorth S, Welzel G, Fuss M, et al. Neuropsychological out- come after fractionated stereotactic radiotherapy (FSRT) for base of skull meningiomas: A prospective 1-year follow-up. Radiother Oncol 2003;69:177–182. 37. Khuntia D, Brown P, Li J, et al. Whole-brain radiotherapy in the management of brain metastasis. J Clin Oncol 2006;24: 1295–1304. 38. Armstrong C, Ruffer J, Corn B, et al. Biphasic patterns of mem- ory deficits following moderate-dose partial-brain irradiation: Neuropsychologic outcome and proposed mechanisms. J Clin Oncol 1995;13:2263–2271. 39. Li J, Bentzen SM, Renschler M, et al. Regression after whole- brain radiation therapy for brain metastases correlates with sur- vival and improved neurocognitive function. J Clin Oncol 2007;25:1260–1266. 40. Armstrong CL, Hunter JV, Ledakis GE, et al. Late cognitive and radiographic changes related to radiotherapy: Initial pro- spective findings. Neurology 2002;59:40–48. 41. Vigliani MC, Sichez N, Poisson M, et al. A prospective study of cognitive functions following conventional radiotherapy for supratentorial gliomas in young adults: 4-Year results. Int J Radiat Oncol Biol Phys 1996;35:527–533. 42. Grosshans DR, Meyers CA, Allen PK, et al. Neurocognitive function in patients with small cell lung cancer: Effect of pro- phylactic cranial irradiation. Cancer 2008;112:589–595. 43. Arriagada R, Le Chevalier T, Borie F, et al. Prophylactic cranial irradiation for patients with small-cell lung cancer in complete remission. J Natl Cancer Inst 1995;87:183–190. 44. Klein M, Heimans J, Aaronson N, et al. Effect of radiotherapy and other treatment-related factors on mid-term to long-term cognitive sequelae in low-grade gliomas: A comparative study. Lancet 2002;360:1361–1368. S26 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 27. 45. Surma-aho O,Niemela¨ M, Vilkki J, et al. Adverse long-term ef- fects of brain radiotherapy in adult low-grade glioma patients. Neurology 2001;56:1285–1290. 46. Kiebert GM, Curran D, Aaronson NK, et al., for theEORTC Ra- diotherapy Co-operative Group. Quality of life after radiation therapy of cerebral low-grade gliomas of the adult: Results of a randomised phase III trial on dose response (EORTC trial 22844). Eur J Cancer 1998;34:1902–1909. 47. Brown P. Effects of radiotherapy on cognitive function in patients with low-grade glioma measured by the Folstein Mini-Mental State Examination. J Clin Oncol 2003;21:2519–2524. 48. Gregor A, Cull A, Traynor E, et al. Neuropsychometric evaluation of long-term survivors of adult brain tumours: Relationship with tumour and treatment parameters. Radiother Oncol 1996;41:55–59. 49. Kleinberg L, Wallner K, Malkin MG. Good performance status of long-term disease-free survivors of intracranial gliomas. Int J Radiat Oncol Biol Phys 1993;26:129–133. 50. Aoyama H, Shirato H, Tago M, et al. Stereotactic radiosurgery plus whole-brain radiation therapy vs stereotactic radiosurgery alone for treatment of brain metastases: A randomized controlled trial. JAMA 2006;295:2483–2491. 51. Flickinger JC, Kondziolka D, Maitz AH, et al. Analysis of neu- rological sequelae from radiosurgery of arteriovenous malfor- mations: How location affects outcome. Int J Radiat Oncol Biol Phys 1998;40:273–278. 52. Merchant TE, Conklin HM, Wu S, et al. Late effects of confor- mal radiation therapy for pediatric patients with low-grade gli- oma: Prospective evaluation of cognitive, endocrine and hearing deficits. J Clin Oncol 2009;27:3691–3697. 53. Brown RT, Madan-Swain A, Walco GA, et al. Cognitive and academic late effects among children previously treated for acute lymphocytic leukemia receiving chemotherapy as CNS prophylaxis. J Pediatr Psychol 1998;23:333–340. 54. Meadows AT, Gordon J, Massari DJ, et al. Declines in IQ scores and cognitive dysfunctions in children with acute lymphocytic leukaemia treated with cranial irradiation. Lancet 1981;2:1015–1018. 55. Ellenberg L, McComb JG, Siegel SE, et al. Factors affecting in- tellectual outcome in pediatric brain tumor patients. Neurosur- gery 1987;21:638–644. 56. Merchant TE, Lee H, Zhu J, et al. The effects of hydrocephalus on intelligence quotient in children with localized infratentorial ependymoma before and after focal radiation therapy. J Neuro- surg 2004;101:159–168. 57. Hirsch JF, Renier D, Czernichow P, et al. Medulloblastoma in childhood: Survival and functional results. Acta Neurochir (Wien) 1979;48:1–15. 58. Duffner PK. Long-term effects of radiation therapy on cognitive and endocrine function in children with leukemia and brain tumors. Neurologist 2004;10:293–310. 59. Mayer R, Sminia P. Reirradiation tolerance of the human brain. Int J Radiat Oncol Biol Phys 2008;70:1350–1360. 60. Omuro AMP, Ben-Porat LS, Panageas KS, et al. Delayed neu- rotoxicity in primary central nervous system lymphoma. Arch Neurol 2005;62:1595–1600. 61. Schlegel U, Pels H, Oehring R, et al. Neurologic sequelae of treatment of primary CNS lymphomas. J Neurooncol 1999; 43:277–286. 62. Shah GD, Yahalom J, Correa DD, et al. Combined immunoche- motherapy with reduced whole-brain radiotherapy for newly diagnosed primary CNS lymphoma. J Clin Oncol 2007;25: 4730–4735. 63. Chan YL, Yeung DK, Leung SF, et al. Dynamic susceptibility contrast-enhanced perfusion MR imaging in late radiation-in- duced injury of the brain. Acta Neurochir Suppl 2005;95: 173–175. 64. Price SJ, Jena R, Green HA, et al. Early radiotherapy dose re- sponse and lack of hypersensitivity effect in normal brain tissue: A sequential dynamic susceptibility imaging study of cerebral perfusion. Clin Oncol (R Coll Radiol) 2007;19:577–587. 65. Fuss M, Wenz F, Scholdei R, et al. Radiation-induced regional cerebral blood volume (rCBV) changes in normal brain and low- grade astrocytomas: quantification and time and dose-dependent occurrence. Int J Radiat Oncol Biol Phys 2000;48:53–58. 66. Hahn C, Zhou S, Raynor R, et al. Dose-dependent effects of ra- diation therapy on cerebral blood flow, metabolism, and neuro- cognitive dysfunction. Int J Radiat Oncol Biol Phys 2009;73: 1082–1087. 67. Maruyama K, Kamada K, Ota T, et al. Tolerance of pyramidal tract to gamma knife radiosurgery based on diffusion-tensor tractography. Int J Radiat Oncol Biol Phys 2008;70:1330–1335. Radiation dose–volume effects in brain d Y. R. LAWRENCE et al. S27
- 28. QUANTEC: ORGAN-SPECIFIC PAPERCentral Nervous System: Optic Nerve/Chiasm RADIATION DOSE–VOLUME EFFECTS OF OPTIC NERVES AND CHIASM CHARLES MAYO, PH.D.,* MARY K. MARTEL, PH.D.,y LAWRENCE B. MARKS, M.D.,z JOHN FLICKINGER, M.D.,x JIHO NAM, M.D.,z AND JOHN KIRKPATRICK, M.D., PH.D.{ *Department of Radiation Oncology, University of Massachusetts School of Medicine, Worcester, MA; y Department of Radiation Oncology, M. D. Anderson Cancer Center, Houston, TX; z Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC; x Department of Radiation Oncology, University of Pittsburgh Presbyterian Hospital, Pittsburgh, PA; { Department of Radiation Oncology, Duke University Medical Center, Durham, NC Publications relating radiation toxicity of the optic nerves and chiasm to quantitative dose and dose–volume measures were reviewed. Few studies have adequate data for dose–volume outcome modeling. The risk of toxicity increased markedly at doses 60 Gy at z1.8 Gy/fraction and at 12 Gy for single-fraction radiosurgery. The evidence is strong that radiation tolerance is increased with a reduction in the dose per fraction. Models of threshold tolerance were examined. Ó 2010 Elsevier Inc. Optic, Nerve, Chiasm, Tolerance, Radiotherapy. 1. CLINICAL SIGNIFICANCE The therapeutic dose levels for tumors in the central nervous system and head-and-neck area are often constrained by the radiation tolerance of the optic apparatus. Visual impairment from radiation-induced optic neuropathy (RION) is uncom- mon but disabling (1, 2). It usually presents with painless rapid visual loss. Vasculature injury has been suggested as a significant contributor to RION (3, 4). Treatment of radio- therapy (RT)-associated visual loss is limited. 2. ENDPOINTS Visual impairment is typically defined according to the visual acuity (3, 5–8) and is typically defined as 20/100 vision or less, meaning that the patient can see at 20 feet no more than a normal person can see at 100 feet. Furthermore, impairment is often described by the size/extent of the ‘‘visual fields’’ (how much of the potentially visible region can be visualized). For instance, patients often lose vision of one-half or a quadrant of the visual field owing to injury of a part of the optic nerves/chiasm. The interval between RT and the development of visual symptoms is generally #3 years (mode, 1–1.5; median, 2.5) (2, 9). Optic nerve injury typically results in monocular visual loss, except if it occurs very close to the optic chiasm, where fibers looping up from the contralateral medial eye/retina can be affected. Injury to the entire chiasm can cause bilateral vision loss. Temporary injury limited to the inferior central optic chiasm from pituitary adenoma results in bilateral upper outer quadrant visual field impairment. The loss of a proximal optic tract causes loss of the same half of the visual field in each eye. Because the optic tracts spread out on their way toward the occipital cortex, injuries along the way typically result in small visual field cuts. Uncertainties exist in scoring the toxicity. Acuity problems can result from cataracts, dry eye or radiation retinopathy (usually distinguishable by examination). Vascular insuffi- ciency to the retina, optic nerves, tracts, or occipital lobes can also cause visual impairments, particularly visual field deficits. Because patients often undergo RT to many of these areas concurrently, it can be challenging to know how to accurately ascribe the clinical events. Lesions anterior to the chiasm will affect the ipsilateral eye, lesions of the chiasm will affect the bilateral temporal visual fields, and lesions posterior to the chiasm will affect visual fields in both eyes. 3. CHALLENGES DEFINING VOLUMES The optic nerves progress from the posterior aspect of the center of the globe roughly through the center of the orbit, bracketed by the rectus muscles. They angle up through the optic canals just medial to the anterior clinoid process of the lesser wings of the sphenoid bone. The axonal bundles of the left and right optic nerves, divide at the optic chiasm. Reprint requests to: Charles Mayo, Ph.D., Department of Radia- tion Oncology, HB-200, University of Massachusetts Memorial Medical Center, 55 Lake Ave. N, Worcester, MA 01655. Tel: (774) 442-5551; Fax: (774) 422-5006; E-mail: charles.mayo@ umassmemorial.org Conflict of interest: none. Received Nov 14, 2008, and in revised form July 10, 2009. Accepted for publication July 15, 2009. S28 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S28–S35, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.07.1753
- 29. The medial fiberscross to the contralateral optic tract, and the lateral fibers continue on the ipsilateral tract. The optic chiasm forms an X shape at this junction. Typically, it is just superior to the sella turcica, with the nerves crossing just anterior to the pituitary stalk. It is bracketed laterally by the internal carotid arteries and is inferior to the third ven- tricle (10–12). With conventional computed tomography or magnetic resonance imaging, the optic tracts are visible for only 1–2 cm posterior to the optic chiasm before the fibers spread and appear to blend into the rest of the brain parenchyma. The optic nerve is thin, usually 2–5 mm thick (10). Depending on the orientation of the scan plane relative to the brain, the optic nerve and chiasm can appear on multiple images. Computed tomography-magnetic resonance imaging (T1- and T2-weighted imaging/fast fluid-attenuated inversion recovery imaging) is recommended for better definition. Continuous axial images at #3 mm spacing increase the resolution of the optic apparatus over the entire course. It is essential to contour the optic apparatus in continuity, because gaps in the structures (e.g., where the optic nerves pass through the optic canal) will result in exclusion of the dose from the missing volume for that structure’s dose–volume histogram. 4. REVIEW OF DOSE–VOLUME DATA Complication data for RT-induced optic nerve and chiasm injury have been reported for several external beam RT deliv- ery systems, including fractionated photons, stereotactic radiosurgery (SRS), protons (with or without photons), and carbon ions. Selected studies are summarized in Tables 1 and 2. The average follow-up was 42 and 50 months for studies with and without an incidence of RION, respectively. Multiple fraction therapy The maximum dose (Dmax) to the optic structures is often the only dosimetric data reported. Emami et al. (13) did not report the partial volume tolerance data for the optic nerve and chiasm. For whole organ tolerance, Emami et al. (13) listed the doses corresponding to 5% probability of blindness within 5 years of treatment and the 50% probability within 5 years as 50 and 65 Gy, respectively. The data for the incidence of toxicity with conventional fractionation are summarized in Fig. 1. A probabilistic component clearly exists, because some patients receiving greater doses did not sustain complications. A steep increase in the incidence might exist past 60 Gy. None of the patients (70y) in the study by Parsons et al. (4) with a Dmax 59 Gy developed RION. In the study by Martel et al. (14), the aver- age maximum chiasm and nerve dose was 53.7 Gy (range, 28–70) and 56.8 Gy (range, 0–80.5) for patients without RION. The optic nerves had received a Dmax of $64 Gy with 25% of the volume receiving 60 Gy for patients with moderate to severe complications. Jiang et al. (15) reported no incidence of ipsilateral RION for a dose 56 Gy and a 5% incidence at 10 years for a dose 60 Gy at #2.5 Gy/fraction. The range of low-risk total doses is reflected in the plan- ning constraints reported. Hoppe et al. (16) and Martel et al. (14) constrained the Dmax to 54 and 60 Gy, respec- tively. Daly et al. (17) constrained the dose to the hottest 1% of the volume to 54 and 45 Gy for the nerves and chiasm, respectively. Tolerance might be lower in patients with pituitary tumors. Complications at doses as low as 46 Gy at 1.8 Gy/fraction have been reported (7, 18, 19). Mackley et al. (18) and van den Bergh et al. (7) constrained the optic structure Dmax to 46 and 45 Gy, respectively. The RION latency was shorter in patients with pituitary tumors. The average latency was 10.5 and 31 months (range, 5–168) in patients with pituitary targets and nonpituitary targets, respectively (18, 19). Evidence has shown that the mean dose is greater for patients with complications vs. those without (14) and the maximum doses are similar for both groups. This might indi- cate that a volume effect exists. However, dose–volume data to support this are scarce in the published reports. There is some indication that keeping 5–30% of the optic nerve to less than z50–60 Gy might reduce the incidence of compli- cations (14, 20, 21). The risk of nerve injury appears to be related to the fraction size. Parsons et al. (4) reported 15-year actuarial rates of RION for total doses of 60 to 70 Gy of 50% vs. 11% at $1.9- vs. 1.9-Gy dose/fraction, respectively. No patients treated twice daily with 1.2 Gy/fraction developed RION. At greater total doses, 70–83 Gy, the incidence was 33% vs. 11% for $1.9 vs. 1.9 Gy/fraction and 12% for 1.2-Gy twice-daily fractions. Bhandare et al. (20) noted similar reduc- tions in RION rates for once- vs. twice-daily fractionations. The proton results have been consistent with the photon results. Note, that the proton doses are presented as Cobalt Gray Equivalent (CGE), reflecting the greater biologic effect owing to the greater linear energy transfer of particles compared with photons. Widely accepted proton dosimetry standards were developed later than those for photons (22–24), and some studies have reflected a revision of the dose estimates according to these changes (25). Many proton patients were also treated with photons. Most proton series have reported a very low incidence of RION. Those reporting cases of RION, noted a threshold in the range of 55–60 CGE, consistent with that of photons. As with photons, many patients with doses within this range or greater have not developed RION. Wenkel et al. (25), Noel et al. (26), Weber et al. (27), and Nishimura et al. (28) reported using a Dmax constraint to the optic structures of 54, 55, 56, and 60 CGE, respectively. More aggressive frac- tionation regimens ($3 CGE/fraction) with greater linear energy transfer, carbon ions, reported 54 CGE as a planning constraint (29). Single fraction therapy Dose–volume analyses with radiosurgery are challenging owing to the small volumes irradiated and rapid dose Tolerance of optic nerves and chiasm to RT d C. MAYO et al. S29
- 30. gradients. Image segmentationuncertainties and distinctions between the mean dose vs. Dmax, could be particularly relevant for SRS. Tishler et al. (30) reviewed optic nerve injury from the early radiosurgery experience. They proposed 8 Gy as a limit for optic tolerance from their analysis, which cited the lowest dose for optic neuropathy as 9.7 Gy. Stafford et al. (31) reported that optic neuropathy occurred in 4 of 215 patients receiving a median dose of 10 Gy to the optic chi- asm, with chiasm/optic nerve Dmax of 0.4–16 Gy. The risk of RION was estimated at 1.7%, 1.8%, 0%, and 6.9% for a Dmax of 8, 8–10, 10–12, and 12 Gy, respectively. Of the 4 patients, 3 had undergone previous external beam RT with doses in the range of 45–58.8 Gy. Pollock et al. (32) observed no cases of RION in 62 patients undergoing gamma knife SRS for nonfunctioning pituitary adenomas. The median Dmax to the optic apparatus was 9.5 Æ 1.7 Gy. They reported using 12 Gy as an optic structure dose con- straint. Leber et al. (33) analyzed optic neuropathy risks in 50 patients 24–60 months (median follow-up, 40 months) after gamma knife SRS for benign skull base tumors. They reported optic neuropathy risks of 0% with 10 Gy, 27% with 10 to 15 Gy, and 78% with $15 Gy, respectively. 5. FACTORS AFFECTING RISK Parsons et al. (4) reported an increased risk of RION with increasing age. None of the 38 patients in the 20–50-year range developed RION, even though the reported optic nerve doses were 60 Gy for 58% and 70 Gy for 26% of patients. In contrast, RION was noted in older patients. For patients with doses 60 Gy, the incidence was 26% vs. 56% for the 50–70 vs. 70-year age groups. Similarly, Bhandare et al. (20) noted RION in 0%, 4%, 13%, and 14% of patients aged 20, 20–50, 51–70, and 70 years, respectively. Data on other clinical factors such as chemotherapy, diabe- tes mellitus, and hypertension have been inconsistent. Mini- mal data are available on re-irradiation of the optic apparatus and the effect of the interval between courses on RT tolerance. Flickinger et al. (34) found that 1 of 10 patients studied after repeat irradiation developed RION (they had received an initial 40 Gy, with a 7.5-year interval, and then received 46 Gy; both at 2 Gy/fraction). 6. MATHEMATICAL/BIOLOGIC MODELS The original Lyman-Kutcher-Burman normal tissue complication probability volumetric modeling parameters were estimated (35) as TD50= 65 Gy, n = 0.25, and m = 0.14. The dose–response data from Jiang et al. (15) (z1.5– 2.2 Gy/fraction) suggested TD50 z72–75 Gy. Martel et al. (14) and Brizel et al. (36) estimated TD50 at 72 and 70 Gy, respectively. The Parsons’ dose response extrapolated TD50 to 70 Gy. Isoeffect models have been used to estimate the threshold Dmax values. In linear quadratic modeling, the a/b can be very small. Jiang et al. (15) estimated the a/b at 1.6 for the optic nerves, but the lower 95% confidence interval value was À7. For the optic chiasm, they found an a/b of 0. Flick- inger et al. (37) also found an a/b of 0 in their modeling. The inadequacies of the linear-quadratic model for SRS have recently been discussed by Kirkpatrick et al. (38). Al- ternative biologically effective dose models that incorporate the number of fractions (Optic Ret) or number of fractions and overall treatment time (Neuret) have been explored. Flickinger et al. (39) examined complications vs. the normal- ized total dose (NTD) calculated from the Neuret formula (NTD 1.8 [Neuret]). This formulation is designed to repre- sent the equivalent dose delivered in 1.8-Gy fractions, 5 d/ wk. They found the actuarial risk of optic neuropathy was Table 1. Selected studies documenting dose to optic structures without radiation-induced optic neuropathy Investigator(ref)/ #Patients Disease/technique Prescription dose (range)/fraction (range) Dmax Mean/median dose Daly (17)/36 Paranasal sinus, nasal cavity/photon IMRT 70 (63–72) Gy CTV 1.8 Gy/fx GTV 2.12 Gy/fx Chiasm 52.3 Æ 5.1 Gy Nerve 59.1 Æ 7.7 Gy Chiasm 39.5 Æ 4.2 Gy Nerve 48.1 Æ 3.7 Gy Hoppe (21)/85 Paranasal sinus, nasal cavity/photon mixed 63 (50–70) Gy (1.8–2.0) Gy/fx Chiasm 52 (4–105) Gy Nerve 54 (4–105) Gy Chiasm 45 (5–51) Gy Nerve 35 (6–81) Gy Weber (27)/29 Chordoma, chondrosarcoma/proton C: 74 (67–74) CGE (1.8–2.0) CGE/fx CS:68(64–74) CGE (1.8–2.0) CGE/fx Chiasm 58.1 (12.2–68.6) CGE Nerve 51.7 (9.0 –74.9) CGE Chiasm 47.0 (3.9–60.7) CGE Nerve 16.5 (0.6–60.2) CGE Nishimura (28)/14 Olfactory neuroblastoma/proton 65 CGE 2.5 CGE/fx 67.7 (35.1–68.9) CGE 27.3 (6.5–53.3) CGE Lee (47)/11 Craniopharyngioma/CyberKnife 25 (18–38) Gy 5 (3.8–6.7) Gy/fx 5 Gy/fx NR Pollock (32)/62 Nonfunctioning pituitary adenoma/gamma knife 16.3 (11–20) Gy Single fraction 9.5 Gy Æ 1.7 (5.0–12.6) Gy NR Abbreviations: Dmax = maximum dose; IMRT = intensity-modulated radiotherapy; CTV = clinical target volume; GTV = gross tumor volume; fx = fraction; CGE = Cobalt Gray Equivalent; NR = not reported; RION = radiation-induced optic neuropathy. Average reported mean follow-up was 38 months (range, 15–60) for all studies not reporting RION. Some of data were estimated from text, tables, and figures of the published articles. S30 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 31. Table 2. Selectedstudies documenting incidence of radiation induced optic neuropathy Investigator(ref)/#Patients Disease/technique Prescribed treatment dose (range), dose/fraction (range) Incidence of RION Dose detail for group* Aristizabal et al. (19)/122y Pituitary adenoma/ conventional 60 Co 40 to 46 Gy 1.8 to 2.2 Gy/fx 0/7 2 Gy/fx 2/99 2–2.2 Gy/fx 2/16 2.2 Gy/fx Mackley et al. (18)/34 Pituitary adenoma/photon IMRT 45.9 Gy (45–49.3) 1.7 Gy/fx(1.7–2.0) 1/34z 49.3 Gyxx Flickinger et al. (39)/21 Craniopharyngioma/photon non-IMRT 57.9 Gy (51.3–70) 1.83 Gy/fx (1.61–2.76) 2/21z 61.5 Gyxx Pigeaud-Klessens et al. (48)/56 Mixed sites/photon non- IMRT 61.8 Gy (84–25) 6/56zx Nerve 64.3 Gy (59–65)xx 69 Gy Nerve 60 Gy Chiasm Martel et al. (14)/20 Paranasal sinus/photon non-IMRT 50.4–70.2 Gy 1.8 Gy/fx 1/20z Chiasm 59.5 Gyxx 6/20z Nerve 63.1 Gy (47.5–75.5)xx Mean 55.2 Gy (38.3– 72.9) 0/2{ 50 to 55 Gy 1/4{ 55 to 60 Gy 0/2{ 60 to 65 Gy 2/10{ 65 to 80 Gy Jiang et al. (15)/219 Paranasal sinus/photon non-IMRT NR 3% (0–9) Nerve (1/39j ) 50–60 Gy, $2.1 Gy/fx, 5-y incidence (95% CI) 34% (8–53) Nerve (20/59j ) 61–78 Gy, $2.2 Gy/fx, 5-y incidence (95% CI) 4% (0–9) Chiasm (4/110j ) 50–60 Gy, $2.1 Gy/fx, 5-y incidence (95% CI) 13% (2–24) Chiasm (9/66j ) 61–76 Gy, $2.2 Gy/fx , 5-y incidence (95% CI) Parsons et al. (4)/131 Head-and-neck cancer/ photon, non-IMRT 55 to 75 Gy 1.2–2.6 Gy/fx 0/21 55 to 65 Gy, 1.9 Gy/fx 5/7 55 to 65 Gy, $ 1.9 Gy/fx 1/16 55 to 60 Gy, 70 y 1/15 60 to 65 Gy, 70 y 6/73 65 to 75 Gy, 70 y Goldsmith et al. (40)/49 Meningioma/photon, non- IMRT 53.6 Gy (45–59.4) 1.0–1.8 Gy/fx 1/49z Optic Ret = 8.9 Gyxx Bhandare et al. (20),# /273 Nasopharynx, paranasal sinus, nasal cavity/photon, non-IMRT 50 Gy to 70 Gy $1.8 or 1.1–1.2 Gy/fx twice daily** 3/27 50 to 60 Gy, $1.8 Gy/fx 16/90 60 to 70 Gy, $1.8 Gy/fx 1/14 50 to 60 Gy, 1.1–1,2 Gy/ fx twice daily 4/69 60 to 70 Gy 1.1–1.2 Gy/fx twice daily Hoppe et al. (16)/39 Paranasal sinus, nasal cavity/photon mixed BED 70 Gy (48–72) 1/39z 77 Gyxx Noel et al. (26)/45 Base of skull/photon, non-IMRT + proton 67 CGE (60–70) 1.8–2.0 CGE/fx 1/45 Chiasm #58 CGExx Wenkel et al. (25)/46 Meningioma/photon, non-IMRT + proton 59 CGE (53.1–74.1) 1.8–2.13 CGE/fx 3/46z 56.4–62 CGExx 1/46z 63 CGExx Schulz-Ertner et al. (29)/96 Base of skull, chordoma/carbon ion 60 CGE (60–70) 3–3.5 CGE/fx 3/96z Chiasm 60 CGExx 1/96z 54 CGExx Tishler et al. (30)/62 Meningioma (n = 44), mixed histologic type/ Gamma Knife (n = 33), linear accelerator (n = 29) 10–40 Gyyy Single fraction 0/35 8 Gy 1/2 8–10 Gy 3/15 10 Gy (Continued) Tolerance of optic nerves and chiasm to RT d C. MAYO et al. S31
- 32. 30% for patientsreceiving a NTD 60 Gy at 1.8 Gy/fraction. Goldsmith et al. (40) found Optic Ret 8.9 Gy was signifi- cant in predicting RION. Shrieve (41) supported the use of Optic Ret = 8.9 Gy = total dose/(number of fractions)0.53 model as a guide for selecting the Dmax values in a hypofrac- tionation regimen. Figure 2 summarizes the data relating the total dose and dose per fraction and the models. For fractionations 2 Gy/ fraction, the ‘‘tolerance doses’’ were estimated to be greater with the linear-quadratic model than with the NTD or Optic Ret. Optic Ret provided the most conservative estimates of the Dmax and had the advantage of being easy to calculate in clinical practice. The NTD model was more consistent with the threshold values. The available data are insufficient for the range 2.0 Gy/fraction to judge the accuracy of the NTD or Optic Ret curves or to define an empirical curve for guidance. Figure 2 demonstrates the disagreement among the models and the significant lack of published data, partic- ularly in the range used for hypofractionation protocols. 7. SPECIAL SITUATIONS Data implicating the total dose and fraction size as the two most important treatment-related risk factors for optic nerve/chiasm injury are strong. Most have been derived from studies that used either conventional fractionation or single-fraction techniques. Minimal (or no) data have been derived from patients receiving hypofractionated schedules; thus, care should be taken in that setting. Fur- thermore, volume dependence is not well understood. Many of the studies that provided good statistical informa- tion on RION were performed in an era before the routine use of computed tomography-based planning, dose–volume histogram analysis, and steep dose gradients across struc- tures. Because the different portions of the optic nerves/chi- asm carry nerve fibers associated with particular parts of the visual field, it is logical to assume that these nerves have a ‘‘parallel architecture’’ in the very-small-volume range (1–3 mm). For treatment with rapid dose gradients, one would expect to observe injury to a part of the nerve, with a resultant visual field defect, rather than necessarily a large field defect. The latter might occur if the injury was mediated by a more global process (e.g., a vascular in- sult causing a more general nerve injury). With the high ra- diation doses and uniformly sharp gradients used in radiosurgery and intensity-modulated RT, proper training in accurately delineating the optic system is critical for lim- iting complications without limiting tumor control. Table 2. Selected studies documenting incidence of radiation induced optic neuropathy (Continued) Investigator(ref)/#Patients Disease/technique Prescribed treatment dose (range), dose/fraction (range) Incidence of RION Dose detail for group* Leber et al. (33)/45 Base of skull, mixed histologic features/Gamma Knife 14.3 Gy (8–25) Single fraction 0% (0/31 eyesj ) 10 Gy 26.7% (6/22 eyesj ) 10 to 15 Gy 77.8% (10/13 eyesj ) $15 Gy Stafford et al. (31)/215 Meningioma (n = 122), pituitary adenoma (n = 86), craniopharyngioma (n = 7)/Gamma Knife, previous photon (n = 23) 18 Gy (12–30)zz Single fraction 1/58 8 Gy 1/58 8–10 Gy 0/67 10–12 Gy 2/29 12 Gy Abbreviations as in Table 1. Data estimated from tables, figures, and text reported in studies, because exact incidence data not always provided; 1 patient in study by Parson et al. (4) with event in 55–60-Gy range was treated to 59 Gy; 1 event in study by Martel et al. (14) in 55–60-Gy range received 59.5 Gy. * Estimated Dmax unless otherwise noted. y In report by Aristizabal et al. (19), 88 (72%) of 122 received 40 Gy (26 patients 46 Gy); most patients received 2–2.2 Gy/fx, 16 received 2.2 Gy/fx, and only 4 received 1.8 Gy/fx. z Subgroup dose analysis not performed, documents dose characteristics for observed RION. x In report by Pigeaud-Klessens et al. (48), 3 patients with isolated retinopathy not included in numerator; mixed tumor sites included nose, pharynx, nasopharynx, and sinus. { Re-analysis, by us, of moderate to severe complication data presented in figures of original report; 2 patients received 50 Gy. j Author provided actuarial estimate of percentage incidence. Fractional value was estimated by us based on data provided in the paper. # Dose to nerves was specified as minimum delivered to one-third of optic nerve, dose to chiasm was specified as mean. ** In report by Bhandare et al. (20), 109 patients received #1.8 Gy/fx and 63 received 1.8 Gy/fx; 101 patients were treated with twice-daily fractions at 1.1–1.2 Gy/fx. yy Estimated ‘‘maximum cavernous sinus dose range,’’ rather than prescription doses, as in other studies. zz In report by Stafford et al. (31), 3 of 4 patients (2 at 10 Gy, 1 at 12 Gy) with complications had been treated with previous conventional fractionated photons to 45–58.8 Gy. xx Detail is for all patients in study, rather than for subgroup analysis of narrow, defined, dose range. Incidence for this dose detail may differ from ratio in incidence column. S32 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 33. ‘‘Overcontouring’’ the structuresto add an implicit buffer will lead to significant errors in dose estimates. 8. RECOMMENDED DOSE–VOLUME LIMITS From the dosimetric data and predictive model results discussed previously (‘‘Review of Dose–Volume Data,’’ ‘‘Factors Affecting Risk,’’ and ‘‘Mathematical/Biologic Models’’), some general guidelines for treatment planning can be given. The dose limits need to be considered in the clinical context. In some settings, it might be reasonable to accept greater risks. The Emami estimate of 5% probability of blindness within 5 years of treatment for a dose of 50 Gy appears inaccurate. From the present data review, 50 Gy is closer to a ‘‘near zero’’ incidence. The incidence of RION was unusual for a Dmax 55 Gy, particularly for fraction sizes 2 Gy. The risk increases (3–7%) in the region of 55–60 Gy and becomes more substantial (7–20%) for doses 60 Gy when fraction- ations of 1.8–2.0 Gy are used. The patients with RION treated in the 55–60 Gy range were typically treated to doses in the very high end of that range (i.e., 59 Gy). For particles, most investigators found that the incidence of RION was low for a Dmax 54 CGE. One exception to this range was for pitu- itary tumors, in which investigators used a constrained Dmax of 46 Gy for 1.8 Gy/fraction. For single-fraction SRS, the studies have indicated the incidence of RION is rare for a Dmax 8 Gy, increases in the range of 8–12 Gy, and becomes 10% in the range of 12–15 Gy. Unlike the fractionated series, most of these data were derived from the same treatment planning/delivery system (Gamma Knife). This might or might not affect the dose estimates using other systems. Consistent agreement has been reached on the low risk of RION for a Dmax of #10 Gy, and one major study indicated a low risk with a Dmax of #12 Gy. 9. FUTURE TOXICITY STUDIES Multi-institutional studies of RION incidence for plans using rapid dose gradients of intensity-modulated RT fields and dose–volume histogram analysis of nerve and chiasm are needed to examine the volumetric dose response. 0% 5% 10% 15% 20% 25% 30% 7065605550 Max Dose to Optic Nerve (Gy) Flickinger (2/21) Pigeaud-Klessens(6/56) Radiation Induced Optic Neuropathy in Selected Studies (1.8-2.0 Gy/fx) Author and (incidence) are shown next to points Bars show dose range in each group Martel (1/4) Daly (0/36)Martel (0/2) )58/0(eppoHWeber (0/29) Martel (0/2) Parsons (1/16) Parsons (1/15) Parsons (6/73) Martel(2/10) IncidenceinGroup Fig. 1. Selected data from Tables 1 and 2 used to compare incidence of radiation-induced optic neuropathy (RION) vs. maximum dose (Dmax) to optic nerves. Selected studies generally used fraction sizes with range of 1.8–2.0 Gy, assessed the dose to the nerve di- rectly from their best estimate of dose distribution in the structure (i.e., not as a partial volume average), did not include pituitary le- sions (lower tolerance), and selected patient age 70 years (if segre- gated). Bars illustrate range of doses for groups characterized by incidence values. Points offset from 0% to #1% were shifted to clearly show range bars. For points displayed at 0%, available range information was outside 50–70 Gy. Threshold for RION appears to be 55–60 Gy. However, range bars illustrate treatment in 60–65 Gy range for some studies without RION. Data estimated from tables, figures, and text reported in the studies, because exact incidence data were not always provided. The 1 patient in the study by Parsons et al. (4) with an event in the 55–60-Gy range was treated to 59 Gy. The 1 patients with an event in the study by Martel et al. (14) in the 55–60-Gy range received 59.5 Gy. 0 10 20 30 40 50 60 70 14121086420 Dose per Fraction (Gy) TotalDose(Gy) Model: LQ extrapolation from 1.8 Gy/fx, 59.4 Gy with α/β=3.3 Model: LQ extrapolation from 1.8 Gy/fx, 59.4 Gy with α/β=1.6 Model: Iso Neuret(NSD) = 60 Gy, 1.8 Gy/fx Model: Iso Optic RET = 8.9 Gy Literature Findings: 10% Incidence RION Literature Findings: 1-9% Incidence RION Literature Findings: No Incidence RION Only a few detailed publications in SRS region Lack of published data in hypo-fractionation region Majority of published data pre-date planning and treatment delivery technology that allows for steep dose gradients in or near optic structures. Effect on partial volume tolerance needs further exploration. Models and literature indicate better tolerance at lower dose per fraction. Applicability of models to predict RION from conventional to SRS fractionations Fig. 2. Isoeffect linear-quadratic model extrapolations and alternative biologically effective threshold models (curves) compared with reported maximum optic nerve/chiasm doses detailing incidence of radiation-induced optic neuropathy (RION) (symbols) for full range of dose per fraction. Linear-quadratic model was unreliable for extrapolating from fractionated (1.8–2.0-Gy/fraction) dose range to single-fraction range. Detailed data needed for low (1.8 Gy) and hypofractionated regions to better define organ response. Tolerance of optic nerves and chiasm to RT d C. MAYO et al. S33
- 34. A more uniformapproach to defining RION that explicitly addresses the differences between changes in acuity vs. visual fields and the role of gadolinium-enhanced magnetic resonance imaging for diagnosis of RION (7, 8) is needed. Routinely providing statistical data on the total dose and the dose per fraction seen by the optic structures would improve our understanding of the interdependence of the dose per fraction and the threshold doses. Routinely noting the types and dosages of concurrent chemotherapy agents would improve our understanding of their effect on the incidence of toxicity. Studies of anti-angiogenic agents, such as bevacizumab, as a potential treatment of radiation-induced damage to the optic apparatus (42, 43) are needed. Improving consistency within and among institutions in defining the optic nerves and chiasm is important for an accu- rate determination of the dose thresholds and the dose– volume effects. 10. TOXICITY SCORING Several formalized systems are available for scoring visual impairment. The Common Terminology Criteria for Adverse Events, versions 3.0 (44) and 4.0, as well as Common Toxic- ity Criteria, version 2.0 (45) are available from the Website of the National Cancer Institute Cancer Therapy Evaluation Program (available from: www.ctep.cancer.gov). Other systems frequently used include the Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer (46) and the Late Effects of Normal Tissues-Subjective, Objective, Management and Analytic scoring system (6). Visual impairment can be fairly well scored using the latter system, which addresses both objec- tive and subjective findings. Patients suspected of having an injury should be evaluated to assess for contributing fac- tors that might affect the vision and to assist with care and visual correction. REFERENCES 1. Lessell S. Friendly fire: Neurogenic visual loss from radiation therapy. J Neuroophthalmol 2004;24:243–250. 2. Danesh-Meyer HV. Radiation-induced optic neuropathy. J Clin Neurosci 2008;15:95–100. 3. Gordon KB, Char DH, Sagerman RH. Late effects of radiation on the eye and ocular adnexa. Int J Radiat Oncol Biol Phys 1995;31:1123–1139. 4. Parsons JT, Bova FJ, Fitzgerald CR, et al. Radiation optic neu- ropathy after megavoltage external-beam irradiation: Analysis of time–dose factors. Int J Radiat Oncol Biol Phys 1994;30: 755–763. 5. Rubin P, Constine LS, Fajardo LF, et al. for the RTOG Late Effects Working Group. Overview: Late Effects of Normal Tissues (LENT) scoring system. Int J Radiat Oncol Biol Phys 1995;31:1041–1042. 6. Pavy JJ, Denekamp J, Letschert J, et al. EORTC Late Effects Working Group. Late Effects toxicity scoring: the SOMA scale. Int J Radiat Oncol Biol Phys 1995;31:1043–1047. 7. van den Bergh AC, Dullaart RP, Hoving MA, et al. Radiation optic neuropathy after external beam radiation therapy for acro- megaly. Radiother Oncol 2003;68:95–100. 8. Hudgins PA, Newman NJ, Dillon WP, et al. Radiation-induced optic neuropathy: Characteristic appearances on gadolinium- enhanced MR. AJNR Am J Neuroradiol 1992;13:235–238. 9. Kline LB, Kim JY, Ceballos R. Radiation optic neuropathy. Ophthalmology 1985;92:1118–1126. 10. Celesia GG, DeMarco PJ Jr. Anatomy and physiology of the vi- sual system. J Clin Neurophysiol 1994;11:482–492. 11. Netter FH, Hansen JT. Atlas of Human Anatomy. 4th ed. Phil- adelphia: WB Saunders; 2006. 12. Duus P. Topical Diagnosis in Neurology: Anatomy, Physiol- ogy, Signs, Symptoms. 3rd rev. Stuttgart: Thieme; 1998. 13. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 14. Martel MK, Sandler HM, Cornblath WT, et al. Dose–volume complication analysis for visual pathway structures of patients with advanced paranasal sinus tumors. Int J Radiat Oncol Biol Phys 1997;38:273–284. 15. Jiang GL, Tucker SL, Guttenberger R, et al. Radiation-in- duced injury to the visual pathway. Radiother Oncol 1994; 30:17–25. 16. Hoppe BS, Nelson CJ, Gomez DR, et al. Unresectable carci- noma of the paranasal sinuses: Outcomes and toxicities. Int J Radiat Oncol Biol Phys 2008;72:763–769. 17. Daly ME, Chen AM, Bucci MK, et al. Intensity-modulated ra- diation therapy for malignancies of the nasal cavity and para- nasal sinuses. Int J Radiat Oncol Biol Phys 2007;67:151–157. 18. Mackley HB, Reddy CA, Lee SY, et al. Intensity-modulated radiotherapy for pituitary adenomas: The preliminary report of the Cleveland Clinic experience. Int J Radiat Oncol Biol Phys 2007;67:232–239. 19. Aristizabal S, Caldwell WL, Avila J. The relationship of time- dose fractionation factors to complications in the treatment of pituitary tumors by irradiation. Int J Radiat Oncol Biol Phys 1977;2:667–673. 20. Bhandare N, Monroe AT, Morris CG, et al. Does altered fractionation influence the risk of radiation-induced optic neuropathy? Int J Radiat Oncol Biol Phys 2005;62:1070–1077. 21. Hoppe BS, Stegman LD, Zelefsky MJ, et al. Treatment of nasal cavity and paranasal sinus cancer with modern radiotherapy techniques in the postoperative setting—The MSKCC experi- ence. Int J Radiat Oncol Biol Phys 2007;67:691–702. 22. Vatnitsky S, Moyers M, Miller D, et al. Proton dosimetry inter- comparison based on the ICRU report 59 protocol. Radiother Oncol 1999;51:273–279. 23. Newhauser WD, Myers KD, Rosenthal SJ, et al. Proton beam dosimetry for radiosurgery: Implementation of the ICRU Report 59 at the Harvard Cyclotron Laboratory. Phys Med Biol 2002;47:1369–1389. 24. International Commission on Radiation Units and Measure- ments. Report 78: Prescribing, recording and reporting proton- beam therapy. J ICRU 2007;7:49–81. 25. Wenkel E, Thornton AF, Finkelstein D, et al. Benign meningi- oma: partially resected, biopsied, and recurrent intracranial tumors treated with combined proton and photon radiotherapy. Int J Radiat Oncol Biol Phys 2000;48:1363–1370. 26. Noel G, Habrand JL, Mammar H, et al. Combination of photon and proton radiation therapy for chordomas and chon- drosarcomas of the skull base: The Centre de Protontherapie D’Orsay experience. Int J Radiat Oncol Biol Phys 2001;51: 392–398. 27. Weber DC, Rutz HP, Pedroni ES, et al. Results of spot-scanning proton radiation therapy for chordoma and chondrosarcoma of S34 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 35. the skull base:The Paul Scherrer Institut experience. Int J Radiat Oncol Biol Phys 2005;63:401–409. 28. Nishimura H, Ogino T, Kawashima M, et al. Proton-beam ther- apy for olfactory neuroblastoma. Int J Radiat Oncol Biol Phys 2007;68:758–762. 29. Schulz-Ertner D, Karger CP, Feuerhake A, et al. Effectiveness of carbon ion radiotherapy in the treatment of skull-base chordomas. Int J Radiat Oncol Biol Phys 2007;68:449–457. 30. Tishler RB, Loeffler JS, Lunsford LD, et al. Tolerance of cranial nerves of the cavernous sinus to radiosurgery. Int J Radiat Oncol Biol Phys 1993;27:215–221. 31. Stafford SL, Pollock BE, Leavitt JA, et al. A study on the radiation tolerance of the optic nerves and chiasm after ste- reotactic radiosurgery. Int J Radiat Oncol Biol Phys 2003; 55:1177–1181. 32. Pollock BE, Cochran J, Natt N, et al. Gamma knife radiosurgery for patients with nonfunctioning pituitary adenomas: Results from a 15-year experience. Int J Radiat Oncol Biol Phys 2008;70:1325–1329. 33. Leber KA, Bergloff J, Pendl G. Dose–response tolerance of the visual pathways and cranial nerves of the cavernous sinus to ste- reotactic radiosurgery. J Neurosurg 1998;88:43–50. 34. Flickinger JC, Deutsch M, Lunsford LD. Repeat megavoltage irradiation of pituitary and suprasellar tumors. Int J Radiat Oncol Biol Phys 1989;17:171–175. 35. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 36. Brizel DM, Light K, Zhou SM, et al. Conformal radiation ther- apy treatment planning reduces the dose to the optic structures for patients with tumors of the paranasal sinuses. Radiother Oncol 1999;51:215–218. 37. Flickinger JC, Kondziolka D, Lunsford LD. Radiobiological analysis of tissue responses following radiosurgery. Technol Cancer Res Treat 2003;2:87–92. 38. Kirkpatrick JP, Meyer JJ, Marks LB. The linear-quadratic model is inappropriate to model high dose per fraction effects in radiosurgery. Semin Radiat Oncol 2008;18:240–243. 39. Flickinger JC, Lunsford LD, Singer J, et al. Megavoltage exter- nal beam irradiation of craniopharyngiomas: Analysis of tumor control and morbidity. Int J Radiat Oncol Biol Phys 1990;19: 117–122. 40. Goldsmith BJ, Rosenthal SA, Wara WM, et al. Optic neuropathy after irradiation of meningioma. Radiology 1992;185:71–76. 41. Shrieve DC, Hazard L, Boucher K, et al. Dose fractionation in stereotactic radiotherapy for parasellar meningiomas: Radiobio- logical considerations of efficacy and optic nerve tolerance. J Neurosurg 2004;101(Suppl. 3):390–395. 42. Finger PT. Anti-VEGF bevacizumab (Avastin) for radiation op- tic neuropathy. Am J Ophthalmol 2007;143:335–338. 43. Finger PT. Radiation retinopathy is treatable with anti-vascular endothelial growth factor bevacizumab (Avastin). Int J Radiat Oncol Biol Phys 2008;70:974–977. 44. Trotti A, Colevas AD, Setser A, et al. CTCAE v3.0: develop- ment of a comprehensive grading system for the adverse effects of cancer treatment. Semin Radiat Oncol 2003;13:176–181. 45. Trotti A, Byhardt R, Stetz J, et al. Common toxicity criteria: Version 2.0. an improved reference for grading the acute effects of cancer treatment: Impact on radiotherapy. Int J Radiat Oncol Biol Phys 2000;47:13–47. 46. Cox JD, Stetz J, Pajak TF. Toxicity criteria of the Radiation Therapy Oncology Group (RTOG) and the European Organiza- tion for Research and Treatment of Cancer (EORTC). Int J Ra- diat Oncol Biol Phys 1995;31:1341–1346. 47. Lee M, Kalani MY, Cheshier S, et al. Radiation therapy and Cy- berKnife radiosurgery in the management of craniopharyngio- mas. Neurosurg Focus 2008;24:E4. 48. Pigeaud-Klessens ML, Kralendonk JH. Radiation retino- and opticopathy: A prospective study. Doc Ophthalmol 1992;79: 285–291. Tolerance of optic nerves and chiasm to RT d C. MAYO et al. S35
- 36. QUANTEC: ORGAN-SPECIFIC PAPERCentral Nervous System: Brain Stem RADIATION ASSOCIATED BRAINSTEM INJURY CHARLES MAYO, PH.D.,* ELLEN YORKE, PH.D.,y AND THOMAS E. MERCHANT, D.O., PH.D.z *Department of Radiation Oncology, University of Massachusetts Medical School, Worcester, MA, y Department of Medical Physics, Memorial Sloan Kettering Hospital, New York, NY, and z Division of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, TN Publications relating brainstem radiation toxicity to quantitative dose and dose–volume measures derived from three-dimensional treatment planning were reviewed. Despite the clinical importance of brainstem toxicity, most studies reporting brainstem effects after irradiation have fewer than 100 patients. There is limited evidence relating toxicity to small volumes receiving doses above 60–64 Gy using conventional fractionation and no definitive criteria regarding more subtle dose–volume effects or effects after hypofractionated treatment. On the basis of the available data, the entire brainstem may be treated to 54 Gy using conventional fractionation using photons with limited risk of severe or permanent neurological effects. Smaller volumes of the brainstem (1–10 mL) may be irradiated to maximum doses of 59 Gy for dose fractions #2 Gy; however, the risk appears to increase markedly at doses 64 Gy. Ó 2010 Elsevier Inc. Brainstem, Radiation, Tolerance, NTCP. 1. CLINICAL SIGNIFICANCE Central nervous system (CNS) tolerance to radiation therapy (RT) is of concern for patients treated for primary or meta- static disease involving the brain and head and neck. 2. ENDPOINTS The common toxicity criteria of the Cancer Therapy Evaluation Program (CTEP) grades brainstem injury on the basis of symptoms (Grade 1—mild or asymptomatic; Grade 2—moderate, not interfering with activities of daily living (ADLs); Grade 3—severe interference with ADLs, possible intervention; Grade 4—life-threatening or dis- abling, intervention indicated; and Grade 5—Death) (1). Se- vere RT-induced CNS injury is typically manifest months to years after treatment. Tumor recurrence and constitutional symptoms from other diseases and treatments may confound the diagnosis. Thestudy ofRT-inducedCNS injury is challeng- ing because (1) the incidence of injury is generally low, (2) survivals are short for most patients, (3) formal grading of brainstem effects is subjective and is often characterized cate- gorically (yes–no) for cranial neuropathy, and (4) for patients with intracranial tumors, it is often difficult to distinguish be- tween side effects and disease progression. For patients irradi- ated to head and neck sites, the distinction between brainstem and other neurological complications is often unclear. 3. CHALLENGES OF DEFINING VOLUMES Defining the brainstem on axial imaging is usually straightforward, although it requires special attention to the superior extent and interfaces at the cerebral and cerebellar peduncles where the brainstem borders are indistinct. The brainstem includes the midbrain, pons, and medulla. The midbrain is inferior to the third ventricle and the optic tracts. The inferior border of brainstem is at the pyramidal decussa- tion found at the level of the foramen magnum where the brainstem becomes the spinal cord. Segmentation or visuali- zation of coronal or sagittal planes may be helpful when de- fining the brainstem on neuroimaging. The brainstem is a stable structure; however, anatomic shift may occur from tumor and after surgery. By neuroimaging, Luft et al. deter- mined average brainstem volume in 48 healthy volunteers (average age 40 years, range, 20–73) to be 34 (range, 27– 43) mL (2). Merchant et al. reported age-dependent increases in brainstem volume in children diagnosed with infratentorial ependymoma (3). The volume of the brainstem can be af- fected by surgery and neurodegenerative conditions (4). Address reprint requests to: Charles S. Mayo, Ph.D., Department of Radiation Oncology, HB200, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA 01655. Tel: (744) 442 5551; Fax: (744) 442 5006; E-mail: charles. mayo@umassmemorial.org Conflicts of interest: none. Acknowledgment—We thank Drs. Brian Kavanagh, John Kirkpa- trick, and John Flickinger for their helpful suggestions and express special thanks to Dr. Larry Marks for his diligent efforts in editing this article. Received Nov 26, 2008, and in revised form July 16, 2009. Accepted for publication Aug 17, 2009. S36 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S36–S41, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.08.078
- 37. 4. REVIEW OFDOSE–VOLUME DATA A literature review was undertaken to extract relevant brainstem tolerance data from studies published in the era of CT-based treatment planning, including recent or active protocols in which brainstem or neurologic toxicity was reported. The review focused on articles that provided quan- titative brainstem dose and dose–volume measures related to toxicity (5–24). General features of studies representing the adult population are listed in this section and in Table 1. Because of the marked interstudy variations in reporting dose and outcome, it was not possible to generate a unifying dose–response curve from the available data. Only five of the reviewed studies had more than 50 patients (5–10), and most did not undertake statistical analysis of toxicity. The reported range of median follow-up times was 9–60 months with death limiting follow-up in some studies (18, 22, 23). Brainstem necrosis or MRI-based evidence of injury were reported in five studies (6, 7, 13, 14, 21). Neuro- logic toxicities were reported in eight (6–8, 10, 11, 13, 14, 20). Treatment planning limits on the high dose component of the brainstem dose–volume histogram (DVH) in multifrac- tion studies are shown in Table 1. Five studies used photons only, at conventional (1.2- to 2-Gy) fractionation (5, 9, 11–13). Uy et al. (13) reported brainstem necrosis for 1 of 40 meningioma patients treated with serial tomotherapy. For this patient, the treatment plan maximum dose (Dmax) was 55.6 Gy, and the absolute vol- ume of brainstem that exceeded 54 Gy (aV54) was 4.7 mL. Reporting on 48 patients with nasopharyngeal cancer treated with 1.2 Gy/fraction twice daily to 74.4 Gy and concomitant chemotherapy, Jian (11) noted 3 patients with Grade 1 neuro- logic deficit. Five studies used protons only (15, 17) or a mixture of protons and photons (6, 7, 14, 16) using a relative biologic effectiveness (RBE) dose conversion factor of 1.1 from phys- ical dose to cobalt gray equivalent (CGE). A change in proton dose calibration in 1995 affected two series (6, 7, 14). Proton doses were 6.5% greater than originally stated. The doses reported by Wenkel et al. (14) were recalculated to reflect the new calibration whereas those reported by Debus et al. (6, 7) were not. These studies placed separate limits on the maximum dose to the center and surface of the brainstem (Table 1). Debus’s study was the largest, reporting on 367 skull-base tumor patients treated with a combination of pho- ton and proton conformal radiation therapy between 1974 and 1995. There were 19 late brainstem-related toxicities, including three deaths. Significant predictors of toxicity by univariate analysis were as follows: Dmax 64 Gy, aV50 5.9 mL, aV55 2.7 mL, aV60 0.9 mL, two or more skull-based surgeries, diabetes, and high blood pressure. Pre- dictors by multivariate analysis were aV60 0.9 mL CGE, two or more skull-based surgeries, and diabetes. In Wenkle’s study of 46 patients with recurrent meningioma, the median Dmax brainstem dose was 58.0 (range, 12.1–66.3) CGE. One patient developed brainstem injury with a dose that ex- ceeded an unspecified constraint value by 10%; two others with neurologic toxicities had brainstem doses that exceeded the constraints in Table 1; less restrictive constraints had been used initially. Two small studies demonstrated high brain- stem doses without toxicities (15, 17). Median doses of 63.1 (range, 49.6–68.1) CGE and 48.5 (range, 15.8–63.3) CGE to the surface and center of the brainstem, respectively, were safe for the 29 patients in the study by Weber et al. (17). Brainstem DVHs were evaluable in 11 of the 14 patients treated without brainstem complications at 2.5 CGE/fraction in the study by Nishimura et al. (15). Maximum brainstem dose ranged from 50.7 to 66.3 CGE for four patients with the largest values. Dose to center was 63.7 CGE for the pa- tient who received 66.3 CGE to the surface. Dose to center was 35.1 CGE in the others. Single fraction stereotactic radiosurgery (SRS) was used in five studies (8, 10, 18–20). Each included a wide range of pre- scription doses and isodose levels, making it difficult to draw conclusions. The largest SRS study, by Foote et al. (10), fol- lowed 149 vestibular schwannoma patients treated with LINAC-based SRS between 1988 and 1998; 41 were treated before and 108 after 1994. Large single fractions (10–22.5 Gy) were used. Their analysis revealed a ‘‘learning curve’’ with a 5% and 2% actuarial 2-year rate of facial and trigeminal neuropathies, respectively, for patients treated after 1994 com- pared with 29% for both neuropathies for the earlier patients. Table 1. Selected reports of planning constraints used to limit brain stem toxicity Photon constraints No. patients Particle constraints No. patients Jian11 * aV65 3 mL (BID) Weber17y Surface #63 CGE 48 aV60 5 mL (BID) 29 Center #54 CGE Hoppe 9z Dmax 50 Gy Nishimura15x Surface 64 CGE 85 14 Center 53 CGE Daly12z D1% #54 Gy Noel16{,k Surface #64 CGE 36 45 Center #53 CGE Schoenfeld5 * aV55 0.1 cc Debus6,7{,k,** Surface #64 CGE 100 367 Center #53 CGE Wenkel14{,**,yy Surface #64 CGE 46 Center #53 CGE Abbreviation: aVXX = Absolute volume at dose XXGy; BID = twice daily; CGE = Cobalt Gray Equivalent; Dmax = maximum dose. * Either nasopharynx, oropharynx, hypopharynx or larynx. y Chordoma or chondrosarcoma. z Nasal Cavity and/or paranasal sinus. x Olfactory neuroblastoma. { Photons + proton boost. k Base of skull. ** Studies that noted complications if limits were exceeded. yy Meningioma. Radiation associated brainstem injury d C. MAYO et al. S37
- 38. Significant risk factorsby univariate analysis for cranial nerve palsy were Dmax $17.5 Gy (facial neuropathy), prescribed dose $12.5 Gy (any cranial neuropathy), prior open resection, age 62 years, pons-petrous tumor diameter 8 mm, tumor volume 1.7 mL; length of irradiated cranial nerve 16 mm, distance from brainstem to end of tumor in petrous bone, and planning without MR imaging (trigeminal neuropathy). Risk factorsonmultivariate (multiple Coxregression) analysis wereDmax, treatment before or after 1994, previous resection, and distance from brainstem to end of tumor in petrous bone. Substituting prescription dose for Dmax made a small loss in predictive strength. Authors concluded that there was signifi- cant increase in nerve complication for peripheral doses $15 Gy on the basis of cutpoint analysis. There was only one multifractionated SRS study (21). Clark et al. found brainstem complications in 4 of 20 patients treated for meningioma with a hypofractionation protocol of six fractions of 7 Gy each normalized to 90 % of the maxi- mum target dose. The brainstem was near enough to receive dose for all patients in this group. Complications were found to correlate with a mean biological effective dose (linear-qua- dratic model, a/b = 2.5 Gy) 70 Gy. Pediatric CNS tumors No toxicity was reported in pediatric patients with brain- stem glioma (treated with opposed lateral fields that encom- passed the majority of the brainstem) to doses of 54–60 Gy at 2 Gy/fraction, 75.6 Gy at 1.26 Gy twice daily (22) or 78 Gy at 1 Gy twice daily (23). The primary limitation of these studies was the short median survival, #12 months. Of 32 patients treated to 72 Gy twice daily, in combination with recombi- nant beta-interferon, there was at least one treatment-related death (24). There is no evidence that the tolerance of the pediatric patient differs from the adult. Most pediatric protocols for CNS tumors recommend doses 54 Gy, and separate brain- stem dose limits are usually absent. Merchant et al. studied 68 patients with infratentorial ependymoma treated with surgery and conformal RT (54– 59.4 Gy) (3). With follow-up of 5 years post-RT, partial recovery of tumor/surgery-acquired neurological deficits was more common in patients with fewer surgeries, fewer CSF shunting procedures, smaller tumor sizes, and smaller RT planning target volumes, as well as in female patients. In patients with full or normal recovery, a considerable por- tion of the brainstem received over 60 Gy (aV60 = 7.8 Æ 1.4 mL, V60 = 37% Æ 6.3%). There was no difference in brainstem recovery based on absolute (15.4 Æ 0.9 mL) or per- cent (76.4% Æ 3%)volume of the brainstem that received more than 54 Gy. Difference in these values for patients with- out full recovery was not statistically significant. One male patient died with autopsy-confirmed residual tumor and focal areas of brainstem necrosis. His mean brainstem dose was 59 Gy, and he had significant perioperative morbidity after two surgeries, including hemiparesis and unilateral and complete cranial nerve deficits involving the lower cranial nerves. 5. FACTORS AFFECTING RISK An increased rate of toxicity has been associated with tar- gets that are larger and closer to the brainstem (10, 18), lack of MRI-based planning (10), the number of surgeries, hydro- cephalus, diabetes, and hypertension (3, 6, 10). 6. MATHEMATICAL/BIOLOGICAL MODELS The1991Emamireview(25),withsupportingdataavailable at that time, specified a 5-year, 5% rate of complications,which they defined as ‘‘necrosis/infarct,’’ would result from 50, 53, and 60 Gy delivered to the whole, two thirds, and one third of the brainstem, respectively (25). The corresponding Ly- man-Kutcher-Berman (LKB) parameters for calculation of the normal tissue complication probability (NTCP) were n = 0.16, m = 0.14, with a tolerance dose for 50% probability of havingthiscomplication(TD50)equalto65Gy(26).Thesepa- rameters may be overly conservative. For example, they esti- mate a 12% risk of severe complications for 54 Gy to the whole brainstem or 3% risk of complications when the particle constraints (Table 1) are used to characterize the brainstem DVH for partial volume irradiation. The estimated risks are large in comparison to those observed in the studies cited, sug- gesting the need for further examination of these parameter values. For example, a Lyman model with larger TD50 ($72 Gy) or smaller m ($0.1) would reduce the predicted risks to 5% or 1%, respectively. Larger n ($0.25) would predict smaller risk for exposures that followed constraints such as those in Table 1 but not for irradiation of the whole brainstem. Studies with sufficient dose–volume complication data for quantitative examination of model parameters for conventional fractionation are needed. 7. SPECIAL SITUATIONS Applicability of the linear quadratic (LQ) model for ex- treme hypofractionation is controversial. Flickinger et al. (27) attempted to fit the LQ model to a variety of neurologic outcomes, including facial neuropathy (31 events/218 acous- tic neuroma patients) for patients receiving stereotactic radio- surgery with $2 years of follow-up. Their attempts to fit these complications and other endpoints failed because they re- quired large negative values for a/b. Meeks et al. fit the Ly- man plus LQ model to the outcomes (cranial neuropathy) and DVHs of 118 patients treated with LINAC-based radio- surgery for acoustic neuroma (based on patients from a previ- ous study with $1 year follow-up) (28). Multivariate analysis showed brainstem Dmax 16 Gy as the most significant risk factor for delayed cranial neuropathy. They found that the original LKB model parameters with a/b = 3.3 Gy resulted in NTCP estimates that underestimated complication proba- bility (26). The first 50 patients were used to derive a better fit and the results were applied to all 118 patients. The best fit was achieved using n = 0.04, m = 0.15, a/b = 2.1 Gy, and TD50 = 15.3 Gy; no confidence intervals were given. They found agreement with their NTCP calculation for these two groups with 33.2 % and 5.7 % before and after 1994, S38 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 39. respectively. The averageNTCP was 7.2% (range, 0%–80%) vs. 77% (range, 29%–100%) for patients with no permanent vs. permanent cranial neuropathy. Their curve on 3% iso-com- plication extrapolated to 14.2 Gy for partial volume z0 (i.e., Dmax). Using their parameters, we calculate NTCP values equal to 1%, 13%, 61%, and 94% for partial volume irradiation of one third of the brain stem to doses of 12.5, 14.2, 16, and 17.5 Gy, respectively, demonstrating agreement with their fig. 3a. We approximate NTCP results for Dmax by calculating for a small partial volume (1%), finding values of 0.2 %, 3.2%, 26%, and 68% for the same doses. This illustrates the rapid in- crease in NTCP over the range of doses discussed for SRS. 8. RECOMMENDED DOSE–VOLUME LIMITS Data and LQ models of isoeffect doses for total dose vs. dose per fraction are presented in Fig. 1. Data are grouped us- ing the categories of reported complication, cut point, dose constraint, no complication, and other reference. Cut points were dose values reported to be statistically significant for in- creased risk but not necessarily for low vs. high risk. Re- ported dose constraints used in treatment planning are presumed to be associated with low risk, although authors do not quantify the expected incidence. The ‘‘no complica- tion’’ category includes reports that provided statistical data on brainstem doses 50 Gy. Data not applicable to the other categories are categorized as ‘‘other reference,’’ i.e., the cal- culated 3% isocomplication, Dmax value extrapolated in the previous section, Special Situations. Because a range of dose fractionation schedules are used, three curves have been cal- culated using the linear quadratic model using a/b values dis- cussed by authors examined in this study. The solid curves identify schedules isoeffective to 64.3 Gy treated in 1.89 Gy/fraction with a/b = 3.3 (thick) (28) or 2.5 (thin) (21). The dashed curve shows schedules isoeffective to 14.2 Gy treated in a single fraction using a/b = 2.1 (28). The entire brainstem may be treated to 54 Gy using conven- tional fractionation with limited risk of severe or permanent neurological effects (3). Smaller volumes of the brainstem (1–10 cc) may be irradiated to maximum doses of 59 Gy for dose fractions #2 Gy. The risk appears to increase markedly at doses 64 Gy. However, there is insufficient information to determine whether there is a further volume effect. Figure 1 highlights the lack of information in the 4 to 8 Gy range. The applicability of the LQ fit curves to this region of hypofractionated regimens is unknown. There is only one re- ported study in the intermediate hypofractionation range, and its impact is blurred by use of ‘‘effective’’ vs. delivered dose statistics (21). We emphasize that in presenting curves that pass through this middle-fraction-size region, we are not making recommendations for clinical choice of threshold. For single fraction SRS, maximum brainstem dose of 12.5 Gy is associated with low (5%) risk. Higher doses (15– 20 Gy) have been used with low reported incidence of compli- cation in patient groups with poor prognosis for long-term sur- vival (e.g., brain stem metastases) (18, 31). However, the apparent safety of these higher doses may be an artifact of the poor survival. Thus, additional longer-term data are needed before recommending these higher doses as relatively safe. 9. FUTURE TOXICITY STUDIES Obtaining deeper understanding of tolerance thresholds and dose, volume, and fractionation effects is hampered by 0 10 20 30 40 50 60 70 0 2 4 6 8 10 12 14 16 18 Dose per Fraction (Gy) TotalDose(Gy) LQ Extrapolation from 64.3 Gy, 1.89 Gy/Fraction using / = 3.3 LQ Extrapolation from 64.3 Gy, 1.89 Gy/Fraction using / = 2.5 LQ extrapolation from 14.2 Gy in 1 using / =2.1 Complications Dose Constraints Cut Point No Complication Other Reference Weber(Surface) Jian (3 mL, BID) Selected data on brainstem radiation tolerance Debus(DMax) Debus(0.9mL) Uy (DMax) Schoenfeld(0.1 mL) Debus, Noel, Wenkel, Nishimura (Center) Clark(~Dmax) Foote(Prescribed Dose) Foote(Tumor Margin) Meeks (calculated 3% iso-complication for 0% partial volume) Nishimura (DMax) Debus, Noel, Wenkel, Nishimura (Surface) Weber (Center) Daly (1% of BS) Foote(Peripheral Dose) Fig. 1. Comparison of selected data on brainstem tolerance and dose constrains compared to linear quadratic (LQ) model extrapolations. Data points are marked with the corresponding author and dose parameter considered in parenthesis (e.g., surface or maximum dose). Center, 0.9 mL, 0.1 mL, and 3 mL refer to the minimum dose to that hottest volume. Some data were estimated from the cited articles. Cut points illustrate thresholds determined by authors to correlate with significant increase in incidence of brainstem necrosis or neuropathy. Little quantitative data on brainstem doses is available in the dose range of stereotactic radiosurgery and hypofractionation. BID = twice daily; BS = Brain Stem; Dmax = maximum dosage. Radiation associated brainstem injury d C. MAYO et al. S39
- 40. the lack ofclearly defined data in the literature. To provide unambiguous data of the range of doses safely employed by clinicians and improve understanding of dose–volume effects, we make the following suggestions: 1. We encourage publication of detailed brainstem dose– volume and outcomes data for patients with long-term follow-up even when no toxicity has been observed. These data are especially needed for emerging fraction- ated SRT regimens. 2. In the absence of a formal structure for interinstitutional NTCP data sharing, we suggest that future studies be designed with mechanisms for acquiring and reporting de- tailed dosimetric and outcome information in a form that might be used for NTCP modeling. For example, publica- tion of an ‘‘atlas’’ as described by Jackson, is a technically simple way to provide detailed information from a study in which DVHs are produced as part of the normal plan- ning process (29). For hypofractionated treatments, the method of correcting dose distribution information for fractionation should be clearly described, but the underly- ing physical dose–volume information should also be made accessible. 3. Common, clinically practical, formal grading systems should be used to define the toxicities (see the next sec- tion, Toxicity Scoring) in future publications to facilitate data pooling and intercomparisons. 4. At a less detailed level, studies of brainstem toxicity out- comes should report the mean and standard deviation of at least four brainstem dosimetric variables: Dmax, Dmax per fraction, D1mL, and mean dose. For patients experiencing brainstem radiation necrosis or severe neu- ropathy, the specific values of these points should be noted. 5. Development of formal, communitywide methods for collection of multi-institutional data from both academic and nonacademic clinics would support the goal of obtain- ing sufficient data for robust modeling. 10. TOXICITY SCORING The Common Toxicity Criteria system was replaced by the Common Terminology for Criteria for Adverse Events (CTCAE v4.0) for use in CTEP protocols. The brainstem is one component of the brain for which specific toxicity assess- ment is possible (1, 30). The baseline history and physical ex- amination is requisite to the longitudinal study of brainstem function. Special attention should be given to the baseline neurologic exam and the assessment of cranial nerve, motor, sensory, and cerebellar function. Heart rate and blood pres- sure assessments are critical for patients with a prior history of surgery near the brainstem. A history of postoperative sei- zure, apnea, and neurogenic hypertension should be docu- mented, along with developmental progression for very young children. The same assessments should be repeated at regular intervals, with documentation of improving or worsening of symptoms. Longitudinal studies of brainstem effects should consider T1, T2, and diffusion-tensor imaging to evaluate the brainstem and white matter trajectories for signs of ischemia due to the combined effects of tumor and/or surgery and for structural alterations that might be used to predict late effect (6, 7). REFERENCES 1. Cancer Therapy Evaluation Program. Common Terminology Cri- teria for Adverse Events, Version 4.0. Publish Date: May 27, 2009. Available at: http://ctep.cancer.gov/protocolDevelopment/ electronic_applications/ctc.htm. 2. Luft AR, Skalej M, Schulz JB, et al. Patterns of age-related shrinkage in cerebellum and brainstem observed in vivo using three-dimensional MRI volumetry. Cereb Cortex 1999;9:712– 721. 3. Merchant TE, Chitti RM, Li C, et al. Factors associated with neurological recovery of brainstem function following postop- erative conformal radiation therapy in infratentorial ependy- moma. Int J Radiat Oncol Biol Phys 2010;76:496–503. 4. Klockgether T, Skalej M, Wedekind D, et al. Autosomal dom- inant cerebellar ataxia type I. MRI-based volumetry of posterior fossa structures and basal ganglia in spinocerebellar ataxia types 1, 2 and 3. Brain 1998;121:1687–1693. 5. Schoenfeld GO, Amdur RJ, Morris CG, et al. Patterns of fail- ure and toxicity after intensity-modulated radiotherapy for head and neck cancer. Int J Radiat Oncol Biol Phys 2008; 71:377–385. 6. Debus J, Hug EB, Liebsch NJ, et al. Brainstem tolerance to con- formal radiotherapy of skull base tumors. Int J Radiat Oncol Biol Phys 1997;39:967–975. 7. Debus J, Hug EB, Liebsch NJ, et al. Dosevolume tolerance of the brainstem after high-dose radiotherapy. Front Radiat Ther Oncol 1999;33:305–314. 8. Pollock BE, Gorman DA, Brown PD. Radiosurgery for arterio- venous malformations of the basal ganglia, thalamus, and brain- stem. J Neurosurg 2004;100:210–214. 9. Hoppe BS, Stegman LD, Zelefsky MJ, et al. Treatment of nasal cavity and paranasal sinus cancer with modern radio- therapy techniques in the postoperative setting—the MSKCC experience. Int J Radiat Oncol Biol Phys 2007; 67:691–702. 10. Foote KD, Friedman WA, Buatti JA, et al. Analysis of risk fac- tors associated with radiosurgery for vestibular schwannoma. J Neurosurg 2001;95:440–449. 11. Jian JJ, Cheng SH, Tsai SY, et al. Improvement of local control of T3 and T4 nasopharyngeal carcinoma by hyperfractionated radiotherapy and concomitant chemotherapy. Int J Radiat Oncol Biol Phys 2002;53:344–352. 12. Daly ME, Chen AM, Bucci MK, et al. Intensity-modulated radiation therapy for malignancies of the nasal cavity and paranasal sinuses. Int J Radiat Oncol Biol Phys 2007;67: 151–157. 13. Uy NW, Woo SY, Teh BS, et al. Intensity-modulated radiation therapy (IMRT) for meningioma. Int J Radiat Oncol Biol Phys 2002;53:1265–1270. 14. Wenkel E, Thornton AF, Finkelstein D, et al. Benign meningi- oma: partially resected, biopsied, and recurrent intracranial tu- mors treated with combined proton and photon radiotherapy. Int J Radiat Oncol Biol Phys 2000;48:1363–1370. S40 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 41. 15. Nishimura H,Ogino T, Kawashima M, et al. Proton-beam ther- apy for olfactory neuroblastoma. Int J Radiat Oncol Biol Phys 2007;68:758–762. 16. Noe¨l G, Habrand JL, Mammar H, et al. Combination of pho- ton and proton radiation therapy for chordomas and chondro- sarcomas of the skull base: The Centre de ProtonthZˇrapie D’Orsay experience. Int J Radiat Oncol Biol Phys 2001;51: 392–398. 17. Weber DC, Rutz HP, Pedroni ES, et al. Results of spot-scanning proton radiation therapy for chordoma and chondrosarcoma of the skull base: The Paul Scherrer Institut experience. Int J Ra- diat Oncol Biol Phys 2005;63:401–409. 18. Kased N, Huang K, Nakamura JL, et al. Gamma Knife radiosur- gery for brainstem metastases: The UCSF experience. J Neuro- oncol 2008;86:195–205. 19. Fuentes S, Delsanti C, Metellus P, et al. Brainstem metastases: Management using gamma knife radiosurgery. Neurosurgery 2006;58:37–42. 20. Maruyama K, Kondziolka D, Niranjan A, et al. Stereotactic ra- diosurgery for brainstem arteriovenous malformations: Factors affecting outcome. J Neurosurg 2004;100:407–413. 21. Clark BG, Souhami L, Pla C, et al. The integral biologically ef- fective dose to predict brainstem toxicity of hypo-fractionated stereotactic radiotherapy. Int J Radiat Oncol Biol Phys 1998; 40:667–675. 22. Freeman CR, Krischer JP, Sanford RA, et al. Final results of a study of escalating doses of hyperfractionated radiotherapy in brainstem tumors in children: a Pediatric Oncology Group study. Int J Radiat Oncol Biol Phys 1993;27:197–206. 23. Packer RJ, Boyett JM, Zimmerman RA, et al. Outcome of chil- dren with brainstem gliomas after treatment with 7800 cGy of hyperfractionated radiotherapy. A Children’s Cancer Group Phase I/II trial. Cancer 1994;74:1827–1834. 24. Packer RJ, Prados M, Phillips P, et al. Treatment of children with newly diagnosed brainstem gliomas with intravenous recombinant beta-interferon and hyperfractionated radiation therapy: A Chil- dren’sCancerGroupPhaseI/IIstudy.Cancer1996;77:2150–2156. 25. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 26. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 27. Flickinger JC, Kondziolka D, Lunsford LD. Radiobiological analysis of tissue responses following radiosurgery. Technol Cancer Res Treat 2003;2:87–92. 28. Meeks SL, Buatti JM, Foote KD, et al. Calculation of cranial nerve complication probability for acoustic neuroma radiosur- gery. Int J Radiat Oncol Biol Phys 2000;47:597–602. 29. JacksonA,YorkeED,RosenzweigKE.Theatlasofcomplications incidence: A proposal for a new standard for reporting the results of radiotherapy protocols. Semin Radiat Oncol 2006;16:260–268. 30. Pollock BE, Flickinger JC. A proposed radiosurgery-based grading system for arteriovenous malformations. J Neurosurg 2002;96:79–85. 31. Lorenzoni JG, Devriendt D, Massager N. Brain stem metastases treated with radiosurgery: prognostic factors of survival and life expectancy. Surg Neurol 2009;71:188–196. Radiation associated brainstem injury d C. MAYO et al. S41
- 42. QUANTEC: ORGAN SPECIFICPAPER Central Nervous System: Spinal Cord RADIATION DOSE–VOLUME EFFECTS IN THE SPINAL CORD JOHN P. KIRKPATRICK, M.D., PH.D.,* ALBERT J. VAN DER KOGEL, PH.D.,y AND TIMOTHY E. SCHULTHEISS, PH.D.z From the *Department of Radiation Oncology, Duke University Medical Center, Durham, NC; y Department of Radiation Oncology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; and z Department of Radiation Physics, City of Hope Cancer Center, Duarte, CA Dose–volume data for myelopathy in humans treated with radiotherapy (RT) to the spine is reviewed, along with pertinent preclinical data. Using conventional fractionation of 1.8–2 Gy/fraction to the full-thickness cord, the estimated risk of myelopathy is 1% and 10% at 54 Gy and 61 Gy, respectively, with a calculated strong dependence on dose/fraction (a/b = 0.87 Gy.) Reirradiation data in animals and humans suggest partial repair of RT-induced subclinical damage becoming evident about 6 months post-RTand increasing over the next 2 years. Reports of myelopathy from stereotactic radiosurgery to spinal lesions appear rare (1%) when the maximum spinal cord dose is limited to the equivalent of 13 Gy in a single fraction or 20 Gy in three fractions. However, long-term data are insufficient to calculate a dose–volume relationship for myelopathy when the partial cord is treated with a hypofractionated regimen. Ó 2010 Elsevier Inc. QUANTEC, Spinal cord, Myelopathy, Radiosurgery. CLINICAL SIGNIFICANCE The spinal cord consists of bundles of motor and sensory tracts, surrounded by the thecal sac, which is, in turn, encased by the spinal canal (1). Although the cord proper extends from the base of skull through the top of the lumbar spine, individ- ual nerves continue down the spinal canal to the level of the pelvis. Portions of the spinal cord are often included in radio- therapy (RT) fields for treatment of malignancies involving the neck, thorax, abdomen, and pelvis. In addition, metastatic disease to the bony spine, often requiring RT, is encountered in $40% of all cancer patients (2). Though rare, RT-induced spinal cord injury (i.e., myelopathy) can be severe, resulting in pain, paresthesias, sensory deficits, paralysis, Brown-Sequard syndrome, and bowel/bladder incontinence (3). In this analysis, we consider three clinical scenarios for the development of myelopathy following: (1) de novo irradiation of the complete spinal cord cross-section via conventionally fractionated external beam RT, (2) reirradiation of the complete spinal cord cross-section after a previous course of conventional external beam RT, and (3) irradiation of a partial cross-section of the cord using high-dose/fraction stereotactic radiosurgery. ENDPOINTS Herein, myelopathy is defined as a Grade 2 or higher myelitis, per Common Terminology Criteria for Adverse Events v3.0 (4). Asymptomatic changes in the cord detected radiographically or mild signs/symptoms such as Babinski’s sign or L’Hermitte syndrome are not classified as myelopathy for purpose of this analysis. Thus, a diagnosis of myelopathy is based on the appearance of signs/symptoms of sensory or motor deficits, loss of function or pain, now frequently con- firmed by magnetic resonance imaging. Radiation myelopa- thy rarely occurs less than 6 months after completion of radiotherapy and most cases appear within 3 years (5). In some situations, the question of recurrent tumor can con- found the diagnosis of RT-induced myelopathy. Magnetic res- onance imaging is useful in this regard with surgical resection/ biopsy as indicated for diagnosis and, potentially, therapy. CHALLENGES DEFINING VOLUMES In conventional external beam RT, the field generally encompasses the entire circumference of the cord, vertebral body, and spinal nerve roots at the treated levels. Thus, pre- cise organ definition is not critical in conventional RT apart from appropriately identifying the level of the involved cord. Delineation of the cord in body radiosurgery is unset- tled (6) with various studies contouring the critical organ in the axial plane as the spinal cord, the spinal cord +2–3 mm, the thecal sac and its contents, or the spinal canal. As the high-dose regions may extend superiorly and inferiorly to Reprint requests to: John P. Kirkpatrick, M.D., Ph.D., Depart- ment of Radiation Oncology, Duke University Medical Center, Box 3085, Durham, NC 27710. Tel: (919) 668-7342; Fax: (919) 668-7345; E-mail: jkirk@radonc.duke.edu Acknowledgment—Dr. Kirkpatrick has a research grant from Varian Medical Systems, Palo Alto, Ca. Received March 10, 2009, and in revised form April 17, 2009. Accepted for publication April 22, 2009. S42 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S42–S49, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.04.095
- 43. the target, severalstudies extend the critical organ volume above and below the target volume (e.g., 6 mm inferiorly and superiorly in the case of Henry Ford Hospital) (7). REVIEW OF DOSE–VOLUME DATA Preclinical studies A large number of small-animal studies have explored spi- nal cord tolerance to de novo radiation and reirradiation, in- cluding time-dependent repair of such damage. Several reports suggest regional differences in radiosensitivity across the spinal cord (8, 9). The clinical endpoint in most studies is paralysis, with the spinal cord showing nonspecific white matter necrosis. The pathogenesis of injury is generally believed to be primarily from vascular/endothelial damage, glial cell injury, or both (3, 9). Using focused protons, Bijl demonstrated large regional differences in rat spinal cord radiosensitivity (10, 11). There was a rightward shift in the dose–response curve from 21 Gy (ED50) with full thickness irradiation vs. 29–33 Gy for lateral cord treatment (wide and narrow geometry, respectively), and 72 Gy when only the central portion of the cord was treated. White matter necrosis was observed in all paralyzed rats, with none seen in animals not exhibiting paralysis. No damage was observed in central grey matter for doses up to 80 Gy. The differences in central vs. peripheral response were attributed to vascular density differences in these regions, with a potential role for differen- tial oligodendrocyte progenitor cell distribution. However, an alternative explanation may be functional differences in the cord white matter regions irradiated, especially given the clinical endpoint of paralysis, which would not be expected if sensory tracts were preferentially irradiated. No similar published reports are available in higher order species, mak- ing application of these findings to highly conformal radio- therapy techniques, such as stereotactic body RT (SBRT) or intensity-modulated proton therapy, difficult. Animal studies support a time-dependent model of repair for radiation damage to the spinal cord (12–17). For example, Ang (13) treated the thoracic and cervical spines of Rhesus monkeys to 44 Gy, and then reirradiated these animals with an additional 57 Gy at 1–2 years, or 66 Gy at 2–3 years, yield- ing aggregate doses of 101 and 110 Gy, respectively. The study endpoint was lower extremity weakness or balance dis- turbances at 2.5 years after reirradiation. Of 45 animals eval- uated at the end of the observation period, 4 developed endpoint symptoms. A reirradiation tolerance model devel- oped by combining these data with those of a prior study of single-dose tolerance in the same animal model (14) resulted in an estimated recovery of 34 Gy (76%), 38 Gy (85%), and 45 Gy (101%) at 1, 2, and 3 years, respectively. Under conservative assumptions, an estimated overall recovery of 26 Gy (61%) was calculated. De novo irradiation—conventional radiotherapy in humans A recent analysis used published reports of radiation mye- lopathy in 335 and 1,946 patients receiving radiotherapy to their cervical and thoracic spines, respectively (18). Although a few of these patients received relatively high doses/fraction, none were treated using stereotactic techniques to exclude a portion of the circumference of the cord. These data are summarized in Tables 1 and 2. Note that the dose to the cord is the prescribed dose reported in those studies; typi- cally, dosimetric data were not available to calculate the true cord dose. An a/b ratio of 0.87 Gy was estimated from the data and used to calculate the 2-Gy dose per fraction equivalent total dose for each regimen, as described in the following section. Note that this a/b ratio is less than the values of 2–4 Gy frequently encountered in the literature and predicts a more severe effect at larger doses per fraction. Reirradiation of the spinal cord In evaluating reirradiation of the spinal cord, one must not only consider the dose regimen for each course and the vol- ume and region (re)irradiated but also the time interval be- tween the courses of RT (35). Table 3 summarizes published reports involving reirradiation of the spinal cord using both conventional, full-circumference external beam RT and SBRT. For purposes of comparing different regi- mens, an a/b of 3 Gy was used to calculate the biologically equivalent dose in Gy3 and both a/b values of 1 and 3 Gy were employed to calculate the 2-Gy per fraction equivalent dose. In all of these studies, the median interval between Table 1. Summary of published reports of cervical spinal cord myelopathy in patients receiving conventional radiotherapy (18) Institution Dose (Gy) Dose/fraction (Gy) Cases of myelopathy/ total number of patients Probability of myelopathy* 2-Gy dose equivalenty Wake Forest (19) 60 2 1/12 0.090 60.0 65 1.63 0/24 0.000 56.6 Caen (5) 54 3 7/15 0.622 72.8 Brookhaven (20) 19 9.5 4/13 0.437 68.6 Florida (21) 47.5 1.9 0/211 0.000 45.0 52.5 1.9 0/22 0.000 49.8 60 2 2/19 0.118 60.0 Yugoslavia (22) 65 1.63 0/19 0.000 56.6 * Calculated using the percentage of patients experiencing myelopathy corrected for overall survival as a function of time by the method in (18). y Calculated using a/b = 0.87 Gy (18). Radiation dose-volume effects in the spinal cord d J. P. KIRKPATRICK et al. S43
- 44. courses was atleast 6 months and only a small number of cases were treated at intervals less than 6 months. Note that few cases of myelopathy are reported despite large cumula- tive doses, with essentially no cases of myelopathy observed for cumulative doses #60 Gy in 2-Gy equivalent doses. These data are consistent with the observations of post-RT repair observed in the animal models. SBRT of the spine in humans Published reports of radiation myelopathy from SBRT to the spine are summarized in Table 4. These studies include de novo RT alone, reirradiation alone, and combination of the two (mixed series.) FACTORS AFFECTING RISK Animal studies suggest that the immature spine is slightly more susceptible to radiation-induced complications and the latent period is shorter (13, 57–59). For example, Ruifrok (57) found that the 50% effect dose in 1-week-old rats was 19.5 Gy vs. 21.5 Gy in adult animals (p 0.05). The latency to complications increased from about 2 weeks after irradia- tion in the 1-week-old rats to 6–8 months in the adults (59). Although the ultimate white matter changes were the same in animals independent of age, vasculopathy increased with increasing age at irradiation (59) Though the literature on radiation-induced myelopathy is sparse, care should be exer- cised in irradiating the pediatric spine because of the increased sensitivity of the child’s developing central nervous system and bone to ionizing radiation (60) In rats, the use of various chemotherapy agents during ra- diotherapy has been shown to increase the radiosensitivity of the spinal cord. Administration of intrathecal ara-C (61) or in- traperitoneal fludarabine (62) immediately before irradiation of the spinal cord showed an enhanced effect on radiation-in- duced injury, yielding a dose modifying factor of 1.2–1.3. There are rare reports of radiation myelopathy at relatively low doses in human patients post chemotherapy (63–66). Dosimetry data are limited for this small number of cases and it is difficult to draw any absolute conclusions. Note that many chemotherapeutic agents are neurotoxic in their own right (67) and caution is advised in their concurrent use during irradiation of the central nervous system (68). MODELS Conventionally fractionated, full-circumference irradiation Using the data in Tables 1 and 2, Schultheiss (18, 69) es- timated the risk of myelopathy as a function of dose using a probability distribution model. In this model, the probabil- ity of myelopathy was derived from the data in Tables 1 and 2 adjusted for estimated overall survival (18). A good fit to the combined cervical and thoracic cord data was not possible and separate analyses were performed. For the cervical cord data, values of D50 = 69.4 Gy and a/b = 0.87 Gy were obtained with a Pearson c2 statistic of 2.1 for 5 degrees of freedom, providing a reasonable fit of the model as shown in Figure 1. The 95% confidence interval was 66.4 to 72.6 Gy for D50 and 0.54 to 1.19 Gy for a/b. At 2- Gy per fraction, the probability of myelopathy is 0.03% at 45 Gy and 0.2% at 50 Gy. However, the further one gets in the tail of the dose– response function, the more dependent the estimates become on the statistical distribution used to model this function. Because of the dispersion in thoracic data, it is not possible to obtain a good fit to the data. As shown in Figure 2, thoracic cord data points generally lie to the right of the dose–response curve for the cervical cord. This suggests that the thoracic cord is less radiation sensitive than the cervical cord. Table 2. Summary of published reports of thoracic spinal cord myelopathy in patients receiving conventional radiotherapy (18) Institution Dose (Gy) Dose/fraction (Gy) Cases of myelopathy/total number of patients Probability of myelopathy* 2-Gy dose equivalenty MCV (23) 45 3 1/16 0.093 60.7 MGH (24) 45 3 0/75 0.000 60.7 Abramson (25) 40 4 4/271 0.063 67.9 MUSC (26) 40 4 6/45 0.332 67.9 Leicester (27) 40 4 1/43 0.284 67.9 Iowa (28) 40 4 0/42 0.000 67.9 Mt. Vernon (29) 34.4 5.7 13/145 0.278 78.9 Norway (30) 38 3Â6 Gy + 5Â4 Gy 8/157 0.196 77.0 38 3Â6 Gy + 3Â4 Gy + 2Â2 Gy 9/230 0.151 67.4 Berlin (31) 66.2 2.45 8/142 0.256 76.5 Virginia (32) 40 5 x 4 Gy + 8 x 2.5 Gy 2/248 0.028 57.4 UK NIRC (33, 34) 18.4 9.2 3/524 0.032 64.5 39.8 3.06 2/153 0.062 54.5 * Calculated using the percentage of patients experiencing myelopathy corrected for overall survival as a function of time by the method in (18). y Calculated using a/b = 0.87 Gy (18). S44 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 45. Table 3. Summaryof published reports involving reirradiation of the spinal cord Institution Cases of myelopathy/ total patients Median F/U (months) BED, initial course, (Gy3) Median (Range) BED, reirradiation (Gy3) Median (range) Interval between courses (months) Median (range) Total BED (Gy3) Median (range) 2- Gy dose equivalent, a/b = 3 Gy Median (range) 2- Gy dose equivalent, a/b = 1 Gy Median (range) MSK (36) 0/37 8 60 (10–101) 16 5–50 19 (2–125) 79 (21–117) 47 (13–70) 51 (8–100) VU (37) 0/34 — — — 100 60 60 Munich (38, 39) 0/15 30 70 (34–83) 50 (38–83) 30 (6–96) 115 (91–166) 69 (54–100) 70 (48–107) Mayo (40) 4/54 4* 60 37 10 (1–51) 97 58 62 Cases with myelopathy 4 All 60 73y (29–115) 9 (5–21) 133 (109–175) 80 (65–105) 83 (69–89) Henry Ford (41) 0/1 60 75 72 144 147 88 86 UCI (42) 0/1 8 75 42 37 117 70 67 Ontario (43) 0/2 3–9 (40–56) (18–35) (8–20) (58–91) (35–57) (28–51) VU (44) 0/8 56 (29–78) 42 (36–83) 30 (4–152) 106 (65–159) 64 (39–96) 69 (48–93) Brescia (45) 0/5 168 47 (32–47) 55 (33–67) 24 (12–36) 94 (80–113) 57 (48–68) 56 (47–67) Hamburg (46) 0/62 12 29 (29–47) 29 (29–47) 6 (2–40) 69 (59–77) 41 (35–46) 53 (48–57) Melbourne (47) 0/6 15 All 73 36 (32–39) 15 106 (103–109) 63 (62–65) 66 (64–68) Princess Margaret (48) Cases with myelopathy 11/– 11 72 (28–96) 42 (14–86) 11 (2–71) 115 (100–138) 69 (60–83) 80 (65–94) Stereotactic body radiotherapy Korea (49) Case with myelopathy No myelopathy 1/3 1 2 24 (60–81) 81 60, 81 (64–154) 154 64, 90 (18–120) 18 54, 120 (145–235) 235 145, 150 (87–141) 141 87, 90 (98–179) 179 98,114 * Overall survival. y One patient received two courses of reirradiation, 1 received three courses. Radiationdose-volumeeffectsinthespinalcorddJ.P.KIRKPATRICKetal.S45
- 46. Table 4. Summaryof 9 published reports of spinal cord doses and myelopathy in patients receiving stereotactic radiosurgery Institution (ref.) Cases of myelopathy/total patients Total dose (Gy) Dose/fraction (Gy) Dose to cord (Gy) BED to cord (Gy3) Proportion of patients previously irradiated to involved segment of spine Stanford and Pittsburgh (50) 6/1075 12.5–25 5–25 Dmax: 3.6–30 Range: 24–141 Gy3 55% 25 12.5 Dmax: 26.2 Dmax: 141 20 10 Dmax: 19.2 Dmax: 81 21 10.5 Dmax: 13.9 Dmax: 46 24 8 Dmax: 29.9 Dmax: 129 20 2 Dmax: 8.5 Dmax: 33 20 20 Dmax: 10 Dmax: 43 Henry Ford (7) 1/86* 10–18 10–18 Mean Æ SD Dmax: 12.2 Æ 2.5 D1: 10.7 Æ 2.3 D10: 8.6 2.1 Maximum Dmax: 19.2 D1: 15.8 D10: 13 Mean Æ SD Dmax: 62 Æ 4.6 D1: 49 Æ 4.1 D10: 33 Æ 3.6 Maximum Dmax: 142 D1: 99 D10: 69 0% 18y 18 Mean Æ SD Dmax: 13.8 Æ 2.2 D1: 12.1 Æ 1.9 D10: 9.8 Æ 1.5 Mean Æ SD Dmax: 77 Æ 3.8 D1: 61 Æ 3.1 D10: 42 Æ 2.3 16 16 Dmax:14.8 D1: 13.0 D10: 9.6 Dmax:88 D1:69 D10: 40 Korea (49) 2/9 21–44 3–5 Median Dmax:32.9 D25:11.0 Range Dmax: 11–37 D25: 1.2–24 Median Dmax:106 D25:21 Range Dmax: 19–172 D25: 1–88 33% 30 10 Dmax: 35.2 D25: 15.5 Dmax:172 D25: 42 33 11 Dmax: 32.9 D25: 24.0 153 88 NYMC (51)z 3/31 Median: 10 Median: 5 Median: 6.0 12 Unknown 100 50 12 12 20 5 UCSF (52) 0/38 24 8 Median D0.1cc: 10.5 D1cc: 7.4 Median D0.1cc: 23 D1cc: 14 62% UCSF (53) 0/16 21 7 Median Dmax: 20.9 D0.1cc: 16.6 D1cc: 13.8 Range Dmax: 4.3–23 D0.1cc: 3.4–22 D1cc: 2.8–19 Median D0.1cc: 61 D1cc: 22 Range D0.1cc: 7–76 D1cc: 6–54 6% MDACC (54) 0/63 30 patients: 30 33 patients: 27 30 patients: 6 33 patients: 9 30 patients: 10 33 patients:9 30 patients: 16.7 33 patients: 18 56% Pittsburgh (55) 0/50 19 19 Mean Dmax: 10 Range Dmax: 6.5–13 Mean Dmax: 21 Range Dmax: 11–32 96% (Continued) S46 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 47. The applicability ofthe linear-quadratic model at high dose per fraction encountered in radiosurgery is controversial and the biologically equivalent doses calculated using a/b = 3 Gy in Table 4 are intended solely for roughly comparing reg- imens. In particular, it is not appropriate to extrapolate cord tolerance data obtained at a low dose per fraction to regimens using 10 Gy or more/fraction (70). SPECIAL SITUATIONS As discussed in detail previously, hypofractionation via radiosurgery is increasingly employed in the treatment of spinal lesions. Though reports of toxicity are rare, the fol- low-up time is short and patient numbers small. Caution should be observed in specifying the dose, taking special care to limit the dose to the cord by precise immobilization and image guidance. Predictions based on conventional frac- tionation should not be applied to such treatments without further careful study. The effect of concurrent chemotherapy is essentially unknown in that situation. RECOMMENDED DOSE–VOLUME LIMITS With conventional fractionation of 2 Gy per day including the full cord cross-section, a total dose of 50 Gy, 60 Gy, and $69 Gy are associated with a 0.2, 6, and 50% rate of myelop- athy. For reirradiation of the full cord cross-section at 2 Gy per day after prior conventionally fractionated treatment, cord tolerance appears to increase at least 25% 6 months after the initial course of RT based on animal and human studies. For partial cord irradiation as part of spine radiosurgery, a maximum cord dose of 13 Gy in a single fraction or 20 Gy in three fractions appears associated with a 1% risk of injury. Table 4. Summary of 9 published reports of spinal cord doses and myelopathy in patients receiving stereotactic radiosurgery (Continued) Institution (ref.) Cases of myelopathy/total patients Total dose (Gy) Dose/fraction (Gy) Dose to cord (Gy) BED to cord (Gy3) Proportion of patients previously irradiated to involved segment of spine Duke (56) 0/32 Median:18 Median: 7 Mean Æ SD Dmax: 14.4Æ2.3 D1: 13.1Æ2.2 D10: 11.5Æ2.1 Maximum Dmax: 19.2 D1: 17.4 D10: 15.2 Mean Æ SD Dmax: 46.0Æ13.2 D1: 39.0Æ10.8 D10: 31.2Æ8.1 Maximum Dmax: 78.3 D1: 59.1 D10: 46.5 58% All patients within that institutional series are shown in normal font; myelopathy cases shown in bold italics. * Patients surviving at least 1 year. y Results for subset of 39 lesions treated at Henry Ford Hospital with a single 18-Gy fraction. z For the NYMC data (51), the cord dose was calculated assuming that the total dose was delivered in two fractions. Although the cord dose for the patients developing myelopathy were not given in the paper, the total BED to the tumor for the 3 patients experiencing myelopathy was 53.3, 60, and $167 Gy3 vs. 50 Gy3 for patients without myelopathy. Fig. 1. The dose–response function for the myelopathy of the cervi- cal spinal cord and data points (,) derived from Table 1. The prob- ability of myelopathy was calculated from the data in Table 1, adjusted for estimated overall survival per (18). 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 40 50 60 70 80 Equivalent dose in 2-Gy fractions Probability Fig. 2. The dose–response function for myelopathy of the cervical cord (solid line) and data points for the thoracic spinal cord () de- rived from Table 2. The probability of myelopathy was calculated from the data in Tables 1 and 2, adjusted for estimated overall sur- vival per (18). Radiation dose-volume effects in the spinal cord d J. P. KIRKPATRICK et al. S47
- 48. FUTURE TOXICITY STUDIES Incases where it is appropriate to irradiate only a partial circumference of the cord (as in irradiation of vertebral body lesions) or spare the interior of the cord (epidural dis- ease), dose tolerance may be increased. SBRT, particularly using intensity-modulated RT techniques, appears well suited for that purpose, as it can be used to deliver con- cave-shaped RT dose distributions around organs at risk (56). Studies to better understand the importance of the spa- tial distribution of dose (and, hence, the utility of partial cir- cumferential sparing) would be useful. For SBRT of spinal lesions, multi-institutional data need to be carefully collected over several years’ time to better esti- mate the risk of acute and long-term toxicity. At a minimum, participating institutions should report detailed demograph- ics, current treatment factors (anatomic location of the target lesion, cord volume, number of vertebral segments involved, number of fractions, Dmax, D1, D10, D50, D0.1cc, and D1cc,), history of concurrent and prior therapies (including the time interval from, dose and fractionation of previous radio- therapy to the involved levels), and treatment-related toxic- ity, particularly neurologic deficits. Given the low frequency of neurologic deficits in patients receiving spinal radiotherapy, further animal studies de- signed to understand the relationship between dose, fraction- ation dose distributions, and time between treatment courses would be useful. TOXICITY SCORING We recommend that the Common Terminology Criteria for Adverse Events (version 3) be used to score both acute and late spinal cord injury. REFERENCES 1. Goetz C. Textbook of clinical neurology. 2nd ed. Chicago, IL: Saunders; 2003. 2. Klimo P, Jr., Thompson CJ, Kestle JR, et al. A meta-analysis of surgery versus conventional radiotherapy for the treatment of metastatic spinal epidural disease. Neuro Oncol 2005;7:64–76. 3. Schultheiss TE, Kun LE, Ang KK, et al. Radiation response of the central nervous system. Int J Radiat Oncol Biol Phys 1995; 31:1093–1112. 4. Cancer Therapy Evaluation Program, Common Terminology Criteria for Adverse Events, Version 3.0, DCTD, NCI, NIH, DHHS, March 31, 2003. Available online at: http://ctep. cancer.gov. Accessed August 31, 2008. 5. Abbatucci JS, DeLozier T, Quint R, et al. Radiation myelopathy of the cervical spinal cord. Time, dose, and volume factors. Int J Radiat Oncol Biol Phys 1978;4:239–248. 6. Saghal A, Larson D, Chang EL. Stereotactic body radiosurgery for spinal metastases: A critical review. Int J Radiat Oncol Biol Phys 2008;71:652–665. 7. Ryu S, Jin JY, Jin R, et al. Partial volume tolerance of the spinal cord and complications of single-dose radiosurgery. Cancer 2007;109:628–636. 8. Philippens ME, Pop LA, Visser AG, et al. Dose-volume effects in rat thoracolumbar spinal cord: The effects of nonuniform dose distribution. Int J Radiat Oncol Biol Phys 2007;69:204– 213. 9. Coderre JA, Morris GM, Micca PL, et al. Late effects of radia- tion on the central nervous system: Role of vascular endothelial damage and glial stem cell survival. Radiat Res 2006;166:495– 503. 10. Bijl HP, van Luijk P, Coppes RP, et al. Dose-volume effects in the rat cervical spinal cord after proton irradiation. Int J Radiat Oncol Biol Phys 2002;52:205–211. 11. Bijl HP, van Luijk P, Coppes RP, et al. Regional differences in radiosensitivity across the rat cervical spinal cord. Int J Radiat Oncol Biol Phys 2005;61:543–551. 12. Ang KK, van der Kogel AJ, van der Schueren E, et al. The effect of small radiation doses on the rat spinal cord: The concept of partial tolerance. Int J Radiat Oncol Biol Phys 1983;9:1487– 1491. 13. Ang KK, Price RE, Stephens LC, et al. The tolerance of primate spinal cord to re-irradiation. Int J Radiat Oncol Biol Phys 1993; 25:459–464. 14. Ang KK, Jiang GL, Feng Y, et al. Extent and kinetics of recov- ery of occult spinal cord injury. Int J Radiat Oncol Biol Phys 2001;50:1013–1020. 15. Knowles JF. The radiosensitivity of the guinea-pig spinal cord to X-rays: The effect of retreatment at one year and the effect of age at the time of irradiation. Int J Radiat Biol Relat Stud Phys Chem Med 1983;44:433–442. 16. Ruifrok AC, Kleiboer BJ, van der Kogel AJ. Repair kinetics of radiation damage in the developing rat cervical spinal cord. Int J Radiat Biol 1993;63:501–508. 17. Wong CS, Hao Y. Long-term recovery kinetics of radiation damage in rat spinal cord. Int J Radiat Oncol Biol Phys 1997; 37:171–179. 18. Schultheiss TE. The radiation dose-response of the human spi- nal cord. Int J Radiat Oncol Biol Phys 2008;71:1455–1459. 19. McCunniff AJ, Lliang MJ. Radiation tolerance of the cervical spinal cord. Int J Radiat Oncol Biol Phys 1989;16:675–678. 20. Atkins HL, Tretter P. Time-dose considerations in radiation my- elopathy. Acta Radiol Ther Phys Biol Gy 1966;5:79–94. 21. Marcus RB, Jr., Million RR. The incidence of myelitis after ir- radiation of the cervical spinal cord. Int J Radiat Oncol Biol Phys 1990;93:3–8. 22. Jeremic BJ, Djuric L, Mijatovic L. Incidence of radiation mye- litis of the cervical spinal cord at doses of 5500 cGy or greater. Cancer 1991;68:2138–2141. 23. Hazra TA, Chandrasekaran MS, Colman M, et al. Survival in carcinoma of the lung after a split course of radiotherapy. Br J Radiol 1974;47:464–466. 24. Choi NCH, Grillo HC, Gardiello M, et al. Basis for new strate- gies in postoperative radiotherapy of bronchogenic carcinoma. Int J Radiat Oncol Biol Phys 1980;6:31–35. 25. Abramson N, Cavanaugh PJ. Short-course radiation therapy in carcinoma of the lung. Radiology 1973;108:685–687. 26. Fitzgerald RH, Marks RD, Wallace KM. Chronic radiation myelitis. Radiology 1982;144:609–612. 27. Madden FJF, English JSC, Moore AK, et al. Split course radi- ation in inoperable carcinoma of the bronchus. Eur J Cancer 1979;15:1175–1177. 28. Guthrie RT, Ptacek JJ, Hjass AC. Comparative analysis of two regimens of split course radiation in carcinoma of the lung. Am J Roentgenol 1973;117:605–608. 29. Dische S, Warburton MF, Sanders MI. Radiation myelitis and survival in the radiotherapy of lung cancer. Int J Radiat Oncol Biol Phys 1988;15:75–81. 30. Hatlevoll R, Host H, Kaalhus O. Myelopathy following radio- therapy of bronchial carcinoma with large single fractions: A retrospective study. Int J Radiat Oncol Biol Phys 1983;9: 41–44. S48 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 49. 31. Eichhorn HJ,Lessel A, Rotte KH. Einfuss verschiedener Bestrahlungsrhythmen auf Tumor-und Normalgewebe in vivo. Strahlentheraphie 1972;146:614–629. 32. Scruggs H, El-Mahdi A, Marks RD, Jr., et al. The results of split-course radiation therapy in cancer of the lung. Am J Roent- genol Radium Ther Nucl Med 1974;121:754–760. 33. Macbeth FR, Bolger JJ, Hopwood P, et al. Randomized trial of palliative two-fraction versus more intensive 13-fraction radio- therapy for patients with inoperable non-small cell lung cancer and good performance status. Medical Research Council Lung Cancer Working Party [see comment]. Clin Oncol (R Coll Radiol) 1996;8:167–175. 34. Macbeth FR, Wheldon TE, Girling DJ, et al. Radiation myelop- athy: Estimates of risk in 1048 patients in three randomized trials of palliative radiotherapy for non-small cell lung cancer. The Medical Research Council Lung Cancer Working Party. Clin Oncol (R Coll Radiol) 1996;8:176–181. 35. Nieder C, Grosu AL, Andratschke NH, et al. Proposal of human spinal cord reirradiation dose based on collection of data from 40 patients. Int J Radiat Oncol Biol Phys 2005;61:851–855. 36. Wright JL, Lovelock DM, Bilsky MH, et al. Clinical outcomes after reirradiation of paraspinal tumors. Am J Clin Oncol 2006; 29:495–502. 37. Langendijk JA, Kasperts N, Leemans CR, et al. A phase II study of primary reirradiation in squamous cell carcinoma of head and neck. Radiother Oncol 2006;78:306–312. 38. Grosu AL, Andratschke N, Nieder C, et al. Retreatment of the spinal cord with palliative radiotherapy. Int J Radiat Oncol Biol Phys 2002;52:1288–1292. 39. Nieder C, Grosu AL, Andratschke NH, et al. Update of human spinal cord reirradiation tolerance based on additional data from 38 patients. Int J Radiat Oncol Biol Phys 2006;66: 1446–1449. 40. Schiff D, Shaw EG, Cascino TL. Outcome after spinal reirradia- tion for malignant epidural spinal cord compression. Ann Neu- rol 1995;37:583–5899. 41. Ryu S, Gorty S, Kazee AM, et al. Reirradiation of human cer- vical spinal cord. Am J Clin Oncol 2000;23:29–31. 42. Kuo JV, Cabebe E, Al-Ghazi M, et al. Intensity-modulated radiation therapy for the spine at the University of California, Irvine. Med Dosim 2002;27:137–145. 43. Bauman GS, Sneed PK, Wara WM, et al. Reirradiation of pri- mary CNS tumors. Int J Radiat Oncol Biol Phys 1996;36: 433–441. 44. Sminia P, Oldenburger F, Slotman BJ, et al. Re-irradiation of the human spinal cord. Strahlenther Onkol 2002;178: 453–456. 45. Magrini SM, Biti GP, de Scisciolo G, et al. Neurological dam- age in patients irradiated twice on the spinal cord: A morpho- logic and electrophysiological study. Radiother Oncol 1990; 17:209–218. 46. Rades D, Stalpers LJA, Veninga T, et al. Evaluation of five ra- diation schedules and prognostic factors for metastatic spinal cord compression. J Clin Oncol 2005;23:3366–3375. 47. Jackson MA, Ball DL. Palliative retreatment of locally recurrent lung cancer after radical radiotherapy. Med J Aust 1987;147: 391–394. 48. Wong CS, Van Dyk J, Milosevic M, et al. Radiation myelopa- thy following single courses of radiotherapy and retreatment. Int J Radiat Oncol Biol Phys 1994;30:575–581. 49. Gwak H-S, Yoo H-J, Youn S-M, et al. Hypofractionated stereo- tactic radiotherapy for skull base and upper cervical chordoma and chondrosarcoma: Preliminary results. Stereotact Funct Neurosurg 2005;83:233–243. 50. Gibbs IC, Patil I, Gerszten PC, et al. Delayed radiation-induced myelopathy after spinal radiosurgery. Neurosurg 2009;64(2 Suppl):A67–A72. 51. Benzil DL, Saboori M, Mogilner AY, et al. Safety and efficacy of stereotactic radiosurgery for tumors of the spine. J Neurosurg 2004;101(Suppl 3):413–418. 52. Sahgal A, Choua D, Amesa C, et al. Proximity of spinous/para- spinous radiosurgery metastatic targets to the spinal cord versus risk of local failure. Int J Radiat Oncol Biol Phys 2007;69:S243. 53. Sahgal A, Chou D, Ames C, et al. Image-guided robotic stereo- tactic body radiotherapy for benign spinal tumors: The Univer- sity of California San Francisco preliminary experience. Technol Cancer Res Treat 2007;6:595–604. 54. Chang EL, Shiu AS, Mendel E, et al. Phase I/II study of stereo- tactic body radiotherapy for spinal metastasis and its pattern of failure. J Neurosurg Spine 2007;7:151–160. 55. Gerszten PC, Burton SA, Welch WC, et al. Single-fraction radiosurgery for the treatment of spinal breast metastases. Can- cer 2005;104:2244–2254. 56. Nelson JW, Yoo DS, Wang Z, et al. Stereotactic body radiother- apy for lesions of the spine and paraspinal regions. Int J Radiat Oncol Biol Phys 2009;73:1369–1375. 57. Ruifrok AC, Kleiboer BJ, van der Kogel AJ. Radiation toler- ance of the immature rat spinal cord. Radiother Oncol 1992; 23:249–256. 58. Ruifrok AC, Kleiboer BJ, van der Kogel AJ. Radiation toler- ance and fractionation sensitivity of the developing rat cervical spinal cord. Int J Radiat Oncol Biol Phys 1992;24:505–510. 59. Ruifrok AC, Stephens LC, van der Kogel AJ. Radiation response of the rat cervical spinal cord after irradiation at differ- ent ages: Tolerance, latency and pathology. Int J Radiat Oncol Biol Phys 1994;29:73–79. 60. Friedman DL, Constine LS. Late effects of cancer treatment. In: Halperin EC, Constine LS, Tarbell NJ, Kun LE, editors. Pediat- ric radiation oncology. Philadelphia: Lippincott, Williams Wilkins; 2005. 61. Ruifrok AC, van der Kogel AJ. The effect of intraspinal cyto- sine arabinoside on the re-irradiation tolerance of the cervical spinal cord of young and adult rats. Eur J Cancer 1993;29A: 1766–1770. 62. Gre´goire V, Ruifrok AC, Price RE, et al. Effect of intra-perito- neal fludarabine on rat spinal cord tolerance to fractionated irra- diation. Radiother Oncol 1995;36:50–55. 63. Ruckdeschel JC, Baxter DH, McKneally MF, et al. Sequential radiotherapy and Adriamycin in the management of broncho- genic carcinoma: The question of additive toxicity. Int J Radiat Oncol Biol Phys 1979;5:1323–1328. 64. Bloss JD, DiSaia PJ, Mannel RS, et al. Radiation myelitis: A complication of concurrent cisplatin and 5-fluorouracil chemotherapy with extended field radiotherapy for carcinoma of the uterine cervix. Gynecol Oncol 1991;43:305–308. 65. Chao MW, Wirth A, Ryan G, et al. Radiation myelopathy following transplantation and radiotherapy for non-Hodgkin’s lymphoma. Int J Radiat Oncol Biol Phys 1998;41:1057–1061. 66. Seddon BM, Cassoni AM, Galloway MJ, et al. Fatal radiation myelopathy after high-dose busulfan and melphalan chemother- apy and radiotherapy for Ewing’s sarcoma: A review of the literature and implications for practice. Clin Oncol (R Coll Ra- diol) 2005;17:385–390. 67. Lee YY, Nauert C, Glass JP. Treatment-related white matter changes in cancer patients. Cancer 1986;57:1473–1482. 68. Schultheiss TE, Kun LE, Ang KK, et al. Radiation response of the central nervous system. Int J Radiat Oncol Biol Phys 1995; 31:1093–1112. 69. Schultheiss TE, Thames HD, Peters LJ, et al. Effect of latency on calculated complication rates. Int J Radiat Oncol Biol Phys 1986;12:1861–1865. 70. Kirkpatrick JP, Meyer JJ, Marks LB. The linear-quadratic model is inappropriate to model high-dose per fraction effects. Semin Radiat Oncol 2008;18:240–243. Radiation dose-volume effects in the spinal cord d J. P. KIRKPATRICK et al. S49
- 50. QUANTEC: ORGAN-SPECIFIC PAPERCentral Nervous System: Ear RADIATION THERAPY AND HEARING LOSS NIRANJAN BHANDARE, M.S.,* ANDREW JACKSON, PH.D.,y AVRAHAM EISBRUCH, M.D.,z CHARLIE C. PAN, M.D.,z JOHN C. FLICKINGER, M.D.,x PATRICK ANTONELLI, M.D.,jj AND WILLIAM M. MENDENHALL, M.D.* From the *Departments of Radiation Oncology and jj Otolaryngology, University of Florida College of Medicine, Gainesville, Florida; y Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY; z Department of Radiation Oncology, University of Michigan; and x Department of Radiation Oncology, University of Pittsburgh Medical Center A review of literature on the development of sensorineural hearing loss after high-dose radiation therapy for head- and-neck tumors and stereotactic radiosurgery or fractionated stereotactic radiotherapy for the treatment of vestibular schwannoma is presented. Because of the small volume of the cochlea a dose–volume analysis is not fea- sible. Instead, the current literature on the effect of the mean dose received by the cochlea and other treatment- and patient-related factors on outcome are evaluated. Based on the data, a specific threshold dose to cochlea for sen- sorineural hearing loss cannot be determined; therefore, dose–prescription limits are suggested. A standard for evaluating radiation therapy–associated ototoxicity as well as a detailed approach for scoring toxicity is presented. Ó 2010 Elsevier Inc. Radiotherapy, Sensorineural hearing loss, Ototoxicity, Auditory, Ear, QUANTEC. 1. CLINICAL SIGNIFICANCE Radiation therapy (RT) may damage the cochlea and/or acous- tic nerve, leading to sensorineural hearing loss (SNHL) (1–4), with resultant long-lasting compromise in the quality of life. This report focuses on RT-induced SNHL in adults who have received fractionated RT, stereotactic radiosurgery (SRS), and fractionated stereotactic RT (FSRT) for head- and-neck cancers and vestibular schwannomas (VS). 2. ENDPOINTS SNHL is traditionally defined as a clinically significant in- crease in bone conduction threshold (BCT) at the key human speech frequencies (0.5–4.0 kHz), as seen in pure-tone audi- ometry. However, reports of SNHL after fractionated RT vary in terms of: (a) the frequencies evaluated (e.g., 2 or 4 kHz alone (5,6) and/or pure tone average [PTA] of frequen- cies between 0.5–3.0 kHz) (7–9); (b) the control/standard used for comparison (e.g., pre-RT BCT of same ear (10) or post-RT BCT of the contralateral ear (5), or age-specific standard (4)); and (c) the change in BCT (DBCT) that is defined as clinically significant (e.g., 20 dB (5, 6), 15 dB (7, 8), 10 dB (5)). The de- gree ofhearing lossafterRTforhead-and-neckcancerisworse at higher frequencies, as presented in Figures 1a–c (5–8, 10– 12). Although early changes in hearing can be reversible, per- sistent hearing loss (HL) continues to increase with time (11). Selected studies on SNHL after head-and-neck radiation ther- apy are shown in Table 1. Hearing status after SRS for VS is evaluated using the Gardner-Robertson hearing grade (GRHG) scale, which in- cludes both PTA and speech discrimination scores (SDS) (13). HL after SRS for VS is commonly presented as pre- RT to post-RT variation in GRHG as: (a) pretreatment hearing preservation (HP) in terms of (i) serviceable hearing (SH), as hearing that is useful with or without a hearing aid, or (ii) mea- surable hearing (MH), as any hearing with detectable audio- metric responses; and (b) improvement or loss in hearing expressed as change in GRHG. Selected studies on the treat- ment of vestibular schwannomas are shown in Table 2. Acute SNHL has been reported after SRS (14), but not after fractionated RT. Hearing impairment has been reported within 3 to 24 months after single-fraction SRS (13, 15), with a median time to onset of 4 months (15, 16). Although it can occur as early as 3 months after completing fractionated RT, the median latency is 1.5–2.0 years (10, 11). 3. CHALLENGES DEFINING VOLUMES Computed tomography (CT)-magnetic resonance imaging fusion is helpful in defining the inner ear. Its small size and location (embedded deep in the temporal bone) make it chal- lenging to delineate on CT scans and requires the appropriate bone window, level, and image thickness (preferably Reprint requests to: William M. Mendenhall, M.D., PO Box 100385, Gainesville, FL 32610. Tel: (352) 265-0287; Fax: (352) 265-7045; E-mail: mendwm@shands.ufl.edu Conflict of interest: None. Received March 18, 2009, and in revised form April 23, 2009. Accepted for publication April 27, 2009. S50 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S50–S57, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.04.096
- 51. #1.0 mm). Thecochlea is a conical structure with its base resting anterior to the internal auditory canal and its apex pointed anteriorly, inferiorly, and laterally, toward the carotid artery. The vestibule is located posterior to the cochlea and lateral to the internal auditory canal. The internal auditory ca- nal is a readily apparent landmark for identification of the co- chlea and vestibule on CT (Figure 2). The volume of cochlea can be defined on axial CT images as the net volume defined by the bony labyrinth. In adults, the reported average volume of the cochlea using CT varies from 0.13 mL (range, 0.11– 0.15 mL) (17) to 0.56 mL (range, 0.15–0.91 mL) (5). 4. REVIEW OF DOSE–VOLUME DATA Standard fractionated RT for head-and-neck cancer A dose–volume analysis is impractical for the cochlea due to its small volume and the limitations associated with its de- lineation. Several studies have attempted to relate mean or median cochlear dose to persistent hearing loss (6, 10, 18). Pan (5) prospectively studied BCTs in 31 patients 1–36 months after unilateral RT with standard fractionation using changes seen in the contralateral ear as standard (0.25-8 kHz). DBCTs 10 dB were rarely seen unless the corre- sponding difference in mean cochlear dose was $45 Gy. The doses to the contralateral cochlea varied between 0.5 and 31.3 Gy (mean, 4.2 Gy). Honore (10) retrospectively estimated mean cochlear doses in 20 patients with head-and-neck cancer (1.8–4.3 Gy/frac- tion) and observed DBCT 7–79 months post-RT. Doses were reconstructed from patient-specific CT scans or proxy phantoms. A dose-response relationship was observed for DBCT 15 dB at 4 kHz, but not at other frequencies. Chen (6) retrospectively studied 22 patients treated with RT for nasopharyngeal cancer (with fraction sizes from 1.6–2.3 Gy and concurrent/adjuvant chemotherapy) and studied DBCT 12–79 months post-RT. A significant increase in hearing loss (DBCT of $20 dB at one frequency or $10 dB at two consecutive frequencies) was observed for all fre- quencies (0.5–4 kHz) when the mean dose received by the cochlea was 48 Gy. Van der Putten (12) retrospectively evaluated DBCT 2–7 years after RT in 21 patients with unilateral parotid tumors (fraction sizes 1.8–3.0 Gy). Using the contralateral ear as a control, SNHL (DBCT 15 db difference in $three fre- quencies between 0.25–12 kHz) was seen when mean doses received by the cochlea were 50 Gy. Oh (8) prospectively studied DBCTs (0.25–4 kHz) 3–12 months post-RT in 25 patients with nasopharyngeal cancer (fraction size 2 Gy). In this study, the inner ear doses were Fig. 1. Mean dose response for sensorineural hearing loss (SNHL) at (a): 4 kHz; (b): 0.5–2 kHz; and (c): all frequencies (0.25–12 kHz). Data from: Figure 3 of Chen et al. (6) (retrospective study; SNHL defined as a $20-dB increase in the bone-conduction threshold at $1 year; patients received concurrent and adjuvant cisplatin chemo- therapy); Figure 1 of Honore et al. (10) (retrospective study; SNHL defined as 20-dB increase in the bone-conduction threshold at $0.5– 6.5 years); Figure 2 of Pan et al. (5) (prospective study; SNHL de- fined as a 20-dB difference between bone-conduction thresholds for ipsilateral and contralateral ears at 1 year; doses are ipsilateral-ear mean doses minus contralateral-ear mean doses); Table 2 of Oh et al. (8) (prospective study; SNHL defined as a 15-dB increase in the bone-conduction threshold at 1 year; patients received neoadju- vant and concurrent cisplatin chemotherapy); Tables 1 and 2 of Kwong et al. (7) (prospective study; SNHL defined as a 15-dB in- crease in the bone-conduction threshold at 1 year; patients received neoadjuvant and concurrent chemotherapy; ears received the full prescription dose; prescriptions were converted to biologically ef- fective dose in 2 Gy fractions using a/b = 3 Gy); Fig 2 of van der Putten et al. (12) (retrospective study; SNHL defined as a 15-dB in- crease in the average of all pure-tone thresholds at 2–17 years). Hearing loss and the inner ear d N. BHANDARE et al. S51
- 52. high (63–70 Gy),and hearing loss (DBCT $15 db from base- line) was associated with total dose received by the inner ear. SRS for vestibular schwannomas Volume–length effect. A dose–volume analysis is not feasi- ble because of the small nerve diameter, lack of visibility on CT, and variable thickness. Nevertheless, the location and length of the cochlear nerve involved with tumor and the pre- scription/marginal tumor dose reflect the dose received by the cochlear nerve (16, 19). For example, the cochlear nerve may receivelessradiationifitliesonthetumorsurfacevs.ifitpasses through the core. SRS was found to be more likely to preserve hearing in patients with small VS (3 cm) vs. larger lesions (20). When SRS is used to treat intracanalicular VS with an ir- radiated nerve length of 4–12 mm, neither the tumor position in the canal (lateral vs. medial) nor the length of the nerve corre- lated with long-term hearing preservation. However, the mar- ginal/prescription dose to the tumor was significant as was the dose extending beyond the tumor volume inside the canal wasthemostimportantfactorresponsibleforcochlearnervein- jury in SRS patients (13). Intracanalicular tumor volume (100 mm3 vs. $100 mm3 ) and intracanalicular integrateddose (dose  volume) are also thought to influence hearing loss (21). Total dose effect. In one SRS study, patients receiving a mean maximum cochlear nucleus dose in the brain stem of 6.9 Gy and mean cochlear dose of 9.1 Gy retained useful hearing, whereas those in patients with hearing declines re- ceived 11.1 Gy and 7.8 Gy (22). In another study, serviceable hearing was preserved in 100% of the patients receiving mar- ginal tumor doses #14 Gy but dropped to 20% in those re- ceiving 14 Gy (13). Other studies noted increased hearing preservation with marginal tumor doses of 10–16 (vs. 25) Gy (23), and 12–14 (vs. 16–20) Gy (24, 25). 5. FACTORS AFFECTING RISK Treatment-related factors (1) The mean total dose to the cochlea during fractionated RT, or to the eighth cranial nerve in SRS for VS, is a dom- inant factor in post-RT hearing status (see Review of Dose–volume Data). (2) The effect of dose per fraction (# or 2.0 Gy) has not been thoroughly described. (3) The one study comparing once-daily vs. twice-daily frac- tionation observed no effect (4). Some studies suggest that the patients treated for VS with FSRT have a better chance of maintaining serviceable hearing when com- pared with those treated by SRS (23–25). Hypofractio- nated RT with four fractions of 5 Gy, or five fractions of 4 Gy, may have less toxicity than SRS in fractions of 10–12 Gy (26). (4) The possible synergistic toxicity of chemotherapy com- bined with RT has been studied prospectively (5, 7, 8, 11, 18), and retrospectively (4, 6, 10, 12). Cisplatin is known to cause hearing loss (24). Increased toxicity has been observed in patients treated with both adjuvant and concurrent cisplatin-RT (4, 6, 18). Low (18) reported results at 1 and 2 years after RT delivered with concur- rent and adjuvant cisplatin and found significant in- creases both in BCT at 4 kHz and in BCTs averaged over 0.5, 1, and 2 kHz. Conversely, no such increase has been seen in patients treated with neoadjuvant cis- platin followed by RT (i.e., without concurrent cis- platin/RT) (7, 8, 11). Patient-related factors (1) The rate of post-RT SNHL appears to increase with age (50) (4, 5, 7, 10, 11, 27). Grau (28) found a significant relationship between higher patient age and increased risk of hearing loss, but, when corrected for dose, the cor- relation disappeared. Higher rates of post-RT SNHL have been reported in males compared with females (7, 11). Other studies have not observed any difference in the incidence of SNHL between sexes or races (4). (2) Greater post-RT hearing losses (i.e., greater thresholds) have been associated with better pre-RT hearing (i.e., lower thresholds) (5, 10). (3) Post-RT otitis media has been associated with an in- creased risk of SNHL (4, 7, 11). (4) Compared with sporadic VS, VS secondary to neurofi- bromatosis (NF2) after SRS or FSRT exhibits lower hearing preservation and increased hearing deterioration (23, 29, 30). (5) Cerebral spinal fluid shunt has been suggested to increase the risk of HL after RT in children and perhaps adults (31). 6. MATHEMATICAL/BIOLOGICAL MODELS The values of TD5/5 = 60 Gy, TD50/5 = 70 for SNHL sug- gested by Emami (34) are not supported in the literature and Fig. 2. Axial computed tomography image through the skull base. EAC = external acoustic canal; C = cochlea; V = vestibule; IAC = internal auditory canal. S52 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 53. should not beutilized in treatment planning. Nevertheless, the information on dose–response modeling for post-RT SNHL remains limited. Pan (5) constructed a linear model demonstrating the dif- ferences between pre-RT and post-RT BCTs (corresponding to frequencies varying from 0.25 to 8 kHz) for the ipsilateral and contralateral ears and their association with relative dose scale, age, test frequency, and baseline (i.e., pre-RT) BCT and presented these differences in the form of nomograms. Because of its complexity, the details of the model cannot be presented here (5). In brief, hearing loss was found to de- pend on frequency tested, age, baseline hearing, and dose to inner ear. Honore (10) presented a logistic model of the probability of post-RT hearing loss $15 dB at 4 kHz, including only dose, which indicated that D50 = 48 Gy (95% confidence in- terval not reported) and g50 = 0.70 (range, 0.22–1.18). Ad- justing for patient age and pretreatment hearing level revealed a steeper dose-response curve with g50 = 3.4 (95% confidence interval, 0.3–6.5). Their multivariate logistic regression model is presented. P ¼ exp b0 þ X i bixi !, 1 þ exp b0 þ X i bixi !# (1) Where x1 = dose in Gy, x2 = pretreatment hearing thresh- old in dB, x3 = observation time in years, b0 = -24.9, b1 = 0.30 GyÀ1 (0.03–0.56), b2 = -0.44 dBÀ1 (-0.86–0.01), and b3 = 0.46 yearÀ1 (0.02–0.90) with a p value of 0.05. Honore (10) also modeled a post-RT increase in BCT at 4 kHz with multiple linear regressions. Dose, age, and pretherapeutic hearing level were significant (p 0.05), with the coefficients (95% confidence intervals): 0.31 (Æ0.15) dB/Gy, 0.53 (Æ0.21) dB/year, and -0.28 (Æ0.22) dB/dB, respectively. The constant shift in hearing level in this model, -21.6 (Æ11.2) dB, was relatively large. Chen (6) constructed linear models for post-RT changes in BCTs at frequencies between 0.5 and 4 kHz and found that dose was significant at all frequencies. In a multivariate linear model, RT dose, number of cycles of cisplatin, and time to post-RT hearing test were significant at 4 kHz. At 2 and 3 kHz, RT dose and time to posttreatment hearing test were sig- nificant. At 1 kHz, only RT dose was significant. In addition, hearing loss in the opposite ear was seen to be highly signif- icant, which may provide additional evidence of the toxicity of concurrent plus adjuvant cisplatin. Van der Putten (12) fitted an NTCP model to the incidence of asymmetrical SNHL (with a minimum of three frequencies from 0.25–12 kHz) as a function of mean dose to the ipsilat- eral inner ear and obtained D50 = 53.2 Gy with g50 of 2.74 and D10 = 42 Gy. The incidence of hearing loss at 4 and 2 kHz as reported by Honore (10), Chen (6), and Pan (5) are shown in Figures 1a and 1b. The data of Van der Putten (12), on hearing loss at combined frequencies, are shown for comparison in Figure 1c. The sources for these data and caveats concerning the comparisons implied by these plots are given in the figure legend. It is clear that the response seen by Pan (5) is consid- erably smaller than that seen by the other studies. This could be due to a number of factors, the most obvious being the rel- ative endpoint and relative dose scale used by Pan, and the influence of chemotherapy in Chen (6). However, the compli- cation rate seen by Honore (10) (in patients treated without chemotherapy) is of the same order as that of Chen (6). Flickinger (19) modeled the effects of minimum tumor dose Dmin and transverse tumor diameter (Td) with multivar- iate logistic regression analysis (equation 1) for the risk of acoustic neuropathy (defined as any variation in either PTA or SDS resulting in decline in GRHG for patients with at least Class IV hearing) in patients treated with SRS for VS in two datasets. The coefficients b1 (1/Gy) for Dmin were 0.166, 0.158 (with respective p = 0.00745, 0.1084; SEcoeff, 0.091, 0.097). The coefficients b2 (1/cm) for Td were 0.752, 0.818 (with respective p = 0.0079, 0.039; SEcoeff, 0.276, 0.276). The constants b0 were -4.57, -4.48 (with respective p = 0.0044, 0.0076; SEcoeff, 1.56, 1.64). In addition to the limited information on modeling SNHL, there remain several limitations in both prospective and retro- spective studies in the current literature, such as a relatively small number of patients, variation in the standard for HL, frequencies evaluated, and other approximations (e.g., the use of a proxy phantom in retrospective studies), thereby making the choice of any specific model for routine clinical utilization difficult. 7. SPECIAL SITUATIONS (1) Data on cisplatin-RT suggest that radiation doses to the cochlea should be strictly limited when delivered with cisplatin. (2) Data presented may not be applicable to fractionation schedules beyond the ranges studied. (3) Data presented in this review apply to adult patients only; for data on pediatric patients, see Hua et al. (32). (4) Data for hearing response after SRS or FSRT for spo- radic tumors may not be representative of the patients with VS secondary to NF2. 8. RECOMMENDED DOSE–VOLUME LIMITS (WHERE POSSIBLE WHILE RETAINING THE DESIRED TARGET COVERAGE) (1) For conventionally fractionated RT, to minimize the risk for SNHL, the mean dose to the cochlea should be lim- ited to #45 Gy (5, 6) (or more conservatively #35 Gy) (10). Because a threshold for SNHL cannot be deter- mined from the present data, to prevent SNHL the dose to the cochlea should be kept as low as possible. (2) For SRS for VS, the prescription dose should be limited to 12–14 Gy for hearing preservation(24, 25, 33). Hearing loss and the inner ear d N. BHANDARE et al. S53
- 54. Table 1. Selectedstudies for SNHL after head-and-neck radiation therapy Influence of variables on the outcome Author Number of patients in study Mean cochlear dose (Gy)/Rx dose (Gy) Dose per fraction (Gy) Chemoradiation (cisplatin based) Chemo-radiation Age Post-RT SOM Gender Time to hearing test Pre-RT hearing level Standard used for comparison Endpoint for SNHL (shift in BCT)/ frequencies (kHz) tested Prospective Grau et al., 1999 (28) 22 NS/60–68 2–2.81 No, RT alone — No* — — No No Same ear Nominal shifts in BCT (in dB) reported/ 0.5, 1.0, 2.0, 4.0 Kwong et al., 1996 (7) 132 NS/71.3–85 2–3.5/2y Yesz , neoadjuvant No Yesx Yes Yesjj Yes No Same ear 15/avg. of 0.5, 1, 2 15; 4 Ho et al., 1999 (11) 294 70–91y /59.9–70 2–3.5/2y Yesz , neoadjuvant No Yes — — Yes No Same ear 10/avg. of (0.5, 1, 2) 10; 4{ Oh et al., 2004 (8) 32 54.3–81.4/70 2 Yesz , neoadjuvant and concurrent No Yesz ** Yes Yesjj Yes — Same ear 15/avg. of (0.5, 1, 2) 15; 4 Pan et al., 2005 (5) 22 Ipsi:z 14.1–68.8 Contra:z 0.5–31.3/40–70 NS RT alone (18) Concurrent chemo. (4) — Yes — No No Yesyy Contralateral ear 20/0.25, 0.5, 1, 2{ , 4{ , 8 Low et al., 2006 (18) 115 NS/70 2 Yesz , concurrent and adjuvant Yes (4 kHz) — — — — — Same ear Nominal shifts in BCT (in dB) reported/4, avg. of (0.5, 1.0, 2.0) Retrospective Honore et al., 2002 (10) 20 7.1–68/ 50–68 2–4.3 No, RT alone — Yes — — No Yesyy Same ear 15/0.5, 1, 2, 4 20; 4{ Chen et al., 2006 (6) 22 28.4–70 1.6–2.34 Yes, concurrent and adjuvant Yes (4 kHz) No No — Yes No Same ear 20/0.5, 1, 2{ , 3, 4{ Van der Putten et al.,2006 (12) 52 29.2–77.3/50–70 1.8–3.0 No, RT alone — — — — — — Contralateral 15/0.25–12 for $3 of these frequencies Abbreviations: NS = not specified; AS = absolute shift in the hearing threshold reported; SOM = serous otitis media; RT = radiation therapy; CT = bone conduction threshold; db = decibels; SNHL = sensorineural hearing loss; Rx = prescription. * Dose and age component of HL separated. y Total doses calculated as BED in 2 Gy fractions, with a/b = 3 Gy. z The primary endpoint of a prospective clinical trial. x Older age found significant. jj Rate of HL male female. { Data for these endpoints reconstructed from figures for this paper. ** Younger age found significant. yy Better pre-RT hearing associated with worse post RT HL. S54I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010
- 55. (3) A suggestedhypofractionation schedule for VS, to pro- vide likely tumor control and preserve hearing, is a total prescription dose of 21–30 Gy in 3–7 Gy per fraction over 3–10 days, though data on this schedule are limited. 9. FUTURE TOXICITY STUDIES (1) Larger single and multi-institutional prospective trials utilizing pre- and posttreatment hearing tests are required to establish absolute hearing loss as a function of fre- quency and the absolute radiation dose received by each cochlea, and verify the reported observations re- garding SNHL after RT for head-and-neck cancers. (2) The response of SNHL to chemoradiation needs to be de- termined in prospective trials as a function of both cis- platin and radiation doses as well as chemo-regimen (neoadjuvant, concurrent, or adjuvant). (3) In the treatment of VS, the effects of fractionation (SRS vs. FSRT with standard fractionation and hypofractiona- tion), the location and length of the acoustic nerve rela- tive to the tumor, and doses received by it, require systematic prospective investigation. 10. TOXICITY SCORING Existing scoring systems (e.g., Radiation Therapy Oncol- ogy Group, Late Effects on Normal Tissues / Subjective, Ob- jective, Management and Analytic, National Cancer Institute Common Terminology Criteria for Adverse Events) have limitations. We make the following recommendations for coding toxicity. SNHL after fractionated RT for head-and-neck cancers (1) Hearing loss should be determined through pre- and post- RT audiometric evaluations of the same ear. In Table 2. Selected studies on the treatment of vestibular schwannomas Author and year No. of patients in study Marginal tumor dose (Gy)* Follow-up Tumor control (%) Hearing status (%) SRS Hirsch et al., 1988 (34) 126 18–25 Mean 4.7 y 86 HP: 26 Noren et al., 1993 (35) Total: 254 NF2: 61 18–20 10–15 1–17 y Unilateral:94 NF2: 84 HP: 22 Moderate HD: 55 Severe HD: 23 Foote et al., 1995 (36) 36 16–20 2.5–36 mo 100 HP (SH): 10 at 1 y 42 Æ 17 at 2 y Flickinger et al., 1996 (37) 273 CT: 118, MRI: 155 12–20 — 96.48 HL, MRI: 32 Æ 7 at 3 y HL, CT: 61 Æ 7 at 3 y Kondziolka et al., 1998 (38) 162 12–20 Mean: 16.6 6–102 mo (60% 5 y) 94 HP (SH): 47 HP (MH): 51 Lunsford et al., 1998 (39) 402 Earlier in series: 17 Later in the series: 12– 14 Mean: 36 mo 93 HP: 39 at 5 y HP: 68 at last 5 y Flickinger et al., 2001 (40) 190 11–18 Median: 13 Median: 30 mo Max: 80 mo 91 at 5 y HP:74 HI:7 FSRT/HP-FSRT Andrews et al., 2001 (23) GK-SRS: 64 (NF2: 5) FSRT: 46 (NF2: 10) GK-SRS:12 SRT: 50 (2 Gy/fx) GK-SRS: 119 Æ 67 weeks SRT: 115 Æ 96 weeks GK-SRS: 98 SRT: 97 HP, GK: 33 HP, SRT: 81 Williams et al., 2002 (41) 125 Tumors 3 cm: 25/5 fx Tumors $3 cm: 30/10 fx 1.0–5.7 y Median: 1.8 y 100 HP: 46 HL: 36 HI: 18 Meijer et al., 2003 (26) Total: 37 SRS:12 HPFSRT: 25 SRS: 10–12 HPFSRT: 20–25 12–61 mo Mean: 25 mo — HP: 91 Combs et al., 2005 (24) 106 FSRT: 57.6 (1.8 Gy/fx) 3–172 mo 94.3 at 3 y, 93 at 5 y HP: 94 at 5 y Abbreviations: SRS = stereotactic radiosurgery; SOM = Serous Otitis Media; HL = hearing loss; MRI = magnetic resonance imaging; BCT = bone conduction threshold; CT = computed tomography; SRT = stereotactic radiotherapy; NF2: neurofibromatosis type 2; FSRT = fractionated SRT; HPFSRT = hypofractionated SRT; HPRT = hypofractionation trial; GRHG = Gardener- Robertson Hearing Grade; HG = hearing grade; HP = hearing preservation corresponding either to serviceable hearing (SH; GRHG-I, II) or measurable hearing (MH; GRHG: III, IV); HD = hearing deterioration; HI = hearing improvement; NR = not reported; UH = useful hearing; GK = gamma knife; fx = fraction; y = year; mo = months. * Single fraction unless otherwise stated. Hearing loss and the inner ear d N. BHANDARE et al. S55
- 56. retrospective studies, ifpre-RT audiometric evaluations for the ipsilateral ears are not available, the contralateral ear may be preferable to an age-specific standard, but both should be viewed as substandard relative to pre- RT ipsilateral data. (2) To avoid transient post-RT hearing fluctuations, hearing should be tested starting 6 months post-RT and at least biannually thereafter. (3) SDS and four-frequency (0.5, 1.0, 2.0, and 3.0 kHz) bone conduction pure tone average should be used, as en- dorsed by the American Academy of Otolaryngology- Head and Neck Surgery Committee on Hearing and Equilibrium (9). (4) For high-frequency HL, 6 kHz bone conduction thresh- olds should be measured, because a) the basal turn of the cochlea (i.e., highest frequencies) are the first to be affected, b) 6 kHz is highest frequency bone conduction threshold measured with standard bone conducting trans- ducers, and c) bone conduction thresholds minimize the influence of concomitant middle and external ear pathol- ogy. (5) Additionally, a measurement at 4 kHz may facilitate comparison with the present datasets. (6) ‘‘Clinically significant hearing loss’’ should be consid- ered as an increase in the threshold of 10 dB in post- RT BCT, or a decline of 10% in an SDS evaluation, as assessed by an expert. (7) Clinically significant HL observed in two consecutive PTA evaluations is considered as persistent. Toxicity scoring after RT for VS (1) Preservation of pretreatment hearing level: (a) preserva- tion pre-RT GRHG I-IV hearing or (b) in pre-RT GRHG V patients, with no speech discrimination but testable PTA, a preservation of PTA scores. (2) SH (corresponding to GRHG I-II); commonly defined as PTA # 0 and SDS $50%. (3) MH is any hearing with detectable audiometric response. (4) Either an improvement or loss in hearing expressed as a change in GRHG. REFERENCES 1. Jereczek-Fossa BA, Zarowski A, Milani F, et al. Radiotherapy- induced ear toxicity. Cancer Treat Rev 2003;29:417–430. 2. Bhide SA, Harrington KJ, Nutting CM. Otological toxicity after postoperative radiotherapy for parotid tumours. Clin Oncol (R Coll Radiol) 2007;19:77–82. 3. Raaijmakers E, Engelen AM. Is sensorineural hearing loss a pos- sible side effect of nasopharyngeal and parotid irradiation? A sys- tematic review of the literature. Radiother Oncol 2002;65:1–7. 4. Bhandare N, Antonelli PJ, Morris CG, et al. Ototoxicity after ra- diotherapy for head and neck tumors. Int J Radiat Oncol Biol Phys 2007;67:469–479. 5. Pan CC, Eisbruch A, Lee JS, et al. Prospective study of inner ear radiation dose and hearing loss in head-and-neck cancer pa- tients. Int J Radiat Oncol Biol Phys 2005;61:1393–1402. 6. Chen WC, Jackson A, Budnick AS, et al. Sensorineural hearing loss in combined modality treatment of nasopharyngeal carci- noma. Cancer 2006;106:820–829. 7. Kwong DL, Wei WI, Sham JS, et al. Sensorineural hearing loss in patients treated for nasopharyngeal carcinoma: A prospective study of the effect of radiation and cisplatin treatment. Int J Ra- diat Oncol Biol Phys 1996;36:281–289. 8. Oh YT, Kim CH, Choi JH, et al. Sensory neural hearing loss af- ter concurrent cisplatin and radiation therapy for nasopharyn- geal carcinoma. Radiother Oncol 2004;72:79–82. 9. Committee on Hearing and Equilibrium. Committee on Hearing and Equilibrium guidelines for the evaluation of hearing preser- vation in acoustic neuroma (vestibular schwannoma). American Academy of Otolaryngology-Head and Neck Surgery Founda- tion, Inc. Otolaryngol Head Neck Surg 1995;113:179–180. 10. Honore HB, Bentzen SM, Moller K, et al. Sensori-neural hear- ing loss after radiotherapy for nasopharyngeal carcinoma: Indi- vidualized risk estimation. Radiother Oncol 2002;65:9–16. 11. Ho WK, Wei WI, Kwong DL, et al. Long-term sensorineural hearing deficit following radiotherapy in patients suffering from nasopharyngeal carcinoma: A prospective study. Head Neck 1999;21:547–553. 12. van der Putten L, de Bree R, Plukker JT, et al. Permanent uni- lateral hearing loss after radiotherapy for parotid gland tumors. Head Neck 2006;28:902–908. 13. Niranjan A, Lunsford LD, Flickinger JC, et al. Dose reduction improves hearing preservation rates after intracanalicular acous- tic tumor radiosurgery. Neurosurgery 1999;45:753–762. 14. Pollack AG, Marymont MH, Kalapurakal JA, et al. Acute neurological complications following gamma knife surgery for vestibular schwannoma. Case report. J Neurosurg 2005; 103:546–551. 15. Subach BR, Kondziolka D, Lunsford LD, et al. Stereotactic radiosurgery in the management of acoustic neuromas associ- ated with neurofibromatosis Type 2. J Neurosurg 1999;90: 815–822. 16. Linskey ME, Lunsford LD, Flickinger JC. Tumor control after stereotactic radiosurgery in neurofibromatosis patients with bi- lateral acoustic tumors. Neurosurgery 1992;31:829–838. 17. Pacholke HD, Amdur RJ, Schmalfuss IM, et al. Contouring the middle and inner ear on radiotherapy planning scans. Am J Clin Oncol 2005;28:143–147. 18. Low WK, Toh ST, Wee J, et al. Sensorineural hearing loss after radiotherapy and chemoradiotherapy: A single, blinded, ran- domized study. J Clin Oncol 2006;24:1904–1909. 19. Flickinger JC, Kondziolka D, Lunsford LD. Dose and diameter relationships for facial, trigeminal, and acoustic neuropathies following acoustic neuroma radiosurgery. Radiother Oncol 1996;41:215–219. 20. Pollock BE, Lunsford LD, Kondziolka D, et al. Outcome analysis of acoustic neuroma management: A comparison of microsurgery and stereotactic radiosurgery. Neurosurgery 1995;36:215–229. 21. Massager N, Nissim O, Delbrouck C, et al. Role of intracanalic- ular volumetric and dosimetric parameters on hearing preserva- tion after vestibular schwannoma radiosurgery. Int J Radiat Oncol Biol Phys 2006;64:1331–1340. 22. Paek SH, Chung HT, Jeong SS, et al. Hearing preservation after gamma knife stereotactic radiosurgery of vestibular schwan- noma. Cancer 2005;104:580–590. 23. Andrews DW, Suarez O, Goldman HW, et al. Stereotactic ra- diosurgery and fractionated stereotactic radiotherapy for the treatment of acoustic schwannomas: Comparative observations of 125 patients treated at one institution. Int J Radiat Oncol Biol Phys 2001;50:1265–1278. S56 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 57. 24. Combs SE,Volk S, Schulz-Ertner D, et al. Management of acoustic neuromas with fractionated stereotactic radiother- apy (FSRT): Long-term results in 106 patients treated in a single institution. Int J Radiat Oncol Biol Phys 2005; 63:75–81. 25. Williams J. Fractionated radiotherapy for acoustic neuromas. Congress of Neurological Surgeons: 50th Annual Meeting 2000. San Antonio, TX: 155. 26. Meijer OW, Vandertop WP, Baayen JC, et al. Single-fraction vs. fractionated linac-based stereotactic radiosurgery for vestib- ular schwannoma: A single-institution study. Int J Radiat Oncol Biol Phys 2003;56:1390–1396. 27. Moretti JA. Sensori-neural hearing loss following radiotherapy to the nasopharynx. Laryngoscope 1976;86:598–602. 28. Grau C, Overgaard J. Postirradiation sensorineural hearing loss: A common but ignored late radiation complication. Int J Radiat Oncol Biol Phys 1996;36:515–517. 29. Flickinger JC, Lunsford LD, Linskey ME, et al. Gamma knife radiosurgery for acoustic tumors: multivariate analysis of four year results. Radiother Oncol 1993;27:91–98. 30. Rowe JG, Radatz MW, Walton L, et al. Clinical experience with gamma knife stereotactic radiosurgery in the management of vestibular schwannomas secondary to type 2 neurofibromatosis. J Neurol Neurosurg Psychiatry 2003;74:1288–1293. 31. Merchant TE, Gould CJ, Xiong X, et al. Early neuro-otologic effects of three-dimensional irradiation in children with pri- mary brain tumors. Int J Radiat Oncol Biol Phys 2004;58: 1194–1207. 32. Hua C, Bass JK, Khan R, et al. Hearing loss after radiotherapy for pediatric brain tumors: Effect of cochlear dose. Int J Radiat Oncol Biol Phys 2008;72:892–899. 33. Flickinger JC, Kondziolka D, Niranjan A, et al. Acoustic neu- roma radiosurgery with marginal tumor doses of 12 to 13 Gy. Int J Radiat Oncol Biol Phys 2004;60:225–230. 34. Hirsch A, Noren G. Audiological findings after stereotactic ra- diosurgery in acoustic neurinomas. Acta Otolaryngol 1988;106: 244–251. 35. Noren G, Greitz D, Hirsch A, et al. Gamma knife surgery in acoustic tumors. Acta Neurochir Suppl (Wien) 1993;58:104–107. 36. Foote RL, Coffey RJ, Swanson JW, et al. Stereotactic radiosur- gery using the gamma knife for acoustic neuromas. Int J Radiat Oncol Biol Phys 1995;32:1153–1160. 37. Flickinger JC, Kondziolka D, Pollock BE, et al. Evolution in technique for vestibular schwannoma radiosurgery and effect on outcome. Int J Radiat Oncol Biol Phys 1996;36:275–280. 38. Kondziolka D, Lunsford LD, McLaughlin MR, et al. Long-term outcomes after radiosurgery for acoustic neuromas. N Engl J Med 1998;339:1426–1433. 39. Lunsford LD, Kondziolka D, Flickinger JC, et al. Acoustic neu- roma management: Evolution and revolution. In: Kondziolka D, editor. Radiosurgery. 2nd ed. Basel: Karger; 1998:1–7. 40. Flickinger JC, Kondziolka D, Niranjan A, et al. Results of acoustic neuroma radiosurgery: An analysis of 5 years’ experi- ence using current methods. J Neurosurg 2001;94:1–6. 41. Williams JA. Fractionated stereotactic radiotherapy for acoustic neuromas. Int J Radiat Oncol Biol Phys 2002;54:500–504. Hearing loss and the inner ear d N. BHANDARE et al. S57
- 58. QUANTEC: ORGAN-SPECIFIC PAPERHead and Neck: Parotid RADIOTHERAPY DOSE–VOLUME EFFECTS ON SALIVARY GLAND FUNCTION JOSEPH O. DEASY, PH.D.,* VITALI MOISEENKO, PH.D.,y LAWRENCE MARKS, M.D.,z K. S. CLIFFORD CHAO, M.D.,x JIHO NAM, PH.D.,z AND AVRAHAM EISBRUCH, M.D.{ *Department of Radiation Oncology, Washington University School of Medicine and Alvin J. Siteman Cancer Center, St. Louis, MO; y Department of Medical Physics, British Columbia Cancer Agency–Vancouver Cancer Center, Vancouver, BC, Canada; z Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC; x Department of Radiation Oncology, Columbia School of Medicine, New York, NY; { Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, MI Publications relating parotid dose–volume characteristics to radiotherapy-induced salivary toxicity were re- viewed. Late salivary dysfunction has been correlated to the mean parotid gland dose, with recovery occurring with time. Severe xerostomia (defined as long-term salivary function of 25% of baseline) is usually avoided if at least one parotid gland is spared to a mean dose of less than z20 Gy or if both glands are spared to less than z25 Gy (mean dose). For complex, partial-volume RT patterns (e.g., intensity-modulated radiotherapy), each parotid mean dose should be kept as low as possible, consistent with the desired clinical target volume coverage. A lower parotid mean dose usually results in better function. Submandibular gland sparing also significantly decreases the risk of xerostomia. The currently available predictive models are imprecise, and additional study is required to identify more accurate models of xerostomia risk. Ó 2010 Elsevier Inc. Xerostomia, salivary parotid glands, submandibular salivary glands, radiotherapy, dose–volume effects. 1. CLINICAL SIGNIFICANCE Radiotherapy (RT) is commonly used to treat head-and-neck tumors. In these treatments, the parotid, submandibular, and minor salivary glands are often incidentally irradiated. A re- duction in salivary function is a common toxicity and reduces the patient’s quality of life (QOL). Inadequate salivary func- tion (‘‘xerostomia’’) leads to multiple problems, including poor dental hygiene, a propensity to oral infections, sleep dis- turbances, oral pain, and difficulty chewing and swallowing. Stimulated salivary production is largely (60–70% of total) derived from the parotid glands, with the balance from other glands. Resting (unstimulated) salivary production is due pri- marily to the submandibular and sublingual glands and nu- merous small oral salivary glands (1). 2. ENDPOINTS Xerostomia can be defined according to the patient’s symptoms (e.g., altered taste or sensations of dryness) or quantified saliva production. Objective criteria include mea- sured salivary production at rest or stimulation and imaging endpoints. Observer-based, Common Terminology Criteria for Adverse Events, include the requirement for frequent drinks of water or diet alterations. Imaging endpoints include scintigraphy of parotid gland ejection fraction over a timed interval (2) and dynamic magnetic resonance imaging sialog- raphy of ductal flow (3). Salivary function is quantifiable. Grade 4 xerostomia is defined by the Late Effects Normal Tissue-Subjective, Objective, Management, Analytic (LENT-SOMA) scale as an objective reduction of $75% of baseline salivary func- tion. Whole mouth salivary function is typically assessed by asking the subject to produce as much saliva as possible within a given period (often 5 min). This can be performed in an unstimulated (at rest) or stimulated manner (in re- sponse to a salivary stimulant). However, salivary function measurements are uncertain and variable, with standard de- viations of z20–30% reported for whole mouth measure- ments (4). The patient-reported outcomes/QOL instruments used have included xerostomia-specific forms (5). Correlations between salivary flow and QOL have been inconsistent. Observer-based monitoring of xerostomia symptoms can underestimate the actual xerostomia symptoms compared with patient-reported symptoms (5). Because many reports of xerostomia after intensity-modulated RT have relied on observer-rated scores, the overall severity of xerostomia in recently published data might have been underestimated. Reprint requests to: Joseph O. Deasy, Ph.D., Department of Ra- diation Oncology, Washington University School of Medicine, 4921 Parkview Pl., St. Louis, MO 63110. Tel: (314) 362-1420; Fax: (314) 362-8521; E-mail: jdeasy@radonc.wustl.edu Partially funded by National Institutes of Health Grant R01 CA85181 (to J. O. Deasy) and Grant CA69579 (L. B. Marks) and by the American Association of Medical Physicists and the Ameri- can Society of Therapeutic Radiology. Conflict of interest: none. Received Feb 6, 2009, and in revised form June 8, 2009. Accepted for publication June 12, 2009. S58 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S58–S63, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.06.090
- 59. Damage Recovery A reductionin salivary function can begin within 1 week of the initiation of RT and usually persists afterward. Func- tion often gradually recovers within z2 years after RT (unless the radiation damage is too severe) (6, 7). Moreover, recovery overshoot (i.e., recovery to 100%) in salivary function can occur (8, 9). Braam et al. (10) reported that re- covery in parotid flow correlated significantly with a reduc- tion in patient-reported dry mouth symptoms. 3. CHALLENGES IN DEFINING VOLUMES Parotid and submandibular salivary glands can be ade- quately delineated on contrast-enhanced computed tomogra- phy images. However, irradiated parotid glands typically shrink during RT, presumably owing to cell loss. On the basis of weekly computed tomography scans of 15 patients, Robar et al. (11) reported little change in the medial parotid gland position during RT. However, the lateral edges shrank, on average, z1 mm/wk during RT (average displacements of 4–6 mm during the RT course), resulting in decreasing gland sparing 4. REVIEW OF DOSE–VOLUME DATA A variety of salivary endpoints have been correlated with the dosimetric dose–volume parameters, including subjective xerostomia and objective stimulated/unstimulated salivary flow. In particular, the mean parotid gland dose (6, 8, 9, 11) has been correlated with whole mouth or individual gland salivary production. Table 1 summarizes the reported dose– volume predictors for salivary flow, the incidence of compli- cations, and salivary function recovery. Minimal gland function reduction occurs at 10–15 Gy mean dose. Gland function reduction gradually increases at radiation doses of 20–40 Gy, with a strong reduction (usually by 75%) at 40 Gy (Fig. 1) (4, 6). Xerostomia risk is re- duced with sparing of at least one parotid gland or even one submandibular gland (12). In one study, patients receiv- ing 30 Gy to the contralateral parotid reported no or mild subjective xerostomia (13). Some recovery of function occurs with time, with the tis- sue dose required for a 50% response (TD50) increasing (i.e., more dose needed for the same level of injury) at longer follow-up times (Fig. 2) (8, 10, 12, 14–16). Figure 3 summa- rizes the existing published data regarding TD50 (dose result- ing in 50% incidence) for a reduction in stimulated saliva by 50–75% (2, 6, 10, 14–20). Whole mouth or ipsilateral sali- vary measurement-based TD50s tend to be lower than scin- tigraphy-based TD50s (z25–45 Gy). Consistent with this, the image-based data shown in Fig. 4 implies a greater TD50 compared with the salivary flow data in Fig. 1. The wide variation in the reported TD50 values is unexplained but could result from several factors, including differences in dose distributions, salivary measurement methods, seg- mentation, intragland sensitivity, and so forth. Table 1. Dosimetric predictors of xerostomia. Dose–volume parameters Investigator Patients (n)/follow-up (mo) Total prescribed target dose (Gy)* ‘‘Functional’’ endpoints assessed Unstimulated Stimulated Blanco et al. (6), 2005 55/6; 29/12 50–71y Stimulated saliva flowz Mean dose 25.8 Gyx Eisbruch et al. (7), 1999 88/1–12 58–72 Saliva flow, stimulated and unstimulated Mean dose #22–25 Gy{ Mean dose #25–26 Gyk V15 66% V30 43% V45 26% V15 67% V30 45% V45 24% Li et al. (9), 2007 142/1–24 60–75 Saliva flow; stimulated and unstimulated# Mean dose 25–30 Gy Mean dose 25–30 Gy Maes et al. (8), 2002 39/1–4 66–70** SEFyy ; stimulated flow, 99m Tc-pertechnetate scintigraphy Mean dose #20 Gyzz Abbreviations: Vx = percentage of gland volume receiving x Gy; 99m Tc = technetium-99 m; SEF = salivary excretion fraction; RT = radiotherapy. * All z1.8–2.0 Gy/fraction. y 1.5–1.8-Gy fractions in low-risk target volumes for intensity-modulated radiotherapy patients. z Grade 4 xerostomia using subjective, objective, management, analytic (SOMA) method; #25% of pretreatment level defined as event. x Mean dose to single parotid gland to reduce stimulated salivary flow from that gland to 25% of pre-RT saliva. { 24 Gy at 1 and 3 months, 22 Gy at 6 months, and 25 Gy at 12 months; threshold dose defined as mean dose above which saliva production appeared to abruptly approach 0. k 26 Gy at 1, 3, and 6 months, 25 Gy at 12 months; threshold dose defined as mean dose above which saliva production appeared to abruptly approach 0. # Predictors defined as mean doses below which efficient function recovery occurs with time, returning to pre-RT levels by 24 months. ** 66–70 Gy to primary tumor and pathologic nodes; 50–70 Gy to tumor bed if postoperatively; 46–50 Gy to elective nodes. yy SEF loss $50% defined as event. zz Corresponded to probability of 70% that SEF loss was 50%. Radiation-induced xerostomia d J. O. DEASY et al. S59
- 60. 5. FACTORS AFFECTINGRISK Non-dose–volume factors could affect the risk of xerosto- mia. Nondosimetric patient factors (e.g., gender and age) and the use of chemotherapy have typically not correlated with xerostomia risk. However, pretreatment salivary function and medications affecting salivary function can affect the risk of xerostomia. 6. MATHEMATICAL MODELING Several investigators have tried to fit dose, volume, and complication risk data to a sigmoidal response function. This mirrors the local function curve derived from imaging measurements (Fig. 4). The Lyman-Kutcher-Burman volume effect parameter, n, is typically set to 1, although the best-fit value of n has sometimes been reported to be either less (6) or greater (14) than 1. Chao et al. (4) fit stimulated whole mouth salivary function to a sum of two exponentials, representing contributions from both glands. Single gland function at 6 months was approximately given by exp(À0.054 Â mean gland dose) (2). This model neglects the known submandib- ular gland contributions, however, which might cause it to overestimate the reduction at low mean doses (mean dose, 15 Gy). More complicated models have shown only minor improvements (6). Consistent with this, patient-specific flow predictions using mean gland doses have significant uncer- tainties (21). The function of the parotid glands should be modeled separately, because the glands seem to respond in- dependently (Fig. 1). Fraction size effects on salivary function Detailed studies addressing fractionation have been lim- ited, with conflicting results. In rats, Franzen et al. (22) esti- mated the a/b ratio for early effects to be high, z20 Gy. The clinical Continuous hyperfractionated accelerated radiother- apy (CHART) experience has suggested that hyperfractiona- tion has a protective effect on late function, consistent with a low a/b ratio (23). However, in rhesus monkeys, acini cell number reduction at 16 weeks after RT was worse for CHART hyperfractionation than for conventional fraction- ation to a similar dose (24), consistent with a relatively high a/b ratio. Thus, it might be that acute effects have a high a/b ratio and late damage (dependent on stem cell recovery [25]) has a low a/b ratio. Possible intragland sensitivity variations Function and response are typically assumed to be uniform throughout the parotid gland. However, this might not be ac- curate. In rats (26), RT to the cranial half produced more functional loss than RT to the caudal half. This finding relates to the specific anatomy of the rat parotid gland, in which the saliva from the caudal part flows through the cranial part and is therefore affected by damage to the cranial ductules. Although human parotid gland anatomy is more complex, Fig. 1. Stimulated whole mouth salivary measurements vs. mean parotid gland dose. Summary of Washington University stimulated salivary results at 6 and 12 months of follow-up. Data showed that when either gland was spared (20 Gy mean dose), ratio of post-radiotherapy (RT) to pre-RT flow is usually 0.25. Note, if either gland was highly spared (10–15 Gy), resulting salivary function will usually be high, regardless of irradiation level of the other parotid gland (data originally presented in Blanco et al. [6], but redrawn here). Fig. 2. Mean percentage of reduction in stimulated salivary flow rate vs. mean parotid gland dose for different follow-up durations (8, 10, 12, 14, 15, 16). Follow-up durations of 1, 6, and 12 months represent ranges of 1–1.5, 6–7, and 12 months, respectively. Linear fits of data from different follow-up intervals shown. Dose–response effect appears present at all times, with shift of data to right with time, suggesting functional repair or regeneration. S60 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 61. it is possiblethat similar phenomena occur in humans, and this might be the cause of some of the variation in the reported mean dose TD50 values. 7. SPECIAL SITUATIONS Submandibular gland sparing can reduce the risk of both stimulated and unstimulated xerostomia (27). Jellema et al. (28) reported that the mean dose to the parotid glands and the mean dose to the submandibular glands were both se- lected on multivariate analysis for patient-reported xerosto- mia. A hypothetical patient receiving a mean dose of 30 Gy to the parotid glands was estimated to have the risk of xero- stomia decrease by z20% if the mean dose to the subman- dibular gland was 0 Gy compared with 50 Gy. Similarly, surgical transfer of the submandibular gland out of the high-dose radiation field was reported to spare z30% of pre- treatment stimulated salivary function (29). Regarding the dose response, Murdoch-Kinch et al. (30) reported that sub- mandibular gland-stimulated salivary function decreased sig- nificantly after a mean dose of 40 Gy. It is, therefore, not clear whether the parotid and submandibular glands have the same dose–volume response characteristics. The mean dose to the oral cavity (containing minor sali- vary glands) has been found to be an independent risk factor in some data sets (7) but not others (25), probably because of technique differences. The chemical modifier amifostine, is a radioprotector and has recently been shown to reduce the rates of xerostomia. Although quantitative data are sparse, Munter et al. (31) noted that amifostine significantly increased the combined parotid and submandibular gland tolerance dose for scinti- graphically measured clearance dysfunction, by a mean dose of approximately 9 Gy. 8. RECOMMENDED DOSE–VOLUME LIMITS Sparing at least one parotid gland appears to eliminate xe- rostomia (Fig. 1), and sparing at least one submandibular gland also appears to reduce xerostomia risk and increase stimulated and unstimulated salivary function. Some of the reduction in stimulated salivary function in Fig. 1 also re- sulted from consistently irradiated submandibular glands. Se- vere xerostomia (long-term salivary function 25% of baseline) can usually be avoided if at least one parotid gland has been spared to a mean dose of less than z20 Gy or if both glands have been spared to a mean dose of less than z25 Gy. For complex partial volume RT patterns (e.g., intensity- modulated RT), the mean dose to each parotid gland should be kept as low as possible, consistent with the desired clinical Fig. 4. Population-based dose vs. local function response (salivary function at rest) from imaging study by Buus et al. (2). Local func- tional decline in metabolic clearance of parotid salivary glands vs. local dose, according to voxel-by-voxel estimated time-activity curves of intravenously injected C11-methionine. Data points from 12 patients shown, along with best-fit curve and 95% confi- dence intervals of curve fit. Individual gland curves reported by Buus et al. (2) deviated significantly from this population average curve (reproduced from Buus et al. [2], used with permission.) This population curve demonstrated functional decline in salivary function even at low doses. Fig. 3. Reported tissue dose required for 50% response for loss of stimulated saliva flow after radiotherapy (RT) (2, 6, 10, 14–20) for single parotid gland. Endpoint considered in reports was salivary flow reduction to 25% (black symbols) or 50% (gray symbols) of pretreatment value. Tissue dose required for 50% response defined as dose at which 50% of patients developed complications. Error bars (if shown) indicate 95% confidence intervals; refer to original publications for exact meaning. 95% Confidence intervals for stud- ies by Munter et al. (19, 20) were estimated from standard errors provided. Lines connect points from data sets with measurements taken at more than one interval after radiotherapy. Most studies used salivary gland scintigraphy. Some studies measured physical production (ipsilateral salivary flow or whole salivary flow; marked with ‘‘I’’ or ‘‘W’’, respectively). Data from Buus et al. (2) (which did not include preradiotherapy assessments) derived by comparing different regions of parotid gland that had received different doses. Each label gives number of patients. Note, most imaging-derived endpoint data had greater values for tissue dose required for 50% re- sponse (TD50) than measured salivary data. CRT = conformal ra- diotherapy; IMRT = intensity-modulated radiotherapy. Radiation-induced xerostomia d J. O. DEASY et al. S61
- 62. target volume coverage.A lower mean dose to the parotid gland usually results in better function, even for relatively low mean doses (10 Gy). Similarly, the mean dose to the parotid gland should still be minimized, consistent with ade- quate target coverage, even if one or both cannot be kept to a threshold of 20 or 25 Gy. Published variations in re- sponse among different patient cohorts were probably related to the lack of an accurate model that correctly includes the ef- fects of multiple salivary glands and intragland sensitivity variations. When it can be deemed oncologically safe, sub- mandibular gland sparing to modest mean doses (35 Gy to see any effect) might reduce xerostomia symptoms. 9. FUTURE TOXICITY STUDIES To improve patient-specific predictions, several questions need additional research: 1. Whether partial sparing (achievable with intensity-modu- lated RT) of the submandibular glands or minor glands within the oral cavity will have a positive effect on pa- tients’ QOL 2. Whether the (arbitrary) 25% salivary threshold is the best quantitative measure with respect to the affects on patient QOL 3. Whether spatial/anatomic variations exist in the local radi- ation effect 4. Whether parotid gland shrinkage during RT should be explicitly accounted for in functional predictions 5. How submandibular sparing should be incorporated into predictive salivary function models 6. The quantitative effect on xerostomia of oral cavity sparing 7. The effect of the radioprotector amifostine on whole mouth salivary function 8. The reason imaging endpoints result in greater TD50 values than direct salivary measurements An overarching goal is the validation of an accurate predic- tive salivary function model. This will probably require com- bining multiple institutional or cooperative group data sets. 10. TOXICITY SCORING To best define xerostomia,we recommend that anobserver- based system (e.g., the Common Terminology Criteria for Adverse Events) be supplemented by a validated QOL mea- surement device (e.g., the XQ (xerostomia questionnaire) [7]) and/or salivary measurements (e.g., whole mouth-stimu- lated measurements). REFERENCES 1. Dawes C, Wood CM. The contribution of oral minor mucous gland secretions to the volume of whole saliva in man. Arch Oral Biol 1973;18:337–342. 2. Buus S, Grau C, Munk O, et al. Individual radiation response of parotid glands investigated by dynamic 11C-methionine PET. Radiother Oncol 2006;78:262–269. 3. Astreinidou E, Roesink JM, Raaijmakers CP, et al. 3D MR sialography as a tool to investigate radiation-induced xerosto- mia: Feasibility study. Int J Radiat Oncol Biol Phys 2007;68: 1310–1319. 4. Chao KSC, Deasy JO, Markman J, et al. A prospective study of salivary function sparing in patients with head-and-neck cancers receiving intensity-modulated or three-dimensional radiation therapy: Initial results. Int J Radiat Oncol Biol Phys 2001;49: 907–916. 5. Meirovitz A, Murdoch-Kinch C, Schipper M, et al. Grading xe- rostomia by physicians or by patients after intensity-modulated radiotherapy of head-and-neck cancer. Int J Radiat Oncol Biol Phys 2006;66:445–453. 6. Blanco AI, Chao KSC, El Naqa I, et al. Dose-volume modeling of salivary function in patients with head-and-neck cancer re- ceiving radiotherapy. Int J Radiat Oncol Biol Phys 2005;62: 1055–1069. 7. Eisbruch A, Kim KM, Terrell JE, et al. Xerostomia and its pre- dictors following parotid-sparing irradiation of head-and-neck cancer. Int J Radiat Oncol Biol Phys 2001;50:695–704. 8. Maes A, Weltens C, Flamen P, et al. Preservation of parotid function with uncomplicated conformal radiotherapy. Radio- ther Oncol 2002;63:203–211. 9. Li Y, Taylor J, Ten Haken R, et al. The impact of dose on pa- rotid salivary recovery in head and neck cancer patients treated with radiation therapy. Int J Radiat Oncol Biol Phys 2007;67: 660–669. 10. Braam PM, Roesink JM, Raaijmakers CP, et al. Quality of life and salivary output in patients with head-and-neck cancer five years after radiotherapy. Radiat Oncol 2007;2:3. 11. Robar JL, Day A, Clancey J, et al. Spatial and dosimetric variability of organs at risk in head-and-neck intensity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2007;68:1121–1130. 12. Saarilahti K, Kouri M, Collan J, et al. Sparing of the submandib- ular glands by intensity modulated radiotherapy in the treatment of head and neck cancer. Radiother Oncol 2006;78:270–275. 13. Portaluri M, Fucilli F, Castagna R, et al. Three-dimensional conformal radiotherapy for locally advanced (stage II and worse) head-and-neck cancer: Dosimetric and clinical evalua- tion. Int J Radiat Oncol Biol Phys 2006;66:1036–1043. 14. Roesink JM, Moerland MA, Battermann JJ, et al. Quantitative dose–volume response analysis of changes in parotid gland function after radiotherapy in the head-and-neck region. Int J Radiat Oncol Biol Phys 2001;51:938–946. 15. Roesink JM, Moerland MA, Hoekstra A. Scintigraphic assess- ment of early and late parotid gland function after radiotherapy for head-and-neck cancer: A prospective study of dose–volume response relationships. Int J Radiat Oncol Biol Phys 2004;58: 1451–1460. 16. Bussels B, Maes A, Flamen P, et al. Dose–response relation- ships within the parotid gland after radiotherapy for head and neck cancer. Radiother Oncol 2004;73:297–306. 17. Eisbruch A, Ten Haken R, Kim H, et al. Dose, volume, and function relationships in parotid salivary glands following con- formal and intensity-modulated irradiation of head and neck cancer. Int J Radiat Oncol Biol Phys 1999;45:577–587. 18. Munter MW, Karger CP, Hoffner SG, et al. Evaluation of sali- vary gland function after treatment of head-and-neck tumors with intensity-modulated radiotherapy by quantitative pertechne- tate scintigraphy. Int J Radiat Oncol Biol Phys 2007;58:175–184. 19. Munter MW, Hoffner S, Hof H, et al. Changes in salivary gland function after radiotherapy of head and neck tumors measured by quantitative pertechnetate scintigraphy: Comparison of in- tensity-modulated radiotherapy and conventional radiation ther- apy with and without amifostine. Int J Radiat Oncol Biol Phys 2007;67:651–659. S62 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 63. 20. Rudat V,Munter M, Rades D, et al. The effect of amifostine or IMRT to preserve the parotid function after radiotherapy of the head and neck region measured by quantitative salivary gland scintigraphy. Radiother Oncol 2008;89:71–80. 21. Deasy JO, Chao KSC, Markman J. Uncertainties in model- based outcome predictions for treatment planning. Int J Radiat Oncol Biol 2001;51:1389–1399. 22. Franzen L, Sundstrom S, Karlsson M, et al. Fractionated irradiation and early changes in noradrenaline induced potassium efflux(86Rb+)inratparotidgland.ActaOncol1992;31:359–364. 23. Leslie MD, Dische S. The early changes in salivary gland func- tion during and after radiotherapy for head and neck cancer. Ra- diother Oncol 1994;30:26–32. 24. Price RE, Ang KK, Stephens LC, et al. Effects of continuous hyperfractionated accelerated and conventionally fractionated radiotherapy on the parotid and submandibular salivary glands of rhesus monkeys. Radiother Oncol 1995;34:39–46. 25. Lombaert IM, Brunsting JF, Wierenga PK, et al. Rescue of sal- ivary gland function after stem cell transplantation in irradiated glands. PLoS ONE 2008;3:e2063. 26. Konings AW, Cotteleer F, Faber H, et al. Volume effects and region-dependent radiosensitivity of the parotid gland. Int J Ra- diat Oncol Biol Phys 2005;62:1090–1095. 27. Saarilahti K, Kouri M, Collan J, et al. Sparing of the subman- dibular glands by intensity modulated radiotherapy in the treat- ment of head and neck cancer. Radiother Oncol 2006;78:270– 275. 28. Jellema AP, Doornaert P, Slotman BJ, et al. Does radiation dose to the salivary glands and oral cavity predict patient-rated xerostomia and sticky saliva in head and neck cancer patients treated with curative radiotherapy? Radiother Oncol 2005;77: 164–171. 29. Seikaly H, Jha N, Harris JR, et al. Long-term outcomes of submandibular gland transfer for prevention of postradiation xerostomia. Arch Otolaryngol Head Neck Surg 2004;130: 956–961. 30. Murdoch-Kinch CA, Kim HM, Vineberg KA, et al. Dose–effect relationships for the submandibular salivary glands and impli- cations for their sparing by intensity modulated radiotherapy. Int J Radiat Oncol Biol Phys 2008;72:373–382. 31. Munter MW, Hoffner S, Hof H, et al. Changes in salivary gland function after radiotherapy of head and neck tumors measured by quantitative pertechnetate scintigraphy: Comparison of in- tensity-modulated radiotherapy and conventional radiation ther- apy with and without amifostine. Int J Radiat Oncol Biol Phys 2007;67:651–659. Radiation-induced xerostomia d J. O. DEASY et al. S63
- 64. QUANTEC: ORGAN-SPECIFIC PAPERHead and Neck: Larynx/Pharynx RADIATION DOSE–VOLUME EFFECTS IN THE LARYNX AND PHARYNX TIZIANA RANCATI, PH.D.,* MARCO SCHWARZ, PH.D.,y AARON M. ALLEN, M.D.,z FELIX FENG, M.D.,x ARON POPOVTZER, M.D.,z BHARAT MITTAL, M.D.,{ AND AVRAHAM EISBRUCH, M.D.x *Fondazione IRCCS-Istituto Nazionale dei Tumori, Milan, Italy; y Agenzia Provinciale per la Protonterapia, Trento, Italy; z Rabin Medical Center, Petah Tikvah, Israel; x University of Michigan, Ann Arbor, MI; { Northwestern University, Chicago, IL The dose–volume outcome data for RT-associated laryngeal edema, laryngeal dysfunction, and dysphagia, have only recently been addressed, and are summarized. For late dysphagia, a major issue is accurate definition and uncertainty of the relevant anatomical structures. These and other issues are discussed. Ó 2010 Elsevier Inc. Larynx, pharynx, dysphagia, radiotherapy, dose effect. 1. CLINICAL SIGNIFICANCE Radiotherapy (RT) is the primary modality allowing larynx preservation in patients with tumors in the upper aerodiges- tive tract. RT-induced laryngeal edema (due to inflammation and lymphatic disruption) is a common and expected side effect. Progressive edema and associated fibrosis can lead to long-term problems with phonation and swallowing (1). Since the primary goal of larynx preservation is speech and swallowing retention, RT-induced laryngeal dysfunction could undermine this therapeutic approach. In many in- stances, the larynx and pharynx are target structures and pur- posefully receive high radiation doses. Dysphagia is common after chemoradiotherapy of head- and-neck (HN) cancer. For example, patients included in the Radiation Therapy Oncology Group (RTOG) 91-11 trial were randomized to receive RT with or without concurrent cisplatin. The combined modality arm demonstrated im- proved tumor control rates (2). However, 1 year after therapy, 23% of the patients in the chemo-RT arm were unable to eat solid food compared with 9% who had undergone RT alone. Aspiration pneumonia associated with dysphagia after inten- sive chemo-RT has recently been reported (3). The topics reviewed in the present report are the subjects of current intensive research. This review examined key studies published through June 2008. A. LARYNX A2. Endpoints Larynx edema. Edema can be assessed using flexible fiberoptic examination. The grade of larynx edema can be scored according to the RTOG scale as follows: 0, no edema; 1, slight edema; 2, moderate edema; 3, severe edema; and 4, necrosis. Some degree of uncertainty is intrinsic to the sub- jectivity in the interpretation of ‘‘slight’’ and ‘‘moderate’’ in the RTOG scale. Grade 1 edema would correspond to ‘‘minimal’’ thickening of the epiglottis, aryepiglottic folds, arytenoids, and false cords. Grade 2 is a more diffuse and evident edema, although still without significant or symp- tomatic airway obstruction. Vocal function. Vocal function can be assessed objec- tively using instruments (e.g., videostroboscopy for direct visualization to assess supraglottic activity, vocal fold edge, amplitude, mucosal wave, phase symmetry, and glottic closure [4]; aerodynamic measurements of phonation time [5], or human observation [6]). Subjective assessments can be made with validated patient-focused questionnaires to assess various combinations of voice, eating, speech, and social function. A3. Challenges defining volumes The identification of the most important anatomic sites whose dose–volume parameters would primarily affect vocal function remains controversial. Dornfeld et al. (7) considered the dose points in various structures (e.g., base of tongue, epiglottis, lateral pharyngeal walls, pre-epiglottic space, aryepiglottic folds, false vocal cords, and upper esophageal sphincter) to be related to vocal injury. Sanguineti et al. (8) considered the larynx from the tip of the epiglottis superiorly to the bottom of the cricoid inferiorly; the external cartilage framework was excluded from the laryngeal volume. Because of the small size and close proximity of these structures, high-resolution, contrast-enhanced computed Reprint requests to: Avraham Eisbruch, M.D., Department of Ra- diation Oncology, University of Michigan Hospital, Ann Arbor MI 48109. Tel: (734) 936-9337; Fax: (734) 936-7370; E-mail: eisbruch@umich.edu Conflict of interest: none. Received Jan 13, 2009, and in revised form March 26, 2009. Accepted for publication March 27, 2009. S64 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S64–S69, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.03.079
- 65. tomography has beensuggested to facilitate accurate sub- structure definition. A4. Review of dose–volume data Laryngeal edema. Sanguineti et al. (8) found that neck stage, nodal diameter, mean laryngeal dose, and percentage of laryngeal volume receiving $30–70 Gy were all signifi- cantly associated with edema Grade 2 or greater on univariate analysis. On multivariate analysis, the mean laryngeal dose or percentage of volume receiving $50 Gy and neck stage were the only independent predictors. The investigators sug- gested that the percentage of volume receiving $50 Gy and the mean laryngeal dose should be kept as low as possible, ideally 27% and 43.5 Gy, respectively, to minimize the edema (i.e., 20% actuarial incidence at 1 year compared with 45% of patients receiving 44–57 Gy and 80% in patients receiving 57 Gy). Only a few of their patients received concurrent chemotherapy, which might have affected the dose–response relationships. A5. Vocal dysfunction Many studies have shown a good voice outcome after RT for Stage T1 laryngeal cancer (typically 60–66 Gy without chemotherapy). In the locally advanced setting, less informa- tion is available regarding voice quality after treatment. Dornfeld et al. (7) found a strong correlation between speech and doses delivered to the aryepiglottic folds, pre-epiglottic space, false vocal cords, and lateral pharyngeal walls at the level of the false vocal cords. In particular, they noted a steep decrease in function after 66 Gy to these structures. Their study was limited by not having full three-dimensional dose metrics. Fung et al. (5) evaluated the subjective and ob- jective parameters of vocal function. Changes in voice were related to doses to the larynx and pharynx and oral cavity. This suggests that saliva, pharyngeal lubrication, and soft tis- sue/structural changes within the surrounding musculature play an important role in voice function. A6. Factors affecting risk Locally advanced laryngeal cancer frequently causes voice dysfunction that might not improve, even if the cancer has been eradicated. This is one of the reasons patients presenting with marked laryngeal dysfunction might be advised to undergo laryngectomy, rather than a trial of chemo-RT. The addition of concurrent chemotherapy to high-dose RT at least doubles the risk of laryngeal edema and dysfunction. In contrast, RT without chemotherapy, delivered to small fields for Stage T1 glottic larynx cancer, usually results in excellent voice quality (9). A7. Mathematical/biologic models Rancati et al. (10) studied the same study population ana- lyzed by Sanguineti et al. (8). Using Grade 2-3 edema within 15 months after RT as an endpoint, 38 of 66 patients were available for analysis, and 21 of 38 experienced Grade 2-3 edema. Two normal tissue complication probability models were fitted using a maximum likelihood analysis: the Lyman-Kutcher-Burman model and the logit model with the dose–volume histogram reduced to the equivalent uniform dose (EUD).A significant volume effectwas found for edema, consistent with a prevalent parallel architecture of the larynx for this endpoint. Both normal tissue complication probability models fit the clinical data well. The relationship between the EUD and normal tissue complication probability can be de- scribed with n = 0.47 Æ 0.3, D50 (the dose causing 50% risk of complications). replace subsequent ‘‘TD50’’ mentions with ‘‘D50’’in all instances of 46.0Æ 1.85Gy, and asteepness parameter of k = 9.95 Æ 3.46 Gy. The best fit parameters for the Lyman-Kutcher-Burman were n = 0.45 Æ 0.28, m = 0.16 Æ 0.05, and TD50 of 46.3 Æ 1.8 Gy (Table 1). According to these findings, the investigators suggested an EUD of 30– 35 Gy to reduce the risk of Grade 2-3 edema. A8. Special situations and recommended dose–volume limits The exact correlation between voice abnormalities and the degree of laryngeal edema has not been assessed. Also, most studies have not considered pre-RT voice abnormalities (common with advanced lesions) and thus might have over- estimated the degree of RT-related damage. Nevertheless, to minimize the risks of laryngeal edema, it is recommended that the percentage of larynx volume receiving $50 Gy be #27% and the mean laryngeal dose #44 Gy. For model- based predictions, we recommend that the EUD be 30–35 Gy, with a volume parameter (n) of z0.45 (Table 2). A9. Recommendations Radiotherapy affects voice quality in locally advanced HN cancer but less so in early-stage larynx cancer. An interesting conclusion follows this observation: clinically significant vocal dysfunction requires both the larynx and surrounding supralaryngeal structures to be affected. The surrounding tis- sues might be indirectly affected by a reduction in salivary function or directly by effects on the intrinsic musculature and soft tissue. From the published data, it seems reasonable to suggest limiting the mean noninvolved larynx dose to 40–45 Gy and limiting the maximal dose to 63–66 Gy, if possible, according to the tumor extent. Table 1. Larynx edema: estimated parameter values for various NTCP models with their 1D-68% confidence intervals Model n LKB D50 m Rancati et al. (10) 46.3 Gy 0.16 0.45 SD 1.8 Gy 0.05 0.28 LOGEUD D50 k Rancati et al. (10) 46.0 Gy 9.95 0.47 SD 1.85 Gy 3.46 0.3 Abbreviations: NTCP = normal tissue complication probability; LKB = Lyman-Kurcher-Burman; D50 = dose causing 50% risk of complications; LOGEUD = log equivalent uniform dose. Dose–volume effects in larynx and pharynx d T. RANCATI et al. S65
- 66. A10. Future toxicitystudies and toxicity scoring Longitudinal studies consisting of objective scoring of laryngeal edema, voice quality, and patient-reported mea- sures are necessary to assess the intercorrelations among these measures. Such studies should include pretherapy as- sessments to account for tumor-related voice abnormalities and should concentrate on patients receiving concurrent chemo-RT who are at the greatest risk of laryngeal toxicity. B. DYSPHAGIA B2. Endpoints Objective evaluation: instrumental assessment. Video- fluorography includes modified barium swallow and esopha- gography to visualize the oral, pharyngeal, and esophageal phases of swallowing (11). Additional instrumental assessors include manometry and functional endoscopic evaluation of swallowing. Subjective evaluation: observer-assessed. Common Ter- minology Criteria for Adverse Events (CTCAE) are fre- quently used to assess acute toxicity, as is the RTOG/ European Organization for Research and Treatment of Can- cer criteria and the Subjective Objective Management Analytic (SOMA) scale. None of these tools has been tested for its validity in measuring dysphagia. Patient-reported quality of life. Various instruments have been developed to assess the quality of life (QOL) of patients with HN cancer, all of which include questions about swal- lowing dysfunction. Although these instruments all measure some aspects of HN cancer-related QOL, it is not clear which best applies to the assessment of swallowing dysfunctions. All the HN-specific QOL instruments include domains or few questions related to dysphagia. Although each instrument as a whole has been tested for validity, similar tests of the spe- cific dysphagia-related questions have not been performed. B3. Challenges defining volumes Swallowing is complex and involves voluntary and invol- untary stages coordinated through several cranial nerves and muscles (12). Because of this complexity, defining the most important anatomic structures whose dose–volume parame- ters would have a major effect on dysphagia has been difficult and only recently studied. Eisbruch et al. (13) noted ana- tomic/functional changes in pharyngeal constrictors and glot- tic/supraglottic larynx after intensive chemo-RT and explained the post-RT abnormalities in objective swallowing assessments (13, 14). The definition of the pharyngeal con- strictors in their study was somewhat different from the def- inition of the constrictors by Levandag et al. (15). Nevertheless, both groups found significant correlations be- tween the constrictor doses and dysphagia endpoints. Other studies have demonstrated the importance of specific ana- tomic points in the glottic (7) and supraglottic larynx (16) or pharynx (7). Fua et al. (17) noted that the glottic larynx doses were associated with dysphagia in patients who had re- ceived high doses to the larynx. Thus, most studies demon- strated relevance to various dysphagia endpoints of the doses to the glottic and supraglottic larynx and to specific points in the pharynx, notably the pharyngeal constrictors. B4. Review of dose–volume data Laryngopharyngeal disorders resulting in late dysphagia and aspiration are not specific and can result from edema and/or fibrosis of various structures (Table 3). In a prospective study using intensity-modulated RT to reduce dysphagia, Feng et al. (14) demonstrated the dose–volume relationship for swallowing structures in 36 patients treated with chemo- radiotherapy. A strong correlation was observed between the mean doses and the dysphagia endpoints (Fig. 1). Aspiration was observed when the mean dose to the pharyngeal constric- tors was 60 Gy and the dose–volume threshold for the percentage of volume receiving $40, $50, $60, and $65 Gy was 90%, 80%, 70%, and 50%, respectively. For aspira- tion to occur, the glottic/supraglottic larynx dose–volume threshold was a percentage of volume receiving $50 Gy of 50%. In a retrospective study, Jensen et al. (16) found that doses 60 Gy to the supraglottic area, larynx, and upper esophageal sphincter resulted in a low risk of aspiration. Because their study used conventional radiation fields, it is likely that the lack of correlation between the pharyngeal doses and dysphagia was related to the relative uniformity among the patients in the doses delivered to these structures. Table 2. Larynx toxicity: summary of dose–volume relationship and constraints above which toxicity is significantly increased Investigator/patients (n) Critical organs Predictive dose–volume parameter Endpoint Dornfeld et al. (7)/27 patients* Aryepiglottic folds, pre-epiglottic space, false vocal cords, lateral pharyngeal walls Point dose 68 Gy Vocal function Sanguineti et al. (8)/66 patientsy Larynx V50 27%; mean dose 43.5 Gy Laryngeal edema (fiberoptic examination) Rancati et al. (10)/38 patientsz Larynx EUD 30–35 Gy (n = 0.45) Laryngeal edema (fiberoptic examination) Abbreviation: EUD = equivalent uniform dose. * Twenty-two of 27 patients who received chemotherapy plus radiotherapy. y Twelve of 66 patients received chemotherapy plus radiotherapy. z Seven of 38 patients received chemotherapy plus radiotherapy. S66 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 67. Table 3. Organsat risk and dose–volume relationship above which swallowing dysfunction increases significantly Dose–volume data Investigator/patients (n) Critical organs Mean dose (Gy) Median dose (Gy) V50 V60 V65 Endpoint Evaluation method Eisbruch et al. (13), Feng et al. (14)/36 patients IMRT + chemotherapy Larynx PC PC 60 66 50% 80% 85% — 70% 70% — 50% 60% Aspiration Aspiration Stricture VF Caglar (19)/96 patients IMRT + chemotherapy Larynx IC 48* 54 21% 51% Aspiration and stricture VF Doornaert et al. (18)/81 patients RT + chemotherapy Pharyngeal mucosa and constrictors 45 QOL RTOG/EORTC C30 and H/N 35 O’Meara et al. (20)/148 patients 2D-RT plus chemotherapy Pharyngoesophageal inlet 50 Grade 3 plus pharyngoesophageal dysfunction RTOG late Toxicity Levandag et al. (15)/81 patients 3D-CRT/IMRT plus brachytherapy + chemotherapy Superior and middle constrictors 55 Grade 3 EORTC PSS–HN MDADI RTOG QOL QOL Dornfeld et al. (7)/27 patients IMRT + chemotherapy Aryepiglottic fold False cord Lateral pharyngeal Wall near false cord 50 Diet score HN QOL Weight loss PEG tube QOL Clinical assessment Jensen et al. (16)/25 patients 3D-CRT RT alone Larynx/upper esophageal sphincter 60 Aspiration QOL EORTC QOL FEES Abbreviations: V50, V60, V65 = percentage of volume receiving $50, $60, $65 Gy; IMRT = intensity-modulated radiotherapy; PC = pharyngeal constrictors; IC = inferior constrictor; VF = videofluoroscopy; RTOG = Radiation Therapy Oncology Group; 2D-RT = two-dimensional radiotherapy; 3D-CRT = three-dimensional conformal radiotherapy; EORTC = European Organization for Research and Treatment of Cancer; C30 and H/N 35 = EORTC questionnaire modules; PSS–HN = performance status scale for head-and-neck cancer patients; MDADI = M. D. Anderson Dysphagia Inventory; HN = head and neck; QOL = quality of life; PEG = percutaneous endoscopic gastrostomy; FEES = functional endoscopic evaluation of swallowing. * No correlation with stricture formation. Dose–volumeeffectsinlarynxandpharynxdT.RANCATIetal.S67
- 68. Dornfeld et al.(7) reported that swallowing difficulties and the type of diet tolerated worsened progressively with radiation doses 50 Gy to the aryepiglottic folds, false vocal cords, and lateral pharyngeal walls near the false cord. Levandag et al. (15) reported on patients with oropharyn- geal carcinoma treated with three-dimensional conformal RT or intensity-modulated RT with or without brachyther- apy plus chemotherapy. The use of brachytherapy, which reduces the doses to some of the pharyngeal tissues, signif- icantly reduced patient-reported dysphagia. A significant correlation was observed between the mean dose to the superior and middle pharyngeal constrictor muscles and patient complaints of severe dysphagia. A median dose of 50 Gy predicted a 20% probability of dysphagia. This prob- ability increased significantly beyond a mean dose of 55 Gy, with an increase of 19% associated with each additional 10 Gy to the superior and middle constrictors. Doornaert et al. (18) reported a steep dose–effect relationship beyond 45 Gy to the pharyngeal wall and concluded that a mean dose of 45 Gy is the optimal threshold dose for predicting swallowing difficulties. Similar findings were reported in retrospective series by Caglar et al. (19) and O’Meara et al. (20). A paucity of dose–volume data is available on hypophar- yngeal/upper esophageal stricture in HN cancer patients treated with RT plus chemotherapy. Laurell et al. (21) recom- mended a mean dose of 65 Gy to the first 2 cm of proximal esophagus and a mean dose of 60 Gy to the first 5 cm of proximal esophagus as the tolerance dose below which the incidence of esophageal stricture is low. Caglar et al. (19) found that the volume of the larynx or the inferior constrictor receiving 50 Gy was associated with strictures. B5. Factors affecting risk Supportive measures during RT could affect long-term dysphagia. Rosenthal et al. (22) and Mekhail et al. (23) suggested that a nasogastric feeding tube decreases the need for esophageal dilation vs. a percutaneous endoscopic gastrostomy tube. They hypothesized that the nasogastric tube serves as a stent to prevent stricture formation. Amifos- tine (WR 2721) is the most commonly used cytoprotector for reducing the incidence of xerostomia and mucositis (24). However, no data are available to support its role in decreas- ing late swallowing disorders. B6. Mathematical/biologic models The relative paucity of dose–volume data relates to the questions regarding the most important anatomic structures whose dysfunction after chemo-RT causes dysphagia. Data indicating that the pharyngeal constrictors and the larynx are the most likely candidates have been very recently pub- lished, and additional data are being gathered (Table 3). At present, modeling suggests that 50% normal tissue complica- tion probability is observed at mean doses of 50–60 Gy to these structures (Fig. 1). The limitations of these models in- clude treatment variables, the most important of which is con- current chemotherapy, and variations in tumor locations and pretherapy dysphagia, which have been accounted for in very few studies (14). The need to consider pretherapy dysphagia is especially important in laryngeal cancer, in which the rates of pretherapy dysphagia and aspirations are high, and tumor regression after chemo-RT might actually reduce the rate of frank aspiration (25). This could confound the results of retrospective dose–effect studies that do not take into account pretherapy findings. B7. Special situations Much of the data considered in the present review con- cern patients who underwent RT with either relatively sim- ple techniques or intensity-modulated RT approaches that did not explicitly aim at sparing dysphagia-related ana- tomic structures. Thus, high doses were delivered to these structures, and drawing strict dose–volume constraints or volume–effect parameters is far from trivial. In addition, high doses to the larynx, for example, are expected in cases of laryngeal or hypopharyngeal cancers, which are associated with high rates of pre-RT dysphagia and/or aspiration, confounding evaluations of post-RT dose– effect relationships. B8. Recommended dose–volume limits The limited available data have suggested that minimizing the volume of the pharyngeal constrictors and larynx receiv- ing $60 Gy and reducing, when possible, the volume receiv- ing $50 Gy is associated with reduced dysphagia/aspiration. In several cases, such sparing can be achieved without com- promising target doses (13, 14). A separate question is whether such sparing is safe clinically, taking into account the uncertainties in target delineation. This issue was beyond the scope of this report. B9. Future toxicity studies Late dysphagia is often a consequential effect of acute mu- cositis. Careful assessment and reporting of the severity of acute mucositis might shed light on the likelihood of late dys- phagia and its predictors and whether successful reduction in 0 10 20 30 40 50 60 70 80 90 100 20 25 30 35 40 45 50 55 60 65 70 75 80 Mean dose to supraglottic larynx (Gy) Calculatedaspirationprobability(%) Feng et al. Jensen et al logit curve D50=57.5Gy, k=6.57 Fig. 1. Dose–effect relationship for dysphagia according to data from Feng et al. (14) and Jensen et al. (16). Solid line fit to combined data; dotted line fit to 68% confidence area for normal tissue compli- cation probability-logit curve. S68 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 69. acute dysphagia wouldlead to improvements in late swallow- ing abnormalities. Validation of assessors of dysphagia The most commonly used observer-rated dysphagia grad- ing tool is the CTCAE dysphagia item, which has not been validated formally. Similarly, multiple patient-reported QOL instruments have been used, as detailed in the present report, and few have formally been validated regarding their dysphagia components. The issue of what are the most important anatomic structures and substructures whose damage is the likely cause of dysphagia is the subject of current research by many inves- tigators. An important aspect of this research is the effects of the tumor on pretherapy swallowing and on the functional re- sults after therapy. To capture these effects, prospective stud- ies that have included pretherapy evaluations are essential. B10. Toxicity scoring As detailed, prospective evaluation is critical because of tumor-related dysphagia and aspiration, particularly in patients with advanced cancer. Although CTCAE-based scoring is simple and commonly applied, the evidence of ‘‘silent aspiration’’ after RT (aspiration not eliciting a cough owing to a laryngeal sensory deficit) requires objective mea- surement using imaging and interpretation by professional speech/language pathologists. In addition, an objective swallow assessment might help quantify the swallowing assessments. Correlating observer-rated scores such as the CTCAE system, patient-reported scores, and objective swal- lowing dysfunction is recommended for future focused stud- ies. Until more data regarding this issue are available, we recommend the use of the CTCAE system, as well as a patient-reported QOL instrument, for large-scale clinical studies of chemo-RT for HN cancer. REFERENCES 1. Fung K, Yoo J, Leeper HA, et al. Effects of head and neck ra- diation therapy on vocal function. J Otolaryngol 2001;30: 133–139. 2. Forastiere AA, Goepfert H, Maor M, et al. Concurrent chemo- therapy and radiotherapy for organ preservation in advanced la- ryngeal cancer. N Engl J Med 2003;349:2091–2098. 3. Eisbruch A, Lyden T, Bradford CR, et al. Objective assessment of swallowing dysfunction and aspiration after radiation concur- rent with chemotherapy for head and neck cancer. Int J Radiat Oncol Biol Phys 2002;53:23–28. 4. Hirano M. Clinical examination of voice. In: Arnold GE, Winkel F, Wyke BD, editors. Disorders of human communica- tion. New York: Springer-Verlag; 1981. p. 81–84. 5. Fung K, Yoo J, Leeper A, et al. Vocal function following radi- ation for non-laryngeal versus laryngeal tumors of the head and neck. Laryngoscope 2001;111:1920–1924. 6. Hocevar-Boltezar I, Zargi M, Strojan P. Risk factors for voice quality after radiotherapy for early glottic cancer. Radiother Oncol 2009;93:524–529. 7. Dornfeld K, Simmons JR, Karnell L, et al. Radiation doses to structures within and adjacent to the larynx are correlated with long-term diet and speech-related quality of life. Int J Radiat Oncol Biol Phys 2007;68:750–757. 8. Sanguineti G, Adapala P, Endres EJ, et al. Dosimetric predictors of laryngeal edema. Int J Radiat Oncol Biol Phys 2007;68:741–749. 9. Fu KK, Woofhouse RJ, Quivey JM, et al. The significance of laryngeal edema following radiotherapy of carcinoma of the vocal cord. Cancer 1982;49:6555–6558. 10. Rancati T, Sanguineti G, Fiorino C. NTCP modeling of sub- acute/late laryngeal edema scored by fiberoptic examination: evidence of a large volume effect. Int J Radiat Oncol Biol Phys 2007;69(Suppl. 3):S409–S410. 11. Kendall KA, McKenzie SW, Leonard RJ, et al. Timing of events in normal swallowing: A videofluroscopic study. Dys- phagia 2000;15:74–84. 12. Logemann J. Mechanism of normal and abnormal swallowing. In: Cummings JW, Flint PW, Haughey BA, et al., editors. Otolaryn- gology: head and neck surgery. 5th ed. St. Louis: Mosby; 2008. 13. Eisbruch A, Schwartz M, Rasch C, et al. Dysphagia and aspira- tion after chemoradiotherapy for head and neck cancer: Which anatomic structures are affected and can they be spared by IMRT? Int J Radiat Oncol Biol Phys 2004;60:1425–1439. 14. Feng FY, Kim HM, Lyden TH, et al. Intensity-modulated radio- therapy of head and neck cancer aiming to reduce dysphagia: Early dose–effect relationships for the swallowing structures. Int J Radiat Oncol Biol Phys 2007;68:1289–1298. 15. Levandag PC, Teguh DN, Voet P, et al. Dysphagia disorders in patients with cancer of the oropharynx are significantly affected by the radiation therapy dose to the superior and middle constrictor muscle: A dose–effect relationship. Radiother Oncol 2007;85:64–73. 16. Jensen K, Lambertsen K, Grau C. Late swallowing dysfunction and dysphagia after radiotherapy for pharynx cancer: Fre- quency, intensity, and correlation with dose and volume param- eters. Radiother Oncol 2007;85:74–82. 17. Fua TF, Corry J, Milner AD, et al. Intensity-modulated radio- therapy for nasopharyngeal carcinoma: Clinical correlation of dose to the pharyngoesophageal axis and dysphagia. Int J Radiat Oncol Biol Phys 2007;67:976–981. 18. Doornaert P, Slotman BJ, Rietveld DHF, et al. The mean radi- ation dose in pharyngeal structures is a strong predictor of acute and persistent swallowing dysfunction and quality of life in head and neck radiotherapy [Abstract]. Int J Radiat Oncol Biol Phys 2007;69(Suppl):55. 19. Caglar HB, Allen AM, Othus M, et al. Dose to the larynx pre- dicts for swallowing complications following IMRT and che- motherapy. Int J Radiat Oncol Biol Phys 2008;72:1110–1118. 20. O’Meara EA, Machtay M, Moughan J, et al. Association between radiation doses to pharyngeal regions and severe late toxicity in head and neck cancer patients treated with concurrent chemoradiotherapy—An RTOG analysis [Abstract]. Int J Radiat Oncol Biol Phys 2007;69(Suppl):54. 21. Laurell G, Kraepelien T, Mavroidis P, et al. Stricture of the proximal esophagus in head and neck carcinoma patients after radiotherapy. Cancer 2003;97:1693–1700. 22. Rosenthal DI, Lewin JS, Eisbruch A. Prevention and treatment of dysphagia and aspiration after chemoradiation for head and neck cancer. J Clin Oncol 2006;24:2636–2643. 23. Mekhail TM, Adelstein DJ, Rybicki LA, et al. Enteral nutrition during the treatment of head and neck carcinoma: Is percutane- ous endoscopic gastrostomy tube preferable to a nasogastric tube? Cancer 2001;91:1785–1790. 24. Brizel DM, Wasserman TH, Henke M, et al. Phase 3 random- ized trial of amifostine as a radioprotector in head and neck cancer. J Clin Oncol 2000;18:3339–3345. 25. Langerman A, MacCracken E, Kasza K, et al. Aspiration in chemoradiated patients with head and neck cancer. Arch Oto- laryngol Head Neck Surg 2007;133:1289–1295. Dose–volume effects in larynx and pharynx d T. RANCATI et al. S69
- 70. QUANTEC: ORGAN-SPECIFIC PAPERThorax: Lung RADIATION DOSE–VOLUME EFFECTS IN THE LUNG LAWRENCE B. MARKS, M.D.,* SOREN M. BENTZEN, D.SC.,y JOSEPH O. DEASY, PH.D.,z FENG-MING (SPRING) KONG, M.D., PH.D.,x JEFFREY D. BRADLEY, M.D.,z IVAN S. VOGELIUS, PH.D.,y ISSAM EL NAQA, PH.D.,z JESSICA L. HUBBS, M.S.,* JOOS V. LEBESQUE, M.D., PH.D.,jj ROBERT D. TIMMERMAN, M.D.,{ MARY K. MARTEL, PH.D.,# AND ANDREW JACKSON, PH.D.** *Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC; y Department of Human Oncology, University of Wisconsin School of Medicine, Madison, WI; z Department of Radiation Oncology, Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO; x Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; jj Department of Radiation Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands; { Department of Radiation Oncology, University of Texas Southwestern, Dallas, TX; # Department of Radiation Physics, M. D. Anderson Cancer Center, Houston, TX; and **Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY The three-dimensional dose, volume, and outcome data for lung are reviewed in detail. The rate of symptomatic pneumonitis is related to many dosimetric parameters, and there are no evident threshold ‘‘tolerance dose– volume’’ levels. There are strong volume and fractionation effects. Ó 2010 Elsevier Inc. Lung injury, Radiation, QUANTEC, Pneumonitis. 1. CLINICAL SIGNIFICANCE Radiotherapy (RT) plays an important role in the treatment of several tumors in and around the thorax. Clinically significant symptomatic radiation pneumonitis (RP) occurs in approxi- mately 5–50%, 5–10%, and 1–5% of patients irradiated for cancers of the lung, mediastinal lymphatics, and breast, re- spectively (1, 2), and is one of the most common clinical tox- icities in these patients. The risk of RP limits the delivered dose for some and may thus hamper tumor control. A large fraction of patients experience subclinical RT-induced injury (e.g., reductions in formal pulmonary function tests and/or ra- diologic changes) that may be chronic and reduce the patient’s reserve to deal with future cardiopulmonary stresses. 2. ENDPOINTS Several endpoints can be used to define RT-induced lung injury (Table 1). In the context of quantitative analysis of nor- mal tissue effects in the clinic (QUANTEC), consideration is limited to the endpoint of symptoms—arguably the most clinically meaningful endpoint for patients. Approximately 80% of RP is clinically manifest within 10 months of RT. The scoring of symptomatic RP presents several challenges: (1) Dyspnea is nonspecific and can also be caused by, for example, anemia, cardiac arrhythmia, infection, and tumor. In a prospective clinical study, 28% of patients suspected of having RP also had ongoing medical conditions confounding the diagnosis (3). (2) Toxicity grading systems often consider the medical interventions (e.g., steroid use). Therefore, physi- cians who are more apt to prescribe steroids may note a higher reported rate of pneumonitis. Steroid use is Grade 3 in the Ra- diation Therapy Oncology Group (RTOG) scoring system but Grade 2 in several other systems. Requirement of steroids has been omitted from the Common Terminology Criteria for Ad- verse Events version 3.0. (3) Treatment-induced tumor shrink- age may improve overall lung function (especially for central lesions compressing regional airways/vessels), thus perhaps masking the effects of RT on the normal lung. (4) The relevant grade of symptoms is controversial. Grade 1 RP is common and is often not clinically significant. More severe RP is more clinically relevant, but its lower incidence limits the sta- tistical power of analysis based on severe events. 3. CHALLENGES DEFINING VOLUMES The lung is usually considered as a single, paired organ (to- tal lung tissue) rather than as separate ipsi- and contralateral lungs. Because lung volumes vary with breathing, there is Reprint requests to: Lawrence B. Marks, M.D., Department of Radiation Oncology, Box 7512, University of North Carolina, Chapel Hill, NC 27514. Tel: (919) 966-0400; Fax: (919) 966- 7681; E-mail: marks@med.unc.edu Supported in part by National Institutes of Health Grants 85181 (J.O.D.) and CA69579 (L.B.M.), a grant from the Lance Armstrong Foundation (L.B.M.), and an American Society of Clinical Oncol- ogy Career Development Award (F.M.K). Conflict of interest: none. Received Jan 7, 2009, and in revised form June 22, 2009. Accepted for publication June 27, 2009. S70 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No.3, Supplement, pp. S70–S76, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.06.091
- 71. ambiguity in definingits dose–volume histogram (DVH)- based parameters. In the articles herein reviewed, dosimetric information was mostly based on CT images obtained during free breathing. The dosimetric parameters would change had these scans been obtained at specific phases of the respiratory cycle. Segmentation of a thoracic scan can be challenging. There is uncertainty regarding how much of the bronchus should be defined as ‘‘lung,’’ and the lung edges may vary with the window/level setting. Thus, volume-based parame- ters will vary between investigators. The accuracy of any au- tosegmenting tools should be carefully assessed, especially to ensure that portions of atelectatic lung or tumor at soft-tissue interfaces are not inadvertently omitted from the lung. During RT planning, the total lung volume is usually de- fined to exclude the gross tumor volume (GTV). Excluding the planning target volume (PTV) rather than the GTV from the lung volume may reduce the apparent lung exposure (because normal lung within the PTV but outside the GTV will be excluded) and may increase interinstitutional varia- tions (because PTV margins may vary). During treatment there may be changes in GTV, with cor- responding changes in normal tissue anatomy. Thus, plans defined on the basis of pre-RT imaging may not accurately reflect the degree of normal lung exposure. Although this effect has not been widely considered, presumably tumor shrinkage (with movement of normal lung into space previ- ously occupied GTV) will increase normal lung exposure rel- ative to pre-RT plans. Similarly, changes in pleural effusions and re-aeration of lung regions can cause anatomic and func- tional changes. Indeed, the ability to predict changes in lung function according to pre-RT dosimetric data is reduced in patients with tumor-associated airway obstruction (i.e., those most likely to experience re-aeration during therapy) (4). 4. REVIEW OF DOSE–VOLUME DATA The literature on dose–volume parameters and pneumoni- tis is extensive: for this review we identified 70 published articles. The results are inconsistent, both for the best predic- tive metrics and significant comorbid factors. Lyman-Kutcher-Burman DVH reduction scheme and mean lung dose The most widely used normal tissue complication proba- bility model for RP is the Lyman-Kutcher-Burman (LKB) model. This model has three parameters: a position parame- ter, TD50, a steepness parameter, m, and the volume expo- nent, n (where n = 1 the model reverts to mean lung dose [MLD]). Although TD50 is strongly dependent on the grade of RP being considered, n is often regarded as a tissue char- acteristic. Figure 1 shows a meta-analysis of reported n values; it does not include the study by Rancati et al. (5), which used only the ipsilateral lung. The best estimate for n is 1.03 with standard deviation 0.17 (95% confidence inter- val [CI], 0.67, 1.39), the test for heterogeneity of the datasets is not significant, and I2 is zero. The TD50 values cannot be pooled in a meaningful way, because the various reports an- alyzed considered varying grades of RP. The MLD model is widely considered owing to its simplic- ity and effectiveness. It was the metric used by the large multi-institutional analysis of Kwa et al. (6) and often per- forms as well as more complex models. Figure 2A shows a lo- gistic regression fitted to RP vs. MLD data from all published studies of a significant size that had extractable complication rates binned by mean dose. Some of the variation around the fitted curve is possibly explained by differences in patient se- lection, as well as differences in the grade of RP reported in the various studies. Nevertheless, there is a relatively small 68% confidence interval (stippled lines). A similar fit using the probit model (equivalent to fitting the Lyman model with n fixed at 1) gives an essentially identical response func- tion in the region of the data. The gradual increase in dose re- sponse suggests that there is no absolute ‘‘safe’’ MLD below which there is no pneumonitis. The clinically acceptable risk of RP—and therefore the associated planning constraint on MLD—will depend on the risk/benefit ratio in the individual case. A number of non–DVH-based factors may affect the risk of RP (see ‘‘Factors Affecting Risk’’). Finally, it is likely Table 1. Example endpoints for radiotherapy-induced lung injury (and approximate incidence) Regional Global Clinical Bronchial stricture (3%*) Shortness of breath (5–50%) Subclinical Radiologic abnormalities (e.g. computed tomography, perfusion/ventilation scans) (20–80%) Pulmonary function tests, 6-min walk test, blood gases, exercise capacityy Example endpoints used to study radiotherapy-induced lung in- jury can be broadly segregated as shown. * Uncommon with conventional fractionation and doses. More common with brachytherapy, high total doses, and/or hypofractio- nation. y Many patients experience declines in functional assessments, but the magnitude of the decline is variable. Fig. 1. Meta-analysis of reported n values (volume parameter) for the Lyman-Kutcher-Burman (LKB) model using an inverse-vari- ance (IV) weighting method. Recovery of variance estimates from the 95% confidence interval (CI) and use of approximately Æ2*sigma instead of 1.96*sigma gave rise to small deviations in the derived 95% CI as compared with the literature reported values. Data estimated from references 47–49. Fixed = fixed effect model. The n value reflects the manner in which dose–volume parameters lead to complications. A lower value of n suggests that the tissue is sensitive to hot spots (e.g., an organ structured in ‘‘series’’), whereas a higher value of n (closer to 1.0), suggests that the risk is more related to the volume of an organ irradiated (e.g., ‘‘parallel’’ structure). Radiation effects in lung d L. B. MARKS et al. S71
- 72. that the MLD–RPrelationship may have lower predictive power for ‘‘nonstandard’’ dose distributions not included in these analyses, for example after stereotactic body radio- therapy (SBRT), Intensity-Modulated Radiation Therapy (IMRT), or proton therapy. Dose–volume threshold analyses Various Vx values (percentage lung volume receiving $x Gy) are associated with RP risk (Fig. 2B). The observation that a variety of dose levels are predictive suggests that there is no sharp dose threshold below which there is no risk. Within individual datasets there are usually strong correla- tions between the different dosimetric parameters (e.g., V5 and V20), and thus this may partly obscure any ‘‘optimal’’ threshold. Furthermore, the correlations between dosimetric parameters are technique dependent, and readers should care- fully assess the similarity of their treatment technique to the historical reports before using any of these limits as clinical constraints. Radiotherapy-induced dyspnea appears more commonly in patients with lower- vs. upper-lobe tumors and may be bet- ter correlated with RT doses to the lower vs. upper lung (7– 11). An analysis that combined institutional data with RTOG 93-11 (n = 324) concluded that RP is much better predicted (at least for that dataset) according to MLD and positional de- pendence of the high-dose region as opposed to MLD alone (12). 5. FACTORS AFFECTING RISK Several patient- and treatment-related factors have been in- consistently reported to correlate with the risk of developing RP. Vogelius and Bentzen (unpublished data) applied stan- dard meta-analysis methodology to eight factors with mean- ingful data. In summary, there was no significant evidence for an association between RP and GTV laterality (left vs. right lung), comorbidity, or gender. Younger patients, typically defined as 60 or 70 years of age, had a lower risk of RP than older patients. Surgery had a just-significant p value, but the test for heterogeneity was significant (p = 0.03), sug- gesting that the variation among studies cannot be explained by chance alone. Thus, at present, the reduced rate of RP in patients undergoing surgery remains controversial. Interest- ingly, current smokers had a significantly reduced risk of de- veloping RP. Chemotherapy Many systemic agents have known pulmonary toxicities (13) and may exacerbate RT-induced injury. The varying drugs, doses, and schedules (e.g., sequential or concurrent) make any synthesis of data from multiple studies generally not feasible. On the basis of general experience, adding chemo- therapy might be expected to increase the risk of RP. Fig. 2. Rate of radiation pneumonitis after fractionated partial lung radiotherapy (RT) related to (a) mean lung dose and (b) different values of Vx. (a) Mean lung dose. Confidence intervals shown are Æ1 standard deviation. Mean dose–response data from: Memorial Sloan-Kettering Cancer Center (MSKCC) (10 [Fig. 4a]; Radiation Therapy Oncology Group [RTOG] Grade $3, 6 months); Duke, (15 [Table 4]; Common Toxicity Criteria [CTC] Grade $1, 6 months); Michigan (50 [Table 4 and Fig. 2a]; Southwest Oncology Group [SWOG] Grade $2, 6 months)—bin location and time from authors; M. D. Anderson Cancer Center (51 [Fig. 2]; CTC Grade $3, 1 year actuarial—includes concurrent chemo patients); Nether- lands Cancer Institute (NKI) (9 [Fig. 3a]; SWOG Grade $2, 6 months); Washington University (WU) (11 [Fig. 9c]; SWOG Grade $2—no time limit), with bin locations from authors, increased by 11% to approximately account for inhomogeneity corrections; Michigan (52 [Table 1]; SWOG Grade $1) with mean doses calcu- lated from relationship between equivalent uniform dose (n = 0.87) and mean dose from Kwa et al. (53 [Fig. 2a]); Heidelberg (54 [Fig 2. and text]; RTOG acute Grade $1); Milan (55 [Fig. 3]; SWOG Grade $2—no time limit, patients without chronic obstructive pulmonary disease—includes induction chemotherapy patients); Gyeonggi (56 [Table 5]; RTOG Grade $3, 6 months—includes concurrent che- motherapy patients), median values of mean dose in each bin pro- vided by the authors. Dashed line is logistic fit: data fit to the form [f/(1 + f)], where f = exp(b0 + b1 Â dmean). Best-fit values (95% confidence intervals) are b0 = À3.87 (À3.33, À4.49), b1 = 0.126 (0.100, 0.153), corresponding to TD50 = 30.75 (28.7, 33.9) Gy and g50 = 0.969 (0.833, 1.122), where g50 represents the increase in response (measured as percentage) per 1% increase in dose, near the 50% dose–response level. (b) Rates of radiation pneumonitis for different values of Vx. Vx response data from: Yorke V13, V40, (10 [Fig. 4d]); Willner V40, (57 [Fig. 4]); Hernando V30 (15 [Table 6]); Tsujino V20 (58 [Fig. 3]); Kong V13, V20, (50 [Table 4]); Armstrong V25 (59 [Fig. 3]); Kim V20, V30 (56 [Table 5]; Graham V20 (7 [Table 4]); Seppenwoolde V13 48([Fig. 2]); and Wang V5 (51; and Schal- lenkamp V13 (60 [Fig. 2b]). Some data estimated from published re- ports. S72 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 73. Nevertheless,theagentsmostcommonlyusedwithRTforlung cancer, such ascisplatin, carboplatin, paclitaxel, and etoposide, have not been consistently shown to increase the risk of pneu- monitis (7, 11, 14–16). More modern agents have been associ- ated with high rates of pulmonary toxicity when used concurrently with thoracic RT (e.g., docetaxel and gemcita- bine) (1, 17, 18). Radiation dose, time, and fractionation Radiation pneumonitis has a relatively high fractionation sensitivity (19, 20); the best current estimate (Æ1 standard er- ror of the estimate) of the a/b ratio of the linear-quadratic model is 4.0 Æ 0.9 Gy (21). For comparison, the upper bound of the 95% CI for a/b for pulmonary fibrosis is 3.5 Gy. There is also a significant time factor for pneumonitis, with an overall best estimate of the dose recovered per day, Dp, of 0.54 Æ 0.21 Gy/day. Several investigators have suggested methods to adjust the DVH to reflect the impact of fraction size (22, 23). 6. MATHEMATIC/BIOLOGIC MODELS The association between RP risk and MLD (logistic fit to the data in Fig. 2(a) can be expressed as p ¼ expðb0 þ b1,MLDÞ 1 þ expðb0 þ b1,MLDÞ : Best-fit parameters (95% CI) are b0 = À3.87 (À3.33, À4.49) and b1 = 0.126 (0.100, 0.153) GyÀ1 . These estimates yield a predicted TD50 = 30.8 (28.7, 33.9) Gy and g50 = 0.97 (0.83, 1.12) (this parameter represents the increase in response [measured as percentage] per 1% increase in dose, at the 50% dose–response level). A fit using the probit response function (equivalent to a fit of the Lyman model with n = 1) yields TD50 = 31.4 Gy (95% CI, 29.0, 34.7 Gy) and m = 0.45 (0.39, 0.51). The resultant response function is essentially identical to that of the logistic fit in the region occupied by the data. The cur- vature is slightly smaller, resulting in the slightly larger TD50 value. Both fits assumed heterogeneity corrected dose distributions (an approximate correction of 11% was applied to doses from studies using homogeneous calculations). 7. SPECIAL SITUATIONS The data reviewed here are largely derived from patients who received partial-lung irradiation using conformal three-dimensionally planned external-beam RT with conven- tional fractionation (e.g., 1.8–2.0 Gy per fraction). Several special situations are discussed here. Whole-lung irradiation Near-uniform irradiation of both lungs occurs during total- body irradiation as conditioning for stem cell transplants, hemibody RT for diffuse metastases, and whole-lung irradi- ation for prophylaxis or treatment of pulmonary metastases from various malignancies. The risk of RP depends on total dose and fraction size (Fig. 3). The development of RP in these settings is an ominous sign, proving fatal in up to 80% of patients (24). The pathogenesis of RP, in particular after total-body irradiation, is relatively complex and de- pends on multiple patient- and treatment-related factors (25). There are consistent data supporting a protective effect of low dose rate and low dose per fraction. For a recent com- prehensive review, see Sampath et al. (26). Hypofractionation Stereotactic body radiotherapy generally involves 1–5 large fractions (e.g., 14–30 Gy) given over 5–20 days (27, 28). The high-dose volumes are small, and dose gradients are typically uniformly steep, minimizing dose to surround- ing critical structures. However, because numerous beams are used, there are large areas of lung receiving low to me- dium doses (28). Thus, the dose–volume characteristics of SBRT are quite different from those of conventional lung RT and deserve special consideration. Radiation pneumonitis is relatively uncommon after SBRT, usually 10% (28–30) but as high as 25% (31). Bronchial injury/stenosis, an un- usual complication with conventional doses (32), has been associated with SBRT of perihilar/central tumors (28). Intensity-modulated radiotherapy for lung cancer The M. D. Anderson Cancer Center reported a lower rate of symptomatic Grade $3 pneumonitis in 68 patients treated with intensity-modulated radiotherapy (IMRT) compared with a historical control group of 222 receiving conventional three-dimensional conformal RT (33). The Memorial Sloan- Kettering Cancer Center recently noted an acceptable 11% rate of Grade $3 pneumonitis in 55 patients treated with IMRT (34). Postoperative IMRT for mesothelioma has been associated with a high rate of lethal pneumonitis (8– 46%) (35–37), and extreme care should be used to limit lung irradiation in these cases (see next section). 8. RECOMMENDED DOSE/VOLUME LIMITS Recommending dose/volume limits is challenging because there are no clear and consistent ‘‘thresholds’’ for candidate metrics (i.e., the response function is often gradual), and baR 1 679 xf/yGc051 kyDnaV 1891 esoDelgniS )yG(esoD 63 219 8151 4212 0372 IncidenceofPneumonitis 8791razalaS esoDelgniS )4/1( )04/0( )3/3( 9691notweN 003 xf/yGc 051 xf/yGc )62/0( ruerB 8791 xf/yGc571 )44/0( 8891sregruB xf/yGc002 )65/8( 1 9.0 8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0 kyDnaVottiF d ata Fig. 3. Rate of pneumonitis after whole-lung irradiation for diffuse lung or bone metastases, or prophylaxis for occult metastatic disease (24, 61–67). Numbers in parentheses give the incidence of pneumo- nitis divided by the population at risk for each fractionation scheme in each study. Some data estimated from published reports. Radiation effects in lung d L. B. MARKS et al. S73
- 74. the ‘‘acceptable’’ risklevel varies with the clinic scenario. Radiotherapy fields for lung cancer may be appropriately large for target coverage; physicians and patients often need to accept the significant pulmonary risks. Furthermore, there are marked interpatient variations in pre-RT lung func- tion that may impact symptom development, and tumor-re- lated dysfunction may improve after RT. Despite these caveats, it is prudent to limit V20 to #30–35 % and MLD to #20–23 Gy (with conventional fractionation) if one wants to limit the risk of RP to #20% in definitively treated patients with non–small-cell lung cancer. Similar guidelines for other parameters can be extracted from the fig- ures. Limiting the dose to the central airways to #80 Gy may reduce the risk of bronchial stricture (30). In patients treated after pneumonectomy for mesothelioma, it is prudent to limit the V5 to 60%, the V20 to 4–10%, and the MLD to 8 Gy (see Miles et al. [37] for detailed review). 9. FUTURE TOXICITY STUDIES Progress regarding the predictors of RT-induced lung in- jury requires further understanding of the following. Endpoint interaction The study of RT-induced lung injury is confounded by the use of ambiguous endpoints. Many scoring systems combine radiologic, functional, and symptomatic criteria to define a ‘‘global score.’’ Because each endpoint may have different dose–volume dependence, this approach may be counterpro- ductive. Therefore, we recommend that further study of lung injury explicitly consider symptomatic, functional, and radio- graphic endpoints separately. Impact of clinical factors The impact of clinical factors (e.g., pre-RT functional sta- tus, tobacco use) and systemic agents (e.g., chemotherapy) on the risk of RP needs further study. Organ interactions Some pre-clinical data suggest that there may be interac- tions between the lung and heart in the development of RT- associated dyspnea. In rats, the respiratory rate after thoracic RT was related to the volume of lung and heart irradiated (38–40). Impact of an in situ lung cancer on the risk of radiation- induced lung injury The data for whole-lung radiation is derived essentially from patients without primary lung cancers (e.g., elective lung RT for sarcoma), vs. fractionated partial lung radiation, often derived from patients with gross lung cancers. The con- founding effect of tumor in the lung makes the study of RT- induced lung injury extremely challenging. Indeed, in several studies, the ability to predict for RT-induced lung injury is improved in patients without large central or occluding tu- mors. Thus, it might be relevant to develop separate predic- tive models in patients with intact intraparenchymal lung tumors vs. those without such a lesion (i.e., postresection RT for lung cancer, or RT for other thoracic tumors). Radiation response modifiers Amifostine is a thio-organic prodrug believed to scavenge harmful free radicals mediating RT-induced injury. Several randomized studies in patients receiving RT for lung cancer note a reduction in RP in the amifostine arm (41–43), although the largest study (from RTOG) was negative (44). However, this study has been criticized because the drug was adminis- tered once daily (4 days/week) whereas the RT was delivered twice daily (5 days/week), and thus 60% of the RT fractions were delivered without the protector. Such mixed results, combined withthe acutetoxicities of amifostine (nausea/vom- iting, hypotension, infection, and rash), have dissuaded many from using it in routine practice. One small randomized study demonstrated a protective effect of pentoxifylline, but pentox- ifylline is not currently used in routine clinical practice (45). Biomarkers Additional work is needed to assess the predictive ability offered by biomarkers (see Bentzen et al. in this issue), such as transforming growth factor b (measured before and/or during RT) (46). 10. TOXICITY SCORING A Late Effects of Normal Tissue–Subjective, Objective, Management, and Analytic (LENT-SOMA)-type scoring system is recommended because it explicitly considers symp- tomatic, functional, and radiographic endpoints individually. A global score can be generated, but the granular data can be maintained. REFERENCES 1. Mehta V. Radiation pneumonitis and pulmonary fibrosis in non- small-cell lung cancer: Pulmonary function, prediction, and pre- vention. Int J Radiat Oncol Biol Phys 2005;63:5–24. 2. Marks LB, Yu X, Vujaskovic Z, et al. Radiation-induced lung injury. Semin Radiother Oncol 2003;13:333–345. 3. Kocak Z, Evans ES, Zhou SM, et al. Challenges in defining ra- diation pneumonitis in patients with lung cancer. Int J Radiat Oncol Biol Phys 2005;62:635–638. 4. Marks LB, Hollis D, Munley M, et al. The role of lung perfu- sion imaging in predicting the direction of radiation-induced changes in pulmonary function tests. Cancer 2000;88:2135– 2141. 5. Rancati T, Wennberg B, Lind P, et al. Early clinical and radio- logical pulmonary complications following breast cancer radia- tion therapy: NTCP fit with four different models. Radiother Oncol 2007;82:308–316. 6. Kwa SL, Lebesque JV, Theuws JC, et al. Radiation pneumo- nitis as a function of mean lung dose: An analysis of pooled data of 540 patients. Int J Radiat Oncol Biol Phys 1998;42: 1–9. S74 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 75. 7. Graham MV,Purdy JA, Emami B, et al. Clinical dose-volume histogram analysis for pneumonitis after 3D treatment for non-small cell lung cancer (NSCLC). Int J Radiat Oncol Biol Phys 1999;45:323–329. 8. Yorke ED, Jackson A, Rosenzweig KE, et al. Dose-volume fac- tors contributing to the incidence of radiation pneumonitis in non-small-cell lung cancer patients treated with three-dimen- sional conformal radiation therapy. Int J Radiat Oncol Biol Phys 2002;54:329–339. 9. Seppenwoolde Y, De Jaeger K, Boersma LJ, et al. Regional dif- ferences in lung radiosensitivity after radiotherapy for non- small-cell lung cancer. Int J Radiat Oncol Biol Phys 2004;60: 748–758. 10. Yorke ED, Jackson A, Rosenzweig KE, et al. Correlation of do- simetric factors and radiation pneumonitis for non-small-cell lung cancer patients in a recently completed dose escalation study. Int J Radiat Oncol Biol Phys 2005;63:672–682. 11. Hope AJ, Lindsay PE, El Naqa I, et al. Modeling radiation pneumonitis risk with clinical, dosimetric, and spatial parame- ters. Int J Radiat Oncol Biol Phys 2006;65:112–124. 12. Bradley JD, Hope A, El Naqa I, et al. A nomogram to predict radiation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data. Int J Radiat Oncol Biol Phys 2007;69:985–992. 13. Meadors M, Floyd J, Perry MC. Pulmonary toxicity of chemo- therapy. Semin Oncol 2006;33:98–105. 14. Robnett TJ, Machtay M, Vines EF, et al. Factors predicting se- vere radiation pneumonitis in patients receiving definitive che- moradiation for lung cancer. Int J Radiat Oncol Biol Phys 2000; 48:89–94. 15. Hernando ML, Marks LB, Bentel GC, et al. Radiation-induced pulmonary toxicity: A dose-volume histogram analysis in 201 patients with lung cancer. Int J Radiat Oncol Biol Phys 2001; 51:650–659. 16. Kong FM, Ten Haken R, Eisbruch A, et al. Non-small cell lung cancer therapy-related pulmonary toxicity: An update on radia- tion pneumonitis and fibrosis. Semin Oncol 2005;32:S42–S54. 17. Movsas B, Raffin TA, Epstein AH, et al. Pulmonary radiation injury. Chest 1997;111:1061–1076. 18. Onishi H, Kuriyama K, Yamaguchi M, et al. Concurrent two-di- mensional radiotherapy and weekly docetaxel in the treatment of stage III non-small cell lung cancer: A good local response but no good survival due to radiation pneumonitis. Lung Cancer 2003;40:79–84. 19. Tsujino K, Hirota S, Kotani Y, et al. Radiation pneumonitis fol- lowing concurrent accelerated hyperfractionated radiotherapy and chemotherapy for limited-stage smallcell lung cancer: Dose-volume histogram analysis and comparison with conven- tional chemoradiation. Int J Radiat Oncol Biol Phys 2006;64: 1100–1105. 20. Roach M 3rd, Gandara DR, Yuo HS, et al. Radiation pneumo- nitis following combined modality therapy for lung cancer: analysis of prognostic factors. J Clin Oncol 1995;13:2606– 2612. 21. Bentzen SM, Skoczylas JZ, Bernier J. Quantitative clinical ra- diobiology of early and late lung reactions. Int J Radiat Biol 2000;76:453–462. 22. Lebesque JV, Keus RB. The simultaneous boost technique: The concept of relative normalized total dose. Radiother Oncol 1991;22:45–55. 23. Wheldon TE, Deehan C, Wheldon EG, et al. The linear-qua- dratic transformation of dose-volume histograms in fractionated radiotherapy. Radiother Oncol 1998;46:285–295. 24. Fryer CJ, Fitzpatrick PJ, Rider WD, et al. Radiation pneumoni- tis: Experience following a large single dose of radiation. Int J Radiat Oncol Biol Phys 1978;4:931–936. 25. Ozsahin M, Belkace´mi Y, Pe`ne Fo, et al. Interstitial pneumoni- tis following autologous bone-marrow transplantation conditioned with cyclophosphamide and total-body irradiation. Int J Radiat Oncol Biol Phys 1996;34:71–77. 26. Sampath S, Schultheiss TE, Wong J. Dose response and factors related to interstitial pneumonitis after bone marrow transplant. Int J Radiat Oncol Biol Phys 2005;63:876–884. 27. Timmerman RD, Park C, Kavanagh BD. The North American experience with stereotactic body radiation therapy in non-small cell lung cancer. J Thorac Oncol 2007;2:S101–S112. 28. Timmerman R, Galvin J, Michalski J, et al. Accreditation and quality assurance for Radiation Therapy Oncology Group: Mul- ticenter clinical trials using stereotactic body radiation therapy in lung cancer. Acta Oncol 2006;45:779–786. 29. Timmerman R, Papiez L, McGarry R, et al. Extracranial stereo- tactic radioablation: Results of a phase I study in medically in- operable stage I non-small cell lung cancer. Chest 2003;124: 1946–1955. 30. Hara R, Itami J, Komiyama T, et al. Serum levels of KL-6 for pre- dicting the occurrence of radiation pneumonitis after stereotactic radiotherapy for lung tumors. Chest 2004;125:340–344. 31. Yamashita H, Nakagawa K, Nakamura N, et al. Exceptionally high incidence of symptomatic grade 2-5 radiation pneumonitis after stereotactic radiation therapy for lung tumors. Radiat On- col 2007;2:21. 32. Miller KL, Shafman TD, Anscher MS, et al. Bronchial stenosis: an underreported complication of high-dose external beam ra- diotherapy for lung cancer? Int J Radiat Oncol Biol Phys 2005;61:64–69. 33. Yom SS, Liao Z, Liu HH, et al. Initial evaluation of treatment- related pneumonitis in advanced-stage non-small-cell lung cancer patients treated with concurrent chemotherapy and inten- sity-modulated radiotherapy. Int J Radiat Oncol Biol Phys 2007;68:94–102. 34. Sura S, Gupta V, Yorke E, et al. Intensity-modulated radiation therapy (IMRT) for inoperable non-small cell lung cancer: The Memorial Sloan-Kettering Cancer Center (MSKCC) experi- ence. Radiother Oncol 2008;87:17–23. 35. Allen AM, Czerminska M, Ja¨nne PA, et al. Fatal pneumonitis associated with intensity-modulated radiation therapy for meso- thelioma. Int J Radiat Oncol Biol Phys 2006;65:640–645. 36. Rice DC, Smythe WR, Liao Z, et al. Dose-dependent pulmo- nary toxicity after postoperative intensity-modulated radiother- apy for malignant pleural mesothelioma. Int J Radiat Oncol Biol Phys 2007;69:350–357. 37. Miles EF, Larrier NA, Kelsey CR, et al. Intensity-modulated ra- diotherapy for resected mesothelioma: The Duke experience. Int J Radiat Oncol Biol Phys 2008;71:1143–1150. 38. Novakova-Jiresova A, van Luijk P, van Goor H, et al. Pulmo- nary radiation injury: Identification of risk factors associated with regional hypersensitivity. Cancer Res 2005;65:3568–3576. 39. van Luijk P, Novakova-Jiresova A, Faber H, et al. Radiation damage to the heart enhances early radiation-induced lung func- tion loss. Cancer Res 2005;65:6509–6511. 40. Wiegman EM, Meertens H, Konings AWT, et al. Loco-regional differences in pulmonary function and density after partial rat lung irradiation. Radiother Oncol 2003;69:11–19. 41. Komaki R, Lee JS, Milas L, et al. Effects of amifostine on acute toxicity from concurrent chemotherapy and radiotherapy for in- operable non-small-cell lung cancer: report of a randomized comparative trial. Int J Radiat Oncol Biol Phys 2004;58: 1369–1377. 42. Antonadou D, Coliarakis N, Synodinou M, et al. Randomized phase III trial of radiation treatment Æ amifostine in patients with advanced-stage lung cancer. Int J Radiat Oncol Biol Phys 2001;51:915–922. 43. Antonadou D, Throuvalas N, Petridis A, et al. Effect of amifos- tine on toxicities associated with radiochemotherapy in patients with locally advanced non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 2003;57:402–408. Radiation effects in lung d L. B. MARKS et al. S75
- 76. 44. Movsas B,Scott C, Langer C, et al. Randomized trial of amifos- tine in locally advanced non-small-cell lung cancer patients re- ceiving chemotherapy and hyperfractionated radiation: Radiation Therapy Oncology Group trial 98-01. J Clin Oncol 2005;23:2145–2154. 45. Ozturk B, Egehan I, Atavci S, et al. Pentoxifylline in prevention of radiation-induced lung toxicity in patients with breast and lung cancer: A double-blind randomized trial. Int J Radiat On- col Biol Phys 2004;58:213–219. 46. Fu X-L, Huang H, Bentel G, et al. Predicting the risk of symp- tomatic radiation-induced lung injury using both the physical and biologic parameters V30 and transforming growth factor [beta]. Int J Radiat Oncol Biol Phys 2001;50:899–908. 47. Moiseenko V, Deasy JO, Dyk JV. Radiobiological modeling for treatment planning. In: Van Dyk J, editor. The modern technol- ogy of radiation oncology: A compendium for medical physi- cists and radiation oncologists. Vol. 2. Madison, WI: Medical Physics; 2005. 48. Seppenwoolde Y, Lebesque JV, de Jaeger K, et al. Comparing different NTCP models that predict the incidence of radiation pneumonitis. Normal tissue complication probability. Int J Ra- diat Oncol Biol Phys 2003;55:724–735. 49. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of the risk of postoperative pulmonary complications among esophageal cancer patients treated with concurrent chemoradio- therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006; 66:754–761. 50. Kong FM, Hayman JA, Griffith KA, et al. Final toxicity results of a radiation-dose escalation study in patients with non-small-cell lung cancer (NSCLC): Predictors for radiation pneumonitis and fibrosis. Int J Radiat Oncol Biol Phys 2006;65:1075–1086. 51. Wang S, Liao Z, Wei X, et al. Analysis of clinical and dosimet- ric factors associated with treatment-related pneumonitis (TRP) in patients with non-small-cell lung cancer (NSCLC) treated with concurrent chemotherapy and three-dimensional confor- mal radiotherapy (3D-CRT). Int J Radiat Oncol Biol Phys 2006;66:1399–1407. 52. Martel MK, Ten Haken RK, Hazuka MB, et al. Dose-volume histogram and 3-D treatment planning evaluation of patients with pneumonitis. Int J Radiat Oncol Biol Phys 1994;28:575– 581. 53. Kwa SL, Theuws JC, Wagenaar A, et al. Evaluation of two dose-volume histogram reduction models for the prediction of radiation pneumonitis. Radiother Oncol 1998;48:61–69. 54. Oetzel D, Schraube P, Hensley F, et al. Estimation of pneumo- nitis risk in three-dimensional treatment planning using dose- volume histogram analysis. Int J Radiat Oncol Biol Phys 1995;33:455–460. 55. Rancati T, Ceresoli GL, Gagliardi G, et al. Factors predicting radiation pneumonitis in lung cancer patients: A retrospective study. Radiother Oncol 2003;67:275–283. 56. Kim TH, Cho KH, Pyo HR, et al. Dose-volumetric parameters for predicting severe radiation pneumonitis after three-dimen- sional conformal radiation therapy for lung cancer. Radiology 2005;235:208–215. 57. Willner J, Jost A, Baier K, et al. A little to a lot or a lot to a little? An analysis of pneumonitis risk from dose-volume histogram parameters of the lung in patients with lung cancer treated with 3-D conformal radiotherapy. Strahlenther Onkol 2003; 179:548–556. 58. Tsujino K, Hirota S, Endo M, et al. Predictive value of dose-vol- ume histogram parameters for predicting radiation pneumonitis after concurrent chemoradiation for lung cancer. Int J Radiat Oncol Biol Phys 2003;55:110–115. 59. Armstrong JG, Zelefsky MJ, Leibel SA, et al. Strategy for dose escalation using 3-dimensional conformal radiation therapy for lung cancer. Ann Oncol 1995;6:693–697. 60. Schallenkamp JM, Miller RC, Brinkmann DH, et al. Incidence of radiation pneumonitis after thoracic irradiation: Dose- volume correlates. Int J Radiat Oncol Biol Phys 2007;67: 410–416. 61. Newton KA. Total thoracic irradiation combined with intrave- nous injection of autogenous marrow. Clin Radiol 1960;11: 14–21. 62. Newton KA, Spittle MF. An analysis of 40 cases treated by total thoracic irradiation. Clin Radiol 1969;20:19–22. 63. Salazar OM, Rubin P, Keller B, et al. Systemic (half-body) ra- diation therapy: Response and toxicity. Int J Radiat Oncol Biol Phys 1978;4:937–950. 64. Van Dyk J, Keane TJ, Kan S. Radiation pneumonitis following large single dose irradiation: A re-evaluation based on absolute dose to lung. Int J Radiat Oncol Biol Phys 1981;7:461–467. 65. Rab GT, Ivins JC, Childs J, Donald S, et al. Elective whole lung irradiation in the treatment of osteogenic sarcoma. Cancer 1976;38:939–942. 66. Breur K, Cohen P, Schweisguth O, et al. Irradiation of the lungs as an adjuvant therapy in the treatment of osteosarcoma of the limbs. An E.O.R.T.C. randomized study. European Journal of Cancer 1978;14:461–471. 67. Burgers JM, van Glabbeke V, Busson A, et al. Osteosarcoma of the limbs. Report of the EORTC-SIOP 03 trial 20781 investigat- ing the value of adjuvant treatment with chemotherapy and/or prophylactic lung irradiation. Cancer 1988;61:1024–1031. S76 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 77. QUANTEC: ORGAN SPECIFICPAPER Thorax: Heart RADIATION DOSE–VOLUME EFFECTS IN THE HEART GIOVANNA GAGLIARDI, PH.D.,* LOUIS S. CONSTINE, M.D.,y VITALI MOISEENKO, PH.D.,z CANDACE CORREA, M.D.,x LORI J. PIERCE, M.D.,x AARON M. ALLEN, M.D.,k AND LAWRENCE B. MARKS, M.D.{ * Department of Medical Physics, Karolinska University Hospital and Karolinska Institute, Stockholm, Sweden; y Department of Radiation Oncology, University of Rochester Cancer Center, Rochester, NY; z Vancouver Cancer Centre, British Columbia Cancer Agency, Vancouver, BC, Canada; x Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; k Department of Radiation Oncology, Dana- Farber Cancer Institute, Boston, MA; Rabin Medical Center Petach Tikvah, Israel ; and { Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC The literature is reviewed to identify the main clinical and dose–volume predictors for acute and late radiation- induced heart disease. A clear quantitative dose and/or volume dependence for most cardiac toxicity has not yet been shown, primarily because of the scarcity of the data. Several clinical factors, such as age, comorbidities and doxorubicin use, appear to increase the risk of injury. The existing dose-volume data is presented, as well as suggestions for future investigations to better define radiation-induced cardiac injury. Ó 2010 Elsevier Inc. Radiation heart disease, Dose–volume predictors, NTCP, Breast cancer, Lymphoma, Esophagus cancer. 1. CLINICAL SIGINIFICANCE Radiation-associated cardiac disease is seen in patients treated for lymphoma, breast cancer, seminoma, peptic ulcer disease, and lung cancer, as well as in atomic bomb survivors. Acute injury, often manifest as pericarditis, is usually transient but can be chronic. Late injury, often manifest as congestive heart failure (CHF), ischemia, coronary artery disease (CAD), or myocardial infarction (MI) several months to years post-radiation treatment (RT), is more clinically significant. In some disease settings, RT-induced heart dis- ease has offset the improvements in cancer-specific survival provided by adjuvant RT (1). For example, the leading cause of noncancer mortality among long-term RT-treated survi- vors of Hodgkin’s lymphoma is cardiovascular death (2). 2. ENDPOINTS Both clinical and subclinical endpoints describe the spec- trum of RT-induced heart disease (Table 1). The latency of RT-associated cardiac effects ranges from months (pericardi- tis) to decades (CAD, MI). The most clinically significant endpoints analyzed are morbidity (e.g., CHF and ischemic events such as MI) and cardiac deaths. Since these events occur at a relatively high rate in patients who have not undergone irradiation, the best data are derived from rando- mised clinical trials, or population-based studies with or without RT. Overall, the relative risks (RR) of these clinically significant cardiac events are within a range of 1.2 to 3.5 after RT. Subclinical abnormalities are more common, and are noted in up to 50% of patients, depending on the sensitivity of the endpoint considered and the associated comorbidities. Pericardial disease Acute pericarditis during RT is uncommon and usually associated with pericardiac mediastinal tumours. Delayed pericardial disease can occur from months to years after RT; it includes pericarditis and chronic pericardial effusion (usually asymptomatic). Although most cases resolve sponta- neously, approximately 20% develop into chronic and/or con- strictive pericarditis that may necessitate pericardectomy (3). Ischemic heart disease Evidence that ischemic heart disease correlates with RT comes from the Early Breast Cancer Trialists’ Collaborative Group meta-analyses of randomized clinical trials. The most recent update showed an increased RR of mortality from heart disease among women treated with RT vs. no RT ([RR] = 1.27) (1). Long-term cardiac outcomes from randomized clinical trials of postmastectomy RT (4, 5) usually reveal an Reprint requests to: Giovanna Gagliardi, Ph.D., Department of Medical Physics, Karolinska University Hospital and Karolinska In- stitute, 17176 Stockholm, Sweden. Tel: +46-8-517 75025; E-mail: giovanna.gagliardi@karolinska.se Conflict of interest: none. Acknowledgment—Supported in part by grants from the NIH (CA69579) and the Lance Armstrong Foundation (LBM). Received Sept 3, 2008, and in revised form April 16, 2009. Accepted for publication April 16, 2009. S77 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S77–S85, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.04.093
- 78. increased cardiac mortalityrisk (RR = $2.5) associated with left-sided and internal mammary nodal (IMN) RT. Ret- rospective population-based investigations have compared mortality endpoints by laterality of RT vs. surgical controls (6–8). Some investigations have shown an increased risk of cardiac mortality (hazard ratio [HR] = $ 1.5) for left-sided vs. right-sided cancers treated with RT in the 1970s, but not with more modern RT techniques (7, 9, 12). For cardiac morbidity endpoints there is an increase in CAD and/or non-fatal MI with left-sided RT compared with either right-sided RT or no RT (6, 9–13). In two pro- spective studies and one retrospective study subclinical end- points of perfusion defects have been assessed, but their clinical significance is still uncertain (11, 14, 15). At Stan- ford, children and adolescents with Hodgkin’s lymphoma (HL) who underwent mediastinal RT had an increased RR for death from heart disease (RR = 28–37) (16). In the ex- tended analysis including 2,232 patients of all age groups, the RR for death from acute MI was 3.2 (17). The elevated risk, already significant in the first 5 years, remained elevated throughout the follow-up period (20 years); the average in- terval to MI was 10.3 years. In a recent study with 7,033 pa- tients, the RR for lethal MI was 2.5 (18). In another analysis, mediastinal RT for HL had a greater likelihood of causing right coronary or left main or left anterior descending coro- nary artery lesions compared with circumflex lesions, possi- bly because of the location of the former (19). These studies generally included patients treated with doses $30 Gy. In the Stanford data, CAD risk was much reduced at doses #30 Gy. Congestive heart failure Two retrospective studies evaluating CHF among irradi- ated breast cancer patients yielded conflicting results (10, 12). In the Stanford data on 2,232 HL patients, the RR of death from cardiac causes other than MI decreased with use of subcarinal blocking from 5.3 to 1.4 (17). Adams et al. reported findings suggesting a greater impact on diastolic than systolic dysfunction in their investigation of 48 long-term survivors of childhood HL treated with mantle irradiation (median, 40 Gy) (20). Valvular disease For breast cancer patients, data are conflicting regarding the association of RT with valvular dysfunction. In a large study in the Netherlands the risk of valvular dysfunction was higher in the group receiving IMN RT vs. the group with no RT (HR = 3.17) (12), but this was not demonstrated in a smaller study (10). In HL patients, valvular abnormalities include both insuf- ficiency and stenosis, the former being more common and less clinically relevant. Incidence of left-sided valvular re- gurgitation ranges from 16% to 40% (vs. 2% in controls) (21, 22). Data from Stanford on 294 asymptomatic HL survi- vors treated with a mantle technique at a mean dose of 43 Gy showed a 34-fold increased risk of aortic regurgitation (abso- lute incidence, 26.1%) (23). 3. CHALLENGES IN DEFINING VOLUMES Delineation of the clinically relevant subregions of the heart is challenging because their structural definition through the current devices used in treatment planning (e.g., computed tomography [CT]) is imprecise. No imaging modality clearly shows these structures. The heart border may be difficult to differentiate from liver and diaphragm, but the segmenting of the superior border with the large vessels can be more challenging. The heart moves with the respiratory and cardiac cycles: the degree of motion, mainly in the superior–inferior direction, is modest with free breath- ing (24). Furthermore, the anatomy of the great vessels as they intersect the heart is complex. Newer imaging tools, such as magnetic resonance imaging, may be able to better identify cardiac subregions, but their application to RT planning is still limited. Cardiac structures can be defined anatomically and/or based on functionality; this can be problematic because of the anatomic/functional complexities, the interactions of the various structures such as the ventricles, valves, vasculature and their overlying anatomy. Uncertainties remain regarding which region of the heart is functionally most important for RT-induced toxicities. Three main clinical endpoints have been considered in the study of specific dose–volume response relationships: mor- tality from ischemic heart disease, pericarditis, and decreased myocardial perfusion. For these analyses, the volumes con- sidered were either the entire heart (25), pericardium (26, 27), or the left ventricle alone (28) (Tables 2–4). Because cor- onary/ischemic events are a major concern, several investiga- tors have calculated doses to potentially relevant Table 1. Endpoints related to radiation-induced heart disease Regional endpoints Global endpoints Subclinical Localized imaging abnormality (e.g., perfusion defect or regional wall motion abnormality) Myocardial fibrosis Global imaging abnormality (e.g., diffuse hypocontractility) Asymptomatic decline in ejection fraction Clinical Coronary artery disease Myocardial infarction Valvular disease Congestive heart failure Pericarditis/pericardial effusion Arrhythmia Autonomic dysfunction (monotonous heart beat responding to changes in hemodynamic requirements) S78 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 79. substructures such ascoronary arteries or the left ventricle (29–31). 4. REVIEW OF DOSE/VOLUME FACTORS The risk of cardiac events is probably related to both dose and irradiated volume. For example, as breast cancer treat- ment techniques have evolved to reduce cardiac exposure, there has been a steady decline in the RR for RT-associated events (32). In the Stanford HL series, the RR of death from cardiac causes (other than MI) was decreased with use of subcarinal blocking from 5.3 to 1.4 (17). In the large study in the Netherlands, the risk of valvular dysfunction was higher in the group receiving IMN RT vs. the group with no RT (HR = 3.17) (12). Furthermore, whole pericardial irradiation can lead to a high rate of pericarditis that is reduced with shielding of the left ventricular and subcarinal areas (3). Dose is similarly important. In the Stanford series of children and adolescents with Hodgkin’s disease (HD), all of the excess deaths from heart disease were in the patients receiving 42 to 45 Gy (16). Boivin et al. noted that the ante- riorly placed coronary arteries were more often affected by RT (compared with the circumflex artery) (19). In HL, the frequency of both aortic and mitral stenosis and regurgitation is increased, with a threshold RT dose of $30 Gy (20). In this report, 42.6% of patients had at least one significant valve ab- normality. Additional dose/volume data are reviewed later in the text. 5. FACTORS AFFECTING RISK Evidence suggests that the risk of RT-associated heart disease may be affected by baseline patient cardiac risk factors and cardiotoxic chemotherapy. All of these investiga- tions are retrospective in design. Patient risk factors Large population studies have identified factors associated with cardiac disease. Well-validated models such as the Framingham and Reynolds risk models can estimate the risk of future cardiac events based on the presence, number, and severity of baseline cardiac risk factors (33–35) such as age, gender, diabetes mellitus (and hemoglobin A1c), smok- ing, hypertension, total cholesterol, low- and high-density lipoprotein cholesterols, high-sensitivity C-reactive protein, and parental history of early MI at age 60 years. In patients with breast cancer, a multi-institutional study of $10-year survivors noted that smoking and RT synergisti- cally increased the rate of fatal MI (HR = 3.04 vs. no smok- ing/no RT) (12). Similarly, synergy was noted between hypertension and left-sided RT for causing CAD Table 2. Pericarditis/pericardial effusion: Dose–volume predictors and NTCP parameters Authors, Year, Reference Diagnosis, No. of patients, Years of treatment OAR Fractionation schedule, dose data Predictive parameters NTCP parameters Carmel and Kaplan* 1976 (3) Hodgkin’s 377 Patients 1964–1972 Pericardium D pericardium 30 Gy 50% pericarditis, 36% requiring treatment Cosset et al. 1991 (65) Hodgkin’s 499 Patients 1971–1984 35–43 Gy/ 2.5–3.3 Gy/fraction pre-3D dose data D Mediastinum $ 41 Gy d/ fraction $ 3 Gy (marginal significance) Burman et al. 1991 (66) Historical data LKBy TD50 = 48 Gy m = 0.10 n = 0.35 Martel et al. 1998 (26) Esophagus 57 Patients 1985–1991 Pericardium 37.5–49 Gy/ 1.5–3.5 Gy / fraction 3D data Dmean 27.1 Gyz Dmax 47 Gyz d/ fraction 3.5 Gy LKB (95% CI) TD50 = 50.6 Gy (–9; 23.1) m = 0.13 (–0.07; 0.13) n = 0.64 (–0.58; 3) Wei et al. 2008 (27) Esophagus 101 Patients 2000–2003 Pericardium 45–50.4 Gy 1.8–2.0 Gy/fraction 3D data Dmeanpericardium 26.1 Gy V30 46% Abbreviations: CI = confidence interval; LKB = Lyman-Kutcher-Burman (model); OAR = organs at risk; NTCP = normal tissue complica- tion probabilities. * Patients were grouped according to the estimated pericardium doses. Incidence of pericarditis was distributed as follows: 14/198 (7%): #6 Gy; 5/42 (12%): 6–15 Gy;23/123 (19%): 15–30 Gy; 7/14 (50%): 30 Gy. For pericarditis requiring treatment the corresponding distribution was: 3/198 (1.5%), 4/42 (9.5%), 8/123 (6.5%), and 5/14 (36%). y In the LKB model (47, 66) the parameters meaning is TD50: dose to the whole organ which will lead to complication in 50% of the pop- ulation; m is related to the steepness of the dose–response curve, n represents the volume effect (large volume effect for n close to unity; small volume effect for n close to zero). z Corrected to 2 Gy per fraction, a/b = 2.5 Gy. Radiation dose–volume effects in the heart d G. GAGLIARDI et al. S79
- 80. (HR = 11.4vs. right-sided RT without hypertension) (10). The impact of age is unclear, but some studies implicate age 60 years (8), vs. age 50 or 60 years (36), to be associ- ated with MI post-RT. Adult HL survivors with adverse cardiac risk factors (older age, obesity, hypertension, family history of cardiac disease, abnormal lipoprotein levels, and smoking) have an increased risk for cardiac morbidity (37). Treatment risk factors Anthracycline-containing chemotherapy regimens for treatment of breast cancer and Hodgkin’s lymphoma are used routinely. Without RT, anthracyclines are known to have a cumulative dose-dependent risk of dilated cardiomy- opathy and CHF, with a 1% to 5% risk with doses 550 mg/m2 for doxorubicin and 900 mg/m2 for epirubicin, and a sharp increase in risk thereafter (38, 39). In fact, lower doses appear to be associated with cardiac injury in children. Con- gestive heart failure may be wholly or partially reversible with medications such as angiotensin-converting enzyme inhibitors or b-blockers (40). The long-term risk of CHF, especially in patients also treated with paclitaxel and among elderly women, may be higher (41, 42). Fewprospectivestudieshaveaddressedpotential synergistic effects of RT and cardiotoxic chemotherapy among breast can- cer patients. A single institution randomized trial designed to evaluate cardiotoxicity with 10 vs. five cycles of doxorubicin (A) (45 mg/m2 ) and cyclophosphamide (C) (500 mg/m2 ) che- motherapy reported results from a retrospective subgroup anal- ysisamong patients treatedwith RT (43). With a 6-year median follow-up, a significant increase in cardiac events was found among patients receiving 10 cycles of chemotherapy and RT Table 3. Cardiac mortality from ischemic heart disease/myocardial infarction: Dose–volume predictors and NTCP parameters Authors, Year, Reference Diagnosis, No. of patients, Years of treatment OAR Dose data Predictive parameters NTCP parameters Hancock et al. 1993 (17) Hodgkin’s 2232 patients 1960–1990 Heart Dose up to 44 Gy Pre-3D dose data D mediastinum 30 Gy Gagliardi et al. 1996 (25) Breast 809 patients 1964–1976 Heart* 45–50 Gyy 1.8–2.5 Gy/fraction treatments reconstructed in 3D on average patients RSz (CI 68%) D50 = 52.3 Gy (49;57) g = 1.28 (1.04;1.64) s = 1 (0.63; at limit) Eriksson et al. 2000x (51) Hodgkin’s 157 patients 1972–1985 Heart $40 Gyk 2 Gy/fraction Individual treatments reconstructed in 3D on phantom D35 38 Gy RS: Hodgkin’s D50 = 70.3 Gy g = 0.96 s = 1 RS: Hodgkin’s + breast D50 = 63 Gy g = 0.94 s = 1 Carr et al. 2005 (52) Peptic ulcer, 1,859 patients, 1936–1965 Heart (Alderson Phantom) 1.5 Gy /fraction 250-kVp X-rays Treatment simulated on phantom Dmean to 5% 12 Gy heart volume within the beam Dmean 2.5 Gy whole heart volume Paszat et al 2007 (6) Breast, 619 patients, 1982–1988 Heart 40–50 Gy 2–2.67 Gy/fraction to breast{ Pre-3D dose data RT to Internal Mammary Chain Abbreviations: CI = confidence interval; NTCP = normal tissue complication probabilities; OAR = organs at risk; RS = relative seriality (model). * Heart was contoured from infundibulum of right ventricle, right atrium and right atrium auricle, and excluded the pulmonary trunk, ascend- ing aorta, and superior vena cava down to the most caudal slices. Analysis was also performed on the myocardium, providing similar results. y DVH corrected to 2 Gy per fraction, a/b = 3 Gy. z In the RS model, parameter meanings are, respectively: D50 is the dose to the whole organ that will lead to complications in 50% of the population; g is the normalized dose–response gradient; s reflects the degree to which the organ architecture is considered to be serial (s = 1) or parallel (s = 0) (49). x In this study, NTCP analysis was performed also jointly with breast cancer data. It should be emphasized that the use of the steeper dose– volume response curve, i.e., only breast (25), represents a more conservative and thus safer approach. k Note that the prescribed dose here ranged between 7 and 45 Gy but that 43% of patients were treated to 40 Gy and 37% to 42 Gy. Dose– volume histograms were corrected to 2 Gy/fraction, a/b = 3 Gy. { Treatment also involved an anterior boost of 5–20 Gy in 2–3 Gy to breast; photon, or electron anterior Internal Mammary Chain field with total dose of 40–55 Gy in 1.8- to 3.7-Gy fractions. S80 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 81. as compared withestimated baseline cardiovascular risk. In three doxorubicin-based trials (mean dose, 294 mg/m2 ), the rate of CHF was four in 116 vs. two in 521 in patients with vs. without left-sided RT, respectively (p = 0.012). With me- dianfollow-up of only 1.5 years,noincreased frequency of car- diaceventshas beenidentifiedwiththe use oftrastuzumab with doxorubicin and RT vs. no RT (44). A report on 1,474 HL survivors #41 years of age at the time of treatment and followed for a median of 18.7 years provided data of the combined effects of anthracyclines and RT (45). The risks of MI and CHF were increased with stan- dardized incidence ratios of 3.6 and 4.9 respectively, result- ing in 35.7 excess cases of MI and 25.6 of CHF per 10,000 patient/year. Mediastinal RT increased the risks of MI, angina pectoris, CHF and valvular disorders (2- to 7-fold), anthracy- clines significantly added to the elevated risks of CHF and valvular disorders from mediastinal RT, with HRs of 2.81 and 2.10, respectively. The 25-year cumulative incidence of CHF and combined RT and anthracyclines was 7.9%. 6. MATHEMATICAL/BIOLOGICAL MODELS Tables 2 to 4 summarize dose–volume constraints and normal tissue complication probability (NTCP) parameter values for pericarditis, cardiac mortality, and perfusion defects, respectively. Pericarditis/pericardial effusion Several studies conducted over a long period of time, in- cluding pre–three-dimensional (3D) and modern 3D data, note correlation between dose–volume parameters and the pericarditis risk (Table 2). Stewart and Fajardo (46) compiled data from several institutions: in patients with HL in whom the RT field was estimated to include $50% of the external heart contour, the overall pericarditis rate was 6%. There ap- peared to be a steep dose response, with an incidence #5% for low nominal standard doses (NSD; # 1,300 rets com- puted using the NSD formalism), vs. a 5% to 10% rate for $1,400 to 1,600 rets and a rate of $30% for $1,600 rets. A similar steep dose response was seen in patients with breast cancer in whom the irradiated volumes were smaller, with a 0%, $4%, and $20% incidence of pericarditis for 1,800, $1,900, and 2,000 rets, respectively (46). In Car- mel and Kaplan’s classic report, in HL, the high rate of peri- carditis seen with whole pericardial irradiation was reduced to 7% with left ventricle (LV) shielding and to 2.5% with more extended shielding after 30 Gy (3). Two studies on esophageal cancer considered 3D-derived data (26, 27). Martel et al. (26) implicated fraction size as a predictor for pericarditis (e.g., no cases occurring in patients receiving 3.5 Gy/fraction). The mean and maximum doses of 27.1 and 47.0 Gy (corrected for fractionation with a/b = 2.5 Gy) were predictors of pericarditis (p = 0.014) (Table 2). Parameter values were fit to the Lyman-Kutcher-Burman (LKB) model (47). Wei et al. reported that a variety of DVH-based parameters (e.g., V3 to V50 and mean dose) predicted for pericardial effusions. The dosimetric parame- ters were highly correlated with each other, making compar- isons of their predictive abilities difficult. Nevertheless, V30 46% was found to be a discriminator: the risk of effusion was 13% with a V30 46 Gy (or mean pericardial dose 26 Gy) vs. 73% in patients with a V30 46 Gy (or mean dose 26 Gy) (27) (Table 2). Long-term cardiac mortality Data for this endpoint are derived from retrospective stud- ies of patients treated with outdated techniques and target def- initions. The dose–volume constraints and NTCP parameters reported are therefore affected by the intrinsic inaccuracies of the dosimetric data. Some results are reported in Table 3. Patients with HL have an increased rate of cardiac mortal- ity with whole heart doses 30 Gy, in agreement with results from pathological studies (17). A few studies, based on model estimates of 3D dose/ volumes, suggest that dose and, to a lesser degree the irradi- ated volume, are important parameters. A dose–response curve for cardiac mortality has been derived (25) based on the data from two breast cancer randomized trials of surgery with or without RT, which showed an increased cardiac mor- tality in the RT group (5, 48). The data were fit to an NTCP model (49) (Table 3). The value of s = 1 (s being the param- eter related to tissue architecture) suggests a limited volume Table 4. Cardiac perfusion defects: Dose–volume predictors and NTCP parameteters Authors, Year, Reference Diagnosis, No. of patients, Years of treatment OAR Fractionation schedule, Dose data Predictive parameters NTCP parameters Das et al. 2005 (28) Breast 73 Patients, 1998 (started) Left ventricle contoured on SPECT 45–60 Gy/ 1.8–2.0 Gy/fr Individual 3D data Left ventricular volume V23, V33 RS (95% CI) D50 = 12 Gy (8;24) g = 0.6 (0.4;4.6) s = 1 (0.6;1) LKB* (95% CI): TD50 = 29 Gy (18;44) s (dose var) = 12 Gy (8;35) a = 6.3 (2.5;9.8) Abbreviations: 3D = three-dimensional; CI = confidence interval; LKB = Lyman-Kutcher-Burman (model); NTCP = normal tissue compli- cation probabilities; OAR = organs at risk; RS = relative seriality (model). * Conventionally the parameters m and n are used in the LKB model. In this case s = m x TD50 and a = 1/n. Radiation dose–volume effects in the heart d G. GAGLIARDI et al. S81
- 82. dependence. A jointanalysis of the breast cancer and Hodg- kin’s material (50, 51) yielded higher D50 (i.e., dose giving 50% of complication probability) and a lower g (steepness) values than in the breast analysis (Fig. 1); note that different parts of heart are irradiated in the two situations. Carr et al. examined the long-term outcomes of patients treated for peptic ulcer disease between 1937 and 1965 using (typically) orthovoltage RT, with the field including a portion of the cardiac apex (estimated 5% of heart volume) but only a small part of the coronary vessels (52). The RR of coronary artery disease was increased in patients in whom the (in-field) cardiac apex dose exceeded $12 Gy, corresponding to an estimated mean heart dose 2.6 Gy. Similarly, in 4,414 breast cancer survivors with a minimum of 10 years of follow-up treated between 1970 and 1986, the risk of cardiovascular dis- ease was found to increase with mean cardiac doses (12). The maximum heart distance (MHD), that is, the maximum dis- tance from the posterior edge of the tangent field to the heart contour, has been proposed as a surrogate for the irradiated heart volume in the high-dose region in patients treated with tangential fields (53). However, in 1,601 breast patients with 0 to 24 years (median, 16 years) of follow-up, there was no clear association between the MHD and cardiovascular disease risk; the potential role of low heart doses was discussed (13). Cardiac perfusion defects Extensive analysis of perfusion defects induced by radio- therapy in the left ventricle have been prospectively carried out in a group of 73 breast cancer patients (Table 4). Subclin- ical injury, inferred from abnormalities on regional myocar- dial perfusion imaging tests, occurred in a volume- dependent manner: an incidence of 20% was found for tan- gential fields including 5% of the LV vs. 50% with 5% LV volume (54). Two NTCP models (LKB and relative seriality[RS]) were fitted to the data (28). A serial behavior of the LV is suggested by the fit with the RS model; however, the D50 values obtained from the two fits were mutually inconsistent. The clinical siginificance of these perfusion defects has not been clearly established (54). 7. SPECIAL SITUATIONS Several aspects, both general and heart specific, have to be considered when applying NTCP models and dose–volume constraints to clinical treatment planning. First, there are anatomical and functional considerations in defining the organ or parts of the organ at risk, e.g., heart vs. pericardium vs. coronary vessels. For example, applying peri- carditis NTCP parameters obtained from the pericardium dose distribution to the whole heart is more acceptable in a calcula- tion and/or comparison exercise than in clinical situations. The recent study by Wei et al. suggests that clinical data on pericar- dial effusions are better correlated with parameters derived from the dose–volume histograms (DVHs) of the pericardium than with those of the whole heart (27). Second, the irradiated heart in patients with breast cancer is at or beyond the field edges. In these volumes, the accuracy of the dose calculations varies between different treatment plan- ning systems (TPS) (55) and influences NTCP modelling, due to the differences in heart dose calculated; even small dif- ferences might be relevant if NTCP should be kept low. Third, if inhomogeneity corrections for the low density of lung tissue are not made in the treatment plan, the heart dose is underestimated, thus affecting the evaluation of the dosi- metric predictors (56). Fourth, because of differences in setup accuracy, the planned and actual cardiac exposures can vary, with implica- tions for the estimated NTCP (57). Fifth,theparametersderivedforthevariousmodelsarebased on limited clinical data in a reduced number of diseases and which generally do not involve a wide range of fraction sizes. Therefore, these models may not be applicable in the evolving era of hypofractionation and in a broader range of diseases. Finally, concerning the applicability of the results obtained, the main criterion remains diagnosis. Dosimetric modeling data may be most applicable in the disease setting from which they were derived. For example it may be questionable to ap- ply results based on Hodgkin’sdisease studies to breast cancer cases, considering the different irradiated volumes. 8. RECOMMENDED DOSE/VOLUME LIMITS Radiation-induced cardiac complications have different significance and implications depending on the clinical scenario. As such constraints/NTCP values can be used only for guidance; they must always be considered in relation to probability of tumor control and the specific patient Fig. 1. Dose–response curves for long-term cardiac mortality based on Hodgkin’s disease (HD) and breast cancer data sets. From Eriks- son et al. (51), with permission. Curves were obtained by fitting, re- spectively, Stockholm and Oslo breast cancer trials data (25) (denoted ‘‘Breast’’ in the figure); data from a patient cohort treated for HD (denoted ‘‘Hodgkin’’), the joint material (denoted ‘‘Hodgkin + Breast’’). Plotted curve corresponds to a uniform irradiation of one third of the heart volume, in the interval of the clinical data. Param- eter values are also reported. Note that in the interval of the clinical and dosimetric data of interest, the curve from breast data only is much steeper than the other curves. S82 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 83. situation. Nevertheless, thefollowing broad dose/volume guidelines are suggested. In patients with breast cancer, it is recommended that the irradiated heart volume be minimized to the greatest possible degree without compromising the target coverage. In many cases, conformal blocking and breath-hold techniques can essentially eliminate the heart from the primary beams. If NTCP models for cardiac mortality are used, it should be considered that an NTCP value $5% could jeopardise the beneficial effect on survival of RT (1). So as not to underes- timate this risk, the most conservative approach is provided by the use of the steeper dose–response curve (Fig. 1), that is, the one from the breast data (25). For partial irradiation, conservative (NTCP) model-based estimates predict that a V25Gy 10% (in 2 Gy per fraction) will be associated with a 1% probability of cardiac mortality $15 years after RT. For this a conservative (i.e., overly safe) model was used that may overestimate the risk. Conversely, as the time horizon (i.e., follow-up interval) used is modest, this may underestimate the risk. In general, when applying NTCP models, it is recommended that the user be aware of the assumptions involved in the parametrisations, for exam- ple, organ at risk definition, corrections for fractionation, dose calculation algorithms, and confidence intervals. It is rare in the modern era to treat lymphoma with radia- tion but without chemotherapy. Historically, whole heart doses up to 30 Gy were reasonably well tolerated (17). For the vast majority of lymphoma patients who receive chemo- therapy (particularly doxorubicin) and RT, it seems prudent to limit whole heart doses to $15 Gy, with field reductions, as appropriate in the given clinical situation, to areas of per- sistent (post-chemotherapy) residual tumor or to areas of pre- vious bulky involvement. For pericarditis, according to the Wei et al. study, the risk increases with a variety of dose parameters, such as mean pericardium dose 26 Gy, and V30 46% (27). NTCP param- eters as in Table 2 can be considered for clinical studies (26). Care should be taken to differentiate between the DVHs for the heart vs. the pericardium. Even though the relevance of perfusion defects as a clinical endpoint is questionable, evidence of subclinical myocardial injury has been demonstrated and might be relatively com- mon. The irradiated volume of the left ventricle has been shown to be the most important predictor of a perfusion defect. Although currently there is no direct evidence that success- ful treatment of traditional cardiac risk factors will alter the natural history of radiation-associated cardiac disease, it is prudent to optimize patient cardiovascular risk profiles (58–60). 9. FUTURE TOXICITY STUDIES Improved toxicity prediction requires prospective clinical trials based on 3D dosimetric data and careful long-term fol- low-up of patients who have received potentially cardiotoxic chemotherapy and RT. Prospective cardiac mortality studies are unlikely to be numerous. Hopefully, the few existing dose–volume predictors for cardiac mortality will be modi- fied by new retrospective analyses based on larger data sets, in which dose to the left descending artery will also be considered. Future longitudinal studies on pericarditis and on perfusion defects are to be expected. The following points should be kept in mind: a) Additional work is needed to better evaluate whether the modern radiotherapy treatment approaches for patients with breast cancer are associated with significant cardiac toxicity. The clinical relevance of the perfusion abnormal- ities, observed despite modern techniques, needs clarifica- tion. b) Additional study is needed to relate doses to subvolumes of the heart (e.g., coronary arteries) to clinical outcomes. Computed tomography contrast could be useful for defin- ing the heart borders. Additional studies are indeed needed in radiation-treated patients with other thoracic tu- mors (e.g., lung cancer), in whom an increased rate of heart disease has been noted (61 ,62) but dose–volume data are lacking. c) Future studies should incorporate baseline cardiovascular risk factors, such as the Framingham or Reynolds score (33–35). This will allow consideration of potential interac- tive effects between RT and traditional cardiac risk factors. d) Additional work is needed to understand the impact of hypofractionated radiation regimens on the heart. e) A deeper understanding of the global physiological effects of thoracic RT is needed (e.g., interactions be- tween the heart and lung irradiation, as suggested in some animal studies) (63). 10. TOXICITY SCORING We recommend that the LENT-SOMA system (64) be considered to describe cardiac effects, as it explicitely addresses clinical, radiological, and functional assessments of cardiac dysfunction. REFERENCES 1. Early Breast Cancer Trialists’ Collaborative Group. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: An over- view of the randomized trials. Lancet 2005;366:2087–2106. 2. Aleman BM, Belt-Dusebout AW, Klokman WJ, et al. Long- term cause-specific mortality of patients treated for Hodgkin’s disease. J Clin Oncol 2003;21:3431–3439. 3. Carmel RJ, Kaplan HS. Mantle irradiation in Hodgkin’s disease. An analysis of technique, tumour eradication, and complica- tions. Cancer 1976;37:2813–2825. 4. Ragaz J, Olivotto IA, Spinelli JJ, et al. Locoregional radiation therapy in patients with high-risk breast cancer receiving adju- vant chemotherapy: 20-Year results of the British Columbia randomized trial. J Natl Cancer Inst 2005;97:116–126. Radiation dose–volume effects in the heart d G. GAGLIARDI et al. S83
- 84. 5. Høst H,Brennhovd I, Loeb M. Postoperative radiotherapy in breast cancer - long term results from the Oslo study. Int J Radiat Oncol Biol Phys 1986;12:727–732. 6. Paszat LF, Vallis KA, Benk VM, et al. A population-based case-cohort study of the risk of myocardial infarction following radiation therapy for breast cancer. Radiother Oncol 2007;82: 294–300. 7. Darby SC, McGale P, Taylor CW, et al. Long-term mortality from heart disease and lung cancer after radiotherapy for early breast cancer: Prospective cohort study of about 300,000 women in US SEER cancer registries. Lancet Oncol 2005;6:557–565. 8. Paszat LF, Mackillop WJ, Groome PA, et al. Mortality from myocardial infarction following postlumpectomy radiotherapy for breast cancer: A population-based study in Ontario, Canada. Int J Radiat Oncol Biol Phys 1999;43:755–761. 9. Højris I, Overgaard M, Christensen JJ, et al. Morbidity and mor- tality of ischemic heart disease in high-risk breast cancer patients after adjuvant postmastectomy systemic treatment with or without radiotherapy: Analysis of DBCG 82b and 82c randomized trials. Lancet 1999;354:1425–1430. 10. Harris EE, Correa C, Hwang WT, et al. Late cardiac mortality and morbidity in early-stage breast cancer patients after breast- conservation treatment. J Clin Oncol 2006;24:4100–4106. 11. Correa CR, Litt HI, Hwang WT, et al. Coronary artery findings after left-sided compared with right-sided radiation treatment for early-stage breast cancer. J Clin Oncol 2007;25:3031–3037. 12. Hooning MJ, Botma A, Aleman BM, et al. Long-term risk of cardiovascular disease in 10-year survivors of breast cancer. J Natl Cancer Inst 2007;99:365–375. 13. Borger JH, Hooning MJ, Boersma LJ, et al. Cardiotoxic effects of tangential breast irradiation in early breast cancer patients: The role of irradiated heart volume. Int J Radiat Oncol Biol Phys 2007;69:1131–1138. 14. Prosnitz RG, Hubbs JL, Evans ES, et al. Prospective assessment of radiotherapy-associated cardiac toxicity in breast cancer pa- tients: Analysis of data 3 to 6 years after treatment. Cancer 2007;110:1840–1850. 15. Gyenes G, Fornander T, Carlens P, et al. Morbidity of ischemic heart disease in early breast cancer 15–20 years after adjuvant radiotherapy. Int J Radiat Oncol Biol Phys 1994;28:1235–1241. 16. Hancock SL, Donaldsson SS, Hoppe RT. Cardiac disease following treatment of Hodgkin’s disease in children and ado- lescents. J Clin Oncol 1993;11:1208–1215. 17. Hancock SL, Tucker MA, Hoppe RT. Factors affecting late mortality from heart disease after treatment of Hodkgin’s disease. J Am Med Assoc 1993;270:1949–1955. 18. Swerdlow AJ, Higgins CD, Smith P, et al. Myocardial infarc- tion mortality risk after treatment for Hodgkin disease: A collab- orative British cohort study. J Natl Cancer Inst 2007;99:206– 214. 19. Boivin JF, Hutchison GB, Lubin JH, et al. Coronary artery disease mortality in patients treated for Hodgkin’s disease. Can- cer 1992;69:1241–1247. 20. Adams MJ, Lipsitz SR, Colan SD, et al. Cardiovascular status in long-term survivors of Hodgkin’s disease treated with chest ra- diotherapy. J Clin Oncol 2004;22:3139–3148. 21. Glanzmann C, Huguenin P, Lutolf UM, et al. Cardiac lesions after mediastinal irradiation for Hodgkin’s disease. Radiother Oncol 1994;30:43–54. 22. Lund MB, Ihlen H, Voss BM, et al. Increased risk of heart valve regurgitation after mediastinal radiation for Hodgkin’s disease: An echocardiographic study. Heart 1996;75:591–595. 23. Heidenreich P, Hancock S, Lee B, Mariscal C, Schnittger I. Asymptomatic cardiac disease following mediastinal irradia- tion. J Am Coll Cardiol 2003;42:743–749. 24. Jagsi R, Moran JM, Kessler ML, et al. Respiratory motion of the heart and positional reproducibility under active breathing con- trol. Int J Radiat Oncol Biol Phys 2007;68:253–258. 25. Gagliardi G, Lax I, Ottolenghi A, et al. Long-term cardiac mor- tality after radiotherapy of breast cancer – application of the rel- ative seriality model. Br J Radiol 1996;69:839–846. 26. Martel MK, Sahijdak WM, Ten Haken RK, et al. Fraction size and dose parameters related to the incidence of pericardial effu- sions. Int J Radiat Oncol Biol Phys 1998;40:155–161. 27. Wei X, Liu HH, Tucker SL, et al. Risk factors for pericardial effusion in inoperable esophageal cancer patients treated with definitive chemoradiation therapy. Int J Radiat Oncol Biol Phys 2008;70:707–714. 28. Das SK, Baydusch AH, Zhou S, et al. Predicting radiotherapy- induced cardiac perfusion defects. Med Phys 2005;32:19–27. 29. Nieder C, Schill S, Kneschaurek, et al. Influence of different treatment techniques on radiation dose to the LAD coronary ar- tery. Radiat Oncol 2007;2:20. 30. Taylor CW, Nisbet A, McGale P, et al. Cardiac exposures in breast cancer radiotherapy: 1950s–1990s. Int J Radiat Oncol Biol Phys 2007;69:1484–1495. 31. Taylor CW, Povall JM, McGale P, et al. Cardiac dose from con- temporary tangential breast cancer radiotherapy in the year 2006. Int J Radiat Oncol Biol Phys 2008;72:501–507. 32. Giordano SH, Kuo Y, Freeman JL, et al. Risk of cardiac death after adjuvant radiotherapy for breast cancer. J Natl Cancer Inst 2005;97:419–424. 33. Wilson PW, D’Agostino RB, Levy D, et al. Prediction of coro- nary heart disease using risk factor categories. Circulation 1998;97:1837–1847. 34. Grundy SM, Pasternak R, Greenland P, et al. AHA/ACC scien- tific statement: Assessment of cardiovascular risk by use of mul- tiple-risk-factor assessment equations: A statement for healthcare professionals from the American Heart Association and the American College of Cardiology. J Am Coll Cardiol 1999;34:1348–1359. 35. Ridker PM, Buring JE, Rifai N, et al. Development and valida- tion of improved algorithms for the assessment of global cardio- vascular risk in women: The Reynolds score. J Am Med Assoc 2007;297:611–619. 36. Hooning MJ, Aleman BM, van Rosmalen AJ, et al. Cause-spe- cific mortality in long-term survivors of breast cancer: A 25- year follow-up study. Int J Radiat Oncol Biol Phys 2007;64: 1081–1091. 37. King V, Constine LS, Clark D, et al. Symptomatic coronary ar- tery disease after mantle irradiation for Hodgkin’s disease. Int J Radiat Oncol Biol Phys 1996;36:881–889. 38. Von Hoff DD, Layard MW, Basa P, et al. Risk factors for doxo- rubicin-induced congestive heart failure. Ann Intern Med 1979; 91:710–717. 39. Ryberg M, Nielsen D, Skovsgaard T, et al. Epirubicin cardio- toxicity: An analysis of 469 patients with metastatic breast can- cer. J Clin Oncol 1998;16:3502–3508. 40. Cardinale D, Colombo A, Sandri MT, et al. Prevention of high- dose chemotherapy-induced cardiotoxicity in high-risk patients by angiotensin-converting enzyme inhibition. Circulation 2006;114:2474–2481. 41. Doyle JJ, Neugut AI, Jacobson JS, et al. Chemotherapy and car- diotoxicity in older breast cancer patients: A population-based study. J Clin Oncol 2005;23:8597–8605. 42. Gianni L, Dombernowsky P, Sledge, et al. Cardiac function fol- lowing combination therapy with paclitaxel and doxorubicin: An analysis of 657 women with advanced breast cancer. Ann Oncol 2001;12:1067–1073. 43. Shapiro CL, Hardenbergh PH, Gelman R, et al. Cardiac effects of adjuvant doxorubicin and radiation therapy in breast cancer patients. J Clin Oncol 1998;16:3493–3501. 44. Halyard MY, Pisansky TM, Dueck AC, et al. Radiotherapy and adjuvant trastuzumab in operable breast cancer: tolerability and adverse event data from the NCCTG phase III trial N9831. J Clin Oncol 2009;27(16):2638–2644. S84 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 85. 45. Aleman BM,van den Belt-Dusebout AW, De Bruin ML, et al. Late cardiotoxicity after treatment for Hodgkin lymphoma. Blood 2007;109:1878–1886. 46. Stewart JR, Fajardo LF. Dose response in human and experi- mental radiation-induced heart disease. Application of the nom- inal standard dose (NSD) concept. Radiology 1971;99:403–408. 47. Lyman JT. Complication probabilities as assessed from dose- volume histograms. Rad Res Suppl 1985;8:S13–S19. 48. Rutqvist LE, Lax I, Fornander T, Johansson H. Cardiovascular mortality in a randomized trial of adjuvant radiation therapy versus surgery alone in primary breast cancer. Int J Radiat On- col Biol Phys 1992;22:887–896. 49. Ka¨llman P, A˚ gren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol 1992;62:249–262. 50. Gagliardi G, Lax I, Rutqvist LE. Partial irradiation of the heart. Semin Radiat Oncol 2001;7:224–233. 51. Eriksson F, Gagliardi G, Liedberg A, et al. Long-term cardiac mortality following radiation therapy for Hodgkin’s disease: Analysis with the relative seriality model. Radiother Oncol 2000;55:153–162. 52. Carr ZA, Land CE, Kleinerman RA, et al. Coronary heart disease after radiotherapy for peptic ulcer disease. Int J Radiat Oncol Biol Phys 2005;61:842–850. 53. Hurkmans CW, Borger JH, Bos LJ, et al. Cardiac and lung complication probabilities after breast cancer irradiation. Radio- ther Oncol 2000;55:145–151. 54. Marks LB, Yu X, Prosnitz RG, et al. The incidence and func- tional consequences of RT-associated cardiac perfusion defects. Int J Radiat Oncol Biol Phys 2005;63:214–223. 55. Polednik M, Abo Madyan Y, Schenider F, et al. Evaluation of calculation algorithms implemented in different commer- cial planning systems on an anthropomorphic breast phan- tom using film dosimetry. Strahlenther Onkol 2007;183: 667–672. 56. Gagliardi G, Lax I, So¨derstro¨m S, et al. Prediction of excess risk of long-term cardiac mortality after radiother- apy of stage I breast cancer. Radiother Oncol 1998;46:63– 71. 57. Louwe RJ, Wendling M, van Herk MB, Mijnheer BJ. Three- dimensional dose reconstruction to estimate normal tissue complication probability after breast irradiation using portal dosimetry. Med Phys 2007;34:1354–1363. 58. Executive Summary of the Third Report of the National choles- terol Education Program (NCEP) Expert Panel on Detection. Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). J Am Med Assoc 2001;285:2486– 2497. 59. Mosca L, Banka CL, Benjamin EJ, et al. Evidence-based guide- lines for cardiovascular disease prevention in women: 2007 Update. J Am Coll Cardiol 2007;49:1230–1250. 60. Jones LW, Haykowsky MJ, Swartz JJ, et al. Early breast cancer therapy and cardiovascular injury. J Am Coll Cardiol 2007;50: 1435–1441. 61. Dautzenberg B, Arriagada R, Chammard AB, et al. A controlled study of postoperative radiotherapy for patients with completely resected nonsmall cell lung carcinoma. Cancer 1999;86:265– 273. 62. Lally BE, Detterbeck FC, Geiger AM, et al. The risk from heart disease in patients with non small cell lung cancer who receive postoperative radiotherapy. Analysis of the Surveillance, Epide- miology, and End Results Database. Cancer 2007. 63. Van Luijk P, Faber H, Meertens H, et al. The impact of heart irradiation on dose-volume effects in the rat lung. Int J Radiat Oncol Biol Phys 2007;69:552–559. 64. LENT-SOMA scales for all anatomic sites. Int J Radiat Oncol Biol Phys 1995;31(1049). 1091. 65. Cosset JM, Henry-Amar M, Meerwaldt JH. Long-term toxicity of early stages of Hodgkin’s disease therapy: The EORTC expe- rience. EORTC Lymphoma Cooperative Group. Ann Oncol 1991;S2:77–82. 66. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. Radiation dose–volume effects in the heart d G. GAGLIARDI et al. S85
- 86. QUANTEC: ORGAN-SPECIFIC PAPERThorax: Esophagus RADIATION DOSE-VOLUME EFFECTS IN THE ESOPHAGUS MARIA WERNER-WASIK, M.D.,* ELLEN YORKE, PH.D.,y JOSEPH DEASY, PH.D.,z JIHO NAM, M.D.,x AND LAWRENCE B. MARKS, M.D.x *Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA; y Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY; z Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO; x Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC Publications relating esophageal radiation toxicity to clinical variables and to quantitative dose and dose–volume measures derived from three-dimensional conformal radiotherapy for non–small-cell lung cancer are reviewed. A variety of clinical and dosimetric parameters have been associated with acute and late toxicity. Suggestions for fu- ture studies are presented. Ó 2010 Elsevier Inc. Esophagitis, Lung cancer, Radiotherapy, Esophagus, Toxicity. 1. CLINICAL SIGNIFICANCE Acute esophagitis (occurring #90 days after treatment in- itiation) is a common side effect of patients undergoing radiotherapy (RT) for thoracic tumors. Concurrent chemora- diotherapy (CCT) or hyperfractionation results in a 15–25% rate of severe (Radiation Therapy Oncology Group [RTOG] Grade 3 or greater) acute esophagitis (1–3) that can require hospitalization, invasive diagnostic tests (e.g., endoscopy), surgical intervention (e.g., percutaneous endoscopic gastro- stomy tube) or RT breaks that could lower local tumor control. Late injury is less commonly reported, perhaps because the patients might not live long enough to manifest toxicity (e.g., the disease-specific survival is relatively short for many tho- racic cancers). Dose escalation of standard fractionated RT and hypofractionated RT regimens (4, 5) can increase the risk of late esophageal toxicity, especially if the survival rates improve. Esophageal stricture often requires periodic dila- tion, usually with good results (6). Death related to late esophageal injury (e.g., tracheoesophageal fistula or esop- hageal perforation) has been reported in only 0.4–1% of patients (7, 8). 2. ENDPOINTS The assigned toxicity grade varies with the scoring system used, making interstudy comparisons challenging. In general, Grade 1 toxicities cause minor changes in a patient’s lifestyle, and Grade 2 or greater toxicities might require medical inter- vention. The currently accepted grading system is the Com- mon Terminology Criteria for Adverse Events, version 3 (9); however, the studies cited in the present report mostly used the RTOG scoring system. In the present review, Grade 2 or greater acute esophagitis (because it constituted the end- point of many studies) and any late esophagitis (Grade 1 or greater), independent of the duration of the late symptoms, were considered clinically significant. Acute esophagitis occurs during RT and often persists for several weeks after RT. The symptoms of severe esophagitis (Grade 3 or greater) typically peak 4–8 weeks from the begin- ning of RT (10). Late esophageal damage, typically stricture and associated dysphagia, develops $3–8 months (range, 5– 40) after RT (11). Abnormal esophageal motility can be noted within 3–4 weeks from RT alone and as early as 1 week after starting concurrent chemoradiotherapy (12). Some of the pitfalls in assigning the acute esophagitis grade are as follows: 1. Esophageal infection can mimic treatment (RT or concur- rent chemoradiotherapy)-related esophagitis. Candidiasis (usually suggested by co-existing oral candidiasis) or, rarely, herpes simplex esophagitis are the main culprits. 2. Pre-existing gastroesophageal reflux can worsen the symptoms of esophagitis and should be treated. Constant burning, unrelated to the act of swallowing, and localized in the lower part of the esophagus is more likely related to the reflux than to the treatment-related esophagitis. Reprint requests to: Maria Werner-Wasik, M.D., Department of Radiation Oncology, Thomas Jefferson University Hospital, 111 S. 11th St., Philadelphia, PA 19107-5097. Tel: (215) 955- 6702; Fax: (215) 955-0412; E-mail: maria.werner-wasik@ jeffersonhospital.org Conflict of interest: none. Received Nov 10, 2008, and in revised form April 30, 2009. Accepted for publication May 2, 2009. S86 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S86–S93, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.05.070
- 87. 3. Incidental irradiationof the stomach, and associated gas- tritis symptoms, can occur when a lower lobe lung mass has been treated. 4. The assignment of Grade 2 (brief intravenous fluid for #24 hours) vs. Grade 3 (hospitalization) esophagitis might be physician-dependent. 3. CHALLENGES DEFINING VOLUMES The adult esophagus length is z25 cm and is defined by its external contour on axial computed tomography (CT) im- ages. The esophagus remains closed when not involved in swallowing, and its lumen is often not easily identifiable throughout its entire length, particularly in the middle and caudal levels. Administration of a thick barium paste can help localize the esophagus, but the swallowing times are short (10 seconds), and the barium paste might not fully opa- cify the entire organ. In addition, high-contrast barium can af- fect the heterogeneity-corrected dose calculations. It is recommended that the entire length of the esophagus, from the cricoid cartilage to the gastroesophageal junction, be identified, requiring that a portion of the neck and upper ab- domen be included in the planning CT scan. In some of the studies (8, 11, 13), the cephalad (‘‘cervical’’) esophagus was not included, causing the absolute esophageal volume to be $20% smaller than if its entirety had been contoured. The esophagus is slightly mobile. In a study of 29 patients undergoing four-dimensional CT scans three times during RT, the cephalad, middle, and caudal esophagus can move #5, 7, and 9 mm in the combined anteroposterior and cranio- caudal directions, respectively (14). Thus, dose–volume analyses using the planning CT scan (as was done in the stud- ies we reviewed), could have some inaccuracies, although no specific margin recommendations can be given at this time. The esophageal circumference varies markedly on sequen- tial axial CT images, a reflection of the swallowing act. This appearance does not reflect the anatomic reality of a relatively uniform circumference (15). Thus, conventional dose–vol- ume histograms (DVHs) might not accurately reflect the par- tial volume doses. In the single study to consider this issue, the predictive value of metrics that were ‘‘corrected’’ for this an- atomic reality were slightly better predictors of outcome than were the ‘‘traditional’’ DVH-based metrics (15). Neverthe- less, the use of alternative three-dimensional dosimetric pa- rameters (e.g., dose–surface-area, dose–circumference histograms, ‘‘anatomically corrected’’ DVHs) as improved predictors of outcome is of unclear utility (11, 15, 16). 4. REVIEW OF DOSE–VOLUME PUBLISHED DATA A total 12 studies published between 1999 and January 2009 that assessed the dose–volume outcome in $90 patients treated for non–small cell lung cancer were reviewed (7, 8, 11, 13, 16–19, 20–23) (Table 1). All but one study (17) used three-dimensional planning. The endpoint was usually RTOG Grade 2 or greater or Grade 3 or greater. Two studies (7, 8) combined acute and late toxicities in a single analysis. The others either analyzed only acute (13, 16, 17, 19, 20, 22, 23) or analyzed acute and late toxicity separately (11, 18). The studies found a correlation with these endpoints for a va- riety of dose–volume factors. The maximal esophagus dose had significant univariate correlation (p # .05), with severe esophagitis in all the stud- ies that included it as a variable (7, 8, 11, 13, 20). However, it only remained significant in multivariate analyses in some of them (7, 8, 11). Ten studies (8, 13, 16, 18, 19–24) searched for correlations between severe acute esophagitis and either the absolute vol- ume (aVdose), absolute area (aAdose), or percentage of a refer- ence volume (Vdose), or reference area (Adose) receiving more than a specified dose. Eight of these studies (13, 16, 19–24) found significant univariate correlations with exposure over a wide dose range (10–80 Gy; Table 1 and Fig. 1). Multivar- iate analysis (16, 19, 20, 22, 24) identified fewer dose–vol- ume combinations. Because of the diverse reporting metrics, we could not find a consensus for the dose–volume thresholds. For example, one study (19) found V35 was the only dosimetric predictor of RTOG Grade 2 or greater acute esophagitis on multivariate analysis, both with and without CCT, and another study (22) found V20 to be the only multi- variate significant factor for 215 patients receiving CCT. However, a third study (16) found a much greater dose region (aA55 and aA80 or aV60 and aV80) to be significant. Some studies found circumferential metrics (e.g., esopha- geal length receiving full circumference dose 40–66 Gy [19] or 50–65 Gy [11]) to be significant, although not supe- rior to simpler volume or area metrics. Four studies (7, 8, 11, 22) found a univariate correlation with the mean dose greater than levels ranging from 34 Gy (7) to 40 Gy (8). A 34-Gy mean dose recommendation was adopted in the RTOG Phase III comparison of 60 Gy vs. 74 Gy with CCT in Grade III non–small-cell lung cancer (RTOG 0617). Dose–volume histogram parameters describing cumula- tive dose 50 Gy have been identified as highly statistically significantly correlated with acute esophagitis in several stud- ies. Some studies (Fig. 1), however, have shown the strongest statistically significant correlations with esophagitis at lower doses (as low as V30), perhaps owing to technique differ- ences. V30 was also implicated in a multivariate modeling study by El Naqa (21). Overall, the data are consistent with some risk of acute esophagitis at intermediate doses (30–50 Gy) and an increasing effect for greater doses. A main obstacle to obtaining definitive dosimetric recom- mendations from the published data is the variety of volumet- ric metrics—the absolute volume or area, relative volume or area, and circumferential measures—all have been analyzed. Reports describing relative metrics might have used different reference volumes (9, 13). Differences in the way other tech- nical factors were handled have less effect. For example, ad- justing DVHs for conventional fraction size and the type of tissue heterogeneity correction used are likely to have only minor effect, the latter because the esophagus is embedded in bulky soft tissue and anteroposterior/posteroanterior Dose–volume effects in esophagus d M. WERNER-WASIK et al. S87
- 88. Table 1. Summaryof large published series investigating treatment-related esophagitis in patients with NSCLC Series/investigator Patients (n) Prescription dose (Gy) range [median]* (special fractionations) CCT (%) Endpointy (rate) Univariate significant factors Multivariate significant factors Duke/Maguire et al. (18), 1999 91 64–86 [79]z (64% twice daily, 1.25–1.6 Gy/fx) 47 Acute G $3 (G3, 11%; G4-5, 0%) None None Any late,x 18% (G1, 9%; G2, 6%; G3, 3%) V50, A50, length of 100% circumference 50 Gy Gender, pre-RT dysphagia, V50, maximum percentage of circumference 80 Gy Thomas Jefferson/ Werner-Wasik et al. (17), 2000{ 105 45–70 [60] (7% twice daily)jj ,# 55 Acute G $3 (G3, 12%; G4, 1%) CCT, twice-daily treatment, female gender CCT, twice-daily treatment Washington University/Singh et al. (7), 2003 207 60–74 [70]** 25.6 Acute G $3 (G3, 4.3% G4, 0.5%) and/oryy late G $3 (G3, 4.8%; G4, 0.5%; G5, 0.5%)zz CCT, Dmax $58 Gy, mean dose 34 Gy, subcarinal nodes, race CCT, Dmax $58 Gy Washington University/Bradley et al. (16), 2004xx 166 60–74 [70]{{ 24.7 Acute G $2 (G2, 22.3%; G3, 4.2%; G4, 0.6%) CCT, aA range (aA5–aA70), aA55 jjjj , aV range (aV5–aV70), aV60 jjjj CCT and aV60; CCT, aV60, and aV80; CCT and aA55; CCT, aA55, and aA80 ‘‘volume and area equally predictive’’ Duke/Ahn et al. (11), 2005## 254 30–86 [66]xx (39% twice daily, 1.25–1.6 Gy/fx) 12.6 Acute G $3 (G3, 8.7%; G4, 0.4%) Twice daily; nodal stage; pretreatment dysphagia; Dmax; mean dose; V50; length of 50%, 75%, or 100%; circumference $50 Gy; maximal percentage circumference $50, 60, 70 Gy Twice daily RT, nodal stage, pretreatment dysphagia Any latex (G2, 2%; G3, 2%; G4, 1%) Length with 75% circumference $70 Gy, length with 100% circumference $50, 55 Gy; maximal percentage circumference $60–80 Gy Previous acute toxicity dominated all dosimetric factors NKI/Belderbos et al. (19), 2005 156 Group 1 (n = 88), 50– 95 at 2.25/fx#,***,yyy Group 2 (n = 68), 66 at 2.75/fx#,*** 23.7zzz Acute G $2 (G2, 20%; G3, 6%; G4, 0.6%) Lyman NTCPxxx ,V range (V20–V60); V35 jjjj , percentage of length, 100%; circumference $40 Gy or $66 Gy; treatment group (column 3); CCT worse than sequential C/RT or RT only; sequential C/RT worse than RT alone; T stage and nodal stage; age{{{ V35, CCT (Continued) S88 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 89. beams are themain component in many treatment plans. Sev- eral studies have provide enough information to estimate the incidence of esophagitis to dosimetric parameters (Fig. 2). There does appear to be a dose–response relationship, al- though the interstudy variations have been large. Neverthe- less, the data are somewhat consistent, with rates of acute Grade 2 or greater esophagitis increasing to 30% as V70 ex- ceeds 20%, V50 exceeds 40%, and V35 exceeds 50%. Table 1. Summary of large published series investigating treatment-related esophagitis in patients with NSCLC (Continued) Series/investigator Patients (n) Prescription dose (Gy) range [median]* (special fractionations) CCT (%) Endpointy (rate) Univariate significant factors Multivariate significant factors University of Michigan/Chapet et al. (13), 2005 101 65–103#,***,yyy 0 Acute G $2 (G2, 13%; G3, 3%) Nodal stage, V range (V40–V70), Dose- percentage volume range (D5–D60), D30 jjjj , D1 cc, 2.5 cc, 5 cc Lyman model NTCP with study-specific parameters Goyang/Kim et al. (20), 2005 124 54–66 [60]#,*** 60 Acute G $3-4 (G3, 12%; G4, 0.8%) CCT, V range (V58– V63), Dmax, Lyman model NTCP (Burman et al. [24] parameters) CCT, V60 (in patients with CCT) Harbin University/ Qiao et al. (8), 2005 208 60–72 [70]** 26 Acute G $3 (G3, 5%; G4, 0.5%; G5, 1%) and/or late G $3 (G3, 5%; G4, 0.5%) CCT, Dmax $60 Gy, mean dose $40 Gy, subcarinal lymph nodes CCT, Dmax $60 Gy MDACC/Wei et al. (22), 2006 215 60–70 [63]*** (16% twice daily, 1.2 Gy/fx) 100 Acute G $3jjjjjj (G3, 20%; G4, 0.5%) aV range (aV15–V45); V range (V10–V45); mean dose $34.5 Gy V20 Barcelona/Rodriquez et al. (23), 2009 100 55–65 [62] 100 Acute G $1 (G2, 29%; G3, 4%) esophagitis index### V50–V55 NA Abbreviations: NSCLC = non–small-cell lung cancer; CCT = concurrent chemotherapy; fx = fraction; G = grade; Vdose (e.g., V20) = relative volume receiving specified dose or more (e.g., $ 20 Gy); RT = radiotherapy; Dmax = maximal dose; Adose = relative surface area receiving specified dose or greater; aVdose, aAdose = absolute volume (V) or area (A) receiving specified dose or greater; D# = dose encompassing hottest percentage of esophagus. D #cc = dose encompassing hottest cubic centimeters of esophagus; NTCP = normal tissue complication probability; RTOG = Radiation Therapy Oncology Group. * All doses at standard fractionation of 1.8–2.2 Gy/d, 5 d/wk, unless otherwise stated. y Unless otherwise specified, RTOG grading was used; RTOG Grade 2, moderate dysphagia or odynophagia, requiring narcotic agents or liquid diet; RTOG Grade 3, severe dysphagia or odynophagia with dehydration or weight loss, requiring nasogastric feeding. z Clinical calculations and prescriptions done without inhomogeneity correction; doses for study retrospectively corrected for inhomogeneity and tabulated above. x Late complications determined from fraction of patients assessable for late toxicity. { No three-dimensional conformal RT but correlation with irradiated esophagus length inferred from length of spine in field was investigated. jj All twice-daily patients also underwent CCT. # Doses were fraction size-corrected using linear-quadratic model and a/b = 10 Gy. ** Doses reported without tissue heterogeneity correction. yy Acute and Late complications analyzed together. zz Percentage of late complications from raw numbers (e.g., 4.8% = 10 patients of 207 patients). xx Same patients analyzed by El Naqa et al. (21). {{ Various treatment techniques and fractionation schedules used; most common was standard fractionation for 45 Gy to clinical target vol- ume with cone-down to 66 Gy total to gross target volume; dose range quoted was overall dose to isocenter, corrected for tissue heterogeneity. jjjj Lowest p value. ## Some patients analyzed by Ahn et al. (10) were also analyzed by Maguire et al. (18). *** Doses were heterogeneity corrected. yyy Esophagus constraint on treatment plan. zzz All CCT patients were in 66-Gy group, a randomized trial of concurrent vs. sequential chemotherapy; they constituted 54% of that group but only 23.7% of total. xxx Found Lyman NTCP model parameters that gave visually good fit to data; significance not stated. {{{ Not specified whether toxicity was more likely at older age. jjjjjj Grading by institutional modification of RTOG. ### See Rodriguez et al. (23) for definition. Dose–volume effects in esophagus d M. WERNER-WASIK et al. S89
- 90. 5. FACTORS AFFECTINGRISK Greater acute esophagitis rates are seen with increased RT aggressiveness (e.g., hyperfractionation, concurrent boost), the addition of CCT, and several clinical factors (e.g., pre-ex- isting dysphagia and increasing nodal stage, with the latter likely a surrogate for larger tumors; Table 1). The incidence of Grade 3 or greater acute esophagitis is z1% for patients treated with once-daily RT alone. It is markedly increased with the addition of CCT (incidence, 6–24%) and is as great as 49% with concurrent gemcitabine. The Continuous Hyper- fractionated Accelerated Radiation Therapy regimen (25) re- ported a 19% rate of severe (Grade 3 or greater) esophagitis. Older patients (70 years of age) were more likely than youn- ger patients to experience high-grade esophagitis in a second- ary analysis of the RTOG 94-10 study (26). Several studies have assessed the putative radioprotector amifostine. Three single-institution Phase III studies (27– 29) suggested a significant benefit (27, 28) or a trend (29) for amifostine in lowering Grade 2 or greater esophagitis. However, the findings are difficult to interpret because of the small patient numbers and low (28) or unknown (27) in- cidence of Grade 3 or greater esophagitis. These results were not confirmed in a large cooperative group Phase III random- ized study of 243 patients (RTOG trial 98-01) (30). 6. MATHEMATICAL/BIOLOGIC MODELS Statistical models The statistical level of correlation between a complication and a set of variables is inadequate for treatment planning purposes. Statistical models aim to supply the missing link. They use the most significant dose–volume or dose–area var- iable and medical factors (e.g., CCT) as variables in a sigmoi- dal function. The typical functional form is %NTCP ¼ 100 exp½c0 þ ccctCCT þ SiðciVdoseiÞŠ= ½1 þ expðc0 þ ccctCCT þ Si½ciVdoseiŠÞ :Š The summation (symbolized by Si) represents a weighted combination of the patient-specific values of the significant dose–volume variables, Vdosei. CCT can be handled by an extra term or by having different sets of coefficients for pa- tients with and without CCT. The model coefficients, ci, are chosen to best match the observed complication rates, and coefficient values are given in the cited studies. The sim- plest models (probably too simple) use a single dose–volume variable (e.g., V35 [19], V20, or mean dose [22]). Others use several DVH-based variables (e.g., a four-variable model [21] selected absolute area points with doses from 30 to 85 Gy). Such statistical models are more sensitive to the DVH shape than those based on a single Vdose point. Lyman-Kutcher-Burman model Two recent studies (13, 19) used the maximum likelihood method to find the Lyman-Kutcher-Burman model parame- ters that correlated well with the incidence of Grade 2 or greater acute esophagitis in their respective populations of Fig. 1. Correlations between acute esophagitis and Vx values (vol- ume greater than x Gy). p Values correlated with relative or absolute volumes (in cubic centimeters); relative volumes used except as noted for 2006 data from Wei et al. (22). Lower values indicate bet- ter correlations with outcomes. As the wide variety of correlation shapes suggests, there does not appear to be any singular ‘‘thresh- old’’ dose above which a toxic effect is observed. Fig. 2. Incidence of acute esophagitis according to Vx (volume re- ceiving more than x Gy). x-Axis values estimated according to range of doses reported. Each curve annotated as follows: Vdose (investiga- tor, number of patients, percentage with concurrent chemotherapy [CCT]. Percentage of patients who received sequential chemother- apy in studies by Ahn et al. (11), Belderbos et al. (19), and Kim et al. (20) was 44%, 38%, and 15%, respectively. Data for V50 (Ahn et al. [11]) at 15, 45, and 75 Gy represent reported rates of Grade 2 or greater acute esophagitis plotted in dose bins at 30%, 30–60%, and 60%, respectively. Similarly, for V70 (Ahn et al. [11]), V50 (Rodriguez et al. [23]), and V60 (Kim et al. [20]), each symbol represents rates of acute esophagitis at 10% vs. 11–30% vs. 31–64%, and #30% vs. $30%, and #30 vs. 30%, respec- tively. Dashed horizontal lines reflect dose ranges ascribed to each data point. Upper x-axis range of greatest data point for V50 (Rodri- guez et al. [23]), V50 (Ahn et al. [11]), and V60 (Kim et al. [20]), are indefinite according to data (light-gray dotted bars). Solid and open symbols represent reported rates of Grade 2 or greater acute esoph- agitis and Grade 3 or greater acute esophagitis, respectively. Thicker and thinner solid lines represent higher and lower doses of Vx, re- spectively (i.e., thicker line for V70 and thinner line for V20). S90 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 91. patients without CCT.Both studies applied tissue inhomoge- neity and linear-quadratic corrections to 2-Gy equivalent reg- imens but used different reference esophageal lengths. Chapet et al. (13) excluded the cervical esophagus; thus, their reference length was approximately 20% shorter than that of Belderbos et al. (19). Table 2 lists the parameters from these two studies and, for comparison, the 1991 parameters (31). Because the 1991 endpoint was a very severe and, in modern times very rare, toxicity of clinical stricture or perforation, it is not surprising that the 1991 Lyman-Kutcher-Burman pa- rameters are different from those from the more recent studies for which the endpoint was RTOG Grade 2 or greater acute esophagitis. Both recent parameterizations (13, 19) yielded mid-size n values, consistent with the correlation with a wide range of significant dose–volume factors noted in the section, ‘‘Review of Dose–Volume Published Data.’’ The Lyman parameters of the two studies agreed within their broad 95% confidence intervals. Relative Seriality Model Parameters for relative seriality model were derived (32) from partial irradiation tabulation of Emami et al. (33). Re- cent planning study (34) found this model/parameter combi- nation predicted a complication rate similar to Lyman model using Burman et al. (31) parameters. However, because both were parameterized to fit the Emami data, neither might be relevant to the studies and milder endpoints reviewed in sec- tion ‘‘Review of Dose–Volume Published Data.’’ General comments Because acute esophagitis events occur mainly during a course of therapy, the rapidity of dose accumulation might be more important than the final overall dose (much of which is delivered after the complication risk has peaked). No cur- rent models account for the course of a complication relative to the number of fractions delivered. It also follows that ex- isting models and dose–volume parameters should not be ap- plied to regimens in which the number of fractions is much different from 30–35 Gy without careful additional study. 7. SPECIAL SITUATIONS Hypofractionation for central lesions can expose parts of the esophagus to relatively large doses per fraction. Predic- tions using conventional fractionation should not be applied to such treatments unless they have been validated by addi- tional study. Although a few reports have been published of serious esophageal toxicity from hypofractionation (35), no comprehensive dose–volume-based analyses have been published. Similarly, no large body of data exists on long- term esophageal toxicity of other altered fractionation schemes (e.g., hyperfractionation; in-field boost). 8. RECOMMENDED DOSE–VOLUME LIMITS At present, it is not possible to identify a single best thresh- old volumetric parameter for esophageal irradiation, because a wide range of Vdose parameters correlate significantly with severe acute esophagitis. In particular, the studies we ana- lyzed illustrate a clear trend demonstrating that volumes re- ceiving 40–50 Gy correlated significantly with acute esophagitis (Fig. 1) (24). In particular, for high-dose conven- tionally fractionated non–small-cell lung cancer treatments, it is prudent to ensure that the dose to even small volumes of the esophagus does not exceed the prescription dose. This is a particular risk of intensity-modulated RT if no esophagus constraints are imposed in the planning process and the radi- ation dose is ‘‘dumped’’ inadvertently in the region of the esophagus. The ongoing Phase III Intergroup trial (RTOG 0617) has recommended (but has not mandated) that the mean dose to the esophagus be kept to 34 Gy and that the esophageal V60 be calculated for each patient enrolled in the trial. These recommendations were based on the Wash- ington University experience (7) (Table 2). An inability to provide specific ‘‘dose limits’’ for the esophagus in this large cooperative group trial illustrates the lack of evidence that any absolute limits can be imposed on the basis of current published data. However, from the clinical reports without detailed dosimetric esophageal dose correlates, it appears safe to give doses as great as 74 Gy to a segment of the esoph- agus with concurrent carboplatin and paclitaxel (36–38). In the section ‘‘Mathematical/Biologic Models,’’ we de- scribed several mathematical models that correlate with the incidence of Grade 2 or greater acute esophagitis for specific study populations. Clinicians with appropriate treatment planning resources might find such models interesting and useful, particularly when making decisions between compet- ing treatment plans. However, it is important to recognize that, at present, these models are tentative as best. A prudent approach to using any mathematical model is to first do a ret- rospective ‘‘test drive’’ to determine whether predictions are in qualitative agreement with the complications observed at one’s own center, subject to local contouring protocols, treat- ment beam arrangements, and patient populations. 9. FUTURE TOXICITY STUDIES New thoracic protocols that have acute esophagitis toxicity as an endpoint should specify one or more dose–volume models to test prospectively. Future analyses of esophagitis should ideally include the time of onset, because the compli- cation occurs from the dose accumulated during the course of Table 2. Three parameterizations of Lyman-Kutcher- Burman model for esophageal complications Investigator TD50 (Gy) n m Burman et al. (31), 1991 68 0.06 0.11 Chapet et al. (13), 2005 51 (29–82) 0.44 (0.11–1.41) 0.32 (0.19–0.57) Belderbos et al. (19), 2005 47 (41–60) 0.69 (0.18–6.3) 0.36 (0.25–0.55) Abbreviation: TD50 = median toxic dose. Burman values derived from ‘‘Emami’’ estimates for more severe endpoint. Dose–volume effects in esophagus d M. WERNER-WASIK et al. S91
- 92. therapy, usually wellbefore the total dose has been delivered. Complication models could potentially be constructed on the basis of the dose accumulated each week and the total dose. Thus, the data analysis would not be a continual cycle of hy- pothesis/model generation, such as is commonly the case to- day. Peer-reviewed treatment planning and outcomes data should be pooled and made permanently available. This might enable a single analysis to confidently uncover the fac- tors that lead to such an array of dose–volume correlations, such as seen in Fig. 1, to derive robust parameter sets for the Lyman or relative seriality models or to derive new semi- mechanistic models. The exclusion of the entire esophageal length/volume from the high-dose radiation region is extremely difficult; how- ever, reducing the radiation dose delivered to a part of esoph- ageal circumference might be feasible. Intensity-modulated RT seems well suited for that purpose, with its ability to de- liver concave-shaped RT dose distributions around organs at risk (39). Studies to better understand the importance of the spatial distribution of the dose (and hence the utility of partial circumferential sparing) would be useful. Additional study is needed to understand the utility of ra- dioprotectors. A prospective assessment of the dose and volume and other factors relating to esophageal injury after hypofractio- nation is needed, given the growing interest in this approach. The identification of biologic markers of radiation sensitiv- ity will be important to explain individual variations in pa- tients’ reactions. 10. TOXICITY SCORING We recommend that the Common Terminology Criteria for Adverse Events, version 3, be used to score both acute and late injury. It is simple and consistent, and its use has been mandated by the National Cancer Institute in the coop- erative group trials since October 2003 (40). Late injury might be scored under several endpoints, including necrosis, obstruction, perforation, or stricture, depending on the pa- tient’s symptoms. REFERENCES 1. Curran W Jr., Scott C, Langer C, et al. Phase III comparison of sequential vs. concurrent chemoradiation for patients with unre- sected stage III non-small cell lung cancer: Initial report of RTOG 9410. Proc ASCO 2000;19:484a. 2. Furuse K, Fukuoka M, Kawahara M, et al. Phase III study of concurrent vs. sequential thoracic radiotherapy in combination with mitomycin, vindesine, and cisplatin in unresectable stage III non-small cell lung cancer. J Clin Oncol 1999;17:2692– 2699. 3. Cox JD, Pajak TF, Asbell S, et al. Interruptions of high-dose ra- diation therapy decrease long-term survival of favorable pa- tients with unresectable non-small cell carcinoma of the lung: Analysis of 1244 cases from 3 RTOG trials. Int J Radiat Oncol Biol Phys 1993;27:493–498. 4. Timmerman R, McGarry R, Yiannoutsos C, et al. Excessive toxicity when treating central tumors in a phase II study of ste- reotactic body radiation therapy for medically inoperable early- stage lung cancers. J Clin Oncol 2006;24:4833–4839. 5. Onishi H, Shirato H, Nagata Y, et al. Hypofractionated stereo- tactic radiotherapy (HypoFXSRT) for stage I non-small cell lung cancer: Updated results of 257 patients in a Japanese multi-institutional study. J Thoracic Oncol 2007;2(7 Suppl. 3):S94–S100. 6. Choi GB, Shin JH, Song HY, et al. Fluoroscopically guided bal- loon dilation for patients with esophageal stricture after radia- tion treatment. J Vascular Intervent Radiol 2005;16:1705–1710. 7. Singh AK, Lockett MA, Bradley JD. Predictors of radiation-in- duced esophageal toxicity in patients with non-small cell lung cancer treated with three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2003;55:337–341. 8. Qiao W-B, Zhao Y-H, Zhao Y-B, et al. Clinical and dosimetric factors of radiation-induced esophageal injury: Radiation-in- duced esophageal toxicity. World J Gastroenterol 2005;11: 2626–2629. 9. CTC/CTCAE Codes. Available from: www.ctep.info.nih.gov/ reporting/ctc.html. Last accessed December 15, 2009. 10. Werner-Wasik M, Scott C, Curran WJ Jr., et al. Correlation be- tween acute esophagitis and late pneumonitis in patients (pts) with locally advanced non-small cell lung cancer (LA-NSCLC) receiving concurrent thoracic radiotherapy (RT) and chemo- therapy: A multivariate analysis of the Radiation Therapy On- cology Group (RTOG) database [Abstract]. Proc ASCO 2002; 21:299a. 11. Ahn S-J, Kahn D, Zhou S, et al. Dosimetric and clinical predic- tors for radiation- induced esophageal injury. Int J Radiat Oncol Biol Phys 2005;61:335–347. 12. Goldstein HM, Rogers LF, Fletcher GH, et al. Radiological manifestations of radiation-induced injury to the normal upper gastrointestinal tract. Radiology 1975;117:135–140. 13. Chapet O, Kong F-M, Lee JS, et al. Normal tissue complication probability modeling for acute esophagitis in patients treated with conformal radiation therapy for non-small cell lung cancer. Radiother Oncol 2005;77:176–181. 14. Dieleman EMT, Senan S, Vincent A, et al. Four-dimensional com- puted tomographic analysis of esophageal mobility during normal respiration. Int J Radiat Oncol Biol Phys 2007;67:775–780. 15. Kahn D, Zhou S, Ahn S-J, et al. Anatomically correct dosimet- ric parameters may be better predictors for esophageal toxicity than are traditional CT-based metrics. Int J Radiat Oncol Biol Phys 2005;62:645–651. 16. Bradley J, Deasy JO, Bentzen S, et al. Dosimetric correlates for acute esophagitis in patients treated with radiotherapy for lung carcinoma. Int J Radiat Oncol Biol Phys 2004;58:1108–1113. 17. Werner-Wasik M, Pequignot E, Leeper D, et al. Predictors of severe esophagitis include use of concurrent chemotherapy, but not the length of irradiated esophagus: A multivariate anal- ysis of patients with lung cancer treated with non-operative ther- apy. Int J Radiat Oncol Biol Phys 2000;48:689–696. 18. Maguire, Sibley GS, Zhou SM, et al. Clinical and dosimetric predictors of radiation-induced esophageal toxicity. Int J Radiat Oncol Biol Phys 1999;45:97–103. 19. Belderbos J, Heemsbergen W, Hoogeman M, et al. Acute esoph- ageal toxicity in non-small cell lung cancer patients after high dose conformal radiotherapy. Radiother Oncol 2005;75:157–164. 20. Kim TH, Cho KH, Pyo HR, et al. Dose–volumetric parameters of acute esophageal toxicity in patients with lung cancer treated with three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2005;62:995–1002. S92 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 93. 21. El NaqaI, Bradley J, Blanco AI, et al. Multivariable model- ing of radiotherapy outcomes including dose–volume and clinical factors. Int J Radiat Oncol Biol Phys 2006;64: 1275–1286. 22. Wei X, Liu HH, Tucker SL, et al. Risk factors for acute esophagitis in non–small-cell lung cancer patients treated with concurrent chemotherapy and three-dimensional confor- mal radiotherapy. Int J Radiat Oncol Biol Phys 2006;66: 100–107. 23. Rodriguez N, Algara M, Foro P, et al. Predictors of acute esoph- agitis in lung cancer patients treated with concurrent three-di- mensional conformal radiotherapy and chemotherapy. Int J Radiat Oncol Biol Phys 2009;73:810–817. 24. Takeda K, Nemoto K, Saito H, et al. Dosimetric correlations of acute esophagitis in lung cancer patients treated with radiother- apy. Int J Radiat Oncol Biol Phys 2005;62:626–629. 25. Saunders MI, Dische S, Barrett A, et al. Randomized multi- centre trials of CHART vs. conventional radiotherapy in head and neck and non-small cell lung cancer: An interim report. Br J Cancer 1996;73:1455–1462. 26. Langer C, Hsu C, Curran W, et al. Do elderly patients with locally advanced non-small cell lung cancer benefit from com- bined modality therapy? A secondary analysis of RTOG 94-10. Int J Radiat Oncol Biol Phys 2001;51(Suppl. 1):20–21. 27. Antonadou D, Coliarakis N, Synodinou M, et al. Randomized Phase III trial of radiation treatment plus/minus amifostine in patients with advanced-stage lung cancer. Int J Radiat Oncol Biol Phys 2001;51:915–922. 28. Leong SS, Tan EH, Fong KW, et al. Randomized double-blind trial of combined modality treatment with or without amifostine in unresectable stage III non-small cell lung cancer. J Clin On- col 2003;21:1767–1774. 29. Komaki R, Lee JS, Milas L, et al. Effect of amifostine on acute toxicity from concurrent chemotherapy and radiotherapy for in- operable non-small cell lung cancer: Report of a randomized comparative trial. Int J Radiat Oncol Biol Phys 2004;58: 1369–1377. 30. Movsas B, Scott C, Langer C, et al. Phase III study of amifostine in patients with locally advanced non-small cell lung cancer re- ceiving intensive chemoradiation: Radiation Therapy Oncology Group 98-01. J Clin Oncol 2005;23:2145–2154. 31. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 32. Ka¨llman P, Agren A, Brahme A. Tumor and normal tissue re- sponses to fractionated non-uniform dose delivery. Int J Radiat Biol 1992;62:249–262. 33. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 34. Ragazzi G, Cattaneo GM, Fiorino C, et al. Use of dose–volume histograms and biophysical models to compare 2D and 3D irra- diation techniques for non-small cell lung cancer. Br J Radiol 1999;72:279–288. 35. Onimaru R, Shirato H, Shimizu S, et al. Tolerance of organs at risk in small-volume, hypofractionated, image-guided radio- therapy for primary and metastatic lung cancers. Int J Radiat Oncol Biol Phys 2003;56:126–135. 36. Xiao Y, Werner-Wasik M, Michalski D, et al. Comparison of three IMRT-based treatment techniques allowing partial esoph- agus sparing in patients receiving thoracic radiation therapy for lung cancer. Med Dosim 2004;29:210–216. 37. Stichcombe T, Lee C, Moore DT, et al. Long-term follow-up of a phase I/II trial of dose escalating three-dimensional conformal thoracic radiation therapy with induction and concurrent carbo- platin and paclitaxel in unresectable stage IIIA/B non-small cell lung cancer. J Thoracic Oncol 2008;3:1279–1285. 38. Schild SE, McGinnis WL, Graham D, et al. Results of a phase I trial of concurrent chemotherapy and escalating doses of radia- tion for unresectable non–small-cell lung cancer. Int J Radiat Oncol Biol Phys 2006;65:1106–1111. 39. Blackstock AW, Ho C, Butler J, et al. Phase IA/IB chemo-radi- ation trial of gemcitabine and dose-escalated thoracic radiation in patients with stage III A/B non-small cell lung cancer. J Thorac Oncol 2006;1:434–440. 40. Colevas AD, Setser A. The NCI Common Terminology Criteria for Adverse Events (CTCAE) v 3.0 is the new standard for on- cology clinical trials. J Clin Oncol 2004;22(14 Suppl.):6098. Dose–volume effects in esophagus d M. WERNER-WASIK et al. S93
- 94. QUANTEC: ORGAN-SPECIFIC PAPERAbdomen: Liver RADIATION-ASSOCIATED LIVER INJURY CHARLIE C. PAN, M.D.,* BRIAN D. KAVANAGH, M.D., M.P.H.,y LAURA A. DAWSON, M.D.,z X. ALLEN LI, PH.D.,x SHIVA K. DAS, PH.D.,k MOYED MIFTEN, PH.D.,y AND RANDALL K. TEN HAKEN, PH.D.* From the *Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI; y Department of Radiation Oncology, University of Colorado, Aurora, CO; z Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada; x Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI; k Department of Radiation Oncology, Duke University Medical Center, Durham, NC The liver is a critically important organ that has numerous functions including the production of bile, metabolism of ingested nutrients, elimination of many waste products, glycogen storage, and plasma protein synthesis. The liver is often incidentally irradiated during radiation therapy (RT) for tumors in the upper- abdomen, right lower lung, distal esophagus, or during whole abdomen or whole body RT. This article describes the endpoints, time- course, and dose-volume effect of radiation on the liver. Ó 2010 Elsevier Inc. Liver, Normal tissue toxicity, Radiation-induced liver disease. 1. CLINICAL SIGNIFICANCE The liver is an important organ with numerous functions in- cluding the production of bile, metabolism of ingested nutri- ents, elimination of waste products, glycogen storage, and protein synthesis. The liver is often incidentally irradiated during radiation therapy (RT) for tumors in the upper abdo- men, right lower lung, distal esophagus, or whole abdomen or whole-body RT. 2. ENDPOINTS The Cancer Therapy Evaluation Program, Common Ter- minology Criteria for Adverse Events (CTCAE), version 3.0, defines Grades 2, 3, 4, and 5 liver dysfunction as jaun- dice, asterixis, encephalopathy or coma, and death, respec- tively. These serious adverse events are rare after radiation therapy (RT). Acute post-RT changes in liver function tests are far more common and occur during and after RT, presum- ably related to self-limited liver inflammation. Such liver enzyme abnormalities are classified under the CTCAE meta- bolic/laboratory category. Grades 2, 3, and 4 elevations of alanine aminotransferase and aspartate aminotransferase include levels that are 2.5–5.0, 5.0–20, and 20 times the upper limit of normal, respectively. Radiographically, clinically insignificant transient declines in computed tomog- raphy (CT)-defined tissue density can be seen 2–3 months after fractionated RT. This observation by itself should not be confused with tumor progression or irreversible liver injury (1). The Child-Pugh scoring system assesses liver dysfunction based on clinical and laboratory parameters (Table 1). It can be used to characterize baseline liver function and posttreat- ment changes in liver function. RT-induced liver disease (RILD) is separated into ‘‘clas- sic’’ and ‘‘nonclassic’’ RILD. Classic RILD involves anic- teric hepatomegaly and ascites, typically occurring between 2 weeks to 3 months after therapy (2). Classic RILD also in- volves elevated alkaline phosphatase (more than twice the upper limit of normal or baseline value). This endpoint can occur in patients who have otherwise fairly well-functioning pretreatment livers. Pathologically, there is occlusion and obliteration of the central veins of the hepatic lobules, retro- grade congestion, and secondary hepatocyte necrosis. Treat- ment options for RILD are limited, and liver failure and death can result. Nonclassic RILD, typically occurring between 1 week and 3 months after therapy, involves elevated liver transaminases more than five times the upper limit of normal or CTCAE Grade 4 levels in patients with baseline values more than five times the upper limit of normal within 3 months after completion of RT, or a decline in liver function (measured by a worsening of Child-Pugh score by 2 or more), in the ab- sence of classic RILD. This endpoint has been described in hepatocellular carcinoma (HCC) patients who have poor Reprint requests to: Charlie C. Pan, MD, Department of Radiation Oncology, University of Michigan Medical School, 1500 E. Medi- cal Center Dr., UH B2 C490, Ann Arbor, MI 48109-5010. Tel: (734) 936-4288; Fax: (734) 763-7370; E-mail: cpan@umich.edu Conflict of interest: none. Received Feb 9, 2009, and in revised form May 29, 2009. Accepted for publication June 23, 2009. S94 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S94–S100, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.06.092
- 95. liver function (hepatitisB infection, Child-Pugh Classes B and C) (3–5). CTCAE, although not as useful for classic RILD, is most useful for scoring nonclassic RILD. The un- derlying pathology of nonclassic RILD is unclear. A confounder of RILD, especially in populations with pre- existing liver dysfunction, is the baseline rate of morbidity within this population due to their preexisting liver disease. In a recent randomized trial in unresectable HCC, there was a 52% rate of serious adverse events among the placebo group because of progression of cirrhosis or HCC (6). An- other described endpoint is hepatitis B reactivation (7), which can contribute to liver function abnormalities. Patients at risk for hepatitis B virus (HBV) should have appropriate serum testing, and prophylactic antiretroviral therapy has been asso- ciated with a lower rate of post-RT reactivation of HBV or exacerbation. No established therapies for classic RILD exist, though the use of anticoagulants and steroids have been suggested. Treatment of RILD is primarily supportive, and diuretics are often used for the ascites. Although a few patients may recover, a substantial fraction will die of liver failure. 3. CHALLENGES DEFINING VOLUMES The liver is relatively easy to identify on CT images. If in- travenous and oral contrast are not used, the left border can be indistinct against the heart or stomach. Ideally, the liver pa- renchyma (minus the biliary duct system and vasculature) should be distinguished as the ‘‘functional’’ component. Lit- erature concerned with modeling liver tolerance to RT typi- cally defines normal liver volume as the total liver minus gross tumor volume (5, 8), presuming that minimal function remains in liver tumors themselves. Extensive work involving fluoroscopy, four-dimensional CT, and cine-magnetic resonance imaging has described liver motion due to breathing and the effect of this motion on de- livered RT dose. Regular breathing can result in liver tumor displacement $2 cm. Strategies to manage this motion in- clude abdominal compression, shallow breathing, breath holding, deformation modeling, gated treatments, and real- time tumor tracking (9–13). Attempts to assess/compensate for liver motion are essential for stereotactic RT and are ad- visable in other circumstances, especially when the normal liver volume irradiated poses a substantial risk of RILD. 4. REVIEW OF DOSE–VOLUME DATA The liver parenchyma is composed of numerous functional subunits. This parallel architecture allows the liver to tolerate substantial focal injury prior to any clinical sequelae. In non- cirrhotic patients, surgical resection that leaves only a 20– 25% liver remnant has been shown to be well tolerated (14). Because of this redundant capacity, partial liver irradi- ation to high doses is possible if adequate normal liver paren- chyma can be spared. Preexisting liver dysfunction secondary to comorbid conditions such as hepatitis B/C in- fection and cirrhosis may render patients more susceptible to RT-induced liver injury. Whole liver RT The classic paper by Ingold (1965) is the first report of a dose–complication relationship for whole-liver RT (15). RILD occurred in 1/8 patients who received 30–35 Gy over 3–4 weeks and 12/27 (44%) patients who received 35 Gy. In the 1991 report by Emami, the total dose 5/5 for whole- liver radiation was estimated to be 30 Gy in 2-Gy fractions (16). More recent experiences include the Radiation Therapy Oncology Group 84-05 dose escalation study of accelerated hyperfractionation in which it was observed that 0/122 pa- tients who received 27–30 Gy in twice daily 1.5 Gy fractions of whole-liver radiation therapy experienced RILD, whereas 5/51 (9.8%) who received 33 Gy in 1.5-Gy fractions devel- oped RILD (17). Partial liver RT Table 2 summarizes the toxicity reported after partial liver RT for primary liver cancer and small volume metastatic dis- ease. In most, the key factor predicting RILD was baseline liver condition. Two studies noted a dosimetric parameter as- sociated with increased toxicity risk: mean dose and V30 (volume receiving $30 Gy). In each series where mean nor- mal liver dose was reported, patients with RILD had a higher mean dose than those without RILD. The University of Michigan (UM) has extensively investi- gated RT dose escalation of primary and metastatic liver can- cers since 1987. Using CT-based RT planning, the parameter effective volume (Veff) of normal liver irradiated was defined as the normal liver volume, which, if irradiated to the pre- scribed dose, would be associated with the same normal tis- sue complication probability (NTCP) as the non-uniform dose delivered. An analysis of 203 patients treated with Table 1. Child-Pugh scoring system to assess severity of liver disease Criterion 1 point 2 points 3 points Bilirubin (total) 2 mg/dL 2–3 mg/dL 3 mg/dL Serum albumin 3.5 g/dL 2.8–3.5 g/dL 2.8 g/dL INR 1.7 1.71–2.20 2.20 Ascites None Controlled with medication Refractory Hepatic encephalopathy None CTCAE Grade I-II (or controlled with medication) CTCAE Grade III-IV (or refractory) Abbreviations: INR = international normalized ratio; CTCAE = Common Terminology Criteria for Adverse Events. Patients are grouped into Child-Pugh Class A if the total score is 5–6, Class B if the score is 7–9, and Class C if the score is 10 or higher. Radiation-associated liver injury d C. C. PAN et al. S95
- 96. three-dimensional conformal RT,and concurrent hepatic ar- terial chemotherapy, demonstrated that small portions of the liver can be irradiated to a very high dose (up to 90 Gy) if the Veff was low (8). Mean liver dose was also a strong predictor of RILD in the UM series (see ‘‘Mathematical/Biological Models’’). Dose–volume limit recommendations are discussed in the Recommended Dose–volume Limits section. Regarding risk, in general, the risks reported in the studies cited within this review are realistic estimates, as the follow-up durations in the studies are greater than the 3–4 months within which RILD typically occurs. 5. FACTORS AFFECTING RISK Preexisting liver dysfunction may render patients more susceptible to RT-induced liver injury (Table 2). Patients with Child-Pugh B or C scores have a higher risk of RT-re- lated problems than those with Child-Pugh A scores (3, 18–20). Additional factors reportedly associated with a higher risk of RILD include hepatitis B carrier status (21), prior transcatheter arterial chemoembolization (18), concurrent chemotherapy (8), portal vein tumor thrombosis (4, 18, 22), tumor stage (18), male sex (8), and Cancer of the Liver Italian Program staging system (18, 22). Although it is likely that the risk of liver injury relates to the dose per fraction received by portions of the liver, it is dif- ficult to characterize the magnitude of any effect because most series include patients treated within a narrow range of dose per fraction. Furthermore, with any size fraction given to the tumor, the adjacent normal liver receives a broad range of doses because of beam entrance/exit zones and pen- umbra, further complicating the analysis. The topic of dose modeling is discussed further in Mathematical/Biological Models, and the topic of hypofractionation is discussed fur- ther in the Special Situations section. 6. MATHEMATICAL/BIOLOGICAL MODELS The Lyman NTCP model has been applied by numerous groups. From the series referenced in Table 2, the range of estimates of the parameters generated among patients with Child-Pugh A or better liver function and no HBV infection are as follows: n, 0.86–1.1; m, 0.12–0.31; and TD50, 39.8– 46.1 Gy (8, 21). For patients with HBV or Child-Pugh B dys- function, the ranges are: n = 0.26–0.7, m = 0.4–0.43, TD50 = 23–50 Gy (3, 21). These patients with worse liver dysfunc- tion likely have lower TD50 values within the previous range, though this needs to be clarified in future studies. Analysis of UM patients treated for primary hepatobiliary cancer or 98 metastases with concurrent continuous hepatic arterial floxuridine (FUdR) or bromodeoxyuridine (BUdR) and RT in twice daily 1.5 Gy fractions revealed a strong cor- relation of RILD with the mean liver dose. No classic RILD was observed when the mean liver dose was 31 Gy, with or without chemotherapy. For patients treated with FUdR, the mean liver doses associated with 5% risk of classic RILD was 28 Gy for primary and 32 Gy for metastatic liver cancer (corrected to 2 Gy fraction equivalent doses using the linear- quadratic [LQ] model, assuming an a/b = 2 Gy). Based on these observations and derived Lyman model parameter esti- mates, the partial volume tolerance of the liver for a defined allowable risk of RILD can be graphed (Figure 1) for a 5% risk of RILD. With ‘‘n’’ of approximately 1 in the Lyman NTCP model, a large volume effect is seen and a strong cor- relation of NTCP with mean liver dose is revealed. Again Table 2. Series of fractionated partial liver irradiation and rates of RILD Study group n Diagnosis Baseline Child-Pugh score Prescription dose fractionation Crude percent RILD Mean normal liver dose in patients with vs. without RILD Factors associated with RILD Michigan (8, 23) 203* PLC + LMC 203 A 1.5 Gy twice daily 9.4% (19/203) 37 Gy vs. 31.3 Gy PLC vs. LMC mean liver dose Taipei (20) 89y HCC 68 A 21 B 1.8–3.0 Gy 19% (17/89) 23 Gy vs. 19 Gy HBV, liver cirrhosis Shanghai (3, 18) 109y PLC 93 A 16 B 4–6 Gy 15.6% (17/109) 24.9 Gy vs. 19.9 Gy Liver cirrhosis Guangdong (20) 94** HCC 43 A 51 B 4–8 Gy 17% (16/94) Note: 4 fatal Not stated Liver cirrhosis S. Korea (Seong, Park) (21) 158y HCC 117 A 41 B 1.8 Gy 7% (11/158) Not stated Dose S. Korea (Kim) (4) 105y HCC 85 A 20 B 2.0 Gy 12.3% (13/105) 25.4 Gy vs. 19.1 Gy Total liver volume receiving 30 Gy or more above 60% Abbreviations: HBV = hepatitis B viral infection; HCC = hepatocellular carcinoma; PLC = primary liver cancer; LMC = liver metastatic disease; RILD = radiation-induced liver damage. * Patients also received FUdR or BUdR; in this series the mean normal liver dose was calculated as corrected for 1.5 Gy twice-daily equiv- alent dose, and the comparison of patients with vs. without RILD refers to the median value of mean normal liver dose, whereas for other series the comparison is between the average (mean) of mean normal liver dose in each group. y At least 77% of patients in these series also received transarterial chemoembolization (TACE). S96 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 97. based on theUM data, Figure 2 demonstrates the relationship between mean liver dose and NTCP for RILD for patients with primary or metastatic liver tumors. When a similar analysis was conducted on different popu- lations from Taiwan (21) and China (18), with a majority of patients having HBV infections, the tolerance of the liver to radiation was less predictable, and the most common effect consisted of elevation of transaminases rather than RILD. HCC patients who were HBV carriers or had Child-Pugh B cirrhosis had a greater susceptibility to RILD and had a smaller volume effect on normal liver response according to Lyman modeling. For patients with HBV treated in Tai- wan, Lyman NTCP parameters for classic and nonclassic RILD are: n 0.26, m 0.4, and TD50 50 Gy (21). The Shanghai group likewise noted differences in Lyman model parameter estimates based on baseline liver dysfunc- tion, with less volume effect for Child-Pugh B relative to Child-Pugh A (3, 18); in this series, fraction sizes were 4–6 Gy (see Table 2). For the patients with Child Pugh B liver dysfunction treated with 4–6 Gy per fraction, Lyman param- eters for classic or nonclassic RILD are n 0.7, m 0.43, and TD50 23 Gy (3). From these patients treated with 4–6 Gy per fraction, the mean liver doses associated with a 5% risk of liver toxicity were estimated to be 23 Gy and 6 Gy for Child-Pugh A and B patients, respectively. One report of damage injury model parameterization of the early UM data led to local damage parameters of D50 = 42 Gy, k = 2; and fraction of liver injury required for RILD pa- rameters of F50 = 0.5, s = 0.05 (23). A subsequent analysis of 203 UM patients led to a lower threshold and a shallower slope for the population cumulative functional reserve: F50 = 0.4, s = 0.08; however, the confidence limits on these pa- rameters were very large (24). In another analysis from the National Taiwan University group, including patients with HCC and gastric cancer patients, valid fits were only obtained for the non-HBV carriers with local damage parameters of D50 = 25 Gy, k = 60; and fraction of liver injury required for RILD parameters of F50 = 0.59, s = 0.12 (25), but these parameters have high uncertainty. Limited data about the utility of V30 exist from studies of mostly HCC patients, with both classic and nonclassic RILD combined together. V30 was found to be useful in segregating higher risk patients from lower risk patients in some studies at cutoff levels of 28–60% (4, 18, 26); however, the effect of V30 is not uniformly observed(5). Otherstudiessuggest theimpor- tance of V20-V40 (4) and V5-V40 (18), but only for Child- Pugh Grade A patients in the latter study. The critical volume model is discussed in the Special Situations section. 7. SPECIAL SITUATIONS Most clinical data published involves analyses of conven- tionally fractionated or hyperfractionated treatment involving daily prescription doses to the tumor in the range of 2 Gy or less. Consequently, the daily doses received by surrounding normal liver parenchyma are even lower. Current interest in the use of stereotactic body radiation therapy (SBRT) raises questions about the extent to which observations made using low dose per fraction are applicable to the setting of SBRT, where the daily prescription dose to the tumor is on the order of 10 Gy or higher, and portions of the normal liver will re- ceive doses in that range. Use of the models discussed in Mathematical/Biological Models should be done with cau- tion, as the LQ conversion for larger fraction sizes will likely be inadequate. SBRT produces transient hypodensity on CT scan that ap- pears within months after treatment and then resolves (27). RILD after SBRT occurs in fewer than 5% of cases with care- ful patient selection and technique. Mendez-Romero (median follow-up, 12.9 months) observed 1 classic and 1 nonclassic Fig. 1. Reference dose vs effective volume for 5% isotoxicity curve for classic radiation-induced liver disease after conformal radiation therapy, delivered in 1.5 Gy twice-daily fractionation, for primary or metastatic tumors. Redrawn from (8). The shaded areas around each curve represent the 80% confidence limits, which overlap above a reference dose of approximately 45 Gy. Fig. 2. Mean liver dose, corrected with LQ modeling for 2.0 Gy fractions vs. Lyman normal tissue complication probability (NTCP) of classic radiation-induced liver disease (RILD) for pri- mary and metastatic liver cancer, redrawn from (24). Radiation-associated liver injury d C. C. PAN et al. S97
- 98. case of RILDamong 8 patients with HCC treated with SBRT for liver tumors; another patient with baseline Child-Pugh B liver dysfunction and HCC experienced portal hypertension and concomitant nonhepatic infection and died 2 weeks after treatment. No Grade 4 or 5 toxicity occurred among the 17 patients with liver metastases, suggesting that patients with HCC are more susceptible to SBRT-related toxicity, espe- cially if there is underlying liver dysfunction (28). In a Phase II study of 61 patients treated with SBRT for colorectal me- tastases treated with 15 Gy  3 within 5–8 days, Hoyer (me- dian follow-up 4.3 years) observed severe toxicity in 1 patient that was possibly related to SBRT (60% of liver re- ceived $10 Gy, median dose 14.4 Gy in three fractions). This patient died of hepatic failure 7 weeks post-RT, but the exact cause was unclear (29). In a Princess Margaret Hos- pital study of 41 patients treated with SBRT, using an NTCP estimate for dose in six fractions (median, 36.0 Gy; range, 24.0–54.0 Gy) and with a median follow-up 17.6 months, for HCC or intrahepatic cholangiocarcinoma, 17% experi- enced progression from Child-Pugh A to B within 3 months after RT (median mean liver dose, 17.5 Gy; range, 5.2–25.2 Gy, in six fractions) (30). In contrast, in 68 patients with liver metastases treated with SBRT (28–60 Gy, in six fractions), the risk of any serious liver toxicity within 3 months was very low (95% confidence interval 0–5.3%), despite similar doses delivered to the liver (median mean liver dose, 16.9 Gy; range, 3–22 Gy, in six fractions) (31). In the University of Colorado (UC) trial of SBRT for liver metastases (median follow-up, 12.9 months), a modification of the critical volume model (32) was applied. For liver SBRT, the fundamental premise is that to preserve adequate liver function, a minimum volume of normal liver must be spared from receiving a dose that might render it nonfunc- tional. This minimum ‘‘critical volume’’ was estimated from partial hepatectomy series to be 700 mL; the maximum dose allowed to this critical volume was estimated to be 15 Gy in three fractions (based on LQ conversion, a/b = 3 Gy) (33). No RILD or other severe toxicity has been observed to date after SBRT given according to these constraints (34). Comparisons between SBRT and conventional fraction- ation or hyperfractionation must be approached cautiously, given uncertainties in the models used to calculate biological equivalence. Recently, Tai combined LQ and Lyman model- ing to generate parameters based on clinical data that may be used to estimate equivalent doses based on differing fraction size (35), but Park has noted problems in the application of LQ modeling for SBRT and offered an alternative survival curve formulation (36). For the purpose of offering a visual example of the typical dose–volume histograms (DVHs) used in those settings, Figure 3 includes mean DVHs from the UM hyperfractionated experience and the UC SBRT ex- perience, but these should not be interpreted as an ideal DVH for these situations. Regarding the UM data, the doses shown in Figure 3A have been corrected to 1.5 Gy per fraction (us- ing LQ model, a/b = 2.5 Gy) and radiation was given with hepatic arterial FUdR (37). The UC data represent DVHs from the first 18 patients treated (33). One additional potential concern related to the use of high dose per fraction treatment is the observation of extrahepatic portal vein occlusion after high-dose intraoperative radiation therapy. Mitsunaga et al. observed 12 cases of extrahepatic portal vein occlusion among 53 patients who underwent pan- creaticoduodenectomy for periampullary disease followed by 20 Gy intraoperative radiation therapy to the resection bed (38). 8. RECOMMENDED DOSE–VOLUME LIMITS All dose–volume recommendations are associated with some uncertainty. Nevertheless, the data for RILD estimates have been reasonably well studied and analyzed. Long-term liver injury or biliary duct system damage is less well under- stood, because few patients have been followed for 5 or more years. Broad guidelines for normal liver dose constraints, for 5% or less risk of RILD, are offered as follows. Fig. 3. Characteristic normal liver (minus gross tumor volume) DVHs for low (a) or high (b) dose per fraction. (a) Mean normal liver DVHs from the University of Michigan for 204 patients who did or did not experience radiation-induced liver disease (RILD). (b) Mean normal liver dose–volume histogram from the University of Colorado SBRT Phase I trial with no RILD observed. See text for additional details. S98 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 99. Palliative whole-liver doses Livermetastases # 30 Gy, in 2 Gy per fraction 21 Gy in seven fractions (39) Primary liver cancers # 28 Gy, in 2 Gy per fraction 21 Gy in seven fractions (40) Therapeutic partial liver RT (standard fractionation) Mean normal liver dose (liver minus gross tumor volume) 28 Gy in 2-Gy fractions for primary liver cancer 32 Gy in 2-Gy fractions for liver metastases Nonuniform liver recommendations (SBRT, three to six fractions) Mean normal liver dose (liver minus gross tumor volume) 13 Gy for primary liver cancer, in three fractions 18 Gy for primary liver cancer, in six fractions 15 Gy for liver metastases, in three fractions 20 Gy for liver metastases, in six fractions 6 Gy for primary liver cancer, Child-Pugh B, in 4–6 Gy per fraction (for classic or nonclassic RILD) Critical volume model-based $ 700 mL of normal liver receives # 15 Gy in three to five fractions 9. FUTURE TOXICITY STUDIES A. Prospective studies with dose-volume data and serial long-term clinical/objective outcomes are needed. Differences in dose per fraction should also be considered. B. The impact of clinical variables (e.g., pre-RT liver func- tion) and other therapies (e.g., chemotherapy) that may impact the liver’s functional reserve need to be assessed. C. The timeframe for post-RT liver regeneration has not been well characterized. D. An improved understanding of the biological pathophys- iology of RT-induced liver injury, especially for nonclas- sic RILD, is needed, with an emphasis on identifying opportunities for injury mitigation by modulation of key signaling pathways (e.g., transforming growth fac- tor-b) (41). In this setting, pretreatment pathologic evalu- ation of the nonmalignant liver could potentially be useful for predicting the NTCP and may be a subject for future research. E. RT effects on nonparenchymal structures within the liver (e.g., biliary duct tolerance). F. Spatial variation in radiation sensitivity. 10. TOXICITY SCORING Studies of RT-induced liver injury should separately re- cord the incidence of classic and non-classic RILD. Preexist- ing liver dysfunction, as measured by the Child-Pugh score, should be recorded, as well as any change in status of Child- Pugh score after treatment. The use of CTCAE criteria for el- evations of aspartate aminotransferase, alanine aminotrans- ferase, alkaline phosphatase, platelet count, bilirubin, albumin, and prothrombin time is advisable to promote con- sistency of reporting. Screening for and treatment of hepatitis B and/or C before RT is recommended. REFERENCES 1. Yamasaki SA, Marn CS, Francis IR, et al. High-dose localized radiation therapy for treatment of hepatic malignant tumors: CT findings and their relation to radiation hepatitis. AJR Am J Roentgenol 1995;165:79–84. 2. Lawrence TS, Robertson JM, Anscher MS, et al. Hepatic toxic- ity resulting from cancer treatment. Int J Radiat Oncol Biol Phys 1995;31:1237–1248. 3. Xu Z-Y, Liang S-X, Zhu J, et al. Prediction of radiation-induced liver disease by Lyman normal-tissue complication probability model in three-dimensional conformal radiation therapy for pri- mary liver carcinoma. Int J Radiat Oncol Biol Phys 2006;65: 189–195. 4. Kim TH, Kim DY, Park J-W, et al. Dose-volumetric parameters predicting radiation-induced hepatic toxicity in unresectable he- patocellular carcinoma patients treated with three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 2007; 67:225–231. 5. Cheng JC-H, Wu J-K, Huang C-M, et al. Radiation-induced liver disease after three-dimensional conformal radiotherapy for patients with hepatocellular carcinoma: Dosimetric analysis and implication. Int J Radiat Oncol Biol Phys 2002;54:156–162. 6. Llovet JM, Ricci S, Mazzaferro V, et al. Sorafenib in advanced hepatocellular carcinoma. N Engl J Med 2008;359:378–390. 7. Kim JH, Park JW, Kim TH, et al. Hepatitis B virus reactivation after three-dimensional conformal radiotherapy in patients with hepatitis B virus-related hepatocellular carcinoma. Int J Radiat Oncol Biol Phys 2007;69:813–819. 8. Dawson LA, Normolle D, Balter JM, et al. Analysis of radia- tion-induced liver disease using the Lyman NTCP model. Int J Radiat Oncol Biol Phys 2002;53:810–821. 9. Shirato H, Seppenwoolde Y, Kitamura K, et al. Intrafractional tumor motion: Lung and liver. Semin Radiat Oncol 2004;14: 10–18. 10. Brock KK, McShan DL, Ten Haken RK, et al. Inclusion of organ deformation in dose calculations. Med Phys 2003;30:290–295. 11. Rosu M, Dawson LA, Balter JM, et al. Alterations in normal liver doses due to organ motion. Int J Radiat Oncol Biol Phys 2003;57:1472–1479. 12. Dawson LA, Brock KK, Kazanjian S, et al. The reproducibility of organ position using active breathing control (ABC) during liver radiotherapy. Int J Radiat Oncol Biol Phys 2001;51: 1410–1421. 13. Guckenberger M, Sweeney RA, Wilbert J, et al. Image-guided radiotherapy for liver cancer using respiratory-correlated com- puted tomography and cone-beam computed tomography. Int J Radiat Oncol Biol Phys 2008;71:297–304. 14. Penna C, Nordlinger B. Colorectal metastasis (liver and lung). Surg Clin North Am 2002;82:1075–1090, x–xi. 15. Ingold JA, Reed GB, Kaplan HS, et al. Radiation hepatitis. Am J Roentgenol Radium Ther Nucl Med 1965;93:200–208. Radiation-associated liver injury d C. C. PAN et al. S99
- 100. 16. Emami B,Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 17. Russell AH, Clyde C, Wasserman TH, et al. Accelerated hyper- fractionated hepatic irradiation in the management of patients with liver metastases: Results of the RTOG dose escalating pro- tocol. Int J Radiat Oncol Biol Phys 1993;27:117–123. 18. Liang S-X, Zhu X-D, Xu Z-Y, et al. Radiation-induced liver disease in three-dimensional conformal radiation therapy for primary liver carcinoma: The risk factors and hepatic radiation tolerance. Int J Radiat Oncol Biol Phys 2006;65:426–434. 19. Hata M, Tokuuye K, Sugahara S, et al. Proton beam therapy for hepatocellular carcinoma patients with severe cirrhosis. Strah- lenther Onkol 2006;182:713–720. 20. Wu DH, Liu L, Chen LH. Therapeutic effects and prognostic factors in three-dimensional conformal radiotherapy combined with transcatheter arterial chemoembolization for hepatocellu- lar carcinoma. World J Gastroenterol 2004;10:2184–2189. 21. Cheng JC-H, Wu J-K, Lee PC-T, et al. Biologic susceptibility of hepatocellular carcinoma patients treated with radiotherapy to radiation-induced liver disease. Int J Radiat Oncol Biol Phys 2004;60:1502–1509. 22. Seong J, Park HC, Han KH, et al. Clinical results and prognostic factors in radiotherapy for unresectable hepatocellular carci- noma: A retrospective study of 158 patients. Int J Radiat Oncol Biol Phys 2003;55:329–336. 23. Jackson A, Ten Haken RK, Robertson JM, et al. Analysis of clin- ical complication data for radiation hepatitis using a parallel ar- chitecture model. Int J Radiat OncolBiolPhys 1995;31:883–891. 24. Dawson LA, Ten Haken RK. Partial volume tolerance of the liver to radiation. Semin Radiat Oncol 2005;15:279–283. 25. Cheng JC-H, Liu H-S, Wu J-K, et al. Inclusion of biological fac- tors in parallel-architecture normal-tissue complication proba- bility model for radiation-induced liver disease. Int J Radiat Oncol Biol Phys 2005;62:1150–1156. 26. Yamada K, Izaki K, Sugimoto K, et al. Prospective trial of com- bined transcatheter arterial chemoembolization and three- dimensional conformal radiotherapy for portal vein tumor thrombus in patients with unresectable hepatocellular carci- noma. Int J Radiat Oncol Biol Phys 2003;57:113–119. 27. Herfarth KK, Hof H, Bahner ML, et al. Assessment of focal liver reaction by multiphasic CT after stereotactic single-dose radiotherapy of liver tumors. Int J Radiat Oncol Biol Phys 2003;57:444–451. 28. Mendez Romero A, Wunderink W, Hussain SM, et al. Stereo- tactic body radiation therapy for primary and metastatic liver tumors: A single institution phase i-ii study. Acta Oncol 2006; 45:831–837. 29. Hoyer M, Roed H, Traberg Hansen A, et al. Phase II study on stereotactic body radiotherapy of colorectal metastases. Acta Oncol 2006;45:823–830. 30. Tse RV, Hawkins M, Lockwood G, et al. Phase I study of indi- vidualized stereotactic body radiotherapy for hepatocellular car- cinoma and intrahepatic cholangiocarcinoma. J Clin Oncol 2008;26:657–664. 31. Lee MT, Kim JJ, Dinniwell R, et al. Phase I study of individu- alized stereotactic body radiotherapy of liver metastases. J Clin Oncol 2009;27:1585–1591. 32. Yaes RJ, Kalend A. Local stem cell depletion model for radiation myelitis. Int J Radiat Oncol Biol Phys 1988;14: 1247–1259. 33. Schefter TE, Kavanagh BD, Timmerman RD, et al. A phase I trial of stereotactic body radiation therapy (SBRT) for liver me- tastases. Int J Radiat Oncol Biol Phys 2005;62:1371–1378. 34. Kavanagh BD, Schefter TE, Cardenes HR, et al. Interim analy- sis of a prospective phase I/II trial of SBRT for liver metastases. Acta Oncol 2006;45:848–855. 35. Tai A, Erickson B, Khater KA, et al. Estimate of radiobiologic parameters from clinical data for biologically based treatment planning for liver irradiation. Int J Radiat Oncol Biol Phys 2008;70:900–907. 36. Park C, Papiez L, Zhang S, et al. Universal survival curve and single fraction equivalent dose: Useful tools in understanding potency of ablative radiotherapy. Int J Radiat Oncol Biol Phys 2008;70:847–852. 37. Dawson LA, Biersack M, Lockwood G, et al. Use of principal component analysis to evaluate the partial organ tolerance of normal tissues to radiation. Int J Radiat Oncol Biol Phys 2005;62:829–837. 38. Mitsunaga S, Kinoshita T, Kawashima M, et al. Extrahepatic portal vein occlusion without recurrence after pancreaticoduo- denectomy and intraoperative radiation therapy. Int J Radiat Oncol Biol Phys 2006;64:730–735. 39. Leibel SA, Guse C, Order SE, et al. Accelerated fraction- ation radiation therapy for liver metastases: Selection of an optimal patient population for the evaluation of late hepatic injury in RTOG studies. Int J Radiat Oncol Biol Phys 1990; 18:523–528. 40. Abrams RA, Cardinale RM, Enger C, et al. Influence of prog- nostic groupings and treatment results in the management of un- resectable hepatoma: Experience with Cisplatinum-based chemoradiotherapy in 76 patients. Int J Radiat Oncol Biol Phys 1997;39:1077–1085. 41. Anscher MS, Crocker IR, Jirtle RL. Transforming growth fac- tor-beta 1 expression in irradiated liver. Radiat Res 1990;122: 77–85. S100 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 101. QUANTEC: ORGAN SPECIFICPAPER Abdomen: Stomach/Small Bowel RADIATION DOSE–VOLUME EFFECTS IN THE STOMACH AND SMALL BOWEL BRIAN D. KAVANAGH, M.D., M.P.H.,* CHARLIE C. PAN, MD.,y LAURA A. DAWSON, M.D.,x SHIVA K. DAS, PH.D.,k X. ALLEN LI, PH.D.,{ RANDALL K. TEN HAKEN, PH.D.,* AND MOYED MIFTEN, PH.D.* *Department of Radiation Oncology, University of Colorado–Denver School of Medicine, Aurora, CO; y Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI; x Department of Radiation Oncology, Princess Margaret Hospital, University of Toronto, Toronto, ON, Canada; k Department of Radiation Oncology, Duke University Medical Center, Durham, NC; and { Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI Published data suggest that the risk of moderately severe ($Grade 3) radiation-induced acute small-bowel toxicity can be predicted with a threshold model whereby for a given dose level, D, if the volume receiving that dose or greater (VD) exceeds a threshold quantity, the risk of toxicity escalates. Estimates of VD depend on the means of structure segmenting (e.g., V15 = 120 cc if individual bowel loops are outlined or V45 = 195 cc if entire peritoneal potential space of bowel is outlined). A similar predictive model of acute toxicity is not available for stomach. Late small-bowel/stomach toxicity is likely related to maximum dose and/or volume threshold parameters qualitatively similar to those related to acute toxicity risk. Concurrent chemotherapy has been associated with a higher risk of acute toxicity, and a history of abdominal surgery has been associated with a higher risk of late toxicity. Ó 2010 Elsevier Inc. QUANTEC, Stomach, Small bowel, Radiation therapy, Toxicity. 1. CLINICAL SIGNIFICANCE The stomach and small bowel are contiguous, hollow visceral digestive organs. The stomach produces gastric acid and other factors that convert ingested food products into absorbable nu- trientsandinitiateperistalticactivity.Thereislessabsorptionof nutrients in the stomach than in the small bowel. The small bowel has three sections (the duodenum, jejunum, and ileum) with a large surface area through which water, carbohydrates, amino acids, and lipids are absorbed into the portal circulation. The stomach and small bowel are often incidentally irradi- ated when targeting tumors in the upper gastrointestinal (GI) tract, inferior lung, and retroperitoneum. The small bowel is also incidentally irradiated during radiation therapy (RT) to the pelvis. 2. ENDPOINTS Nausea and vomiting can occur immediately or within hours after RT to the stomach or small bowel. Days to weeks after the first treatment, RT-induced injury to the stomach ranges from self-limited mucosal inflammation causing dys- pepsia to ulceration and bleeding that can be life threatening. RT)–induced small-bowel mucositis can be expressed as cramping and diarrhea from interference with nutrient ab- sorption, typically developing 1 to 2 weeks after the start of RT. Weight loss can be a secondary consequence. The small bowel is also susceptible to late obstruction oc- curring weeks or months post-RT. In the bowel walls, RT-in- duced fibrosis can cause adhesions that limit bowel mobility and obstruct flow through the gut, sometimes requiring emer- gency surgery. Symptoms of chronic post-RT stomach injury may include long-term dyspepsia and ulceration (1). Chronic small-bowel injury from RT can include persistent diarrhea. In addition to obstruction, late small-bowel injury can manifest as ulcera- tion, fistula, perforation, and bleeding. Although a majority of symptoms occur within 3 years post-RT, patients remain at risk indefinitely. Patients who recover from initial compli- cations are also at risk for future complications. Malabsorp- tion of nutrients can occur as a late effect of RT, though the dose–volume associations for this are not well character- ized (2). The Cancer Therapy Evaluation Program Common Termi- nology Criteria for Adverse Events (CTCAE), Version 3.0, grade numerous types of GI toxicity. In general, Grade 1 tox- icities are radiographic findings of negligible clinical Reprint requests to: Brian D. Kavanagh, M.D., M.P.H., Univer- sity of Colorado–Denver, Department of Radiation Oncology, Cam- pus Mail Stop F706, 1665 Aurora Ct., Suite 1032, Aurora, CO 80045; Tel: (720) 848-0156; Fax: (720) 848-0222; E-mail: Brian. Kavanagh@ucdenver.edu Conflict of interest: none. Received Dec 10, 2008, and in revised form May 6, 2009. Accepted for publication May 6, 2009. S101 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S101–S107, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.05.071
- 102. consequences and arerarely scored in reports of RT-induced toxicity. Grade 2 to 4 toxicities generally reflect injury of moderate, severe, or life-threatening severity, respectively. 3. CHALLENGES IN DEFINING VOLUMES The stomach is a thick-walled muscular organ with a vol- ume of 1.5 to 2 L in adults. Although the stomach usually is easily seen on treatment planning scans, oral contrast can aid in its definition. The stomach wall can vary in position based upon its contents. To minimize variability in the volume and location of the stomach, patients should avoid large meals or carbonated beverages before simulation and treatment. It is sometimes challenging to differentiate small bowel from vessels, nodes, and large bowel on planning CT images. Although oral contrast given before imaging can aid visuali- zation, high-density contrast can affect dose calculations that account for tissue heterogeneity. If treatment beams pass through contrast-containing small bowel seen on the plan- ning CT, one option is to calculate dose without heterogene- ity correction; a medical physicist should be involved in the planning process when there is uncertainty regarding the overall impact of heterogeneity correction in this setting. Al- ternatively, some planning systems allow for contrast to be segmented as a structure that can be assigned water density, thus still allowing for heterogeneity correction that accounts for other structures of variable density (e.g., bone or lung) present within treatment fields. Different methods of delin- eating the small-bowel volume have contributed to variant dose–toxicity relationship observations, as discussed later here. Except for sections of the small bowel that are largely im- mobile (e.g., duodenum and regions with postsurgical adhe- sions), there are day-to-day variations in the bowel location. The capacity for small-bowel mobility within the peritoneal space may be constant throughout a course of conventionally fractionated treatment (3). Martin et al. observed that relative to supine, a prone position with a belly board significantly re- duced the volume of small bowel receiving 80% to 100% of the prescribed dose during pelvic treatment for gynecologic cancer (4). 4. REVIEW OF DOSE–VOLUME DATA Emami et al. estimated doses with a 5% or 50% risk at 5 years (TD5/5 and TD50/5, respectively) for late stomach or small-bowel toxicities but did not offer estimates to predict acute toxicities (5). The TD 5/5 estimate for gastric ulceration or perforation after whole-organ irradiation, 50 Gy, has en- dured as a broad dose limit guideline when fields encompass a large portion of stomach, albeit with rather limited support from actual published data. The TD50/5 estimate for irradia- tion of the entire stomach (65 Gy) is entirely unchallenged, likely because there are few scenarios in which a dose of that magnitude is administered to the stomach—except pos- sibly for a primary unresectable gastric malignancy, in which case the effects of the tumor itself would render separate eval- uation of normal tissue toxicity problematic. The TD5/5 estimate for 1/3 small-bowel irradiation, 50 Gy, remains a commonly applied dose limit when small portions of the small bowel are treated with conventional fractionation, and recently published data are fairly consis- tent with this estimate. The TD50/5 estimate for partial small-bowel irradiation, 60 Gy, is largely unchallenged, as are the whole-organ irradiation TD5/5 and TD50/5 estimates (40 Gy and 55 Gy, respectively). In this section, the available data relating RT dose to acute and late toxicity risk are reviewed. Acute RT-induced toxicity to the stomach Very few published experiences allow for the separation of acute effects on the stomach alone from combined stomach/ small-bowel effects. A Japanese study of patients with stom- ach lymphoma treated with cytoxan, daunorubicin, vincris- tine, and prednisone followed by 40.5 Gy to the primary site and regional nodes yielded a 4% (2/52) rate of Grade $3 acute nausea (6). No hemorrhage or perforation of the stomach was reported. In the Gastrointestinal Tumor Study Group (GITSG) study of unresectable pancreatic cancer, pa- tients receiving 60 Gy AP-PA RT had a 36% incidence of nausea (grade not specified). Volumetric data regarding the portion of stomach included in the fields are not reported. Adding intravenous 5-FU increased the nausea incidence to 48% (7). In a randomized clinical trial of 8 Gy single fraction lower hemi-body RT (including stomach), Sykes et al. observed a 66% rate of moderate–severe nausea with dexamethasone and chlorpromazine vs. a 6% rate with ondansetron (8 mg p.o.1 to 2 h pre-RT and maintenance dose of 8 mg p.o. b.i.d.) (8). In a more recent Canadian study of patients receiv- ing $20 Gy in $15 fractions to an area of $80 cm2 (in the coronal plane) from T11 to L3 (inclusive), adding dexameth- asone to ondansetron improved complete nausea control rates compared to ondansetron alone (23% vs. 12%, p = 0.02) and lowered average nausea scores (p = 0.03) (9). Stomach and small bowel dose–volume histograms were not reported. Late radiation-induced toxicity to the stomach Early reports include the analysis of testicular cancer patients treated with para-aortic RT at Walter Reed Army Medical Center in the 1940s and 1950s (10). The volume of stomach in the field was not quantified. The gastric ulcer- ation rates were 4% (6/161) vs. 16% (9/56) after doses 50 Gy vs. $50 Gy. Likewise, the perforation rates were 2% (3/161) vs. 14% (8/56) after doses 50 Gy vs. $50 Gy. Cosset et al. reported late gastric complications (ulcer of stomach/duodenum, severe gastritis, obstruction) in Euro- pean Organization for Research and Treatment of Cancer (EORTC) trials of RT for Hodgkin’s disease (11). Among 516 patients treated, severe toxicities included the following: ulcers (n = 25), severe gastritis (n = 2), and small-bowel ob- struction and/or perforation (n = 9). Nearly all patients re- ceived close to 40 Gy. Among 345 patients receiving 39 to 41 Gy over 5 weeks, patients with higher fraction sizes were more likely to develop complications (4% after weekly S102 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 103. doses of 5 2 Gy, 9% after 4  2.5 Gy, and 22% after 3  3.3 Gy). There was no documentation of the volume of stom- ach irradiated. Goldstein et al. noted radiological abnormalities of the dis- tal stomach in 8% (10/121) of women 1 to 25 months after 50 Gy to the para-aortic nodes for metastatic cervix cancer (12). The lesions were all ulcers in or near the pylorus; only two required surgical intervention. In addition, 1 of 52 men who received 40 to 50 Gy of para-aortic nodal RT for testic- ular tumors developed gastric outlet obstruction secondary to a pyloric ulcer 3 months later. The effect of adding chemotherapy to RT on late toxicity is uncertain. Cohen et al. reported only 1 Grade 3 GI toxicity in 104 patients treated to 59.4 Gy to a pancreatic tumor with 2- cm margin; half of the patients also received 5-FU and mito- mycin-C (13). However, median overall survival was 9 months and thus was possibly not long enough for some late toxicity to appear. Talamonti et al. observed an unaccept- able rate of gastric and duodenal ulcers from RT to the pan- creatic tumor plus a 2-cm margin with weekly concurrent gemcitabine (50 mg/m2 per week) and protracted intravenous 5-fluorouracil (5-FU; 200 mg/m2 per day) (14). Others have reported no difference between toxicity observed with RT plus 5-FU vs. RT plus gemcitabine alone (600 mg/m2 weekly  6) (15), which was the regimen used in a Eastern Cooper- ative Oncology Group (ECOG) study (16). Using a higher dose of weekly gemcitabine (1,000 mg/m2  3) concurrent with 36 Gy in 15 fractions for unresectable pancreas cancer, Murphy et al. reported an 8% incidence of upper GI bleeding as a late complication. Patients with the larger PTVs (260 cc) were at higher risk of severe acute or late toxicity than were patients with smaller PTVs (17). Thus, for the stomach, a dose on the order of 50 Gy has been associated with a 2% to 6% risk of clinical sever late in- jury, generally concordant with the Emami et al. whole organ TD5/5 estimate. The effect of stomach volume is not well characterized. Acute RT-induced toxicity to the small bowel A literature review for small-bowel complications (diar- rhea, obstruction or constriction, fistula or perforation, ulcer- ation) yielded six studies with quantitative dose–volume analyses (Table 1). In each study, either all or a majority of patients received concurrent chemotherapy, and thus each modality’s independent contribution on toxicity is unknown. The major observations are shown in the table (see Mathe- matical/Biological Models section for further discussion of the threshold model). Concurrent chemotherapy adds to RT-induced acute small-bowel toxicity. In a Gynecologic Oncology Group study, cervix cancer patients who received 45 Gy pelvic RT alone experienced a 5% (9/186) rate of Grade 3 to 4 GI toxicity vs. 14% (26/183) from RT plus weekly cisplatin (40 mg/m2 ) (24). Macdonald et al. observed a 33% (89/ 273) rate of Grade $3 acute toxicity (nausea, vomiting, and diarrhea) from an initial cycle of 5FU (350 mg/m2 /day for 5 days) + lecovorin followed by 5FU + leucovorin con- current with 45 Gy postoperative RT for carcinoma of the stomach or gastroesophageal junction (25). This higher rate is possibly caused by a larger volume of small bowel in the field; the incidence of Grade 3 events in the group that re- ceived no adjuvant therapy was not reported. In the EORTC study comparing preoperative RT (45 Gy) vs. the same plus two cycles of 5-FU, diarrhea of Grade $2 occurred in 17% of patients after RT alone and in 38% of patients after chemo- therapy + RT (p 0.001) (26). However, for rectal cancer acute effects on large bowel are difficult to distinguish from effects on small bowel. Late RT-induced toxicity to the small bowel Mak et al. reviewed 224 rectal cancer patients treated with a median dose of 54 Gy (34–66 Gy) at 1.8 to 2 Gy/fraction; 29 developed small-bowel obstructions 0 to 69 months (me- dian, 7 months) later (27). The small-bowel obstruction rate was 30% in patients treated with fields extending to L1 or L2 vs. 9% with pelvis-only fields. Small-bowel obstruction was higher in the presence of postsurgical adhesions before RT and in the absence of reperitonealization at the time of ini- tial surgery (p 0.05). Hamilton et al. observed a 5% rate of duodenal ulceration in 142 patients treated for Stage I teratoma (28). The RT dose was primarily 40 Gy in 20 fractions (range, 30–51 Gy). De- tailed dose–volume analysis was not reported. The Uppsala University rectal cancer study compared pre- operative pelvic RT, 25.5 Gy delivered in five fractions, vs. 60 Gy in 7 to 8 weeks of split-course postoperative RT, with a reduced field for the last 10 Gy (29). Some patients did not have RT. At a minimum follow-up of 5 years, a surgi- cal or radiographic diagnosis of small-bowel obstruction was made in 5% of patients (14/255) after preoperative RT, 11% (14/127) after postoperative RT, and 6% (5/82) after surgery alone. The Swedish and Dutch randomized rectal trials evaluated preoperative pelvic RT (25 Gy in 5-Gy fractions in 1 week) followed by surgery (30–32). The Swedish trial involved larger treatment fields (superior border, L4) than the Dutch trial (sacral promontory). In the Dutch trial, RT increased rates of fecal incontinence, need for pad wearing, bleeding, and dissatisfaction with bowel function. However, bowel ob- struction rates were the same (11%) with or without preoper- ative RT (30). Long-term follow-up of the Swedish trial patients, by contrast, showed that preoperative RT increased the risk of small-bowel obstruction (14-year actuarial risk 14% vs. 6% in controls, p 0.001) (33). Bujko et al. noted that short-course preoperative RT (25 Gy in 5 fractions in 1 week) and concurrent preoperative RT/chemotherapy (50.4 Gy in 28 fractions with concurrent 5-FU + leucovorin) were associated with a 5% and 1% rate of Grade $3 late GI toxicity (ileus, fistula, or anastomotic stenosis), respectively (median follow-up, 48 months) (34). In the Phase III German Rectal Cancer Study Group (35), pre- vs. postoperative pelvic RT (50.4 Gy in 28 fractions) were associated with a 9% vs. 15% rate of long term GI tox- icity (p = 0.07). This difference was primarily from chronic RT dose–volume effects in the stomach and small bowel d B. D. KAVANAGH et al. S103
- 104. diarrhea; the rateof small-bowel obstruction requiring reop- eration was small and not statistically significantly different between groups (2% vs 1%, p = 0.70). Thus, in modern series, after doses on the order of 50 Gy, late small-bowel obstruction or perforation rates of 2% to 9% have been observed after partial organ irradiation, concordant with the Emami et al. TD5/5 estimate. A dose of 25 Gy in five fractions of preoperative RT is associated with late toxicity within that same range. 5. FACTORS AFFECTING RISK The effect of concurrent chemotherapy to increase acute toxicity is discussed above. Prior abdominal surgery, gener- ally causing some scar tissue in the peritoneal cavity, can pre- dispose a patient to small-bowel obstruction from RT. In the EORTC Hodgkin’s disease trials, the late gastrointestinal complication rate was 2.7% without prior abdominal surgery and 11.5% after prior laparotomy (11). 6. MATHEMATICAL/BIOLOGICAL MODELS Pan et al. reported gastric bleeds after hyperfractionated RT in 12 of 92 patients with liver tumors (36). Median time to bleeds was 3.5 months (range, 1–8 months). Mean dose to the stomach averaged 14 Gy (range, 0.1–68). The minimum dose to the 1 cc receiving the highest dose aver- aged 47 Gy (range, 0.30–93). Using the Lyman-Kutcher- Burman (LKB) model, the parameters TD50(1), m, and n were estimated to be 59 Gy, 0.30, and 0.09, respectively, con- sistent with a dose threshold for bleeding without a large vol- ume effect. Multivariate analysis demonstrated that in addition to NTCP, the maximum dose to stomach and pres- ence of cirrhosis were significantly associated with gastric bleed. Cirrhotic and noncirrhotic patients had an estimated 5% risk of bleeding if the maximum stomach dose was at least 6.8 Gy or 47.9 Gy, respectively. Baglan et al. generated a threshold-type model of acute small-bowel toxicity in an analysis of patients treated for rec- tal cancer (18). A significant association between Grade 3 acute toxicity and absolute volume of small bowel irradiated was found at each dose level, analyzed in 5-Gy bins. Baglan et al. identified V15 as an especially important parameter: for patients without Grade 3 toxicity, the mean V15 was 127 cc, whereas for patients who had Grade 3 toxicity the mean V15 was 319 cc (p 0.001). Other patient-related factors were sta- tistically insignificant, including the sequence of RT and sur- gery. The model was later validated by Robertson et al. in a second cohort of patients (22). In essence, the Baglan–Robertson model predicts a low risk ($10%) of Grade $3 acute small-bowel toxicity for pa- tients whose absolute volumes of small bowel receiving 5 to 40 Gy (V5–V40) are below the curve shown in Fig. 1. Pa- tients whose V5 to V40 values are above the curve have a higher ($40% risk) of Grade $3 toxicity. Quantitatively concordant with the Baglan–Robertson model are two of the studies in Table 1. Gunlaugsson et al. observed a point threshold effect whereby patients with an absolute V15 150 cc experienced a low risk (1/9) of Grade $2 acute toxicity vs. a higher risk (10/19) for V15 $ 150 cc (23). The V15 cutoff in the Baglan–Robertson model was 120 cc. Likewise, results from Tho et al. support the Ba- glan–Robertson model: among 41 patients studied, the abso- lute small-bowel volumes determined at 5-Gy dose intervals (V5–V40 and V 42.75) correlated strongly with diarrhea severity at every dose level (p 0.03), with the strongest cor- relation at low doses (20). All other patient-related factors in the analysis were statistically insignificant. Huang et al. evaluated small-bowel volumes at 10% inter- vals of the prescribed dose and observed volume dependence for toxicity largely consistent with the Baglan–Robertson model (21). Among patients without prior abdominal sur- gery, the mean V16 for those with acute Grade 2 to 3 toxicity was 489 cc, vs. 281 cc for those without toxicity (p = 0.001). Likewise, for patients with prior surgery, the mean V40 was higher in those with Grade 2 to 3 toxicity vs. without (132 cc vs. 56 cc, p = 0.027). Quantitatively but not qualitatively different from the Ba- glan–Robertson model are the observations of Roeske et al., who derived a similar volume threshold–based risk model (19). The Roeske et al. curve, however, contained y-axis (ab- solute volume) values several times greater than those of the Baglan–Robertson model for each dose level along the x-axis. The discrepancy is explained by the methods of delin- eating small bowel: Roeske et al. outlined the entire potential Table 1. Quantitative analyses of acute small bowel toxicity Authors, Reference, No. of patients Primary cancer Prescription dose (Gy) Observed predictor of toxicity Baglan et al. (18) (N = 40) Rectal 45–50 Threshold volume at given doses Roeske et al. (19) (N = 50) Cervix 45 Absolute small bowel volume (peritoneal space) receiving 45 Gy Tho et al. (20) (N = 41) Rectal 45 Absolute small bowel volume receiving 5–40 Gy Huang et al. (21) (N = 80)* Cervix, endometrial 39.6–45 Absolute small bowel volume: 16 Gy (prior surgery) 40 Gy (no prior surgery) Robertson et al. (22) (N = 96) Rectal 45–50 Baglan threshold model doses (see Fig. 1) Gunnlaugsson et al. (23) (N = 28) Rectal 50 Absolute small bowel volume 15 Gy * All studies were retrospective except Huang et al., which was prospective. In all cases the fractionation scheme involved 1.8 to 2.0 Gy per day prescription dose. Most of the studies used concurrent 5-fluorouracil (5FU)–based chemotherapy except for cisplatin alone in the Roeske et al. study, 5FU + cisplatin in Huang et al., and 5FU + oxaliplatin in Gunnlaugsson et al. In the Huang et al. study, 30 patients did not receive chemotherapy. S104 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 105. space of small-bowellocation, whereas Baglan and Robert- son outlined only actual bowel loops. The Roeske volume constraints indicate that peritoneal cavity volume (small- bowel surrogate) above the prescription dose (45–50 Gy) should be held to 195 cc. Chen et al. assessed acute small-bowel toxicity in two co- horts of post- hysterectomy cervix cancer patients receiving adjuvant pelvic RT plus concurrent cisplatin (50 mg/m2 weekly  6) (37). The first 35 patients received conventional four-field box RT, and the next 33 patients received IMRT, in all cases to 50.4 Gy in 1.8-Gy/fractions. Acute GI toxicity was reduced with IMRT, which halved the small-bowel vol- ume receiving 35 Gy, a result concordant with the threshold model concept. All of the previously mentioned work pertains to predic- tions of acute toxicity. Letschert et al. related dose–volume parameters to late small-bowel complications (38). In 111 pa- tients who received pelvic and/or para-aortic RT to a dose of 45 to 50 Gy over 5 weeks, the incidence of late toxicity was related to the volume of bowel within the field. The lowest risk group (three-field pelvic RT, estimated 165 cc of small bowel) had a 6% incidence of severe late toxicity, whereas the highest risk group (opposed anterior and posterior treat- ment fields, estimated 790 cc) had a 37% risk. The authors modeled complication risk as a power law function of volume that predicted isotoxicity for each doubling of the volume of bowel in the field if the RT dose was reduced by 17%. 7. SPECIAL SITUATIONS Most published clinical data involve conventionally frac- tionated treatment with daily prescription doses to the tumor of approximately 2 Gy or less. Current interest in stereotactic body radiation therapy (SBRT) raises questions about the extent to which observations based on low dose per fraction are applicable to SBRT, where the daily dose to the tumor is on the order of $10 Gy. Hoyer et al. reported toxicities in 64 patients treated with SBRT to liver metastases (45 Gy in three fractions over 5– 8 days) (39). With a median follow-up of 4.3 years, one co- lonic perforation and two duodenal ulcerations were noted. In all three cases, portions of the bowel received a total dose of $30 Gy in three fractions. Koong et al. treated 16 patients with locally advanced pancreatic cancer using concurrent 5-FU and RT to 45 Gy in 1.8 Gy fractions, followed by a sin- gle-fraction 25-Gy SBRT boost (40). Two patients (12.5%) developed duodenal ulcers 4 to 6 months later. Schellenberg et al. later reported on 16 patients receiving SBRT (25-Gy single fraction) alone between Cycles 1 and 2 of gemcitabine for pancreas cancer (41). The volume of small bowel receiv- ing 12.5 Gy was 30 cc and 30 cc for patients without and with late toxicity, respectively (p = 0.13). A more recent anal- ysis of a larger cohort, from the same institution, of 77 pa- tients treated with 25 Gy single fraction SBRT (16 had 45 Gy external-beam RT also) included the constraints applied (42). For the stomach, 4% of volume could receive 22.5 Gy, and the 50% isodose line should not reach the nonadja- cent luminal wall. For the small bowel (duodenum), 5% re- ceived 22.5 Gy, and 50% received 12.5 Gy, again not allowing the 50% isodose line to reach the opposite luminal wall. These constraints were associated with a 9% (7/77) crude rate of late stomach or duodenal toxicity. Hoyer et al. observed a higher rate of late toxicity after SBRT (45 Gy in three fractions) for pancreatic cancer: 4 of 22 patients experienced severe mucositis or ulceration of the stomach or duodenum, and 1 of 22 had a nonfatal stomach perforation (43). A dose–volume effect likely explains the observations of these investigators to a large extent; in the Hoyer et al. study, the median volume receiving $30 Gy was 136 cc, notably higher than in the Schellenberg et al. trial. After single-fraction high-dose-rate brachytherapy for liver cancers, Streitparth et al. found a threshold dose to the 1 ml receiving the highest dose (D1 ml) of 11 Gy for general gastric toxicity and 15.5 Gy for ulceration. Among patients with D1 ml 15.5 Gy, 5 of 13 patients experienced gastric ulceration, versus none for D1 ml 15.5 Gy (44). 8. RECOMMENDED DOSE/VOLUME LIMITS Literature on RT-induced stomach toxicity is relatively sparse, with insufficient data to arrive at firm dose–volume constraints for partial volume irradiation. Doses of RT on the order of 45 Gy to the whole stomach are associated with late effects (primarily ulceration) in approximately 5% to 7% of patients. Emerging data suggest that the maximum point dose might be an important predictor of toxicity, but corroborating data are needed to confirm this hypothesis. For SBRT, the volume of stomach receiving 22.5 Gy should be minimized and ideally constrained to 4% of the organ volume, or approximately 5 cc, with maximum point dose 30 Gy for three-fraction SBRT. Fig. 1. Graphic representation of the Baglan–Robertson threshold model for risk of acute small bowel toxicity. Here, ‘‘low risk’’ im- plies $10% and ‘‘high risk’’ $40%. Note that the y-axis represents the absolute volume of individual bowel loops and not the peritoneal space. RT dose–volume effects in the stomach and small bowel d B. D. KAVANAGH et al. S105
- 106. The absolute volumeof small bowel receiving $15 Gy should be held to 120 cc when possible to minimize severe acute toxicity, if delineating the contours of bowel loops themselves. Alternatively, if the entire volume of peritoneal space in which the small bowel can move is delineated, the volume receiving 45 Gy should be 195 cc when possible. Such a limit likely also reduces late toxicity risk, although this correlation is not established. The volume of small bowel receiving higher doses should also be minimized. For SBRT, the small-bowel volume receiving 12.5 Gy in a single frac- tion should ideally be kept to 30 cc with avoidance of cir- cumferential coverage above that dose; for a three- to five- fraction regimen, the maximum point dose should be 30 Gy. 9. FUTURE TOXICITY STUDIES The body of literature relating RT dose to risk of stomach/ small-bowel toxicity is small compared with the amount of data published on RT effects in some other organs. The wide- spread use of computed tomography–based treatment plan- ning should allow expansion of this literature. In addition, the impact of systemic agents on RT-induced stomach and small-bowel toxicity needs to be understood more com- pletely. Characterizing the molecular events of RT-induced stomach and small-bowel injury might reveal opportunities for injury mitigation by modulation of key signaling pathways. 10. TOXICITY SCORING Acute and late RT-induced stomach and small-bowel in- jury scoring should measure nausea, diarrhea, obstruction, bleeding/ulceration, weight loss, and fistulae. The Common Terminology Criteria for Adverse Events v3.0 (CTC AE v3.0) provides a framework to capture data regarding the tim- ing and severity of symptoms. Patient-reported outcomes should also be used when possible. General nutrition surro- gates such as weight or albumin might also serve as markers of RT-induced GI toxicity. REFERENCES 1. Coia LR, Myerson RJ, Tepper JE. Late effects of radiation ther- apy on the gastrointestinal tract. Int J Radiat Oncol Biol Phys 1995;31:1213–1236. 2. Vistad I, Kristensen GB, Fossa˚ SD, et al. Intestinal malabsorp- tion in long-term survivors of cervical cancer treated with radio- therapy. Int J Radiat Oncol Biol Phys 2009;73:1141–1147. 3. Acker JC, Marks LB. The lack of impact of pelvic irradiation on small bowel mobility: Implications for radiotherapy treat- ment planning. Int J Radiat Oncol Biol Phys 1995;32:1473– 1475. 4. Martin J, Fitzpatrick K, Horan G, et al. Treatment with a belly- board device significantly reduces the volume of small bowel irradiated and results in low acute toxicity in adjuvant radiother- apy for gynecologic cancer: Results of a prospective study. Radiother Oncol 2005;74:267–274. 5. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 6. Ishikura S, Tobinai K, Ohtsu A, et al. Japanese multicenter phase II study of CHOP followed by radiotherapy in stage I– II, diffuse large B-cell lymphoma of the stomach. Cancer Sci 2005;96:349–352. 7. Moertel CG, Frytak S, Hahn RG, et al. Therapy of locally unre- sectable pancreatic carcinoma: A randomized comparison of high dose (6000 rads) radiation alone, moderate dose radiation (4000 rads + 5-fluorouracil), and high dose radiation + 5-fluoro- uracil: The Gastrointestinal Tumor Study Group. Cancer 1981; 48:1705–1710. 8. Sykes AJ, Kiltie AE, Stewart AL. Ondansetron versus a chlor- promazine and dexamethasone combination for the prevention of nausea and vomiting: A prospective, randomised study to assess efficacy, cost effectiveness and quality of life following single-fraction radiotherapy. Support Care Cancer 1997;5: 500–503. 9. Wong RK, Paul N, Ding K, et al. 5-Hydroxytryptamine-3 recep- tor antagonist with or without short-course dexamethasone in the prophylaxis of radiation induced emesis: A placebo- controlled randomized trial of the National Cancer Institute of Canada Clinical Trials Group (SC19). J Clin Oncol 2006;24: 3458–3464. 10. Brick IB. Effects of million volt irradiation on the gastrointesti- nal tract. Arch Intern Med 1955;96:26–31. 11. Cosset JM, Henry-Amar M, Burgers JM, et al. Late radiation in- juries of the gastrointestinal tract in the H2 and H5 EORTC Hodgkin’s disease trials: Emphasis on the role of exploratory laparotomy and fractionation. Radiother Oncol 1988;13:61–68. 12. Goldstein HM, Rogers LF, Fletcher GH, Dodd GD. Radiologi- cal manifestations of radiation-induced injury to the normal up- per gastrointestinal tract. Radiology 1975;117:135–140. 13. Cohen SJ, Dobelbower R Jr., Lipsitz S, et al. A randomized phase III study of radiotherapy alone or with 5-fluorouracil and mitomycin-C in patients with locally advanced adenocarci- noma of the pancreas: Eastern Cooperative Oncology Group study E8282. Int J Radiat Oncol Biol Phys 2005;62:1345–1350. 14. Talamonti MS, Catalano PJ, Vaughn DJ, et al. Eastern Cooper- ative Oncology Group Phase I trial of protracted venous infu- sion fluorouracil plus weekly gemcitabine with concurrent radiation therapy in patients with locally advanced pancreas cancer: A regimen with unexpected early toxicity. J Clin Oncol 2000;18:3384–3389. 15. Li CP, Chao Y, Chi KH, et al. Concurrent chemoradiotherapy treatment of locally advanced pancreatic cancer: Gemcitabine versus 5-fluorouracil, a randomized controlled study. Int J Ra- diat Oncol Biol Phys 2003;57:98–104. 16. Loehrer P, Powell ME, Cardenes HR, et al. A randomized phase III study of gemcitabine in combination with radiation therapy versus gemcitabine alone in patients with localized, unresect- able pancreatic cancer. J Clin Oncol 2008;(Suppl):26. abstract 4506. 17. Murphy JD, Adusumilli S, Griffith KA, et al. Full-dose gemci- tabine and concurrent radiotherapy for unresectable pancreatic cancer. Int J Rad Oncol Biol Phys 2007;68:801–808. 18. Baglan KL, Frazier RC, Yan D, et al. The dose-volume relation- ship of acute small bowel toxicity from concurrent 5-FU-based chemotherapy and radiation therapy for rectal cancer. Int J Ra- diat Oncol Biol Phys 2002;52:176–183. 19. Roeske JC, Bonta D, Mell LK, et al. A dosimetric analysis of acute gastrointestinal toxicity in women receiving intensity- modulated whole-pelvic radiation therapy. Radiother Oncol 2003;69:201–207. S106 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 107. 20. Tho LM,Glegg M, Paterson J, et al. Acute small bowel toxicity and preoperative chemoradiotherapy for rectal cancer: Investi- gating dose-volume relationships and role for inverse planning. Int J Radiat Oncol Biol Phys 2006;66:505–513. 21. Huang EY, Sung CC, Ko SF, et al. The different volume effects of small-bowel toxicity during pelvic irradiation between gyne- cologic patients with and without abdominal surgery: A pro- spective study with computed tomography-based dosimetry. Int J Radiat Oncol Biol Phys 2007;69:732–739. 22. Robertson JM, Lockman D, Yan D, et al. The dose-volume re- lationship of small bowel irradiation and acute grade 3 diarrhea during chemoradiotherapy for rectal cancer. Int J Radiat Oncol Biol Phys 2008;70:413–418. 23. Gunnlaugsson A, Kjellen E, Nilsson P, et al. Dose-volume re- lationships between enteritis and irradiated bowel volumes dur- ing 5-fluorouracil and oxaliplatin based chemoradiotherapy in locally advanced rectal cancer. Acta Oncol 2007;46:937–944. 24. Keys HM, Bundy BN, Stehman FB, et al. Cisplatin, radiation, and adjuvant hysterectomy compared with radiation and adju- vant hysterectomy for bulky stage IB cervical carcinoma. N Engl J Med 1999;340:1154–1161. 25. Macdonald JS, Smalley SR, Benedetti J, et al. Chemoradiother- apy after surgery compared with surgery alone for adenocarci- noma of the stomach or gastroesophageal junction. N Engl J Med 2001;345:725–730. 26. Bosset JF, Collette L, Calais G, et al. Chemotherapy with pre- operative radiotherapy in rectal cancer. N Engl J Med 2006; 355:1114–1123. 27. Mak AC, Rich TA, Schultheiss TE, et al. Late complications of postoperative radiation therapy for cancer of the rectum and rec- tosigmoid. Int J Radiat Oncol Biol Phys 1994;28:597–603. 28. Hamilton CR, Horwich A, Bliss JM, et al. Gastrointestinal mor- bidity of adjuvant radiotherapy in stage I malignant teratoma of the testis. Radiother Oncol 1987;10:85–90. 29. Frykholm GJ, Glimelius B, Pahlman L. Preoperative or postop- erative irradiation in adenocarcinoma of the rectum: Final treat- ment results of a randomized trial and an evaluation of late secondary effects. Dis Colon Rectum 1993;36:564–572. 30. Peeters KC, van de Velde CJ, Leer JW, et al. Late side effects of short-course preoperative radiotherapy combined with total mesorectal excision for rectal cancer: Increased bowel dysfunc- tion in irradiated patients—a Dutch colorectal cancer group study. J Clin Oncol 2005;23:6199–6206. 31. Peeters KC, Marijnen CA, Nagtegaal ID, et al. The TME trial after a median follow-up of 6 years: Increased local control but no survival benefit in irradiated patients with resectable rec- tal carcinoma. Ann Surg 2007;246:693–701. 32. Folkesson J, Birgisson H, Pahlman L, et al. Swedish Rectal Cancer Trial: Long lasting benefits from radiotherapy on sur- vival and local recurrence rate. J Clin Oncol 2005;23:5644– 5650. 33. Birgisson H, Pahlman L, Gunnarsson U, et al. Late gastro- intestinal disorders after rectal cancer surgery with and without preoperative radiation therapy. Br J Surg 2008;95: 206–213. 34. Bujko K, Nowacki MP, Nasierowska-Guttmejer A, et al. Long-term results of a randomized trial comparing preoperative short-course radiotherapy with preoperative conventionally fractionated chemoradiation for rectal cancer. Br J Surg 2006; 93:1215–1223. 35. Sauer R, Becker H, Hohenberger W, et al. Preoperative versus postoperative chemoradiotherapy for rectal cancer. N Engl J Med 2004;351:1731–1740. 36. Pan CC, Dawson LA, McGinn CJ, et al. Analysis of radiatio- n-induced gastric and duodenal bleeds using the Lyman- Kutcher-Burman model. Int J Radiat Oncol Biol Phys 2003; 57:S217–S218. 37. Chen MF, Tseng CJ, Tseng CC, et al. Clinical outcome in post- hysterectomy cervical cancer patients treated with concurrent Cisplatin and intensity-modulated pelvic radiotherapy: Com- parison with conventional radiotherapy. Int J Radiat Oncol Biol Phys 2007;67:1438–1444. 38. Letschert JG, Lebesque JV, de Boer RW, et al. Dose-volume correlation in radiation-related late small-bowel complications: A clinical study. Radiother Oncol 1990;18:307–320. 39. Hoyer M, Roed H, Traberg Hansen A, et al. Phase II study on stereotactic body radiotherapy of olorectal metastases. Acta On- col 2006;45:823–830. 40. Koong AC, Christofferson E, Le QT, et al. Phase II study to as- sess the efficacy of conventionally fractionated radiotherapy followed by a stereotactic radiosurgery boost in patients with lo- cally advanced pancreatic cancer. Int J Radiat Oncol Biol Phys 2005;63:320–323. 41. Schellenberg D, Goodman KA, Lee F, et al. Gemcitabine che- motherapy and single-fraction stereotactic body radiotherapy for locally advanced pancreatic cancer. Int J Radiat Oncol Biol Phys 2008;72:678–686. 42. Chang DT, Schellenberg D, Shen J, et al. Stereotactic radiother- apy for unresectable adenocarcinoma of the pancreas. Cancer 2009;115:665–672. 43. Hoyer M, Roed H, Sengelov L, et al. Phase II study on stereo- tactic radiotherapy of locally advanced pancreatic carcinoma. Radiother Oncol 2005;76:48–53. 44. Streitparth F, Pech M, Bo¨hmig M, et al. In vivo assessment of the gastric mucosal tolerance dose after single fraction, small volume irradiation of liver malignancies by computed tomogra- phy-guided, high-dose-rate brachytherapy. Int J Radiat Oncol Biol Phys 2006;65:1479–1486. RT dose–volume effects in the stomach and small bowel d B. D. KAVANAGH et al. S107
- 108. QUANTEC: ORGAN-SPECIFIC PAPERAbdomen: Kidney RADIATION-ASSOCIATED KIDNEY INJURY LAURA A. DAWSON, M.D.,* BRIAN D. KAVANAGH, M.D.,y ARNOLD C. PAULINO, M.D.,z SHIVA K. DAS, PH.D.,x MOYED MIFTEN, PH.D.,y X. ALLEN LI, PH.D.,jj CHARLIE PAN, M.D.,# RANDALL K. TEN HAKEN, PH.D.,# AND TIMOTHY E. SCHULTHEISS, PH.D.** *Department of Radiation Oncology, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada; y Department of Radiation Oncology, University of Colorado, Denver, CO; z Department of Radiology, Division of Radiation Oncology, Baylor College of Medicine and Methodist Hospital, Houston, TX; x Department of Radiation Oncology, Duke University Medical Center, Durham, NC; jj Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI; # Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI; **Department of Radiation Oncology, City of Hope Medical Center and Beckman Research Institute, Duarte, CA The kidneys are the dose-limiting organs for radiotherapy to upper abdominal cancers and during total body ir- radiation. The incidence of radiotherapy-associated kidney injury is likely underreported owing to its long latency and because the toxicity is often attributed to more common causes of kidney injury. The pathophysiology of radiation injury is poorly understood. Its presentation can be acute and irreversible or subtle, with a gradual progressive dysfunction over years. A variety of dose and volume parameters have been associated with renal toxicity and are reviewed to provide treatment guidelines. The available predictive models are suboptimal and re- quire validation. Mitigation of radiation nephropathy with angiotensin-converting enzyme inhibitors and other compounds has been shown in animal models and, more recently, in patients. Ó 2010 Elsevier Inc. Kidney injury, Radiation toxicity, Radiotherapy. 1. CLINICAL SIGNIFICANCE The kidneys are the dose-limiting organs for radiotherapy (RT) to gastrointestinal cancers, gynecologic cancers, lym- phomas, and sarcomas of the upper abdomen and during total body irradiation (TBI). The kidneys are vitally important, re- sponsible for filtering waste metabolites and electrolytes from the blood, producing erythropoietin to stimulate red blood cell production, and modulating blood pressure by fluid/electrolyte balance. The incidence of RT-associated kidney injury is likely underreported owing to its long la- tency and because dysfunction is likely often attributed to more common causes. 2. ENDPOINTS The findings associated with RT-induced kidney injury can be segregated into subclinical and clinical (Table 1). Af- ter TBI, RT-induced kidney injury often includes features of hemolytic-uremic syndrome (e.g., microangiopathic hemo- lytic anemia, and thrombocytopenia) (1). Acute (within 3 months) RT-induced kidney injury is gen- erally subclinical. The signs and symptoms (e.g., decreased glomerular filtration rate [GFR], increased serum b2-micro- globulin) usually develop during the subacute period (3–18 months). Chronic injury (18 months) is characterized by be- nign or malignant hypertension, elevated creatinine levels, anemia, and renal failure (2, 3). If no changes in renal blood perfusion or GFR are observed within 2 years after RT, sub- sequent chronic injury is unlikely (4). RT-induced kidney in- jury can also reduce a patient’s reserve against future renal insults. The long latency for clinical kidney toxicity was high- lighted in a study of 67 patients with peptic ulcer disease, without pre-existing hypertension, who were treated with $20 Gy within 3 weeks (encompassing the left kidney) (5). Of the 67 patients, 31 (46%) developed kidney toxicity within 8–19 years after RT, including 7 patients with fatal uremia (n = 5) or malignant hypertension (n = 2). At autopsy, atrophy of the left kidney with degenerative changes of the small and me- dium arteries were observed. The long latency for RT-induced kidney injury and the high prevalence of confounding non– RT-related factors (see the section ‘‘Patient- and Treatment- Related Factors’’) that can injury the kidneys have hindered our ability to understand the effects of partial kidney RT. Reprint requests to: Laura A. Dawson, M.D., Department of Ra- diation Oncology, Princess Margaret Hospital, University of Tor- onto, 610 University Ave., Toronto, ON M5G 2M9, Canada. Tel: (416) 946-2124; Fax: (416) 946-6566; E-mail: laura.dawson@ rmp.uhn.on.ca Conflict of interest: none. Received Aug 20, 2008, and in revised form Feb 1, 2009. Accepted for publication Feb 3, 2009. S108 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S108–S115, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.02.089
- 109. 3. DEFINING THEKIDNEYS The kidneys are relatively easy to identify on the planning computed tomography (CT) scan, even without intravenous contrast. Typically, the doses delivered to each kidney alone and combined should be evaluated. Ideally, the kidney paren- chyma should be segmented, because this is the ‘‘functional’’ component. The magnitude of errors introduced by including the collecting system in the ‘‘kidney volume’’ is unclear. The existing published data were largely derived from pa- tients treated without computed tomography-based planning, and with delivery techniques associated with substantial do- simetric uncertainty (e.g., the moving strip technique). Even with modern planning, kidney breathing motion or shifts in kidney position are not usually accounted for, introducing uncertainty in the delivered vs. the planned kidney doses (6). The kidneys move inferiorly (by #7 cm) and change shape in the upright vs. supine position (7); thus, if kidney blocks were designed using supine CT scans for patients treated in the upright position (e.g., with TBI), the actual kid- ney doses would be far greater than planned. 4. REVIEW OF DOSE–VOLUME DATA The risk of RT-induced kidney injury largely depends on the use of whole-volume or partial-volume RT to one or both kidneys. In the present report, whole kidney tolerance refers to bilateral, uniform kidney RT, segregated by the use of TBI or not, and partial kidney tolerance includes any partial-volume RT experience, including uniform RT to one kidney. Whole kidney tolerance The dose–response data for whole kidney irradiation in pa- tients undergoing TBI is summarized in Table 2 and Fig. 1. Patients undergoing TBI typically have substantial co-mor- bidities and also receive potentially nephrotoxic chemother- apy. Cheng et al. (8) conducted a comprehensive review of 12 studies reporting kidney toxicity (increased creatinine or hemolytic uremic syndrome) after TBI (Table 2 and Fig. 1). On multivariate analysis, for those reports describing adult-only experience (n = 479 patients), the dose was the only significant factor associated with increased kidney tox- icity. Neither the dose rate nor the number of fractions were significant in their model. For the studies that included adult and pediatric populations (n = 437 patients), significant fac- tors included the dose, dose rate (#6 vs. 6.1–9.9 vs. $10 cGy/min) and the use of fludarabine. Considering all the stud- ies, except for those with pediatric populations only (n = 916 patients), the number of fractions became a significant factor, in addition to the total dose and dose rate. The dose associ- ated with a 5% risk of kidney toxicity, without nephrotoxic drugs, was 9.8 Gy, regardless of the fractionation scheme used (median dose, 12 Gy; range, 7.5–14; median fractions, 6; range 1–11, delivered once or twice daily). The whole kidney dose–response data, excluding TBI, is summarized in Table 3 and Figs. 2 and 3. The dose–response data are consistent with previous reviews (e.g., Emami et al. [9] in 1991 and Cassady [10] in 1995; Fig. 1) that suggested a total dose associated with a 5% and 50% risk of injury at 5 years of 18–23 Gy and 28 Gy, in 0.5–1.25 Gy/fraction, respectively. Increases in creatinine clearance have been observed after 10–20 Gy to both kidneys, at 0.8–1.25 Gy/ fraction (11). Partial kidney tolerance Nephrectomy is more often associated with subclinical elevations in creatinine and late chronic kidney injury than is ‘‘nephron-sparing’’ partial nephrectomy (12). Thus, the global function/reserve appears related to the nephron vol- ume, and tolerance to RT is likely reduced in patients with one (vs. two) kidneys. Table 4 summarizes the key studies describing partial kid- ney tolerance to RT. Unilateral kidney RT is not risk free, as Table 1. Radiation-associated kidney toxicity endpoints Category Physiologic Biochemical Imaging Subclinical Elevated blood pressure Increased weight Elevated serum b2-microglobulin Elevated urine beta2 microglobulin Elevated serum blood urea nitrogen Elevated serum creatinine Elevated serum renin Reduced glomerular filtration rate Decreased creatinine clearance* Proteinuria Urine casts Hematuria Anemia Reduced glomerular function, GFR 99m Tc-DTPA renography Reduced tubular function 99m Tc-DMSA scintigraphy Perfusion deficits on scintigraphy 131 Iodine radiohippurate Asymmetric uptake of intraenous contrast on computed tomography Kidney atrophy Clinical Malignant hypertension Headache, Edema, Dyspnea Fatigue, Nausea, Vomiting Confusion, Coma, Death Abbreviations: 99m Tc-DTPA = 99m Technetium-diethylene-triamine-penta-acetic acid; GFR = glomerular filtration rate; 99m Tc-DMSA = 99m Technetium-dimercaptosuccinyl acid. * Often used to estimate GFR. Radiation-induced kidney injury d L. A. DAWSON et al. S109
- 110. shown by Thompsonet al. (5), who observed a dose response for kidney atrophy and clinical kidney toxicity many years af- ter unilateral kidney RT (13). Willett et al. (14) found a vol- ume-dependent decrease in creatinine clearance after $26 Gy to $50% of one kidney. In gastric cancer patients treated primarily using anteroposterior beams with little dose to the right kidney, a progressive decrease in left (vs. right) renal function, as assessed by renography, was seen 12–18 months after chemoradiotherapy, with an associated increase in se- rum creatinine (15). The volume of the left kidney receiving 20 Gy and the mean left kidney dose were associated with increased risk of renal injury. Regional kidney injury has been detected using scintigraphy after low doses; 5% of the irradiated kidneys developed abnormalities after 3–6 Gy, in 15–30 fractions, independent of the irradiated volume. These findings improved with time, likely due to the reserve capac- ity of the spared kidney tissue (16). Pediatric kidney tolerance Neonates appear to have an increased sensitivity to RT. Doses of 12–14 Gy at 1.25–1.5 Gy/fraction to an entire ne- onate kidney have been associated with a decreased GFR (17) and subsequent abnormalities on bone scan and intra- venous pyelography. Age less than 5 years was associated with increased risk of acute renal dysfunction post TBI in one study (new reference ‘A’) For older children, no con- vincing evidence has shown that the kidney tolerance is dif- ferent from that of adults. A study of 108 children who underwent nephrectomy predominantly for Wilms tumor and RT to the contralateral remaining entire or partial kid- ney showed that abnormal creatinine clearance was dose dependent (18). Abnormal creatinine clearance, defined as 63 mL/min/m2 , was found in 29 (41%) of 70 children re- ceiving 12 Gy, 15 (56%) of 27 children receiving 12–24 Gy, and 10 (91%) of 11 children receiving 24 Gy to the remaining kidney (p .05). All 5 patients with clearance 24 mL/min/m2 had hypertension and elevated blood urea nitrogen, and 4 died of kidney failure. In a different Wilms tumor study, nephropathy was seen in 0 of 17 chil- dren receiving 11–14 Gy to the remaining kidney and 1 (25%) of 4 receiving 14–15 Gy (fraction size not re- ported) (10). In another study, 1 of 38 children with bilat- eral Wilms tumors developed kidney failure after 27 Gy in 21 fractions to the lower half and 12 Gy in 11 fractions to Table 2. Selected studies of bilateral whole kidney toxicity after TBI and transplantation Authors^ Patients (n) Population Total kidney dose (Gy) Fractions (n) Fractions/ d (n) Dose rate (cGy/min) Renal toxicity (%) Chemotherapy regimen* Frisk 2002 22 P 7.5 1 1 15 27.3 1 Lawton 1997 72 A 14 9 3 14 18.1 2 68 A 11.9 9 3 11.9 10.3 2 17 A 9.8 9 3 9.8 0 2 Rabinowe 1991 112 A 12 6 2 7.5 9.8 3 Miralbell 1996 24 P/A 10 6 2 16 4.2 4 32 P/A 12 6 2 16 28.1 4 23 P/A 13.5 6 2 16 34.8 4 Chou 1996 58 P 12 6 2 15 3.4 5 Borg 2002 47 P/A 12 6 2 7.5 2.1 6 Bradley 1998 31 A 12 6 2 12 12.9 7 36 P 13.2 11 3 12 0 7 10 P 13.5 9 2 12 30 7 Tarbell 1990 12 P 14 8 2 10 33.3 8 15 P 12 6 2 10 46.7 8, 9 Igaki 2005 70 P/A 12 6 2 10 20 10 39 A 10 6 2 8.5 0 10 Delgado 2006 65 P/A 7.5 1 1 13 9.2 11 46 P/A 7.5 1 1 13 2.2 12 84 P/A 12 6 2 6 1.2 12 26 P/A 14.4 8 2 6 3.8 11 20 P/A 14.4 8 2 6 0 13 Moreau 2005 140 A 8 4 1 NA 3.6 14 Van Why 1991 39 P 13.2 8 2 14 23.1 15 Abbreviations: P = pediatric; A = adult; P/A = mixed; NA = not available. Modified, with permission, from Cheng et al. (8). ^ All references in first column are included within the review by Cheng et al. (8). * Chemotherapy regimens: 1, teniposide, daunorubicin, vincristine, cyclophosphamide, and cytarabine; 2, cytarabine and cyclophospha- mide; 3, cyclophosphamide with or without cytarabine; 4, cyclophosphamide with or without thiotepa, daunorubicin, busulfan, or cytarabine; 5, cyclophosphamide, cytarabine, methotrexate, and etoposide; 6, cyclophosphamide with or without melphalan, busulphan, or etoposide; 7, cyclophosphamide or etoposide; 8, cyclophosphamide, teniposide, and cytarabine; 9, neuroblastoma—teniposide, cyclophosphamide, cis- platin, and melphalan with or without methotrexate; 10, cyclophosphamide and cytarabine or cyclophosphamide and busulfan; 11, cyclophos- phamide and fludarabine with or without alemtuzumab; 12, cyclophosphamide with or without alemtuzumab, or melphalan, or etoposide; 13, cyclophosphamide with or without alemtuzumab; 14, vincristine, adriamycin, and melphalan; 15, Cyclosporin A and/or amphoterecin B. S110 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 111. the upper halfof the remaining kidney (19). No kidney fail- ure occurred in children receiving bilateral kidney doses of 10–12 Gy, in 1.5–2 Gy/fraction. In the National Wilms Tu- mor Study experience, kidney failure was more common in children with bilateral than unilateral Wilms tumor (20). For the 3 patients with unilateral tumors who developed kidney failure, the dose to the remaining kidney was 15, 18, and 20 Gy in 1.5–2 Gy/fraction. In the review by Cheng et al. (8) of kidney toxicity after TBI, for pediatric patients (n = 192), the use of cyclosporine and teniposide was associated with an increased risk of kid- ney toxicity. When these drugs were excluded, no dose re- sponse was found, and, at doses #13 Gy, the incidence of kidney toxicity was 8% (8). Data on the pediatric kidney partial volume tolerance are not available. RT-induced reduction in compensatory response After injury to one kidney, a compensatory increase in kid- ney function of the spared kidney often occurs. Low-dose RT to the ‘‘spared’’ kidney can blunt this compensation. At 6–9 years after 40 Gy in 1.5-Gy fractions to the left kidney and 12–13 Gy in 1-Gy fractions to the right kidney, the left kidney glomerular and tubular function, as assessed by scintigraphy, had decreased to 21% and 31% of baseline, respectively, with an associated decline in creatinine clearance. The compensa- tory response was reduced compared with that in patients with complete sparing of $70% of one kidney (21). 5. PATIENT- AND TREATMENT-RELATED FACTORS Chemotherapy can enhance RT-associated kidney injury in adults and pediatric populations treated with and without TBI (8, 22) (Fig. 1). The review by Cheng et al. (8) found that after TBI, the use of fludarabine, cyclosporine, or tenipo- side increased the risk of renal injury (odds ratio, 6.2, 5.9, and 10.5, respectively). A TBI dose rate of #6 cGy/min and 6.1– 9.9 cGy/min was associated with an odds ratio of 0.0046 and 0 0.1 0.2 0.3 0.4 0.5 10864 12 14 16 Equivalent Total Dose (Gy) IncidenceofLateRenalToxicity (%x100) Adults + Mixed Adults + Mixed: no NT drugs Bilateral Whole Kidney RT - TBI Fig. 1. Dose–response curve for increased creatinine or hemolytic uremic syndrome after total body irradiation (TBI). Open diamonds represent fitted data for studies that included adults alone or adult/pe- diatric mixed populations (with or without nephrotoxic drugs). Solid squares represent fitted data for same population excluding those treated without nephrotoxic (NT) drugs, cyclosporine, teniposide, or fludarabine. Fractionation schemes (listed in Table 3) were con- verted to ‘‘equivalent’’ doses delivered in six fractions at 10-cGy/ min dose rate. Modified, with permission, from Cheng et al. (8). Table 3. Selected studies of bilateral whole kidney irradiation (non-TBI) Investigator Patients (n) Disease Chemotherapy Dose (Gy) Dose/fraction (Gy) Incidence of injury Endpoint Kunkler 1952 (23) 55 Seminoma None 23 or 28 0.9–1.12 22/55 (40%) 7/55 RF (sBP 160 mm Hg + albuminuria) Death 23 0.92 2/18 (11%)* RF (sBP 160 mm Hg + albuminuria) 28 1.12 18/25 (51%)*RF (sBP 160 mm Hg + albuminuria) Avioli 1963 (24) 10 None Gynecologic cancer (n = 8), Sarcoma (n = 1), Seminoma (n = 1) 7.5–16.5; 20–24 0.5–1.1; 1.0–1.2 0/5; 4/5 No change in GFR; no HTN or RF; Reduced GFR (75- 83%), no HTN or RF Keane 1976 (25) 2 Ovarian cancer None 25, 27 2/2 Reduced CrCl (30 mL/ min), ESRD Churchill 1978 (26) 1 Seminoma Bleomycine and vinblastin 26–38y 1.6 1/1 ARF at 5 wk Irwin 1996 (27) 60 Ovarian cancer, NHL, carcinoid None 7–23 1–1.25 5/60 New HTN, No change in CrCl Schneider 1999 (11) 56 Ovarian cancer Cisplatin (n = 25) 5–17 0.65–1.15 71–76% Reduced CrCl by 2 mL/min, Reduced CrCl (84– 66 mL/min) Abbreviations: RF = renal failure; sBP = systolic blood pressure; GFR = glomerular filtration rate; HTN = hypertension; CrCl = creatinine clearance; ESRD = end-stage renal disease; ARF = acute (1 y) RF; NHL = non-Hodgkin’s lymphoma. * Denominator estimated from text. y Two-thirds of kidneys received 38 Gy. Radiation-induced kidney injury d L. A. DAWSON et al. S111
- 112. 0.083, respectively, comparedwith $10 cGy/min (8). Under- lying renal insufficiency, diabetes, hypertension, liver dis- ease, heart disease, and smoking can also reduce the kidney’s tolerance to RT; however, the magnitude of these effects is unclear. Animal models have suggested that angio- tensin-converting enzyme inhibitors, dexamethasone, and acetylsalicylic acid can prevent and treat RT-induced kidney injury (28–30). Angiotensin-converting enzyme inhibitors improve non–RT-associated kidney failure (31) and, re- cently, were suggested in a randomized trial to reduce the incidence of nephropathy or hemolytic uremic syndrome (3.7% vs. 15%, p = .1) after TBI (32). 6. PREDICTIVE MODELS The Lyman-Burman-Kutcher normal tissue complication probability model parameters (median toxic dose, 28 Gy, n = 0.70, m = 0.10) (33) have been used to describe the tol- erance estimates reported by Emami et al. (9). Cassady (10) pooled the data on bilateral whole kidney RT tolerance and confirmed a threshold dose for RT injury of 15 Gy with a 5% and 50% risk of injury at 5 years for whole-kidney RT of 18 Gy and 28 Gy, respectively, within 5 weeks (Fig. 2). It has been demonstrated that greater doses can be safely deliv- ered to partial kidney volumes (9, 34). Quantitative data to support more refined models are not available. Cheng et al. (8) found a less steep dose response (m = 0.26) after TBI (median dose, 12 Gy in six fractions twice daily). The dose associated with a 5% risk of kidney toxicity was 9.8 Gy. The addition of nephrotoxic drugs made the dose–re- sponse curve steeper (Fig. 1). 7. SPECIAL SITUATIONS The response of the kidney is highly dependent on the frac- tion size; therefore, extrapolation of previous experience to different fraction sizes can be problematic (35–38). One hy- pothesis is that nearly complete sparing of a substantial vol- ume of the kidney should be associated with compensatory effects and preservation of renal function, despite the deliv- ery of focal high doses. Symptomatic kidney injury has not been reported after potent doses of stereotactic body radio- therapy; however, elevations in creatinine have been ob- served 52 months after renal stereotactic body radiotherapy (SBRT) (39). Follow-up of long-term survivors from these series is required to determine the kidney’s and collecting system’s tolerance to SBRT. Few of the published reports on kidney tolerance have focused on intensity-modulated RT (IMRT), and the effects of different spatial dose distributions are not well estab- lished. IMRT often leads to a low dose delivered to a larger volume compared with simpler plans, which might reduce the possibility of a compensatory increase in kidney func- tion. 8. DOSE–VOLUME RECOMMENDATIONS All dose–volume recommendations are associated with substantial uncertainty, because few studies are available of patients who have been followed for $10 years. However, some broad guidelines can be useful and will hopefully be tested in future studies (Table 5 and Fig. 3). 9. AREAS FOR FUTURE STUDY The kidney partial tolerance to RT is largely unknown and deserves more study. Collaborative prospective studies are needed, with collection of dose–volume histogram and spa- tial dose data, along with serial long-term objective outcome assessments. The baseline clinical kidney function and co- morbidities need to be documented, along with the use of Fig. 2. Dose–response curve for symptomatic kidney injury after non–total body irradiation of bilateral kidneys. Note, y axis is different from than that in Fig. 1. Data from review from Cassady et al. (10). Fig. 3. Composite schematic of combined kidney dose–volume histogram of data from Tables 4 and 5, represented as regions associated with minimal (5%), low ($5%), moderate-to-high ($5–30%), high ($30%), or undocumented estimated toxicity risks. Clinical experience that yielded risk estimates for each region also indicated. Actual risks associated with using each region on its own or regions in combination are plan-specific and associated with substantial uncertainty. S112 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 113. nephrotoxic or antihypertensivemedications. Differences in the dose per fraction should also be accounted for. Proposed research topics of importance include the following: –Pathophysiology of RT-induced kidney injury –Interaction between clinical factors and kidney tolerance to RT Table 4. Selected studies addressing partial kidney irradiation Investigator Patients (n) Disease Chemotherapy Dose/fraction (Gy) Dose/volume Incidence Endpoint Kunkler 1952 (23) 60 Seminoma None 0.9–1.12 D33% 18 Gy (18–29 Gy to kidneys) 0/60 No RF (sBP 160 mm Hg + albuminuria Thompson 1971 (5) 67 Peptic ulcer None 1.0–1.3 D50% = 15–35 Gy 31/67 RF or HTN (8–19 y) D50% = 15 Gy 0/2 Kidney atrophy (I/S) D50% = 20 Gy 6/6 Kidney atrophy (I/S) D50% = 30–35 Gy 2/2 Marked kidney atrophy (I/S) 2/2 Malignant HTN Le Bourgeois 1978 (40) 74 Hodgkin’s disease None 1 D15–40% = 20 Gy 74/74 70% Focal decrease in glomerular fn 3/74 Proteinuria, no change in CrCl Birkhead 1979 (41) 23 Hodgkin’s disease 1 Patient 2 D16% = 40 Gy 6/16 Focal scintigraphy changes; no RF Kim 1980 (42) 18 NHL None 1 D25–50% = 25–44 Gy 3/18 Decreased CrCl 5/18 HTN Kim 1984 (43) 18 NHL None 1 D25–50% = 21– 33 Gy 2/9 Reduced blood flow or perfusion D25–50% = 30–40 Gy 4/7 Reduced blood flow or perfusion D25–50% 40 Gy 3/3 Atrophy Willett 1986 (14) 86 Mixed Not stated 1.5–1.8 V26Gy = 50% 10% Decrease in CrCl V26Gy 90% 24% Decrease in CrCl All patients 2/73 4/13 New HTN Increase in HTN medications Flentje 1993 (44) 142 Seminoma None 0.7–1 D50% 18 Gy 0/100 RF or HTN D50% 18–32 Gy 7/42 Dewitt 1993 (22) 7 Seminoma None 2 V25–35Gy = 20–30% 0/7 CrCl or SC Dewitt 1993 (22) 7 NHL None V40Gy = 50% V12–13Gy = 100% 25% Decrease in glomerular fn Sc 31% Decrease in tubular fn Sc Kost 2002 (16) 91 Seminoma (n = 45), NHL (n = 42), RCC (n = 6), Sarcoma (n = 1) 1.8–2.0 V3–6Gy 10% V27Gy = 10% V7.6Gy = 100% 5% 50% 50% Decrease in fn Sc Decrease in fn Sc Decrease in renal flow; no RF Nevinny-Stickel 2007 (34) 19 Cervical cancer 0.4–1.8 V28Gy 25% V23Gy 33% 3/19 Decrease in renal flow; no RF Jansen 2007 (15) 44 Gastric cancer Capecitabine or cisplatin (n = 21) 0.4–1.8 V20Gy (1 kidney) 64% vs. 64% 1/15* 66% vs. 34% decrease in fn (I/S) HTN Welz 2007 (13) 27 Gastric cancer 5-FU, cisplatin, paclitaxel 0.4–1.8 V12Gy 62.5% functional kidneys Trend toward increase Cr; no HTN Abbreviations: Dy% = dose to y% of volume; I/S = irradiated vs. spared; fn = function; RCC = renal cell cancer; 5-FU = 5-fluoruracil; Sc = scintigraphy; Vx Gy = volume receiving x Gy; NHL = non-Hodgkin’s lymphoma; other abbreviations as in Table 1. * Among patients with follow-up $18 months. Radiation-induced kidney injury d L. A. DAWSON et al. S113
- 114. –Mitigating factors andradioprotectors –Renal compensatory effects and how low-dose RT alters the compensatory capacity –Spatial variation in radiation sensitivity (e.g. with func- tional imaging) –Surrogates for risk of clinical toxicity (e.g., cytokines, proteonomics) 10. SCORING TOXICITY Studies of RT-induced kidney injury have been con- founded by the use of variable, most often asymptomatic, endpoints, largely because the symptoms usually occur many years after RT. Because early changes in renal flow and GFR correlate with an increased risk of subsequent symptomatic toxicity, these endpoints should be considered in future studies. The severity of injury should be graded according to the GFR, as has been recommended for all chronic kidney disease (Table 6) (45). Serial urine protein, serum blood urea nitrogen, creatinine clearance, blood pres- sure measurements, and symptoms of renal failure can also been used to grade the severity of RT-induced injury (46). REFERENCES 1. Cruz DN, Perazella MA, Mahnensmith RL. Bone marrow trans- plant nephropathy: A case report and review of the literature. J Am Soc Nephrol 1997;8:166–173. 2. Rubin P, Casarett G. Clinical Radiation Pathology, Vols. 1 and 2. Philadelphia: WB Saunders; 1968. 3. Verheij M, Dewit LG, Valdes Olmos RA, et al. Evidence for a renovascular component in hypertensive patients with late ra- diation nephropathy. Int J Radiat Oncol Biol Phys 1994;30: 677–683. 4. Cohen EP, Robbins ME. Radiation nephropathy. Semin Neph- rol 2003;23:486–499. 5. Thompson PL, Mackay IR, Robson GS, et al. Late radiation ne- phritis after gastric x-irradiation for peptic ulcer. Q J Med 1971; 40:145–157. 6. Ahmad NR, Huq MS, Corn BW. Respiration-induced motion of the kidneys in whole abdominal radiotherapy: Implications for treatment planning and late toxicity. Radiother Oncol 1997; 42:87–90. 7. Reiff JE, Werner-Wasik M, Valicenti RK, et al. Changes in the size and location of kidneys from the supine to standing positions and the implications for block placement during total body irradiation. Int J Radiat Oncol Biol Phys 1999;45: 447–449. 8. Cheng J, Schultheiss T, Wong J. Impact of drug therapy, radi- ation dose and dose rate on renal toxicity following bone mar- row transplantation. Int J Radiat Oncol Biol Phys 2008;71: 436–443. 9. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 10. Cassady JR. Clinical radiation nephropathy. Int J Radiat Oncol Biol Phys 1995;31:1249–1256. 11. Schneider DP, Marti HP, Von Briel C, et al. Long-term evolu- tion of renal function in patients with ovarian cancer after whole abdominal irradiation with or without preceding cisplatin. Ann Oncol 1999;10:677–683. 12. McKiernan J, Simmons R, Katz J, et al. Natural history of chronic renal insufficiency after partial and radical nephrec- tomy. Urology 2002;59:816–820. 13. Welz S, Hehr T, Kollmannsberger C, et al. Renal toxicity of ad- juvant chemoradiotherapy with cisplatin in gastric cancer. Int J Radiat Oncol Biol Phys 2007;69:1429–1435. 14. Willett CG, Tepper JE, Orlow EL, et al. Renal complications secondary to radiation treatment of upper abdominal malignan- cies. Int J Radiat Oncol Biol Phys 1986;12:1601–1604. 15. Jansen EP, Saunders MP, Boot H, et al. Prospective study on late renal toxicity following postoperative chemoradiotherapy in gastric cancer. Int J Radiat Oncol Biol Phys 2007;67:781–785. 16. Kost S, Dorr W, Keinert K, et al. Effect of dose and dose-distri- bution in damage to the kidney following abdominal radiother- apy. Int J Radiat Biol 2002;78:695–702. 17. Peschel RE, Chen M, Seashore J. The treatment of massive he- patomegaly in stage IV-S neuroblastoma. Int J Radiat Oncol Biol Phys 1981;7:549–553. Table 5. Suggested dose–volume constraints for estimated risk of 5% Variable Dose–volume metric Investigator Bilateral kidney irradiation TBI Mean kidney dose 10 Gy Cheng et al. (8) Non-TBI Mean kidney dose 18 Gy Cassady (10) Partial kidney irradiation Bilateral kidneys Mean kidney dose 18 Gy Nevinny-Stickel et al. (34) Bilateral kidneys V28Gy 20% Nevinny-Stickel et al. (34) Bilateral kidneys V23Gy 30% Nevinny-Stickel et al. (34) Bilateral kidneys V20Gy 32% Jansen et al. (15) Bilateral kidneys V12Gy 55% Welz et al. (13)* If mean kidney dose to 1 kidney 18 Gy V6Gy (remaining kidney) 30% Abbreviations: Vx Gy = volume of bilateral kidneys receiving x Gy; TBI = total body irradiation. * Estimated from Welz et al. (13); 62.5% reduced to 55% because 62.5% was functional volume. Table 6. K/DOQI stages of chronic kidney disease (kidney disease occurring for 3 mo) Stage Description GFR (mL/min/1.73 m2 ) 1 Kidney damage with normal or GFR $90 2 Kidney damage with mildly decreased GFR 60–89 3 Moderately decreased GFR 30–59 4 Severely decreased GFR 15–29 5 Kidney failure 15 (or dialysis) Abbreviations: K/DOQI = Kidney/Dialysis Outcomes Quality Initiative; GFR = glomerular filtration rate. Kidney damage defined as pathologic abnormalities or markers of damage, including abnormalities in blood or urine tests or imaging studies. Data from National Kidney Foundation (available from: www. kidney.org). S114 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 115. 18. Esiashvili N,Chiang KY, Hasselle MD, Bryant C, Riffenburgh RH, Paulino AC. Renal toxicity in children undergoing total body irradiation for bone marrow transplant. Radiother Oncol. 2009 Feb;90(2): 242-6. 19. Mitus A, Tefft M, Fellers FX. Long-term follow-up of renal functions of 108 children who underwent nephrectomy for ma- lignant disease. Pediatrics 1969;44:912–921. 20. Paulino AC, Wilimas J, Marina N, et al. Local control in syn- chronous bilateral Wilms tumor. Int J Radiat Oncol Biol Phys 1996;36:541–548. 21. Ritchey ML, Green DM, Thomas PR, et al. Renal failure in Wilms tumor patients: A report from the National Wilms Tumor Study Group. Med Pediatr Oncol 1996;26:75–80. 22. Dewit L, Verheij M, Valdes Olmos RA, et al. Compensatory renal response after unilateral partial and whole volume high- dose irradiation of the human kidney. Eur J Cancer 1993; 29A:2239–2243. 23. Kunkler PB, Farr RW, Luxton RW. The Limit of Renal Toler- ance to X Rays. Br J Radiol 1952;XXV:190- 201. 24. Avioli LV, Lazor MZ, Cotlove E, et al. Early effects of radiation on renal function in man. American Journal of Medicine 1963; 34:329–337. 25. Keane WF, Crosson JT, Staley NA, et al. Radiation-induced renal disease. A clinicopathologic study. Am J Med 1976;60:127–137. 26. Churchill DN, Hong K, Gault MH. Radiation nephritis follow- ing combined abdominal radiation and chemotherapy (bleomy- cin vinblastine). Cancer 1978;47:2162–2164. 27. Irwin C, Fyles A, Wong CS, et al. Late renal function following whole abdominal irradiation. Radiotherapy Oncology 1996; 38:257–261. 28. Donaldson SS, Moskowitz PS, Canty EL, et al. Combination ra- diation-adriamycin therapy: Renoprival growth, functional and structural effects in the immature mouse. Int J Radiat Oncol Biol Phys 1980;6:851–859. 29. Moulder JE, Fish BL, Cohen EP. Treatment of radiation ne- phropathy with ACE inhibitors and AII type-1 and type-2 recep- tor antagonists. Curr Pharm Des 2007;13:1317–1325. 30. Cohen EP, Fish BL, Sharma M, et al. Role of the angiotensin II type-2 receptor in radiation nephropathy. Transl Res 2007;150: 106–115. 31. Verheij M, Stewart FA, Oussoren Y, et al. Amelioration of ra- diation nephropathy by acetylsalicylic acid. Int J Radiat Biol 1995;67:587–596. 32. Cohen EP, Hussain S, Moulder JE. Successful treatment of ra- diation nephropathy with angiotensin II blockade. Int J Radiat Oncol Biol Phys 2003;55:190–193. 33. Cohen EP, Irving AA, Drobyski WR, et al. Captopril to mitigate chronic renal failure after hematopoietic stem cell transplanta- tion: A randomized controlled trial. Int J Radiat Oncol Biol Phys 2008;70:1546–1551. 34. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 35. Nevinny-Stickel M, Poljanc K, Forthuber BC, et al. Opti- mized conformal paraaortic lymph node irradiation is not as- sociated with enhanced renal toxicity. Strahl Onkol 2007; 183:385–391. 36. Svedman C, Sandstrom P, Pisa P, et al. A prospective phase II trial of using extracranial stereotactic radiotherapy in primary and metastatic renal cell carcinoma. Acta Oncol 2006;45:870– 875. 37. Wersall PJ, Blomgren H, Lax I, et al. Extracranial stereotactic radiotherapy for primary and metastatic renal cell carcinoma. Radiother Oncol 2005;77:88–95. 38. Beitler JJ, Makara D, Silverman P, et al. Definitive, high-dose- per-fraction, conformal, stereotactic external radiation for renal cell carcinoma. Am J Clin Oncol 2004;27:646–648. 39. Teh B, Bloch C, Galli-Guevara M, et al. The treatment of pri- mary and metastatic renal cell carcinoma (RCC) with image guided stereotactic body radiation therapy (SBRT). Biomed Im- aging Intev J 2007;3:1–9. 40. LeBourgeois J, Meignan M, Parmentier C, et al. Renal conse- quences of irradiation of the spleen in lymphoma patients. Abritish Journal of Radiology 1979;52:56–60. 41. Birkhead BM, Dobbs CE, Beard MF, et al. Assessment of renal function following irradiation of the intact spleen for Hodgkin disease. Radiology 1979;130:473–475. 42. Kim TH, Freeman CR, Webster JH. The significance of unilat- eral radiation nephropathy. Int J Radiat Oncol Biol Phys 1980; 6:1567–1571. 43. Kim TH, Somerville PJ, Freeman CR. Unilateral radiation ne- phropathy–the long-term significance. Int J Radiat Oncol Biol Phys 1984;10:2053–2059. 44. Flentje M, Hensley F, Gademann G, et al. Renal tolerance to nonhomogenous irradiation: comparison of observed effects to predictions of normal tissue complication probability from different biophysical models. Int J Radiat Oncol Biol Phys 1993;27:25–30. 45. Svedman C. Karlsson K. Rutkowska E. Sandstrom P. Blomgren H. Lax I. Wersall P. Stereotactic body radiotherapy of primary and metastatic renal lesions for patients with only one function- ing kidney. Acta Oncologica. 2008;47(8):1578-83. 46. Levey AS, Eckardt KU, Tsukamoto Y, et al. Definition and classification of chronic kidney disease: A position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 2005;67:2089–2100. Radiation-induced kidney injury d L. A. DAWSON et al. S115
- 116. QUANTEC: ORGAN-SPECIFIC PAPERPelvis: Bladder RADIATION DOSE–VOLUME EFFECTS OF THE URINARY BLADDER AKILA N. VISWANATHAN, M.D., M.P.H.,* ELLEN D. YORKE, PH.D.,y LAWRENCE B. MARKS, M.D.,z PATRICIA J. EIFEL, M.D.,x AND WILLIAM U. SHIPLEY, M.D.{ *Department of Radiation Oncology, Brigham and Women’s Hospital/Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA; y Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY; z Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC; x Department of Radiation Oncology, M. D. Anderson Cancer Center, Houston, TX; { Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA An in-depth overview of the normal-tissue radiation tolerance of the urinary bladder is presented. The most in- formative studies consider whole-organ irradiation. The data on partial-organ/nonuniform irradiation are suspect because the bladder motion is not accounted for, and many studies lack long enough follow-up data. Future studies are needed. Ó 2010 Elsevier Inc. Bladder dose, toxicity. 1. CLINICAL SIGNIFICANCE Radiotherapy (RT) with or without chemotherapy for pelvic malignancies may result in genitourinary (GU) complica- tions. Overall, severe late effects occur in #10% of patients with prostate, bladder, or cervical cancer (1). However, given a possible latency period of several decades between treat- ment and the clinical manifestation of sequelae (2, 3), reports may have underestimated the late GU toxicity rates. The re- ported rates of acute side effects might be more accurate. 2. ENDPOINTS Many endpoints may be used to score bladder injury. In the present report, we focus on clinical symptoms. The symp- toms attributed to RT-related injury can also occur as a conse- quence of other medical co-morbidities, such as infection or aging, particularly for incontinence. The toxicity profile will depend on the treatment regimen of RT with or without sur- gery or chemotherapy, and the origin, extent, and location of cancer. When discussing bladder toxicities in relation to dose and/or volume, a significant heterogeneity of dose can exist, depending on whether the patient has undergone brachyther- apy, teletherapy, or both, and on bladder motion. Acute side effects that occur during RT usually resolve within a few months. Long-term symptoms attributable to global injury include dysuria, frequency, urgency, contracture, spasm, reduced flow, and incontinence. In contrast, symptoms thought to arise fromfocal injury include hematuria,fistula, ob- struction, ulceration, and necrosis. The grading of toxicities ac- cording to treatment given is subjective. One physician might prescribe an intervention sooner than another, leading to a rela- tive ‘‘upgrading.’’ Furthermore, symptoms attributable to the bladder might be urethral in origin. Several scoring systems have been proposed to standardize the reporting of bladder tox- icity, each with a slightly different approach. Some systems have separately considered objective vs. subjective endpoints (e.g., Late Effects of Normal Tissues-Subjective, Objective, Management and Analytic system [LENT-SOMA]), and others have not differentiated between acute and late effects (e.g., Common Terminology Criteria for Adverse Events [CTCAE]) or have ambiguities (e.g., ‘‘spontaneous, pads indi- cated’’ is considered Grade 2 incontinence using the CTCAE). Interstudy comparisons are challenging, because the scoring system used was not always clearly stated. Furthermore, crude, rather than actuarial, rates have often been reported. In general, patient-reported data have been shown to be superior to physi- cian-reporteddata,althoughthecollectionismorecomplex(4). 3. CHALLENGES DEFINING VOLUMES The bladder is a highly distensible organ. Its volume continuously changes with filling, and the post-void residual volume can vary. Furthermore, the bladder can move with positioning, respiration, or bowel filling. Therefore, we Reprint requests to: Akila N. Viswanathan, M.D., M.P.H., De- partment of Radiation Oncology, Brigham and Women’s Hospi- tal/Dana-Farber Cancer Institute, Harvard Medical School, 75 Francis St., L2, Boston, MA 02115. Tel: (617) 732-6331; Fax: (617) 278-6988; E-mail: aviswanathan@lroc.harvard.edu Conflict of interest: none. Acknowledgments—Thank you to Barbara Silver and Christian Kir- isits, ScD for reading the manuscript. Received Aug 28, 2008, and in revised form Feb 6, 2009. Accepted for publication Feb 28, 2009. S116 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S116–S122, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.02.090
- 117. have referred toa dose–volume histogram (DVH) of the blad- der obtained from a single planning computed tomography (CT) image as a ‘‘SimDVH’’ to emphasize that this image is unlikely to represent the true dose distribution delivered to the bladder during the treatment course. The bladder tri- gone, which, functionally, can be more important than the bladder dome, can be difficult to identify on CT. Some reports have defined the bladder to include the entire organ (with urine), and others have used the wall alone (excluding the urine). SimDVH-based and SimDose–surface-histogram- derived metrics have a high degree of correlation (5), and future comparisons of these with regard to late toxicity will provide useful information. Theoretically, if the patient is treated with a constant blad- der volume, the initial CT scan (and associated SimDVH) would indicate the region receiving dose. However, many pa- tients cannot maintain a consistent bladder volume during the treatment course, and have variable emptying and constant filling. Several studies have noted the nonstatic nature of the bladder and reported wall and/or tumor movement of ap- proximately 1–4 cm and volume variations of #44%, using repeated CT scans during therapy (6–8). Determining a true bladder DVH has not been feasible. 4. REVIEW OF DOSE–VOLUME DATA To date, no studies have comprehensively reported the true three-dimensional (3D) bladder dosimetry in relation to toxicities. A single 3D image set (SimDVH) is of question- able validity. Data for whole-bladder RT vs. partial-bladder doses are discussed by cancer type. Bladder cancer Table 1 lists selected series of patients treated with exter- nal-beam RT (EBRT) for bladder cancer, often in conjunc- tion with transurethral resection of the bladder tumor (TURBT) and/or chemotherapy (9–19). Studies published before 1995 have been previously reviewed (1). Figure 1 summarizes selected studies from that 1995 publication, as well as more recent studies in which the whole bladder was treated with photons no more than once daily and the corre- sponding Grade 3 or greater late toxicity rates were reported (9, 11–15, 20–26). Several different fractionation schedules were used; therefore, we plotted the toxicity rate against the normalized total dose in 2-Gy fractions calculated using the linear-quadratic model with an a/b of 6 Gy for consistency with the 1995 study by Marks et al. (1), although others have reported using an a/b of 3 Gy. Two studies included in Fig. 1 reported late toxicity rates of $25% with hypofractionated treatment schedules (20, 21), as did one study of partial-bladder RT that used 2 Gy/fraction to a total of 62 Gy (15). Because these studies used RT portals that en- compassed the entire bladder with a margin large enough to account for motion, we anticipated that the whole bladder re- ceived the prescription dose. Nonetheless, a large variation was found in the reported severe late bladder toxicity rates, indicating that an increasing dose does not account for all toxicity. Variations in reporting, treatment received (with or without surgery and chemotherapy), radiation dose range within a single study, and the modest number of patients in some studies have confounded the interpretation. For partial-bladder RT, care must be taken to ensure that the target volume is adequately covered. Several fraction- ation patterns have been reported; one common regimen has been whole-bladder RT to 52.5–55 Gy in 1.5–1.8-Gy fractions, followed by a partial-bladder boost of 12–15 Gy using 1.5–1.8 Gy/fraction, resulting in a cumulative tumor dose of 64–65 Gy (27). The serious late complication rates were 25% for most of the two-phase studies listed in Table 1 (15–19), suggesting advantages for a boost strategy. The most recent update of the Radiation Therapy Oncology Group bladder cancer trials of TURBT, chemotherapy, and RT reported a late Grade 3 or greater GU toxicity rate of 6% (19). Although studies have suggested that larger fraction size might increase the incidence of late complications (12, 28), similar to accelerated fractionation (10), the currently available data are inadequate to determine late bladder toler- ance quantitatively for the range of doses encountered with EBRT for bladder cancer. Prostate cancer The bladder neck and prostatic urethra are adjacent to, or within, the treated volume for prostate cancer. The distinction between bladder and urethral symptoms cannot be reliably made by the physician. The low rate of GU toxicity in post- prostatectomy series (29, 30) suggests that the prostate and prostatic urethra, rather than the bladder, might cause most GU symptoms. In the era before 3D imaging, a whole-pelvic approach, followed by a boost to the prostate with a margin, resulted in the inferior part of the bladder receiving the full dose. During the past decade, dose escalation and the use of conformal techniques, including intensity-modulated RT (IMRT), have delivered high doses ($70 Gy) to the prostate and, hence, to the inferior portion of the bladder. With these techniques, the superior part of the bladder is either outside the field for the entire treatment or receives approximately the full dose from the first treatment phase but is outside the cone-down field. This is in contrast to the trigone region, which lies immediately adjacent to the prostate and might receive the full prescription dose. The question of dose response for late GU toxicity in pros- tate-cancer treatment has not been resolved. The vast majority of studies found no dose–volume relationship with regard to GU toxicity. A few studies have indicated an association between the prostate dose and either acute or chronic GU toxicity might exist. Dose-volume relationship studies have been limited given the aforementioned constraints on locali- zation of the bladder during treatment, as well as the duration of follow-up necessary to determine chronic toxicity. In a randomized multi-institutional trial of 669 prostate-cancer patients treated with 3D conformal RT, no significant differ- ence in late GU toxicity was noted between the 68-Gy and 78- Gy treatment arms (31). With a median of 7 years of follow- up, the cumulative Grade 2 or greater toxicity rates were 40% Radiation-associated bladder injury d A. N. VISWANATHAN et al. S117
- 118. in the high-dosearm and 41% in the low-dose arm, and the cumulative Grade 3 or greater toxicity rates were 13% and 12%, respectively. However, an overall dose response for Grade 2 or greater GU toxicity was noted in the most recent report of a single-institution study of 1,571 patients by Zelef- sky et al. (32). They reported a cumulative 20% incidence at 10 years after 81 Gy IMRT to the prostate compared with 12% for non-IMRT patients treated to lower doses (32). How- ever, in the entire cohort, only 3% developed Grade 3 GU tox- icity, and no Grade 4 GU toxicity was noted. The median interval to the development of symptoms was 30 months, and 1% developed late GU toxicity after 10 years. The in- vestigators did not attempt to report the DVH values (32). Gynecologic cancer Historical data have indicated that locally advanced cervical cancer treated with high doses (60 Gy) of EBRT alone results in a high incidence of late GU toxicities and a poor outcome (33). Therefore, a combination of EBRT and brachytherapy is used. The dose to the entire bladder with EBRT typically ranges from 40 to 50 Gy, and the total dose with brachytherapy to the region closest to the implant approximates 70–90 Gy and can reach 100 Gy. However, these regions likely vary be- tween fractions, resulting in an unknown true maximum dose for most patients. The International Commission on Radiation Units Report 38 system assigns a bladder dose point; however, thispoint isnot representativeoftheCT-based(34–38) orultra- sound-based (39) volumetric dose maximum and surface area of normal tissue irradiated. Contouring the bladder with a Foley catheter in place during each fraction of brachytherapy more accurately deter- mines the doses received by the bladder. With a median follow-up of 39 months, the mean D2cc of the bladder for 141 patients with locally advanced cervical cancer treated with tandem and ring brachytherapy was 95.3 Æ 21 Gy (a/b = 3); 3 patients experienced Grade 3 or 4 late bladder toxicity, resulting in a 3-year actuarial rate of 4%. Of those treated with a bladder dose to D2cc of #95 Gy, 13% (11 of 87) developed Grade 1–4 late toxicity compared with 17% (9 of 54) if that dose was 95 Gy. These differences were not significant, indicating that the focal dose threshold is not clear from the available data (40–42). No Grade 3 or 4 GU toxicities were reported for 10 patients treated with magnetic resonance imaging-guided interstitial gynecologic brachytherapy with a median D2cc to the bladder of 69 Gy after a 2-year median follow-up (43, 44). Longer follow-up of these studies is needed. 5. FACTORS AFFECTING RISK Co-morbidities Among patients undergoing RT for prostate cancer, an in- creased risk of late GU toxicity has been seen for patients with pre-RT GU morbidity (45–48) and/or acute GU toxicity. After EBRT, an increased rate of Grade 2 or greater GU tox- icity has been seen with increasing age and the use of hor- mones. In cervical cancer, the 10-year bladder complication rate in a series from the M.D. Anderson Cancer Center was 3%. On multivariate analysis, a central pelvic dose of Table 1. Risk of late Grade 3 or greater bladder toxicity in patients treated for bladder cancer in selected series not included in Marks et al. (1) Investigator Patients (n) Simulation imaging Total dose (Gy) Whole-bladder dose (Gy) Partial-bladder dose (Gy) Fraction size (Gy) Fractions (n) EQD2 (Gy) Late Grade $3 toxicity (%) Duncan et al. (9)* 889 2D 55–57.5 55–57.5 2.75–2.88 20 60.2–63.8 17 Moonen et al. (10)* 15 3D 66 66 2 Last 8 b.i.d. 66 0 25 66 66 2 Last 13 b.i.d. 31 Ro¨del et al. (11)* 186* 2D 45–69.4 45–69.4 1.8–2 25–33 45–69.4 4y Scholten et al. (12)* 123 2D 36 36 6 6 (2x/wk) 54 0 Mameghan et al. (13)* 330 2D 65 45–65 1.8–2.5 25–30 43.9– 69 2y Perdona et al. (14)*z 121 3D 65 65 1.8 35 63.4 4y Mangar et al. (15)* (CD) 154 3D 60–64 60–64 — 2 30–32 60–64 42 75 60–64 48–52 12 2 24–26 52/60–64 23 Cowan et al. (16)*x 25 3D 52.5 52 2.63 20 56.3 4 PB 22 57.5 57.5 2.88 20 56.3–63.8 18 PB 16 55 55 3.44 16 57.1–64.9 6 Yavuz et al. (17) (CD) 87 3D 45/67.5 45 22.5 1.8/1.5 CB 35 43.9–65 1 Pos et al. (18) (CD) 47 3D 55 55 — 2/2.75 CB 20 40/55 9 40 40 15 Shipley et al. (19, 27) (CD) 157 2D 64–65 52–55 12–15 1.8/1.5–1.8 36–42 60.9–62.2 6 Abbreviations: EQD2 = equivalent dose in 2-Gy fractions, assuming a/b = 6; 2D = two-dimensional conventional simulation; 3D = CT-based three-dimensional planning; b.i.d. = twice daily; PB = all treatment fields included only part of bladder, as determined by primary tumor site using CT-based planning; CD = first phase included whole bladder followed by cone down to partial bladder with CT-based planning; CB = concomitant boost; CT = computed tomography. * Treatment to the whole bladder as localized with contrast or CT. y Concurrent with chemotherapy. z Bladder in treatment fields; cone down from pelvic fields at median dose of 45 Gy. x Grade 2 or greater toxicity reported. S118 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 119. EBRT 50 Gy(hazard ratio [HR], 3.34; p = .002), black race (HR, 1.89; p = .003), smoking history (HR, 1.81; p = .006), and body mass index 30 kg/m2 (HR, 1.55; p = .05) were sig- nificantly associated with bladder complications (49). Age, diabetes, hypertension, or a history of pelvic inflammatory disease were not significantly related to bladder toxicity (49). From the experience of the senior investigators of the present report, patients taking anticoagulation medications might develop hematuria. Surgery TURBP, prostatectomy, hysterectomy, biopsy or any kind of procedure before RT may potentially increase morbidity. The site of TURBT might heal slowly. Hysterectomy or pros- tatectomy can denervate the bladder, which causes urinary hesitancy or retention, resulting in overflow incontinence. Approximately 5% of patients who undergo radical hysterec- tomy require chronic suprapubic catheterization; 38–50% develop detrusor instability, impairment of bladder sensation, alteration in bladder compliance or capacity, or a reduction in the maximal urethral pressure (50, 51). In one study (52), transurethral prostate resection (TURP) before defini- tive RT resulted in incontinence in 5% of patients compared with 1% who had not undergone TURP. After EBRT for prostate cancer, the rate of urethral stricture has been reported to range from 2% to 5% in patients without previous TURP vs. 6–16% in patients with previous TURP (1). Chemotherapy Changes in bladder function can occur with chemotherapy alone or with concurrent chemoradiotherapy. Cytoxan is independently associated with chronic hemorrhagic cystitis, incontinence, contractions, vesicoureteral reflux, and urothe- lial malignancies (53). In one study with 8 years of follow-up of cervical-cancer patients treated with chemoradiotherapy, 3% developed late bladder side effects (54). During the past one to two decades, selective bladder-preserving approaches for patients with muscle-invasive bladder cancer have included EBRT with concurrent cisplatin-containing chemotherapy. Tumor doses of 64–65 Gy have been well tolerated (19). Chemotherapy administered concurrently with RT can sensitize the normal tissue, although this has not been shown to increase the risk of long-term bladder complications in patients with cervical cancer or bladder cancer. Fractionation Some evidence has supported the association of a high dose per fraction with a greater complication rate (1). Pros- tate-cancer patients treated with 5.17 Gy/fraction twice a week through anteroposterior/posteroanterior fields for 9 weeks with a 3-week break mid-way through therapy had a 19% rate of serious bladder injury (55). These included both global (cystitis and contracture) and focal (fistula) in- jury. Treatment timing could also be a factor. One study of Dose (Gray) IncidenceofGrade3latebladdertoxicity(%) 0 5 10 15 20 25 30 35 40 45 7060504030 Physical Dose Equivalent Dose J,123 A,24 I, 186 F,24 L,330 E,96 B,60 K,154 A, 20 A, 8 A,58 H, 889 D, 34 M,121 G, 62 ytliuQ.A 02 nacnuD.B 12 uY.C 22 narocroC.D 32 laicraM.E 42 notnioP.F 52 namdooG.G 62 2nacnuD.H 9 ledöR.I 11 J netlohcS. 21 ragnaM.K 51 nahgemaM.L 13 anodreP.M 41 A A A B G A F J L E M D C,309 H Fig. 1. Incidence of Radiation Therapy Oncology Group Grade 3 or greater late bladder toxicity in relation to average dose (squares) or linear-quadratic model equivalent dose (triangles) in 2-Gy fractions (assuming a/b = 6 Gy) for studies treating whole bladder only (listed in Table 1 and reviewed by Marks, et al. [1]). Letter in each square denotes data source: pub- lication specified in key as first author followed by superscript reference number. Note, Quilty and Duncan (20) had four dose groups. Number of patients italicized inside each square. No significant correlation was found between complication rate and either dose or equivalent dose. (Courtesy of E.D. Yorke.) Radiation-associated bladder injury d A. N. VISWANATHAN et al. S119
- 120. bladder cancer reporteda 32% risk of severe bladder injury with a split-course technique of 40 Gy to a large volume of the bladder (whole-pelvic fields), followed by 20 Gy (to a small portion of the bladder) at 2 Gy/fraction using two-di- mensional simulation, with three fractions daily and an inter- fraction interval of 4 h (56). A series using whole-bladder RT for bladder cancer found that 66 Gy delivered within 5 weeks with 2 Gy/fraction twice daily for the last 8 days, with at least a 6-h interval between fractions, resulted in no Grade 3 or greater late GU toxicity at 3 years (10). However, twice-daily treatment for the final 13 days (within 4 weeks total) signif- icantly increased the 3-year actuarial GU toxicity rate to 31% (p = .04) (10). In contrast, a randomized trial of 229 patients with muscle-invasive bladder tumors treated without chemotherapy compared 60.8 Gy in 32 fractions twice daily vs. daily RT to 64 Gy. There was no significant difference be- tween accelerated versus conventional fractionation in acute Grade 2 or 3 bladder toxicity (34% vs. 36%) or late chronic hematuria (25% vs. 14%), increased frequence of micturition (60% vs. 66%) or ureteric stenosis (11% vs. 9%) (57). 6/7. MATHEMATICAL/BIOLOGIC MODELS AND SPECIAL SITUATIONS Currently, no quantitative models are available that satis- factorily describe the observed serious late bladder toxicity after EBRT, given the lack of a clear dose response for whole-bladder RT and overall bladder variability. Given the marked uncertainty of the 3D data on which previously described models were based, we do not recommend that any of the previously described model coefficients be used to predict the outcome. Furthermore, whether different pa- rameter sets might be necessary to describe complications in the setting of RT for prostate, bladder, or gynecologic can- cer or in subpopulations of patients with various co-morbid- ities is not known. 8. RECOMMENDED DOSE–VOLUME LIMITS Although constraints have been used by some centers, the values of the set constraints have often not been based on preceding data nor on localization of the bladder during fractionated therapy. Unless treatment is to the whole pelvis, a bladder volume determined from a static simulation CT scan will not represent the treated portion of the bladder during a several-week course of therapy. In the absence of any reli- able data, clinicians might consider the dose limits listed in the conventional fractionation arm of the Radiation Therapy Oncology Group (RTOG) 0415 study of prostate cancer, which included a solid bladder constraint of no more than 15% of the volume to receive a dose 80 Gy, no more than 25% of the volume to receive a dose 75 Gy, no more than 35% of the volume to receive a dose 70 Gy, and no more than 50% of the volume to receive a dose 65 Gy. Bladder cancer The published reports have not provided robust data on which to base strict dose–volume guidelines. Nevertheless, the published data have suggested that restricting whole- bladder or partial-bladder doses to 64–65 Gy in 36 daily frac- tions or in 40–42 twice-daily fractions produces a level of late bladder complications equivalent to Radiation Therapy Oncology Group Grade 3 toxicity in #6% (19). Prostate cancer The dose distributions for conventional four- and six-field 3D conformal RT to the prostate and seminal vesicles, with an approximately 1-cm margin, limit the volume of bladder receiving the prescription dose. The resultant in-target dose distribution will be relatively uniform, with high regions of dose within the bladder unlikely. For IMRT, physicists at several centers use optimization to constrain the high-dose re- gions. Several different constraints have been reported, al- though none have been determined from long-term toxicity data, and all used the SimDVH. Increasingly, many centers use daily image guidance with ultrasound or radiographic im- aging of implanted markers for prostate localization. In the future, imaging will allow clinicians to decrease the pre- scribed margin and might improve our knowledge of the bladder location and delivered dose. Selected centers queried for the present review do not apply bladder constraints when performing prostate brachytherapy. Gynecologic cancer The external-beam component of gynecologic therapy has been limited to 40–50 Gy and rarely results in severe long- term sequelae. However, the addition of brachytherapy increases this dose. In cervical-cancer brachytherapy, an upper dose limit for brachytherapy has not yet been clearly defined (42). 9. FUTURE TOXICITY STUDIES The upper limit of bladder dose tolerance is not known. Future studies detailing the dose–volume data, accounting for organ motion and distension, and having long-term clini- cal follow-up data are needed. In addition, reports in the future should attempt to address some of the issues listed below. The use of 3D imaging during conformal RT will facilitate studies that relate the actual dose–volume parameters to the clinical outcomes. An improved understanding of the physiology of bladder distention might allow construction of deformable models that could facilitate estimates of bladder dose distribution according to the bladder volume and surface area. Statistical methods might also be useful to understand the likely degree of bladder motion during a course of RT and to better estimate the delivered 3D doses. All regions of the bladder might not be equally important for different functions. Studies that estimate the physiologic effect of doses to different regions of the bladder could be helpful. Statistical approaches such as Cox regression proportional hazard models should be used to adjust for the potential con- founding effects of medical co-morbidities and other S120 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 121. treatments. Patients withrecurrent disease should not be in- cluded in such studies because the symptoms from recurrence and repeated treatment could be confounding. Better determination of the linear-quadratic model param- eters describing bladder injury is needed. The radiobiologic determinants of the a/b and the biologic model used to calcu- late a normalized total dose in 2-Gy fractions (EQD2) for high-dose-rate brachytherapy should be analyzed to deter- mine whether they are valid for the high doses administered during cervical-cancer treatment. An increased understand- ing of the applicability of the model to bladder injury, espe- cially in the setting of brachytherapy, is needed. Patient-based, rather than physician-derived, toxicity scor- ing must be reported to better reflect the true symptomatic incidence of bladder injury. 10. TOXICITY SCORING Both physician- and patient-generated reports are impor- tant to assess toxicities. Symptoms can be graded by patient report, including statements ranging from ‘‘not a problem’’ to ‘‘a big problem.’’ Symptoms such as incontinence, hematu- ria, pads used daily, nocturia, dysuria, frequency, and reten- tion can be assessed with more validity using patient- assessment tools rather than physician-assessment tools, in- cluding those that rely on medications prescribed. Given the multiple endpoints that can be used to score toxicity, and to avoid ambiguity, we recommend that objective, quan- titative, scoring systems that explicitly consider multiple pa- tient- and physician-based endpoints be used, such as the LENT-SOMA system. REFERENCES 1. Marks LB, Carroll PR, Dugan TC, et al. The response of the urinary bladder, urethra, and ureter to radiation and chemother- apy. Int J Radiat Oncol Biol Phys 1995;31:1257–1280. 2. Eifel PJ, Levenback C, Wharton JT, et al. Time course and incidence of late complications in patients treated with radiation therapy for FIGO stage IB carcinoma of the uterine cervix. Int J Radiat Oncol Biol Phys 1995;32:1289–1300. 3. Gardner BG, Zietman AL, Shipley WU, et al. Late normal tissue sequelae in the second decade after high dose radiation therapy with combined photons and conformal protons for locally ad- vanced prostate cancer. J Urol 2002;167:123–126. 4. Talcott JA, Rieker P, Clark JA, et al. Patient-reported symptoms after primary therapy for early prostate cancer: Results of a pro- spective cohort study. J Clin Oncol 1998;16:275–283. 5. Xiong L, Viswanathan A, Stewart AJ, et al. Deformable struc- ture registration of bladder through surface mapping. Med Phys 2006;33:1848–1856. 6. Hellebust TP, Dale E, Skjonsberg A, et al. Interfraction varia- tions in rectum and bladder volumes and dose distributions during high dose rate brachytherapy treatment of the uterine cer- vix investigated by repetitive CT-examinations. Radiother Oncol 2001;60:273–280. 7. Muren LP, Smaaland R, Dahl O. Organ motion, set-up variation and treatment margins in radical radiotherapy of urinary bladder cancer. Radiother Oncol 2003;69:291–304. 8. Turner SL, Swindell R, Bowl N, et al. Bladder movement during radiation therapy for bladder cancer: Implications for treatment planning. Int J Radiat Oncol Biol Phys 1997;39: 355–360. 9. Duncan W, Quilty PM. The results of a series of 963 patients with transitional cell carcinoma of the urinary bladder primarily treated by radical megavoltage X-ray therapy. Radiother Oncol 1986;7:299–310. 10. Moonen L, vander Voet H, Horenblas S,et al. Afeasibility study of accelerated fractionation in radiotherapy of carcinoma of the urinary bladder. Int J Radiat Oncol Biol Phys 1997;37:537–542. 11. Rodel C, Grabenbauer GG, Kuhn R, et al. Combined-modality treatment and selective organ preservation in invasive bladder cancer: Long-term results. J Clin Oncol 2002;20:3061–3071. 12. Scholten AN, Leer JW, Collins CD, et al. Hypofractionated radiotherapy for invasive bladder cancer. Radiother Oncol 1997;43:163–169. 13. Mameghan H, Fisher RJ, Watt WH, et al. The management of invasive transitional cell carcinoma of the bladder: Results of definitive and preoperative radiation therapy in 390 patients treated at the Prince of Wales Hospital, Sydney, Australia. Cancer 1992;69:2771–2778. 14. Perdona S, Autorino R, Damiano R, et al. Bladder-sparing, combined-modality approach for muscle-invasive bladder can- cer: A multi-institutional, long-term experience. Cancer 2008; 112:75–83. 15. Mangar SA, Foo K, Norman A, et al. Evaluating the effect of reducing the high-dose volume on the toxicity of radiotherapy in the treatment of bladder cancer. Clin Oncol (R Coll Radiol) 2006;18:466–473. 16. Cowan RA, McBain CA, Ryder WD, et al. Radiotherapy for muscle-invasive carcinoma of the bladder: Results of a random- ized trial comparing conventional whole bladder with dose- escalated partial bladder radiotherapy. Int J Radiat Oncol Biol Phys 2004;59:197–207. 17. Yavuz AA, Yavuz MN, Ozgur GK, et al. Accelerated superfrac- tionated radiotherapy with concomitant boost for invasive blad- der cancer. Int J Radiat Oncol Biol Phys 2003;56:734–745. 18. Pos FJ, van Tienhoven G, Hulshof MC, et al. Concomitant boost radiotherapy for muscle invasive bladder cancer. Radio- ther Oncol 2003;68:75–80. 19. Shipley WU, Bae K, Efstathiou JA, et al. Late pelvic toxicity following bladder-sparing therapy in patients with invasive bladder cancer: Analysis of RTOG 89-03, 95-06, 97-06, 99-06. Proceedings of the American Society for Therapeutic Radiology and Oncology 49th Annual Meeting, Los Angeles, CA. Int J Radiat Oncol Biol Phys 2007;69:S8. 20. Quilty PM, Duncan W. Primary radical radiotherapy for T3 transitional cell cancer of the bladder: An analysis of sur- vival and control. Int J Radiat Oncol Biol Phys 1986;12: 853–860. 21. Duncan W, Williams JR, Kerr GR, et al. An analysis of the radiation related morbidity observed in a randomized trial of neutron therapy for bladder cancer. Int J Radiat Oncol Biol Phys 1986;12:2085–2092. 22. Yu WS, Sagerman RH, Chung CT, et al. Bladder carcinoma: Experience with radical and preoperative radiotherapy in 421 patients. Cancer 1985;56:1293–1299. 23. Corcoran MO, Thomas DM, Lim A, et al. Invasive bladder can- cer treated by radical external radiotherapy. Br J Urol 1985;57: 40–42. 24. Marcial VA, Amato DA, Brady LW, et al. Split-course radio- therapy of carcinoma of the urinary bladder stages C and D1: A Radiation Therapy Oncology Group study. Am J Clin Oncol 1985;8:185–199. Radiation-associated bladder injury d A. N. VISWANATHAN et al. S121
- 122. 25. Pointon RS,Read G, Greene D. A randomised comparison of photons and 15 MeV neutrons for the treatment of carcinoma of the bladder. Br J Radiol 1985;58:219–224. 26. Goodman GB, Hislop TG, Elwood JM, et al. Conservation of bladder function in patients with invasive bladder cancer treated by definitive irradiation and selective cystectomy. Int J Radiat Oncol Biol Phys 1981;7:569–573. 27. Shipley WU, Kaufman DS, Zehr E, et al. Selective bladder pres- ervation by combined modality protocol treatment: Long-term outcomes of 190 patients with invasive bladder cancer. Urology 2002;60:62–68. 28. Quilty PM, Duncan W, Kerr GR. Results of a randomised study to evaluate influence of dose on morbidity in radiotherapy for bladder cancer. Clin Radiol 1985;36:615–618. 29. Zelefsky MJ, Aschkenasy E, Kelsen S, et al. Tolerance and early outcome results of postprostatectomy three-dimensional conformal radiotherapy. Int J Radiat Oncol Biol Phys 1997; 39:327–333. 30. Feng M, Hanlon AL, Pisansky TM, et al. Predictive factors for late genitourinary and gastrointestinal toxicity in patients with prostate cancer treated with adjuvant or salvage radiotherapy. Int J Radiat Oncol Biol Phys 2007;68:1417–1423. 31. Al-Mamgani A, van Putten WL, Heemsbergen WD, et al. Update of Dutch multicenter dose-escalation trial of radiother- apy for localized prostate cancer. Int J Radiat Oncol Biol Phys 2008;71:1028–1033. 32. Zelefsky MJ, Levin EJ, Hunt M, et al. Incidence of late rectal and urinary toxicities after three-dimensional conformal radio- therapy and intensity-modulated radiotherapy for localized pros- tate cancer. Int J Radiat Oncol Biol Phys 2008;70:1124–1129. 33. Logsdon MD, Eifel PJ. FIGO IIIB squamous cell carcinoma of the cervix: An analysis of prognostic factors emphasizing the balance between external beam and intracavitary radiation ther- apy. Int J Radiat Oncol Biol Phys 1999;43:763–775. 34. Fellner C, Potter R, Knocke TH, et al. Comparison of radiog- raphy- and computed tomography-based treatment planning in cervix cancer in brachytherapy with specific attention to some quality assurance aspects. Radiother Oncol 2001;58: 53–62. 35. Pelloski CE, Palmer M, Chronowski GM, et al. Comparison between CT-based volumetric calculations and ICRU reference-point estimates of radiation doses delivered to bladder and rectum during intracavitary radiotherapy for cervical can- cer. Int J Radiat Oncol Biol Phys 2005;62:131–137. 36. Schoeppel SL, LaVigne ML, Martel MK, et al. Three-dimen- sional treatment planning of intracavitary gynecologic implants: Analysis of ten cases and implications for dose specification. Int J Radiat Oncol Biol Phys 1994;28:277–283. 37. Ling CC, Schell MC, Working KR, et al. CT-assisted assess- ment of bladder and rectum dose in gynecological implants. Int J Radiat Oncol Biol Phys 1987;13:1577–1582. 38. Measurements ICoRUa. ICRU report 38: Dose and volume specification for reporting intracavitary therapy in gynecology. Bethesda: International Commission on Radiation Units and Measurements; 1985. 39. Barillot I, Horiot JC, Maingon P, et al. Maximum and mean bladder dose defined from ultrasonography: Comparison with the ICRU reference in gynaecological brachytherapy. Radiother Oncol 1994;30:231–238. 40. Kirisits C, Potter R, Lang S, et al. Dose and volume parameters for MRI-based treatment planning in intracavitary brachyther- apy for cervical cancer. Int J Radiat Oncol Biol Phys 2005; 62:901–911. 41. Potter R, Haie-Meder C, Van Limbergen E, et al. Recommenda- tions from gynaecological (GYN) GEC ESTRO working group (II): Concepts and terms in 3D image-based treatment planning in cervix cancer brachytherapy-3D dose volume parameters and aspects of 3D image-based anatomy, radiation physics, radiobi- ology. Radiother Oncol 2006;78:67–77. 42. Georg P, Dimopoulos J, Kirisits C, et al. The predictive value of dose volume parameters in MRI based cervical cancer brachy- therapy for late adverse side effects in rectum, sigmoid and bladder. Int J Radiat Oncol Biol Phys 2006;66:S42. 43. Viswanathan AN, Racine M, Cormack R. Final results of a prospective study of MR-based interstitial gynecologic brachytherapy. Brachytherapy 2008;7:148. 44. Viswanathan AN, Cormack R, Holloway CL, et al. Magnetic resonance-guided interstitial therapy for vaginal recurrence of endometrial cancer. Int J Radiat Oncol Biol Phys 2006;66: 91–99. 45. Peeters ST, Heemsbergen WD, van Putten WL, et al. Acute and late complications after radiotherapy for prostate cancer: Re- sults of a multicenter randomized trial comparing 68 Gy to 78 Gy. Int J Radiat Oncol Biol Phys 2005;61:1019–1034. 46. Karlsdottir A, Muren LP, Wentzel-Larsen T, et al. Late gastro- intestinal morbidity after three-dimensional conformal radiation therapy for prostate cancer fades with time in contrast to genito- urinary morbidity. Int J Radiat Oncol Biol Phys 2008;70:1478– 1486. 47. Cahlon O, Zelefsky MJ, Shippy A, et al. Ultra-high dose (86.4 Gy) IMRT for localized prostate cancer: Toxicity and biochem- ical outcomes. Int J Radiat Oncol Biol Phys 2008;71:330–337. 48. Schultheiss TE, Lee WR, Hunt MA, et al. Late GI and GU com- plications in the treatment of prostate cancer. Int J Radiat Oncol Biol Phys 1997;37:3–11. 49. Eifel PJ, Jhingran A, Bodurka DC, et al. Correlation of smoking history and other patient characteristics with major complica- tions of pelvic radiation therapy for cervical cancer. J Clin On- col 2002;20:3651–3657. 50. Chen GD, Lin LY, Wang PH, et al. Urinary tract dysfunction after radical hysterectomy for cervical cancer. Gynecol Oncol 2002;85:292–297. 51. Axelsen SM, Bek KM, Petersen LK. Urodynamic and ultra- sound characteristics of incontinence after radical hysterec- tomy. Neurourol Urodyn 2007;26:794–799. 52. Green N, Treible D, Wallack H. Prostate cancer: Post-irradia- tion incontinence. J Urol 1990;144(2 Pt 1):307–309. 53. Levine LA, Richie JP. Urological complications of cyclophos- phamide. J Urol 1989;141:1063–1069. 54. Eifel PJ, Winter K, Morris M, et al. Pelvic irradiation with concurrent chemotherapy versus pelvic and para-aortic irradia- tion for high-risk cervical cancer: An update of Radiation Therapy Oncology Group trial (RTOG) 90-01. J Clin Oncol 2004;22:872–880. 55. Lindholt J, Hansen PT. Prostatic carcinoma: Complications of megavoltage radiation therapy. Br J Urol 1986;58:52–54. 56. Vanuytsel L, Ang KK, Vandenbussche L, et al. Radiotherapy in multiple fractions per day for prostatic carcinoma: Late compli- cations. Int J Radiat Oncol Biol Phys 1986;12:1589–1595. 57. Horwich A, Dearnaley D, Huddart R, et al. A randomised trial of accelerated radiotherapy for localised invasive bladder cancer. Radiother Oncol 2005;75:34–43. S122 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 123. QUANTEC: ORGAN-SPECIFIC PAPERPelvis: Rectum RADIATION DOSE–VOLUME EFFECTS IN RADIATION-INDUCED RECTAL INJURY JEFF M. MICHALSKI, M.D.,* HIRAM GAY, M.D.,* ANDREW JACKSON, M.D.,y SUSAN L. TUCKER, PH.D.,z AND JOSEPH O. DEASY, PH.D.* *Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO; y Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY; and z Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX The available dose/volume/outcome data for rectal injury were reviewed. The volume of rectum receiving $60Gy is consistently associated with the risk of Grade $2 rectal toxicity or rectal bleeding. Parameters for the Lyman- Kutcher-Burman normal tissue complication probability model from four clinical series are remarkably consis- tent, suggesting that high doses are predominant in determining the risk of toxicity. The best overall estimates (95% confidence interval) of the Lyman-Kutcher-Burman model parameters are n = 0.09 (0.04–0.14); m = 0.13 (0.10–0.17); and TD50 = 76.9 (73.7–80.1) Gy. Most of the models of late radiation toxicity come from three-dimen- sional conformal radiotherapy dose-escalation studies of early-stage prostate cancer. It is possible that intensity- modulated radiotherapy or proton beam dose distributions require modification of these models because of the in- herent differences in low and intermediate dose distributions. Ó 2010 Elsevier Inc. Rectum, Radiation injury, NTCP. 1. CLINICAL SIGNIFICANCE Approximately 300,000 patients undergo pelvic radiotherapy (RT) worldwide annually (1). Depending on the techniques and doses used, patients may experience a permanent change in their bowel habits. 2. ENDPOINTS Acute rectal effects occur during or soon after RT and typ- ically include softer or diarrhea-like stools, pain, a sense of rectal distention with cramping, and frequency. Occasion- ally, superficial ulceration causes bleeding that may require endoscopic cauterization, treatment for anemia, or transfu- sion. Late injuries are usually clinically manifest within 3 to 4 years after RT and may include stricture, diminished rec- tal compliance, and decreasing storage capacity with resul- tant small/frequent bowel movements. Injury to the anal musculature can lead to fecal incontinence or stricture. These morbidities can be severe and markedly affect quality of life (QOL). Rectal bleeding is usually self–limited, although some pa- tients require medical management with anti–inflammatory suppositories, antibiotics, endoscopic coagulative therapies, or rarely surgical diversion. In patients with endoscopic rectal abnormalities after RT, the most likely diagnosis is RT effect, and biopsy should not be performed because this may lead to chronic infection, poor healing or ulceration. Radiation Therapy Oncology Group (RTOG) scoring cri- teria are commonly used to report toxicity (2). The original system was criticized as being vague, nonquantitative, and unvalidated. It emphasizes rectal bleeding and stool fre- quency but not fecal incontinence or bowel urgency, both of which impact QOL. Because of its objectivity, the pres- ence of any rectal bleeding has been the sole endpoint reported in some series. Interpreting the rate of RT-induced sequelae is complicated because many symptoms are nonspe- cific and may be related to conditions such as hemorrhoids or irritable bowel disorders. The Common Terminology Criteria for Adverse Events version 3.0 is being used more often in prospective clinical trials (3). It provides more specific descriptions of common toxicities after cancer therapy and is more quantitative than the RTOG scoring criteria. 3. CHALLENGES DEFINING VOLUMES Dose–volume studies have used variable definitions for rectum. The superior limit is usually taken to be the rectosig- moid flexure, but there is uncertainty in determining where this occurs. The inferior limit has been variably defined as Reprint requests to: Jeff Michalski, M.D., Department of Radia- tion Oncology, Washington University School of Medicine, 4921 Parkview Place – Campus Box 8224, St. Louis, MO 63110. Tel: (314) 362-8566; Fax: (314) 747-9557; E-mail: jmichalski@ radonc.wustl.edu Supported by National Institutes of Health Grants NIH RO1 CA85181 and NIH RO1 CA104342. Conflict of interest: none. Received Jan 16, 2009, and in revised form Feb 24, 2009. Accepted for publication March 3, 2009. S123 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S123–S129, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.03.078
- 124. being at thelevel of the anal verge, the ischial tuberosities (or 2 cm below them), or above the anus (the caudal 3 cm of in- testine). Other studies have specified rectal lengths, for example from 1 cm below to 1 cm above the target volume, or from standard treatment fields. Although the rectum is hollow, it is frequently contoured as a solid, including its contents. The position of the rectum at the time of the treatment- planning CT scan is likely not fully representative of the position during RT because of inter- or intrafraction varia- tions in rectal filling, intestinal gas, and bladder filling. These uncertainties are not considered in the present analysis. 4. REVIEW OF DOSE–VOLUME DATA The most frequent endpoints considered in the published analyses are either rectal bleeding or RTOG Grade $2 late rectal toxicity. Grade 2 RTOG toxicity includes moderate di- arrhea and colic, bowel movement more than five times daily, excessive rectal mucus, or intermittent bleeding. Grade 3 consists of obstruction or bleeding requiring surgery. Grade 4 (necrosis/perforation fistula) is rarely encountered in cur- rent practice. Most dose–volume parameters significantly associated with late rectal toxicity consider doses $60 Gy. With a few exceptions, VDose has not been found to be significantly asso- ciated with differences in rectal toxicity for doses #45 Gy. Results are mixed for intermediate doses. In Fig. 1 we show published dose–volume histogram (DVH) thresholds. Rates of Grade $2 rectal toxicity were significantly higher for DVHs passing above these thresholds than for those pass- ing below. Results from each study have been coded by dose spectrum (with red representing the highest biologically equivalent prescription and blue the lowest) and by line thick- ness (proportional to the overall rate of rectal toxicity in the study). This coding shows that at lower prescription doses, larger volumes must be exposed to intermediate doses before substantial toxicity is seen. The curves converge at doses 70 Gy and volumes 20%, showing that dose–volume data from multiple centers con- verge at the high dose range. This implies that these values are more consistently associated with toxicity. To compare clinical DVHs with the thresholds shown in the figure, the DVH and prescription doses were first translated to linear- quadratic equivalent doses delivered in 2-Gy fractions, calcu- lated using a/b = 3 Gy. Thresholds derived from treatments with similar biologically equivalent prescription doses may be found using the color coding specified in the legend. Threshold volumes shown in the graph are for the full length of the anatomic rectum. The reader should bear in mind that, as pointed out in the recommendations below, constraints at intermediate doses need to be validated. Values of VDose tend to be highly correlated with one another across a wide range of doses, especially for patients treated at the same institution with similar techniques. There- fore, volumes exposed to intermediate doses may seem to be significant purely through their correlation with more biolog- ically relevant high-dose volumes. Moreover, the volumes exposed to the highest doses are most subject to the discrep- ancies between the planned and delivered DVH. This too, could lead to an apparent association between toxicity and volumes exposed to intermediate doses. Alternatively, vol- umes exposed to intermediate and high doses might both have biologic significance if, for example, the volumes exposed to intermediate doses play a role in the recovery of tissue exposed to the highest doses (4). 5. FACTORS AFFECTING RISK Factors reportedly associated with complication risk include diabetes mellitus (5–9), hemorrhoids (10, 11), inflam- matory bowel disease (12), advanced age (8), androgen dep- rivation therapy (13, 14), rectum size (15), prior abdominal surgery (7), and severe acute rectal toxicity (7, 14, 16–20). A high rate of acute rectal toxicity is now recognized as asso- ciated with late RT proctopathy (18, 21, 22). In the Dutch ran- domized dose trial for localized prostate cancer, it was an independent significant predictor for late gastrointestinal (GI) toxicity (20, 22). This raises the question as to whether early interventions that lessen acute toxicity might also reduce the risk of late complications, or whether greater- than-expected acute toxicity might be an early indicator of patient hypersensitivity to RT. Dose-volume limits for = grade 2 rectal toxicity with LQ corrected doses (α/β = 3 Gy) LQ equivalent dose in 2 Gy fractions (Gy) 10 20 30 40 50 60 70 80 90 emulov% 0 20 40 60 80 100 Zapatero 70-75.6 Gy: 7% Koper 66 Gy: 33% Wachter 66 Gy: 14% Akimoto 69 Gy: 25% 3 Gy/fr Jackson 75.6 Gy: 19% Jackson 70.2 Gy: 6% Huang 74-78 Gy: 23% Fiorino 70-76 Gy: 9% Cozzarini 66.2-70.2Gy: 11% Hartford 75.6 Gy:34% Grade 1 Fig. 1. Dose–volume histogram thresholds found to be significantly associated with Grade $ 2 rectal toxicity. Thicker lines indicate higher rates of rates of overall toxicity (percentages are indicated on the graph along with the physical prescription dose). Threshold doses are expressed as linear-quadratic equivalent doses delivered in 2-Gy fractions, calculated using a/b = 3 Gy. The associated linear- quadratic equivalent prescription doses are coded by spectrum from lowest (blue), to highest (red). Volumes shown in the graph are based on the full length of the anatomic rectum. Curves for Huang and Wachter were adjusted downward by 15% and by 50% for Hart- ford, to account for the different definitions used for rectal volume. Dose–volume data from multiple centers converge at the high dose range, implying that these values are more consistently associated with toxicity. Abbreviations: LQ = linear quadratic S124 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 125. 6. MATHEMATIC/BIOLOGIC MODELS Thepublished literature includes at least five fits of the Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) model to rectal toxicity data (7, 10, 23–27) (Table 1). With one exception (10) the published parameter estimates have been remarkably consistent, even though the endpoint has varied somewhat among these stud- ies. The volume parameter, n, has usually, but not always, been found to be quite small (0.15). Small values of n indi- cate that high-dose regions play a predominant role in deter- mining the risk of late rectal toxicity (i.e., series architecture), in accordance with the analyses of the DVH cut-points (Fig. 1). An advantage of the LKB model over DVH con- straints is that it yields NTCP values for patient-specific treat- ment plans. 7. SPECIAL SITUATIONS Given the large numbers of patients included in published studies of rectal toxicity, and the relative consistency of their results for rectal bleeding, existing estimates of toxicity from the LKB model are probably better than for most organs. In the Dutch randomized trial, bleeding, high stool fre- quency, and fecal incontinence were scored and modeled separately. Not only were the parameter estimates markedly different for each endpoint, but the organ at risk also differed (27). For rectal bleeding and high stool frequency, modeling based on the DVH of the anorectal wall was best, whereas for fecal incontinence, that of the distal 3 cm of the anal canal wall was most relevant. Furthermore, they estimated the dose-modifying factors for patients with increased risk of rec- tal injury due to prior abdominal surgery. Model-based predictions for treatments with prescribed doses 79.2 Gy and diseases other than prostate cancer, for which there is little data, should be viewed as tentative and require validation. Model predictions may not be representa- tive of settings where intensity modulation or image-guided practices are in place. In the prostate cancer dose escalation trial, RTOG 9406, larger planning target volumes (PTVs) were associated with increased toxicity (28). Image guidance should reduce the volume of rectum that overlaps with the high-dose PTV and yield a planned rectal DVH that more closely approximates the volume of rectum irradiated daily. The NTCP estimates are population-based: a low risk esti- mate does not preclude the occurrence of rectal injury, possi- bly severe, in any individual patient. 8. RECOMMENDED DOSE/VOLUME LIMITS Organ segmentation The rectum should be segmented from above the anal verge to the turn into the sigmoid colon, including the rectal contents. Although there can be variation in defining these landmarks, the superior limit is where the bowel moves ante- riorly, close to the inferior level of the sacroiliac joints, and the inferior limit is commonly at the bottom of the ischial tuberosities. In prostate cancer therapy, an empty rectum at simulation is advised to avoid introducing a systematic error in PTV coverage. A supine position is associated with less variability in daily organ positioning. These conditions are less critical with image-guided RT. Dose–volume constraints for conventional fractionation up to 78 Gy The following dose–volume constraints are provided as a conservative starting point for 3D treatment planning: V50 50%, V60 35%, V65 25%, V70 20%, and V75 15%. However, they have yet to be validated as ‘‘rela- tively-safe.’’ For typical DVHs, the NTCP models predict that following these constraints should limit Grade $2 late rectal toxicity to 15% and the probability of Grade $3 late rectal toxicity to 10% for prescriptions up to 79.2 Gy in standard 1.8- to 2-Gy fractions. Higher doses in the VDose parameter have more impact on the complication probability. Clinicians should strive to min- imize the V70 and V75 volumes below the recommended con- straints without compromising tumor coverage. Reducing the V75 by just 5% from 15% to 10% has a significant impact in the predicted complication probability, whereas reducing the V50 from 50% to 45% makes relatively little difference. Intensity-modulated RT (IMRT) planning yields distinctly different shaped DVH curves than forward-planned 3D con- formal RT (3D-CRT), with considerably decreased rectal volume receiving low to intermediate radiation doses. Although the parameters above provide a safe starting point for both 3D-CRT and IMRT, it is likely that because IMRT can achieve better low to intermediate dose–volume con- straints, the observed rectal toxicity will be lower (20). The Memorial Sloan-Kettering IMRT experience suggests that doses in the intermediate range of 40–60 Gy may become im- portant in patients who are receiving radiation prescriptions in excess of 78 Gy. NTCP models All series from which LKB parameters are reported used 3D-CRT prescribed to doses #79.2 Gy for localized prostate cancer. Depending on the patient geometry, dose prescribed, treatment technique, and other clinical variables, the pro- posed dose–volume constraints might be unachievable (e.g., for doses 79.2 Gy), but every effort should be made to be as close as possible to the constraints especially in the high doses. In situations similar to those from which the model parameters were derived, the LKB model can estimate the complication probability. A meta-analysis of the results from the four studies (10, 24– 26) of Grade $2 late toxicity or rectal bleeding gavethe overall best estimates of the LKB parameters (95% confidence interval) as n = 0.09 (0.04–0.14); m = 0.13 (0.10–0.17); and TD50 = 76.9 (73.7–80.1) Gy. Estimates of TD50 were found to be heterogeneous (the null hypothesis that estimates for a model parameter were drawn from the same distribution was rejected, p 0.01; the inconsistency index [I2 ] was 79%). Although heterogeneity could not be established for es- timates of n (p 0.1), the inconsistency index was substantial Rectal Radiation Dose-Volume Effects d J. M. MICHALSKI et al. S125
- 126. Table 1. Descriptionof endpoints, study details, and Lyman-Kutcher-Burman parameters for published analyses Authors (reference) Endpoint No. of centers/time period studied/RT technique Incidence, % (n) Total prescribed dose (Gy)/fraction size (Gy) Parameters (68% CI) [95% CI] Rectal DVH Tucker et al. (26) Grade $2 RTOG* 42 1994–2000 Mostly 4–7 field 3D-CRT 13.5 (138/1023) 68.4, 73.2, 79.2/1.8 74, 78/2 n = 0.08 [0.04–0.26] m = 0.14 [0.10–0.25] TD50 = 78 [72–84] Gy Rectum plus contents So¨hn et al. (25) Grade $2 CTCAE v3.0y 1 1999–2002 4-field 3D-CRT 16 (51/319) 70.2, 72, 73.8, 75.6, 77.4, 79.2/1.8 a = 11.9 Æ 3.8 n = 1/a = 0.08 m = 0.108 Æ 0.027 TD50/not reported = 78.4 Æ 2.1 Gy Median follow-up: 2.8 y; range, 0.1–6.4 y Rectum plus contents Rancati et al. (24) Grade $2 bleedingz 5 1994–2001 3–4-field 3D-CRT 7.0 (38/547) intact and postprostatectomy 64–79.2/1.8–2 n = 0.23 (0.14–0.42) m = 0.19 (0.15–0.25) TD50/1.5 = 81.9 (76.8–91.2) Gy Rectum plus contents 6.9 (22/321) intact only 70–79.2/1.8–2 n = 0.24 (0.14–0.50) m = 0.14 (0.11–0.19) TD50/1.5 = 75.7 (72.1–81.8) Gy Grade $3 bleedingx 1.6 (9/547) 64–79.2/1.8–2 n = 0.06 Æ 0.01? m = 0.06 Æ 0.005? TD50/1.5 = 78.6 Æ 3.7? Gy Peeters et al.(27) Bleedingk 4 1997–2003 2–4-field 3D-CRT{ 4.9 (23/468) 68 (n = 234), 78 (n = 234)/2 n = 0.13 (0.04–0.25) m = 0.14 (0.11–0.19) TD50/3 = 81 (75–90) Gy Anorectal wall; method of Meijer et al. (35) Frequency 6.4 (30/468) n = 0.39 (0.19–1.11) m = 0.24 (0.18–0.35) TD50/3 = 84 (75–103) Gy Anorectal wall; method of Meijer et al. (35) Fecal incontinence 6.8 (32/468) n = 7.48 (0.56–N) m = 0.46 (0.39–0.52) TD50/3 = 105 (88–138) Gy Anal wall; method of Meijer et al. (35) Cheung et al. (10) Grade $2 toxicity, modified scale# 1 1992–1999 3D-CRT 4-field to 46 Gy 6-field to 78 Gy 22.7 (29/128) 78/2 n = 3.91 [0.031–N] m = 0.156 [0.036–0.271] TD50 = 53.6 [50–75.1] Gy External rectal wall plus contents Without hemorrhoids 16.7 (14/ 84) n = 0.746 [0.026–N] m = 0.092 [0.019–0.189] TD50 = 56.7 [49.9–75.2] Gy (Continued) S126I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010
- 127. (I2 = 40%). Estimatesof m showed no indications of heteroge- neity (p 0.1, I2 = 0). The source of heterogeneity in both n and TD50 was the study from the M. D. Anderson Cancer Center (10). If that data set was excluded, the best estimate of TD50 be- came 78.5 (75.2–81.8) Gy. Other parameters remained the same to 10% in the confidence intervals; however, all indica- tions of heterogeneity disappeared (p 0.1,I2 = 0 for all param- eters). Excluding prostatectomy patients (24) from the analysis resulted in essentially no change in the overall best estimates of parameter values or in measure of heterogeneity. It is notable that the LKB parameters from studies of Grade $3 late rectal bleeding (24, 27) (Table 1) are broadly similar to those above. It might be expected that the dose response for Grade 3 complications should be shifted to higher doses, but this was not seen. However, Rancati et al. (24) showed a decrease in n (to 0.06) for Grade $3 complications, indicat- ing an increased dependence on the highest doses. Daily deviations of rectal position probably result in some patients receiving higher cumulative rectal DVHs than planned. Such patients may skew the corresponding NTCP modeling anal- ysis, making the resulting parameters overestimate the com- plication risk. For this reason, the model predictions have some uncertainty regarding their applicability depending on the immobilization, treatment, and localization techniques used. In the presence of daily localization and IMRT, these models may tend to overestimate the risk of toxicity because the model parameters were based on patients treated mostly without IMRT or daily localization. Patients treated with IMRT have been reported to have lower complication rates than those treated with standard 3D-CRT (20). Hypofractionation Until more clinical data are available for the various hypo- fractionated schedules, DVH dose bins should be adjusted to conventional 1.8- or 2-Gy fractions using the linear-quadratic model with an a/b ratio of 3 for the rectum. Whereas some have proposed a rectal a/b ratio of 5.4 Gy, the choice of a/b ratio of 3 is a reasonably conservative estimate (29). The LKB model could then be used on a linear-quadratic– adjusted DVH to estimate the rectal complication probability. An interim report of a prospective robotic radiosurgery Phase II trial of 36.25 Gy in 5 fractions observed a reduced rate of severe rectal toxicities with an every-other-day vs. consecu- tive-day treatment schedule (30). This observation warrants further exploration. 3D-CRT vs. IMRT Most of the mature published clinical data on dose-related rectal toxicity come from 3D-CRT. Increasingly, IMRT is being used to treat pelvic malignancies, especially localized prostate cancer, often leading to a much lower volume of rec- tal tissue receiving intermediate to high doses. Modeling derived from 3D-CRT treatments may need to be modified to predict complications from IMRT treatments. As dis- cussed in ‘‘Review of Dose–Volume Data,’’ intermediate dose levels are often correlated to the specific 3D treatment techniques used, and rectal volumes exposed to these doses Table1.Descriptionofendpoints,studydetails,andLyman-Kutcher-Burmanparametersforpublishedanalyses(Continued) Authors(reference)Endpoint No.ofcenters/timeperiod studied/RTtechniqueIncidence,%(n) Totalprescribed dose(Gy)/fraction size(Gy) Parameters (68%CI)[95%CI]RectalDVH Burmanetal.(23)Severeproctitis,necrosis, fistula,andstenosis** n=0.12 m=0.15 TD50/5=80Gy *Grade2isdefinedas‘‘moderatediarrheaandcolic;bowelmovement5timesdaily;excessiverectalmucusorintermittentbleeding’’(2),startingorpersisting120daysafterstartoftherapy. y ChronicrectalbleedingthatexcludesGrade1bleedingdefinedas‘‘mildhemorrhage/bleeding;intervention(otherthanironsupplements)notindicated.’’ z ExcludesGrade1or‘‘slight’’bleeding(#2weeks).Latecomplicationsweredefinedasthosedeveloping3monthsafterthecompletionofthetherapy,orthosestartingbeforeandpersisting for3monthsafterthecompletionoftherapy. x Grade3definedasasinglecoagulationprocedureand/ortransfusion.Latecomplicationsweredefinedasthosedeveloping3monthsafterthecompletionofthetherapyorthosestarting beforeandpersistingfor3monthsafterthecompletionoftherapy. k Bleedingrequiringlasertreatmentortransfusionofpackedcellsandstarting120daysafterthestartoftherapy. { Twopatientsreceivedintensity-modulatedradiotherapy. # ExcludesGrade1toxicitydefinedasexcessbowelmovementstwicebaselineand/orslightrectaldischargeorblood. **BasedontheEmamietal.rectaltoleranceestimatesin1991(36)andprovidedforhistoricalpurposesonly. Abbreviations:RT=radiotherapy;CI=confidenceinterval;DVH=dose–volumehistogram;RTOG=RadiationTherapyOncologyGroup;3D-CRT=three-dimensionalconformalradio- therapy;TD50/t=radiationdosethatwouldresultina50%riskofseverecomplicationswithintyearsafterirradiation;CTCAE=CommonTerminologyCriteriaforAdverseEvents;? =deduced usingamethodthatyieldssmalleruncertaintiesthanthoseoftheotherstudies. AllstudiesareprospectiveexceptRancatietal. Rectal Radiation Dose-Volume Effects d J. M. MICHALSKI et al. S127
- 128. are often correlatedto biologically relevant high-dose vol- umes. This may explain why intermediate doses have incon- sistently been associated with rectal toxicity. However, if volumes exposed to intermediate and high doses both have biological significance, then the reduction of rectal volumes exposed to doses in the 45-60 Gy range by IMRT may be- come more important. 9. FUTURE TOXICITY STUDIES Improvements in modeling of late rectal toxicity will likely come from DVHs that more accurately reflect the actual dis- tribution of the doses delivered to the rectum, and the sepa- rate scoring and modeling of different aspects of rectal toxicity (bleeding, stool frequency, and fecal incontinence). Determination of the relevant anatomic structures for the dif- ferent rectal endpoints (7, 31) will improve our ability to pre- dict them. Reporting absolute and relative rectal volumes receiving or exceeding dose thresholds is encouraged. Finally, there is growing recognition that individual fac- tors, such as genetic predisposition, comorbidities, and life- style choices (e.g., diet and smoking habits), can affect normal-tissue complication risk. Identification of the relevant factors for each endpoint, and incorporation of these factors into the dose–volume-based models, will undoubtedly improve the prediction of sequelae. The dose constraint parameters provided here will provide clinicians with guidance for RT treatment planning, but they should not replace clinical judgment. These parameters, especially those at the intermediate dose range (45–60 Gy), require prospective validation. 10. TOXICITY SCORING Current methods of scoring rectal toxicity need to be examined. The inclusion of patient-reported outcomes com- plements objective physician-scored criteria. Tools to score both acute and late effects need to be efficient and validated. Toxicity assessments should measure clinically relevant events that matter to patients. Several QOL scales have been developed and validated that measure the impact of therapy after the treatment of prostate cancer (32, 33). The Expanded Prostate Cancer Index Composite includes a vali- dated bowel domain that is potentially applicable to any patient receiving pelvic RT (33). Although the original RTOG/European Organization for Research and Treatment of Cancer late toxicity scales have been criticized for their lack of specificity and objectivity, quantifiable modifications to the criteria have been proposed (34). In the Dutch random- ized trial five GI indicators were used to characterize the origin and clinical course of toxicity. Using both physician notes and patient self-assessments, Peeters et al. (27) charac- terized GI toxicity according to these five indicators that were correlated to specific anatomic and dose–volume parameters. Development and validation of a rectal toxicity scoring sys- tem that incorporates physician assessments and patient- reported outcomes is a priority. REFERENCES 1. Andreyev HJ. Gastrointestinal problems after pelvic radiother- apy: The past, the present and the future. Clin Oncol (R Coll Radiol) 2007;19:790–799. 2. Cox JD, Stetz J, Pajak TF. Toxicity criteria of the Radiation Therapy Oncology Group (RTOG) and the European Organiza- tion for Research and Treatment of Cancer (EORTC). Int J Radiat Oncol Biol Phys 1995;31:1341–1346. 3. Cancer Therapy Evaluation Program. Common terminology cri- teria for adverse events, version 3.0. Washington, DC: Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Department of Health and Human Services; 2006. 4. Jackson A, Skwarchuk MW, Zelefsky MJ, et al. Late rectal bleeding after conformal radiotherapy of prostate cancer. II. Volume effects and dose-volume histograms. Int J Radiat Oncol Biol Phys 2001;49:685–698. 5. Akimoto T, Muramatsu H, Takahashi M, et al. Rectal bleeding after hypofractionated radiotherapy for prostate cancer: Correla- tion between clinical and dosimetric parameters and the inci- dence of grade 2 or worse rectal bleeding. Int J Radiat Oncol Biol Phys 2004;60:1033–1039. 6. Herold DM, Hanlon AL, Hanks GE. Diabetes mellitus: A pre- dictor for late radiation morbidity. Int J Radiat Oncol Biol Phys 1999;43:475–479. 7. Peeters ST, Lebesque JV, Heemsbergen WD, et al. Localized volume effects for late rectal and anal toxicity after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2006;64: 1151–1161. 8. Skwarchuk MW, Jackson A, Zelefsky MJ, et al. Late rectal tox- icity after conformal radiotherapy of prostate cancer (I): Multi- variate analysis and dose-response. Int J Radiat Oncol Biol Phys 2000;47:103–113. 9. Vavassori V, Fiorino C, Rancati T, et al. Predictors for rectal and intestinal acute toxicities during prostate cancer high-dose 3D-CRT: Results of a prospective multicenter study. Int J Radiat Oncol Biol Phys 2007;67:1401–1410. 10. Cheung R, Tucker SL, Ye JS, et al. Characterization of rectal normal tissue complication probability after high-dose external beam radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2004;58:1513–1519. 11. Huang EH, Pollack A, Levy L, et al. Late rectal toxicity: Dose- volume effects of conformal radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2002;54:1314–1321. 12. Willett CG, Ooi CJ, Zietman AL, et al. Acute and late toxicity of patients with inflammatory bowel disease undergoing irradia- tion for abdominal and pelvic neoplasms. Int J Radiat Oncol Biol Phys 2000;46:995–998. 13. Liu M, Pickles T, Agranovich A, et al. Impact of neoadjuvant androgen ablation and other factors on late toxicity after exter- nal beam prostate radiotherapy. Int J Radiat Oncol Biol Phys 2004;58:59–67. 14. Schultheiss TE, Lee WR, Hunt MA, et al. Late GI and GU com- plications in the treatment of prostate cancer. Int J Radiat Oncol Biol Phys 1997;37:3–11. 15. Wachter S, Gerstner N, Goldner G, et al. Rectal sequelae after conformal radiotherapy of prostate cancer: Dose-volume his- tograms as predictive factors. Radiother Oncol 2001;59:65– 70. 16. Cozzarini C, Fiorino C, Ceresoli GL, et al. Significant correla- tion between rectal DVH and late bleeding in patients treated S128 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 129. after radical prostatectomywith conformal or conventional ra- diotherapy (66.6-70.2 Gy). Int J Radiat Oncol Biol Phys 2003;55:688–694. 17. Fiorino C, Sanguineti G, Cozzarini C, et al. Rectal dose-volume constraints in high-dose radiotherapy of localized prostate can- cer. Int J Radiat Oncol Biol Phys 2003;57:953–962. 18. O’Brien PC, Franklin CI, Poulsen MG, et al. Acute symptoms, not rectally administered sucralfate, predict for late radiation proctitis: longer term follow-up of a phase III trial—Trans-Tas- man Radiation Oncology Group. Int J Radiat Oncol Biol Phys 2002;54:442–449. 19. Vargas C, Martinez A, Kestin LL, et al. Dose-volume analysis of predictors for chronic rectal toxicity after treatment of pros- tate cancer with adaptive image-guided radiotherapy. Int J Ra- diat Oncol Biol Phys 2005;62:1297–1308. 20. Zelefsky MJ, Levin EJ, Hunt M, et al. Incidence of late rectal and urinary toxicities after three-dimensional conformal radio- therapy and intensity-modulated radiotherapy for localized prostate cancer. Int J Radiat Oncol Biol Phys 2008;70:1124– 1129. 21. Denham JW, O’Brien PC, Dunstan RH, et al. Is there more than one late radiation proctitis syndrome? Radiother Oncol 1999; 51:43–53. 22. Heemsbergen WD, Peeters ST, Koper PC, et al. Acute and late gastrointestinal toxicity after radiotherapy in prostate cancer pa- tients: Consequential late damage. Int J Radiat Oncol Biol Phys 2006;66:3–10. 23. Burman C, Kutcher GJ, Emami B, et al. Fitting of normal tissue tolerance data to an analytic function. Int J Radiat Oncol Biol Phys 1991;21:123–135. 24. Rancati T, Fiorino C, Gagliardi G, et al. Fitting late rectal bleed- ing data using different NTCP models: Results from an Italian multi-centric study (AIROPROS0101). Radiother Oncol 2004;73:21–32. 25. Sohn M, Yan D, Liang J, et al. Incidence of late rectal bleeding in high-dose conformal radiotherapy of prostate cancer using equivalent uniform dose-based and dose-volume-based normal tissue complication probability models. Int J Radiat Oncol Biol Phys 2007;67:1066–1073. 26. Tucker SL, Dong L, Bosch W. Fit of a generalized Lyman nor- mal-tissue complication probability (NTCP) model to Grade $ 2 late rectal toxicity data from patients treated on protocol RTOG 94-06. Int J Radiat Oncol Biol Phys 2007;69:S8–S9. 27. Peeters ST, Hoogeman MS, Heemsbergen WD, et al. Rectal bleeding, fecal incontinence, and high stool frequency after con- formal radiotherapy for prostate cancer: Normal tissue compli- cation probability modeling. Int J Radiat Oncol Biol Phys 2006; 66:11–19. 28. Michalski JM, Bae K, Roach M, et al. Long-Term Toxicity Fol- lowing 3D Conformal Radiation Therapy for Prostate Cancer from the RTOG 9406 Phase I/II Dose Escalation Study. Int J Radiat Oncol Biol Phys 2009. 29. Brenner DJ. Fractionation and late rectal toxicity. Int J Radiat Oncol Biol Phys 2004;60:1013–1015. 30. King CR, Brooks JD, Gill H, et al. Stereotactic body radiother- apy for localized prostate cancer: Interim results of a prospective phase II clinical trial. Int J Radiat Oncol Biol Phys 2009;73: 1043–1048. 31. al-Abany M, Helgason AR, Cronqvist AK, et al. Toward a def- inition of a threshold for harmless doses to the anal-sphincter re- gion and the rectum. Int J Radiat Oncol Biol Phys 2005;61: 1035–1044. 32. Litwin MS, Hays RD, Fink A, et al. The UCLA Prostate Cancer Index: Development, reliability, and validity of a health-related quality of life measure. Med Care 1998;36:1002–1012. 33. Wei JT, Dunn RL, Litwin MS, et al. Development and vali- dation of the Expanded Prostate Cancer Index Composite (EPIC) for comprehensive assessment of health-related qual- ity of life in men with prostate cancer. Urology 2000;56: 899–905. 34. Peeters ST, Heemsbergen WD, van Putten WL, et al. Acute and late complications after radiotherapy for prostate cancer: Re- sults of a multicenter randomized trial comparing 68 Gy to 78 Gy. Int J Radiat Oncol Biol Phys 2005;61:1019–1034. 35. Meijer GJ, van den Brink M, Hoogeman MS, et al. Dose-wall histograms and normalized dose-surface histograms for the rec- tum: A new method to analyze the dose distribution over the rectum in conformal radiotherapy. Int J Radiat Oncol Biol Phys 1999;45:1073–1080. 36. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. Rectal Radiation Dose-Volume Effects d J. M. MICHALSKI et al. S129
- 130. QUANTEC: ORGAN-SPECIFIC PAPERPelvis: Penile Bulb RADIATION DOSE–VOLUME EFFECTS AND THE PENILE BULB MACK ROACH, III, M.D., FACR,* JIHO NAM, M.D.,y GIOVANNA GAGLIARDI, PH.D.,z ISSAM EL NAQA, PH.D.,x JOSEPH O. DEASY, PH.D.,x AND LAWRENCE B. MARKS, M.D.y *Department of Radiation Oncology, University of California-San Francisco, San Francisco, CA; y Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC; z Department of Medical Physics, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden; and x Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, St. Louis, MO The dose, volume, and clinical outcome data for penile bulb are reviewed for patients treated with external-beam radiotherapy. Most, but not all, studies find an association between impotence and dosimetric parameters (e.g., threshold doses) and clinical factors (e.g., age, comorbid diseases). According to the data available, it is prudent to keep the mean dose to 95% of the penile bulb volume to 50 Gy. It may also be prudent to limit the D70 and D90 to 70 Gy and 50 Gy, respectively, but coverage of the planning target volume should not be compromised. It is acknowledged that the penile bulb may not be the critical component of the erectile apparatus, but it seems to be a surrogate for yet to be determined structure(s) critical for erectile function for at least some techniques. Ó 2010 Elsevier Inc. Erectile dysfunction, Penile bulb, Radiation. 1. CLINICAL SIGNIFICANCE Erectile dysfunction (ED), the consistent inability to attain or maintain an erection of sufficient quality to permit satisfac- tory sexual intercourse, is a common complication resulting from radiotherapy (RT) for prostate cancer (1). Many patients choose RT for their clinically localized prostate cancer because they believe there may be a lower risk of ED com- pared with radical prostatectomy (RP); however, this remains controversial. Posttreatment ED rates have been reported to be approximately 24% (brachytherapy alone), 40% (brachy- therapy plus external RT), 45% (external RT alone), 66% (nerve-sparing RP), 75% (non–nerve-sparing RP), and 87% for cryosurgery, but physician-reported rates are known to be less reliable than patient-reported outcomes, so the optimal comparison studies have yet to be done (2). 2. ENDPOINTS The time course for RT-associated ED is variable (reported as days to years) and often evolves gradually. Ascribing ED to RT alone is difficult because men lose some erectile function with age, and other common diseases (e.g., diabetes, hypertension) may contribute. Various self-administered questionnaires have been used to assess erectile function in clinical studies (e.g., the International Index of Erectile Func- tion [IIEF]) (3). Additional objective diagnostic tests can be performed (e.g., nocturnal penile tumescence, somatosensory evoked potentials, bulbocavernous reflex latency, penile elec- tromyography, color duplex Doppler ultrasound, dynamic in- fusion cavernosometry, and pharmacotesting), but these are generally applied to establish the etiology of ED (4). 3. CHALLENGES DEFINING VOLUME The anatomy of the pelvic floor is challenging to visualize on CT or MRI, and hence definition of the penile bulb (PB) varies. This may contribute to inconsistent reports (5–15). The PB appears as an oval-shaped, hyperintense midline structure on T2-weighted MR images; on axial CT imaging it is bounded by the crura, corpora spongiosum, and the leva- tor ani muscle (Fig. 1; see ref. 16 for details). At University of California-San Francisco, the bulb is defined as the most prox- imal portion of the penis sitting immediately caudal to the prostate. We also recognize that the bulb itself is not part of Reprint requests to: Mack Roach III, M.D., F.A.C.R., Department of Radiation Oncology, University of California-San Francisco, 1600 Divisadero Street, San Francisco, CA 94143-1708. Tel: (415) 353-7181; Fax: (415) 353-9883; E-mail: mroach@radonc. ucsf.edu Conflict of interest: M.R. has received recent funding from GSK, Siemens, CareCore National, the National Cancer Institute, Molec- ular Insight, TROFEX, General Electric, Novartis, CPAC (Tomo- therapy, Inc.), and has acted as a consultant (Proton and Carbon Accelerator development). L.B.M. has received honoraria from Var- ian Medical Systems, as well as grant support from the National In- stitutes of Health (NIH), the Lance Armstrong Foundation, and the U.S. Department of Defense. J.O.D. receives funding from the NIH, Varian Medical Systems, and Tomotherapy, Inc. I.E.-N. receives funding from the NIH, Varian Medical Systems, and Tomotherapy, Inc. All other authors have no conflict of interest. Received Feb 3, 2009, and in revised form April 7, 2009. Accepted for publication April 10, 2009. S130 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S130–S134, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.04.094
- 131. the erectile apparatusbut consider it an anatomic surrogate for periprostatic tissue likely to receive high doses of RT. 4. REVIEW OF DOSE–VOLUME DATA Published studies assessing the correlations between the dose of external-beam RT, the PB volume irradiated, clinical factors, and ED are summarized in Table 1. Figure 2 shows a summary of PB dose–volume data vs. rates of ED. Studies that reported an association between RT dose and ED sug- gested that a dose of approximately 50 Gy to essentially the entire PB was a threshold dose for an increased risk of ED. However, several studies did not identify an association between RT dose and ED (5, 11, 13). In general, it is difficult to extract a definite conclusion from these results, owing to relatively small numbers of pa- tients, different anatomic definitions and endpoints for defin- ing ED, and some potential methodologic problems. For example, Selek et al. (11) reported that 10 of 28 patients were completely impotent after RT (zero function on a 5- point scale) but that most of these were hypertensive. Further- more, their choice of 0 on their scale to define an event may not be appropriately sensitive. The most widely accepted scale for evaluating sexual function is the IIEF (which spans from 0 to 25). The original IIEF, described by Rosen et al. (3), included 15 items and five domains. They subsequently developed an abridged version of the questionnaire that con- tained five questions, and the scores ranged from 5 to 25 (17). Fig. 1. Penile and erectile tissue anatomy with CT (A) and MR (B–D) images of the penile bulb (*). Adapted from Wallner et al. (16). Radiation effects in penile bulb d M. ROACH III et al. S131
- 132. Table 1. Erectiledysfunction after external-beam radiotherapy and correlated parameters First author, year (reference) N Assessment method* Prescribed dose, treatment OAR definition Severe ED rate (%) Correlated parameters Dose–volume Clinical Fisch, 2001 (7) 21 Questionnairey 65–72 Gy, 3D Penile bulb 33z D70 $70 Gyx No other endpoints analyzed Roach, 2004 (10) 158 Patient report, (RTOG)k 68.4 Gy, 73.8 Gy, 3D Penile bulb{ 41 Median penile bulb dose $52.5 Gy{ No other endpoints analyzed Wernicke, 2004 (14) 29 Questionnairey 66.6– 79.2 Gy, 3D Penile bulb# NS D30 $67 Gy{ D45 $63 Gy{ D60 $42 Gy{ D75 $20 Gy{ Alcohol and smoking not significant, dose and volume significant Selek, 2004 (11) 28 Questionnairey 78 Gy, 3D Penile bulb# 35.7% at 2 y Mean dose to penile structure 38.2 Gy, no dose–volume effect was found# Up to 68% may have had ED posttreatment? ED correlated with hypertension Mangar, 2006 (8) 51 Questionnairey 64 Gy, 74 Gy, 3D Penile bulb, crura and cavernosum** 24 D15, D30, D50, D90 of penile bulb{ Adjusted for age, bulb volume, hypertension, and previous pelvic surgery Zelefsky, 2006 (15) 561 Patient report (NCI)yy 81 Gy, IMRT zz 49 Not evaluated Hormone therapy Brown, 2007 (5) 32 Questionnairey NS, IMRT Penile bulb 34 No relationship noted Hypertension, pre-RT erectile function Cahlon, 2008 (6) 478 Patient report (NCI)yy 86.4 Gy, IMRT zz 30 Not evaluated Age 70 y, diabetes, hormone therapy van der Wielen, 2008 (13) 70 Questionnairey 68 vs. 78 Gy Penile bulb 36 No correlations between ED and dose–volume of crura, or the penile bulb# Adjusted for diabetes and history of cardiovascular disease Pinkawa, 2009 (9) 123 Questionnairey 70.2–72 Gy, 3D NS 73xx Not evaluated Age, diabetes Abbreviations: OAR = organs at risk; ED = erectile dysfunction; RTOG = Radiation Therapy Oncology Group; NCI =National Cancer Institute; NS = not significant. * All assessments are patient-reported, based on questionnaires or morbidity scoring scales (e.g., RTOG, NCI), as noted. y All questionnaires are self-administered. z Potency scale declined $2. x Dx is dose delivered to the x% penile bulb volume. k RTOG radiation morbidity scoring scale. { Penile bulb was defined as proximal portion of the penis. # The penile bulb is here specifically defined as proximal enlargement of the corpus spongiosum that is secured to the urogenital diaphragm and covered by the bulbospongiosus muscle. ** The penile bulb was here defined as a structure, whereas the crura and the cavernosum as a separate one. yy NCI common toxicity criteria for adverse events. zz Penile bulb not defined as a specific structure. xx No erections firm enough for sexual intercourse. S132I.J.RadiationOncologydBiologydPhysicsVolume76,Number3,Supplement,2010
- 133. In the 1999report the authors found that 21 was the optimal cutoff score. Thus, whenever possible investigators are en- couraged to use this cutoff to define ED instead of the mild, moderate, and severe categories (unless independently validated). Thus for example, in the case of the report by Se- lek et al. (11) it is likely than only assigning patients with a score ‘‘0’’ as being impotent underestimated the true base- line level of ED in their study population (see recommenda- tions in ‘‘Toxicity Scoring’’). In addition, several of these studies included a sizable frac- tion of patients who received phosphodiesterase type 5 inhib- itors that might attenuate the effects of RT on sexual function (18, 19). Earlier studies were less likely to be contaminated by this issue because these agents were not available when most of these patients were treated (7, 10). Brown et al. (5) studied 32 patients and noted no dose– response association for ED. However, they used intensity- modulated RT and attempted to spare the PB, resulting in a mean dose to the bulb of only 25 Gy. Thus, their data do not explicitly refute the presence of a dose–response associ- ation at higher doses. Several studies reported a significant dose–volume effect correlatedwithriskofED using the metrics of Dx (i.e.,the min- imum dose received by x% volume of the PB). For example, Fisch et al. (7) noted ED in 0, 80%, or 100% of patients with a D70 of 0–40, 40–70, and 70 Gy, respectively. Similarly, Mangar et al. (8) reported that a D90 $50 Gy is associated with a significant risk of ED. Wernicke et al. (14) reported that D30, D45, D60, and D75 correlated with an increased risk of ED. Roach et al. (10) reported a significant correlation between a median PB dose of 52.5 Gy and an increase in ED. Brachytherapy studies are mixed in their support for an as- sociation between PB doses and ED. Merrick et al. (20) used a matched-pair study of ED after brachytherapy and related PB dose–volume metrics to patient-reported questionnaire data. The rate of ED was associated with doses to the PB (par- ticularly median dose [D50]) and to a lesser degree the crura. On the other hand, the Macdonald et al. (21) review of 342 patients after brachytherapy failed to show an association between median PB dose and ED. 5. FACTORS AFFECTING RISK Patient-related factors for ED have not been emphasized, except for a few reports. Post-RT ED rates have been reported to be higher with baseline pretreatment ED, diabe- tes, smoking history, or a history of hypertension (5, 7, 20, 22). The data, however, are somewhat conflicting (Table 1). 6. MATHEMATIC/BIOLOGIC MODELS Penile bulb dose–volume parameters may be associated with the incidence of ED, although the results are conflicting to prove a clear correlation between those parameters (Fig. 2). For example, van der Wielen et al. (23) reviewed the litera- ture and concluded that ‘‘sparing of the penile bulb to im- prove potency-preservation is not sufficiently supported by the current literature.’’ and questioned whether the poten- tial ‘‘oncological risk’’ was justified given the uncertainty of potency sparing. It is possible that the key anatomic struc- tures involved in ED pathophysiology have not been defined. Moreover, dosimetric accuracy of the true accumulated dose distribution has seldom been examined in detail. The data are sparse. Overall, the data plotted in Fig. 2 may be consistent with either a causal or surrogate relationship. 7. SPECIAL SITUATIONS Hormonal therapy itself is associated with the ED. Several studies reported the deleterious impact of hormonal therapy on erectilefunction(3, 17,23–27).However,theassociation of hor- monal therapy with RT dose/volume of the PB is unknown. 8. RECOMMENDED DOSE/VOLUME LIMITS On the basis of the data available, it is prudent to keep the mean dose to 95% of the PB volume to 50 Gy. It may also be prudent to limit the D70 and D90 to 70 Gy and 50 Gy, respec- tively. It is acknowledged that the PB may not be the critical component of the erectile apparatus, but it seems to be a sur- rogate for yet to be determined structure(s) critical for erectile function for at least some techniques. Fig. 2. Incidence of erectile dysfunction according to the radiation dose to the penile bulb. The x axis values are estimated according to the range of doses reported. The data for Fisch et al. (7) at 20, 55, and 80 Gy represent the reported rates of erectile dysfunction at 40, 40–70, and 70 Gy, respectively. Similarly, for Wernicke et al. (14) and Roach et al. (10), each symbol represents the rates of erectile dysfunction at #42 vs. 42 and 52.5 vs. $52.5 Gy, re- spectively. The dashed horizontal lines reflect the dose ranges as- cribed to each data point. The upper x-axis range of the highest data point for Fisch et al. (7) and Roach et al. (10) are unknown. The mean doses of van der Wielen et al. (13) and Mangar et al. (8) are estimated from the subgroup data. The x-axis values for Wer- nicke et al. (14) are D60 and for Fisch et al. (7) are D70 (i.e., min- imum dose received by 60% or 70% volume of the penile bulb). A thick solid line represents the fitted model with sample size correc- tion, with 95% confidence intervals (dotted curves). Radiation effects in penile bulb d M. ROACH III et al. S133
- 134. 9. FUTURE TOXICITYSTUDIES Standard methods to define the PB and associated critical structures should become more widely used. A standard method to score ED should be more widely adopted. System- atic prospective clinical trials that attempt to relate the three- dimensional dose–volume parameters from all of the poten- tially critical structures to clinical outcomes should be con- sidered. Such studies may help to identify which pelvic structures are critical for ED. Dosimetric/imaging studies es- timating uncertainties in the overall accumulated ‘‘true dose distribution’’ should be considered. This may be a key cause of inconsistencies between reported results. Anatomic stud- ies to better define the critical anatomic sites for RT-associ- ated ED may be helpful. Well-characterized data (including full dose distribution and imaging information) should be pooled from multiple studies where possible. 10. TOXICITY SCORING We recommend that patients undergo pre- and post-RT as- sessment of ED using the IIEF. Patients can be grouped into five groups according to their scores; for example, in none (25–22), mild (21–17), mild to moderate (16–12), moderate (11–8), and severe (7–5). It is important that the evaluation of ED is performed with a detailed history including sexual, medical, and psychosocial status and other laboratory tests (3, 17, 26, 27). Further clinical studies may be needed to val- idate the IIEF for the assessment of ED after RT. REFERENCES 1. Sanda MG, Dunn RL, Michalski J, et al. Quality of life and sat- isfaction with outcome among prostate-cancer survivors. N Engl J Med 2008;358:1250–1261. 2. Robinson JW, Moritz S, Fung T. Meta-analysis of rates of erec- tile function after treatment of localized prostate carcinoma. Int J Radiat Oncol Biol Phys 2002;54:1063–1068. 3. Rosen RC, Riley A, Wagner G, et al. The international index of erectile function (IIEF): A multidimensional scale for assess- ment of erectile dysfunction. Urology 1997;49:822–830. 4. Broderick GA. Evidence based assessment of erectile dysfunction. Int J Impot Res 1998;10(Suppl. 2):S64–S73. discussion S77–S69. 5. Brown MW, Brooks JP, Albert PS, et al. An analysis of erectile function after intensity modulated radiation therapy for local- ized prostate carcinoma. Prostate Cancer Prostatic Dis 2007; 10:189–193. 6. Cahlon O, Zelefsky MJ, Shippy A, et al. Ultra-high dose (86.4 Gy) IMRT for localized prostate cancer: Toxicity and biochem- ical outcomes. Int J Radiat Oncol Biol Phys 2008;71:330–337. 7. Fisch BM, Pickett B, Weinberg V, et al. Dose of radiation received by the bulb of the penis correlates with risk of impo- tence after three-dimensional conformal radiotherapy for pros- tate cancer. Urology 2001;57:955–959. 8. Mangar SA, Sydes MR, Tucker HL, et al. Evaluating the rela- tionship between erectile dysfunction and dose received by the penile bulb: Using data from a randomised controlled trial of conformal radiotherapy in prostate cancer (MRC RT01, ISRCTN47772397). Radiother Oncol 2006;80:355–362. 9. Pinkawa M, Gagel B, Piroth MD, et al. Erectile dysfunction af- ter external beam radiotherapy for prostate cancer. Eur Urol 2009;55:227–236. 10. Roach M, Winter K, Michalski JM, et al. Penile bulb dose and impotence after three-dimensional conformal radiotherapy for prostate cancer on RTOG 9406: Findings from a prospective, multi-institutional, phase I/II dose-escalation study. Int J Radiat Oncol Biol Phys 2004;60:1351–1356. 11. Selek U, Cheung R, Lii M, et al. Erectile dysfunction and radi- ation dose to penile base structures: A lack of correlation. Int J Radiat Oncol Biol Phys 2004;59:1039–1046. 12. Skala M, Rosewall T, Dawson L, et al. Patient-assessed late tox- icity rates and principal component analysis after image-guided radiation therapy for prostate cancer. Int J Radiat Oncol Biol Phys 2007;68:690–698. 13. van der Wielen GJ, Hoogeman MS, Dohle GR, et al. Dose-vol- ume parameters of the corpora cavernosa do not correlate with erectile dysfunction after external beam radiotherapy for pros- tate cancer: Results from a dose-escalation trial. Int J Radiat On- col Biol Phys 2008;71:795–800. 14. Wernicke AG, Valicenti R,DiEva K, et al. Radiation dose delivered to the proximal penis as a predictor of the risk of erectile dysfunction after three-dimensional conformal radiotherapy for localized pros- tate cancer. Int J Radiat Oncol Biol Phys 2004;60:1357–1363. 15. Zelefsky MJ, Chan H, Hunt M, et al. Long-term outcome of high dose intensity modulated radiation therapy for patients with clin- ically localized prostate cancer. J Urol 2006;176:1415–1419. 16. Wallner KE, Merrick GS, Benson ML, et al. Penile bulb imag- ing. Int J Radiat Oncol Biol Phys 2002;53:928–933. 17. Rosen RC, Cappelleri JC, Smith MD, et al. Development and evaluation of an abridged, 5-item version of the International In- dex of Erectile Function (IIEF-5) as a diagnostic tool for erectile dysfunction. Int J Impot Res 1999;11:319–326. 18. Weber DC, Bieri S, Kurtz JM, et al. Prospective pilot study of sil- denafil for treatment of postradiotherapy erectile dysfunction in patients with prostate cancer. J Clin Oncol 1999;17:3444–3449. 19. Zelefsky MJ, McKee AB, Lee H, et al. Efficacy of oral sildenafil in patients with erectile dysfunction after radiotherapy for carci- noma of the prostate. Urology 1999;53:775–778. 20. Merrick GS, Butler WM, Wallner KE, et al. The importance of radiation doses to the penile bulb vs. crura in the development of postbrachytherapy erectile dysfunction. Int J Radiat Oncol Biol Phys 2002;54:1055–1062. 21. Macdonald AG, Keyes M, Kruk A, et al. Predictive factors for erectile dysfunction in men with prostate cancer after brachy- therapy: Is dose to the penile bulb important? Int J Radiat Oncol Biol Phys 2005;63:155–163. 22. Goldstein I, Feldman MI, Deckers PJ, et al. Radiation-associ- ated impotence. A clinical study of its mechanism. JAMA 1984;251:903–910. 23. van der Wielen GJ, van Putten WLJ, Incrocci L. Sexual function after three-dimensional conformal radiotherapy for prostate cancer: Results from a dose-escalation trial. Int J Radiat Oncol Biol Phys 2007;68:479–484. 24. Chen CT, Valicenti RK, Lu J, et al. Does hormonal therapy in- fluence sexual function in men receiving 3D conformal radia- tion therapy for prostate cancer? Int J Radiat Oncol Biol Phys 2001;50:591–595. 25. D’Amico AV, Manola J, Loffredo M, et al. 6-month androgen suppression plus radiation therapy vs. radiation therapy alone for patients with clinically localized prostate cancer: A random- ized controlled trial. JAMA 2004;292:821–827. 26. Kratzik CW, Schatzl G, Lunglmayr G, et al. The impact of age, body mass index and testosterone on erectile dysfunction. J Urol 2005;174:240–243. 27. Rosenberg MT. Diagnosis and management of erectile dysfunction in the primary care setting. Int J Clin Pract 2007;61:1198–1208. S134 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 135. QUANTEC: VISION PAPER ACCURATEACCUMULATION OF DOSE FOR IMPROVED UNDERSTANDING OF RADIATION EFFECTS IN NORMAL TISSUE DAVID A. JAFFRAY, PH.D.,* PATRICIA E. LINDSAY, PH.D.,* KRISTY K. BROCK, PH.D.,* JOSEPH O. DEASY, PH.D.,y AND W. A. TOME´, PH.D.z From the *Radiation Medicine Program, Princess Margaret Hospital, Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; y Department of Radiation Oncology, Washington University, St. Louis, MO; and z Departments of Human Oncology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI The actual distribution of radiation dose accumulated in normal tissues over the complete course of radiation ther- apy is, in general, poorly quantified. Differences in the patient anatomy between planning and treatment can occur gradually (e.g., tumor regression, resolution of edema) or relatively rapidly (e.g., bladder filling, breathing motion) and these undermine the accuracy of the planned dose distribution. Current efforts to maximize the therapeutic ratio require models that relate the true accumulated dose to clinical outcome. The needed accuracy can only be achieved through the development of robust methods that track the accumulation of dose within the various tissues in the body. Specific needs include the development of segmentation methods, tissue-mapping algorithms, uncer- tainty estimation, optimal schedules for image-based monitoring, and the development of informatics tools to sup- port subsequent analysis. These developments will not only improve radiation outcomes modeling but will address the technical demands of the adaptive radiotherapy paradigm. The next 5 years need to see academia and industry bring these tools into the hands of the clinician and the clinical scientist. Ó 2010 Elsevier Inc. Dose accumulation, Normal tissue effects, Deformation, Four-dimensional, Informatics. THE DOSE DELIVERED Continued advances in clinical practice demonstrate that there is more work to be done both in terms of the accuracy of dose computation methods and the accurate accumulation of dose in the dynamic anatomy of the human body. In addi- tion to reducing the volume irradiated to therapeutic levels, imaging and targeting technologies are highlighting the dy- namic nature of patient anatomy over the course of therapy (1, 2). Leaving aside the difficulty of mapping tumor regres- sion, investigators have established the potential to estimate the ‘‘true dose’’ or DA to any volume of normal tissue applied over the course of therapy (3, 4) with numerous studies dem- onstrating the degree of dose variation that is occurring over the course of therapy in normal structures (5, 6). It has thus been established that ‘‘planned dose’’ does not necessarily equal ‘‘delivered dose’’ for any given fraction or for the treat- ment as a whole. Moreover, changes in tumor and normal tis- sue during therapy suggest that the ultimate quantity of interest is DA—particularly for normal tissues. Remarks above notwithstanding, radiation oncology is a leader among medical disciplines with respect to the clear and quantitative specification of intervention, and the dili- gence pursued in the assurance that the therapy is accurately delivered (7, 8). Despite this level of consistency in dose de- livery, remarkable variations in normal tissue response re- main. Of course, there may also be variations in intrinsic radiosensitivity that dictate these outcomes; however, dose variation is known to affect response. This has led to the hy- pothesis that patient-specific estimates of DA over the course of therapy can predict, in part, for patient-specific variations in normal tissue toxicity. Testing of this hypothesis requires the development of accurate and precise methods for dose ac- cumulation within the human body in the presence of ana- tomical and morphological changes. Remarkably, a review of the literature suggests that this is not an insurmountable task, but requires a focused activity within the community if the hypothesis is to be tested for clinically important end- points. Moreover, only careful studies that include estimates of DA will allow us to confidently disentangle the effects of dosimetry and radiobiological sensitivity. Reprint requests to: David A. Jaffray, Ph.D., Radiation Medicine Program, Princess, Margaret Hospital, 610 University Ave., Tor- onto, Ontario, Canada M5G2M9. Tel: (416) 946-2387; Fax: (416) 946-6566; E-mail: david.jaffray@rmp.uhn.on.ca Conflict of interest: None. Acknowledgment—This article was derived from discussions held at the QUANTEC conference in Madison, Wisconsin, in November 2007. Discussion participants included: A. Eisbruch, J. Galvin, A. Hope, D.A. Jaffray, T.R. Mackie, W. Tome, J. Van Dyk, and E. Yorke. Received March 13, 2009, and in revised form June 27, 2009. Accepted for publication June 29, 2009. S135 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S135–S139, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.06.093
- 136. TOWARD ACCURATE DOSEESTIMATION The necessary elements to achieve routine determination of DA include: (1) a time-dependent description of the patient anatomy and treatment parameters over the course of therapy, (2) a method to calculate the dose applied at each of those time points, and (3) the ability to generate a cumulative deliv- ered dose distribution over the course of therapy for each small (few mm3 ) subvolume of tissue. It should be noted that these elements set aside the additional complexity asso- ciated with iatrogenic cell or fluid loss over the course of ther- apy - a largely ignored complexity in this context. Time-dependent descriptors of the patient anatomy and treatment Volumetric imaging (computed tomography [CT], mag- netic resonance [MR], positron emission tomography) and three-dimensional treatment planning are now elements of routine care in radiation oncology. The adoption of inverse planning techniques for intensity-modulated radiation ther- apy has also driven the creation of standard protocols for con- touring and segmentation (9), as well as the continuing development of automated segmentation tools in the treat- ment planning domain (10). The development of time-depen- dent associations of anatomical structures is also being pursued to assist in the segmentation of time-course studies (11, 12). In addition to advances in imaging and segmenta- tion for simulation, image-guidance technologies at the time of treatment are being employed for directing therapy. Current systems, such as kV and megavoltage cone-beam CT, megavoltage CT, and, in the future, MR imaging, while assuring geometric targeting of the tumor, also provide a po- tential wealth of valuable information about the patient’s nor- mal anatomy. Thus, it is now possible to have an image-based record of the relevant anatomy at each fraction of the treatment. However, this valuable imaging information will only con- tribute to dose record activities if effective, automated seg- mentation methods are developed to address the laborious nature of manual segmentation. The development of model-based approaches to segmentation is congruent with an important trend toward the adoption of structured descrip- tions or atlases of patient anatomy. Further efforts in this area do not need to be overly complex, but, rather, rigorous and unifying (13, 14). For example, the failure to develop stan- dards for contouring of relevant anatomy (e.g., inner and outer wall of rectum, or superior/inferior extent of rectum) continues to confound inter-institutional comparisons as well as intra-institutional standardization. In addition to image-based descriptions of the patient anat- omy, developments in intensity-modulated radiation therapy have required the use of electronic descriptions of the de- tailed treatment parameters (e.g., DICOM-radiation therapy control points) that are stored within the electronic medical record and verified at each treatment fraction. In combination with the guidance images, the records provide a highly descriptive account of the treatment from which DA could be accurately determined, provided image-guidance adjust- ments are recorded, the machine is operating within specified tolerances, and accurate dose calculation methods are available. Improvements in the accuracy of dose calculation Accurately accounting for tissue heterogeneities is funda- mental to improving the modeling and prediction of dose– volume effects in radiation therapy. The accuracy of a calcu- lated dose distribution is strongly dependent on the algorithm used to account for heterogeneities (15, 16). Monte Carlo methods, which can model the transport of radiation through all the components of the treatment unit head, as well as through the CT-based patient geometry, represent the gold standard of dose calculations (17, 18). The use of Monte Carlo dose calculations for research studies prospectively and even retrospectively is growing (19, 20). The benefits of which are expected to be realized in regions of substantial tissue heterogeneity (e.g., for lung or head-and-neck treat- ments), as well as in low dose (21) or out-of-field regions (22). Despite calculation advances, currently used dose–vol- ume constraints are typically based on data largely calculated either without any accounting for tissue heterogeneities, or using very simple methods (23–25). The impact of heteroge- neity corrections, or the type of heterogeneity corrections, on the dose–volume analysis of treatment outcomes is poorly studied. Recent work shows that tumor control probability modeling was affected by the underlying dose calculation ac- curacy (retrospective Monte Carlo–based corrections vs. path-length based corrections) (26). As its use propagates, proton therapy will not only alter the dose to normal tissues and contribute to our understanding of dose–volume effects, but also highlight the dose computation challenges that re- main for this technology (27). Development of tissue deformation and tracking tools The development and validation of deformable registration algorithms has enabled tracking of mobile tissues over the treatment course and, in some cases, during the treatment frac- tion. Tissue deformation tracking can improve the accuracy of DA for both the target volume and the critical normal tissues. Validation of these methods is typically achieved using intrin- sic features (e.g., bifurcations in blood vessels) or fiducials (e.g., gold markers) that can be confidently localized and com- pared with the deformation estimate of displacement (28, 29). The lung presents a unique challenge as the volume changes substantially between inhale and exhale. Studies have inves- tigated the effect of different interpolation methods on the accumulation of dose with changes in volumes (30). Using four-dimensional cone beam CT images (31) or, in the future, dynamic MR imaging (32), obtained at each treatment frac- tion should improve the accuracy of the DA distribution by modeling the breathing motion and the residual setup uncer- tainties that cannot be accounted for with simple couch corrections. Geometric tracking of tissue over the course of treatment becomes increasingly difficult in the presence of large changes in tissue volume (33, 34). Ultimately, the S136 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 137. deformation algorithms needto address challenges such as, hollow organs (bladder, rectal wall, small bowel), changes in volume (e.g., liver), varying organ substructure (e.g., lobes of liver and lung), and, mechanical perturbations brought about by the disease (cancer or comorbidity). OPPORTUNITIES AND NEEDS Robust and streamlined methods for accurate accumulation of dose As described previously, the literature demonstrates the feasibility of generating a record of DA. However, significant labor is currently required to perform these studies. Contour- ing and segmentation methods need to be developed that al- low these activities to be pursued at reasonable workloads, preferably in a proactive fashion during the course of therapy, even on a fraction-by-fraction basis. This level of perfor- mance would integrate dose accumulation into the patient management workflow and also enable online planning activities. Visual and quantitative summaries of the segmen- tation results should be made available. These should require a minimum of effort to evaluate through efficient access (e.g., web-based) and work list management. Advancing the performance of deformation modeling re- quires both additional information and the creation of quan- titative tools. The development of novel image-based methods of measuring deformation and the underlying me- chanical characteristics of normal and diseased tissues should be pursued. The trend toward high dose per fraction stereo- tactic body radiation therapy will heighten risks associated with occasional anatomical displacements. The development of multiorgan system deformation models and dose tracking will become of greater importance in these areas as the field pushes for broader application of stereotactic body radiation therapy methods. The validation of these more complex sys- tems will require both the development of phantoms that re- flect realistic anatomical changes and the collection/sharing of large deformation datasets that contain ‘‘ground truth’’ es- timates of the deformation. In the development and publica- tion of these methods, investigators should clearly specify the documented performance of their algorithms and the condi- tions under which the algorithms are not likely to perform well (e.g., volume change, slipping surfaces). Development of novel dosimetry systems for validation of dose calculations The validation of these dose tracking methods and the as- surance of their performance over a range of spatial scales should also be a priority for the field. Recent advances in do- simeter technologies, such as implanted metal-oxide-semi- conductor field-effect transistor MOSFET detectors (35), optical point (36), and volumetric methods (37), MR-based gel technologies (38), and carbon-nanotube approaches (39, 40) offer the promise of validating accumulated delivered dose distribution in phantoms or patients. Incorporating de- formation and dose validation phantoms (41) is likely to be necessary to evaluate the end-to-end performance of these systems. Novel metrics for characterizing dose estimation accuracy and precision Dose accumulation methods will always be imperfect due to challenges of calculation in complex geometries (e.g., het- erogeneities in atomic number), absence of imaging data to describe the geometry of the patient (e.g., missing volumes or motion that exceeds the sampling rate), or weaknesses in the machine model being employed. DA estimates need to be accompanied by companion uncertainty estimates. The development of methods to describe confidence intervals on the dose and volume data could be used to extract higher quality sub-datasets from patient studies and ask more spe- cific questions. Furthermore, sensitivity analyses could be applied to estimate the dose uncertainty corresponding to these various conditions and would be a valuable input to out- comes modeling activities. It should be noted that even sim- ple parameters, such as weight loss, patient treatment protocol (e.g., use of bowel preparation in prostate cases to understand the degree of variation rectal dose delivered), or the use of heterogeneity corrections in the dose calculation would all represent important qualifiers of the four-dimen- sional dose record. Uncertainty analysis should not be restricted to the dose accumulation activity. The development of predictive schemes that estimate the uncertainties in the planned dose distribution would also be of value to the field. These calcu- lations would require, however, the establishment of a model and database of geometric uncertainties (systematic and ran- dom components; potential trends; both target and normal structures) for the patient population and treatment facility to which the individual patient corresponds. It is reasonable that such a tool would be integrated within the planning sys- tems architecture and the resulting uncertainties recorded in the electronic treatment planning records for subsequent con- sideration in outcomes analysis. Dose and volume as a predictive factor in multivariate analyses It is known that other factors, besides dose, are crucial to an understanding of outcome variability. Advances in our un- derstanding of molecular biology and the development of ge- nomic and proteomic analyses of patient tissue carry significant promise (42). However, depending on the relative scale of these effects, it may not be possible to isolate such a dependence in the presence of large undocumented varia- tions in another important variable, such as DA (43). The link- age between simple variables such as dose and volume have been demonstrated to correlate with proteomic assays col- lected during radiation therapy (44). Maximizing sensitivity for biomarker validations will require accurately controlling for the differences between ‘‘certain dose distributions’’ and ‘‘uncertain dose distributions,’’ as measured along a con- tinuum. The ability to routinely follow patient cohorts with precise and accurate dose tracking is thus a prerequisite for Improving dose estimation in normal tissues d D. A. JAFFRAY et al. S137
- 138. fully benefiting fromgenomic and proteomic studies of nor- mal tissue radiosensitivity. Hence, these records need to be of sufficient flexibility to allow complex volume (alternative structures [e.g., portions of the lung]) and time dependent ef- fects (e.g., variations in dose rate across intensity-modulated radiation therapy practice) to be integrated into the analysis. SUMMARY The goal of generating accurate DA distributions to target and normal tissues as a part of routine radiotherapy practice is feasible. However, key research and development areas need to be accelerated, including: auto-segmentation, defor- mation modeling, dose accumulation, dose calculation in complex environments, and methods of estimating the uncer- tainty in the accumulated dose distribution over the course of therapy. In addition to these research initiatives, informatics developments are necessary to make the tracking of dose a feasible and viable activity, including, support for workflow tools that allow automated image segmentation and dose ac- cumulation with efficient review and validation. Finally, the efforts will not succeed without a corresponding level of in- vestment in the leadership required to formulate standardized methods and nomenclature to allow the volumetric results to be compared in a direct and productive fashion. It should go without saying that accomplishing the goal of accurate nor- mal tissue dose response would also assist in tumor dose-re- sponse characterization, provide methods for adaptive approaches, and eliminate a confounding variable in studies of individualized normal tissue radiosensitivity. Accurately estimating DA is a critical element in the drive to maximize the performance and safe application of radiation therapy for the individual patient. REFERENCES 1. Kutcher GJ, Mageras GS, Leibel SA. Control, correction, and modeling of setup errors and organ motion. Seminars in Radia- tion Oncology 1996;5:134. 2. Langen KM, Jones DT. Organ motion and its management. Int J Radiat Oncol Biol Phys 2001;50:265–278. 3. Keall PJ, Beckham WA, Booth JT, et al. A method to predict the effect of organ motion and set-up variations on treatment plans. Australas Phys Eng Sci Med 1999;22:48–52. 4. Yan D, Jaffray DA, Wong JW. A model to accumulate fraction- ated dose in a deforming organ. Med Phys 1999;44:665. 5. Bos LJ, van der Geer J, van Herk M, et al. The sensitivity of dose distributions for organ motion and set-up uncertainties in prostate IMRT. Radiother Oncol 2005;76:18–26. 6. O’Daniel JC, Garden AS, Schwartz DL, et al. Parotid gland dose in intensity-modulated radiotherapy for head and neck can- cer: is what you plan what you get? Int J Radiat Oncol Biol Phys 2007;69:1290–1296. 7. ICRU50. ICRU report 50: Prescribing, recording, and reporting photon beam therapy. Bethesda, Maryland: International Com- mission on Radiation Units and Measurements; 1993. 8. ICRU62. ICRU report 62: Prescribing, recording, and reporting photon beam therapy (Supplement to ICRU Report 50). Be- thesda, MD, USA: International Commission on Radiation Units and Measurements; 1999. 9. Gregoire V, De Neve W, Eisbruch A, et al. Intensity-modulated radiation therapy for head and neck carcinoma. Oncologist 2007;12:555–564. 10. Pekar V, McNutt TR, Kaus MR. Automated model-based organ delineation for radiotherapy planning in prostatic region. Int J Radiat Oncol Biol Phys. 2004;60:973–980. 11. Ezhil M, Starkschall G, Mohan R, et al. Validation of a model- based segmentation approach to propagating normal anatomic regions of interest through the 10 phases of respiration. Int J Ra- diat Oncol Biol Phys 2008;71:900–906. 12. Wang H, Garden AS, Zhang L, et al. Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-di- mensional computed tomography images using deformable im- age registration method. Int J Radiat Oncol Biol Phys 2008;72: 210–219. 13. Kim JJ, Breen SL, Aj Waldron, et al. A Standardized Nomen- clature System for Head and Neck (HN) IMRT Contouring, Planning and Quality Assurance. Int J Radiat Oncol Biol Phys 2007;70. S473. 14. Gregoire V, Coche E, Cosnard G, et al. Selection and delinea- tion of lymph node target volumes in head and neck conformal radiotherapy. Proposal for standardizing terminology and pro- cedure based on the surgical experience. Radiother Oncol 2000;56:135–150. 15. Papanikolaou N, Battista J, Boyer A, et al. AAPM Report No. 85: Tissue inhomogeneity corrections for megavoltage photon beams. Madison, WI: Medical Physics Publishing; 2004. 16. Ahnesjo A, Aspradakis MM. Dose calculations for external pho- ton beams in radiotherapy. Phys Med Biol 1999;44:R99–155. 17. Verhaegen F, Seuntjens J. Monte Carlo modelling of external radiotherapy photon beams. Phys Med Biol 2003;48:R107– R164. 18. Chetty IJ, Curran B, Cygler JE, et al. Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treat- ment planning. Med Phys 2007;34:4818–4853. 19. Lindsay PE, El Naqa I, Hope AJ, et al. Retrospective monte carlo dose calculations with limited beam weight information. Med Phys 2007;34:334–346. 20. Stroian G, Martens C, Souhami L, et al. Local Correlation Be- tween Monte-Carlo Dose and Radiation-Induced Fibrosis in Lung Cancer Patients. Int J Radiat Oncol Biol Phys 2008;70: 921–930. 21. Jang SY, Liu HH, Mohan R. Underestimation of low-dose radi- ation in treatment planning of intensity-modulated radiother- apy. Int J Radiat Oncol Biol Phys 2008;71:1537–1546. 22. Kry SF, Titt U, Followill D, et al. A Monte Carlo model for out- of-field dose calculation from high-energy photon therapy. Med Phys 2007;34:3489–3499. 23. Bradley J, Graham MV, Winter K, et al. Toxicity and outcome results of RTOG 9311: A phase I-II dose-escalation study using three-dimensional conformal radiotherapy in patients with inop- erable non-small-cell lung carcinoma. Int J Radiat Oncol Biol Phys 2005;61:318–328. 24. Kwa SLS, Lebesque JV, Theuws JCM, et al. Radiation pneumonitis as a function of mean lung dose: an analysis of pooled data of 540 patients. Int J Radiat Oncol Biol Phys 1998;42:1–9. 25. Emami B, Lyman J, Brown A, et al. Tolerance of normal tissue to therapeutic irradiation. Int J Radiat Oncol Biol Phys 1991;21: 109–122. 26. Mu Y, Hope A, Lindsay P, et al. Statistical Modelling of Tumor Control Probability for Non-small-cell Lung Cancer Radiother- apy. Int J Radiat Oncol Biol Phys 2008;72. S448. 27. Goitein M. Magical protons? Int J Radiat Oncol Biol Phys 2008;70:654–656. S138 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 139. 28. Kashani R,Hub M, Balter J, et al. Objective Assessment of De- formable Image Registration in Radiotherapy: A Multi-Institu- tional Study. Med Phys 2008;35:5944–5953. 29. Brock KK. A Multi-Institution Deformable Registration Accu- racy Study. Int J Radiat Oncol Biol Phys (Abstract) 2007;69. S44. 30. Rosu M, Chetty IJ, Balter JM, et al. Dose reconstruction in de- forming lung anatomy: dose grid size effects and clinical impli- cations. Med Phys 2005;32:2487–2495. 31. Sonke JJ, Zijp L, Remeijer P, et al. Respiratory correlated cone beam CT. Med Phys 2005;32:1176–1186. 32. Raaymakers BW, Raaijmakers AJ, Kotte AN, et al. Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose de- position in a transverse magnetic field. Phys Med Biol 2004;49: 4109–4118. 33. Siker ML, Tome WA, Mehta MP. Tumor volume changes on serial imaging with megavoltage CT for non-small-cell lung cancer during intensity-modulated radiotherapy: How reliable, consistent, and meaningful is the effect? Int J Radiat Oncol Biol Phys 2006;66:135–141. 34. Kupelian PA, Ramsey C, Meeks SL, et al. Serial megavoltage CT imaging during external beam radiotherapy for non-small- cell lung cancer: observations on tumor regression during treat- ment. Int J Radiat Oncol Biol Phys 2005;63:1024–1028. 35. Scarantino CW, Ruslander DM, Rini CJ, et al. An implantable radiation dosimeter for use in external beam radiation therapy. Med Phys 2004;31:2658–2671. 36. Rink A, Vitkin IA, Jaffray DA. Suitability of radiochromic me- dium for real-time optical measurements of ionizing radiation dose. Med Phys 2005;32:1140–1155. 37. Oldham M, Siewerdsen JH, Kumar S, et al. Optical-CT gel-dosimetry I: basic investigations. Med Phys 2003;30: 623. 38. McJury M, Oldham M, Cosgrove VP, et al. Radiation dosimetry using polymer gels: methods and applications. Br J Radiol 2000;73:919–929. 39. Sinha N, Ma J, Yeow JT. Carbon nanotube-based sensors. J Nanosci Nanotechnol 2006;6:573–590. 40. Sinha N, Yeow JT. Carbon nanotubes for biomedical applica- tions. IEEE Trans Nanobioscience 2005;4:180–195. 41. Kashani R, Hub M, Kessler ML, et al. Technical note: a physical phantom for assessment of accuracy of deformable alignment algorithms. Med Phys 2007;34:2785–2788. 42. Rosen EM, Fan S, Rockwell S, et al. The molecular and cellular basis of radiosensitivity: implications for understanding how normal tissues and tumors respond to therapeutic radiation. Cancer Invest 1999;17:56–72. 43. Bentzen SM. From cellular to high-throughput predictive as- says in radiation oncology: challenges and opportunities. Semin Radiat Oncol 2008;18:75–88. 44. Menard C, Johann D, Lowenthal M, et al. Discovering clinical biomarkers of ionizing radiation exposure with serum proteo- mic analysis. Cancer Res 2006;66:1844–1850. Improving dose estimation in normal tissues d D. A. JAFFRAY et al. S139
- 140. QUANTEC: VISION-PAPER IMAGING FORASSESSMENT OF RADIATION-INDUCED NORMAL TISSUE EFFECTS ROBERT JERAJ, PH.D.,* YUE CAO, PH.D.,y RANDALL K. TEN HAKEN, PH.D.,y CAROL HAHN, M.D.,z AND LAWRENCE MARKS, M.D.zx *University of Wisconsin, Madison, WI; y University of Michigan, Ann Arbor, MI; z Duke University, Durham, and x University of North Carolina, Chapel Hill, NC Imaging can provide quantitative assessment of radiation-induced normal tissue effects. Identifying an early sign of normal tissue damage with imaging would have the potential to predict organ dysfunction, thereby allowing reoptimization of treatment strategies based on individual patients’ risks and benefits. Early detection with noninvasive imaging may enable interventions to mitigate therapy-associated injury before its clinical manifesta- tion. Furthermore, successive imaging may provide an objective assessment of the impact of such mitigation ther- apies. However, many problems make application of imaging to normal tissue assessment challenging, and further work is required to establish imaging biomarkers as surrogate endpoints of clinical outcome. The performance of clinical trials in which normal tissue injury is a clearly defined endpoint would greatly aid in realization of these goals. Ó 2010 Elsevier Inc. Normal tissue effects, Imaging, Biomarker. INTRODUCTION Radiation therapy (RT) may induce local tissue damage that in turn, depending on the severity and the volume affected, may lead to organ dysfunction (Fig. 1). Organ dysfunction may be clinical (symptomatic) or subclinical (asymptomatic). When imaging to assess normal tissue effects is quantitative, it can represent a useful imaging biomarker (Fig. 1). Imaging biomarkers are closely connected with anatomic, physio- logic, and molecular changes that characterize the radia- tion-induced tissue damage or organ dysfunction. However, only when imaging biomarkers are correlated to clinical end- points can they become surrogate endpoints of clinical injury (Fig. 1). Identifying an early sign of normal tissue damage with imaging would have the potential to predict organ dys- function, thereby allowing reoptimization of treatment strat- egies based on individual patients’ risks and benefits. However, some imaging biomarkers may prove to be overly sensitive and too nonspecific to be useful as surrogate end- points. Understanding of underlying pathophysiology of normal tissue damage and the associated molecular and cellular pro- cesses that lead to long-term effects such as cell death and ap- optosis can help identify precursors of organ dysfunction, which can be explored as potential imaging biomarkers (1). However, because knowledge of the normal tissue effects is incomplete, choice of imaging biomarkers is often prag- matic, and markers may be identified without researchers un- derstanding the underlying molecular mechanisms. Even with incomplete understanding of underlying biology, imag- ing biomarkers may be successfully used as surrogate end- points of clinical injury. In addition, they may help to elucidate the spatial and temporal development of underlying molecular processes that drive RT associated injury. Choos- ing imaging techniques that are sensitive to early biological processes of normal tissue damage is important. Acute and late normal tissue injury occurs from a complex interaction between radiation-induced death of parenchymal cells, damage to the supporting vasculature, and associated inflammatory and fibrotic reactions. Long-term depletion of tissue-specific stem cells or progenitor cells can lead to fibro- sis, organ dysfunction, and necrosis (1). This interaction be- tween basic cellular and molecular process and physiologic expression divides imaging assessment into two distin- guished biological levels: (1) imaging of anatomic (struc- tural) changes in affected organs and (2) imaging of functional, molecular, and cellular processes of RT-induced injury. Topics related to these assessments and the potential for further research are discussed here. Address reprint requests to: Robert Jeraj, Ph.D., Department of Medical Physics, University of Wisconsin, 1005 Wisconsin Insti- tutes for Medical Research, 1111 Highland Avenue, Madison, WI 53705. Tel: (608) 263-8619; Fax: (608) 262-2413; E-mail: rjeraj@wisc.edu Conflict of interest: No conflicts of interest noted. Received Feb 9, 2009, and in revised form Aug 10, 2009. Accepted for publication Aug 13, 2009. S140 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S140–S144, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.08.077
- 141. CURRENT APPROACHES ANDSTATUS OF NORMAL TISSUE TOXICITY IMAGING Anatomical imaging Radiation therapy commonly causes changes that can be detected by planar X-ray or CT imaging. For example, in pa- tients treated for lung or breast cancer, approximately 50%– 100% and 0%–63%, respectively, have radiologic evidence of lung damage via chest X-ray (CXR) or CT (2). These changes in imaging, however, do not necessarily correlate well with symptomatic injury. Similarly, in the liver, radio- logic changes are often evident post-RT either before or in the absence of clinical symptoms (3, 4). Post-RT CT and MRI can detect nonspecific morphologic abnormalities in the brain that may reflect RT-induced tumor or normal tissue inflammation/necrosis or surgery-induced changes (e.g., en- hancement along the resection margin) (5). A principal limi- tation of defining injury in this manner is that injury is often identified months to years following RT when any opportu- nity to intervene to ameliorate the effects has likely been lost. Functional and molecular imaging Functional imaging may provide an in vivo model of RT effects on both tumors and normal tissues. The potential ad- vantage of functional and molecular imaging over anatomic imaging is that it may be more physiologically and clinically important and may better reflect underlying pathophysiologic processes. Many functional and molecular imaging modali- ties have been used to monitor normal tissue responses, the most common being fluorodeoxyglucose positron emission tomography (FDG-PET), although other isotopes have also been used (e.g., 15 O for monitoring of blood flow changes). Single photon emission computed tomography (SPECT) is often used to measure perfusion but can also be used to image radiolabeled receptors overexpressed in certain tumors. MRI has become useful to assess functional metrics such as re- gional perfusion (i.e., in the heart), ventilation (i.e., in the lung), and metabolic states (i.e., with MR spectroscopy). Functional MRI (fMRI) has the ability to assess regional brain activity in response to stimuli. Data for several organ systems such as lung (6–8), heart (9–13), liver (14, 15), brain (16–19), and parotid (20, 21) have already revealed correla- tions of radiation dose with changes measurable by a variety of functional imaging modalities. OPPORTUNITY AND FUTURE FOR NORMAL TISSUE TOXICITY IMAGING Imaging as a precursor of injury manifestation A large body of converging evidence, from histopathol- ogy, molecular biology, animal models, and clinical observa- tions, suggests that RT-induced normal tissue injury is a dynamic and progressive process (1, 22). Given that it is ex- tremely difficult to obtain human normal tissue after irradia- tion for histological and biological analysis and for longitudinal examination, it is important to establish in vivo functional and molecular imaging as a biomarker for early as- sessment and prediction of delayed or late organ dysfunction. Preclinical experiments, which can provide unique data on normal tissue injury dynamics, can be extremely helpful in this process (23, 24). Identifying an early sign or precursor of normal tissue damage, e.g., during or shortly after the course of fractionated RT, could predict the delayed organ dysfunction. For exam- ple, cardiac functional imaging may allow for early detection of treatment-associated dysfunction. This is particularly im- portant because these changes often do not manifest clini- cally for at least 10 years posttreatment (25). In patients treated for breast cancer, SPECT can detect myocardial per- fusion defects in the irradiated left ventricle that are associ- ated with wall motion abnormalities. However, there are no systematic changes in either ejection fraction or clinical car- diac events. Similarly, although SPECT lung perfusion imag- ing has been used quantitatively to relate changes in regional perfusion/ventilation (e.g., function) to the regional radiation dose (6–8), there is limited correlation between the sum of these regional injuries (i.e., the integrated response) and changes in global lung function (e.g., pulmonary function tests). Changes in MRI-defined gadolinium enhancement ki- netics may be associated with different phases of radiation pneumonitis (26). Similarly, abnormalities in FDG-PET studies may relate to symptomatic pneumonitis and provide an objective measure of interpatient variability of biological response (27–29). Reoptimization of treatment strategies on the basis of indi- vidual patients’ risks and benefits is another area that could benefit from normal tissue toxicity imaging. For example, the basic pathophysiology of RT-induced liver disease is ve- nous occlusion. Symptoms generally occur 2 weeks to 2 months following completion of RT, and the clinical out- come ranges from mild, reversible damage to death. There- fore, early monitoring of venous perfusion would have the potential to select patients with preclinical signs of perfusion changes before the onset of symptomatic RT-induced injury. It has been shown that the reduction in regional portal venous perfusion during the course of radiation therapy and local dose distribution in the liver are two independent predictors Local tissue damage Clinical Normal tissue effects IMAGING Imaging biomarker as a surrogate endpoint Imaging biomarker Subclinical Manifestation Organ dysfunction Imaging as a biomarker ResolutionLocal tissue damage IMAGING Imaging biomarker as a surrogate endpoint Imaging biomarker Organ dysfunction Fig. 1. Relation between normal tissue effects and their clinical manifestation and role of imaging to assess the effects. Imaging for assessment of normal tissue effects d R. JERAJ et al. S141
- 142. for regional portalvenous perfusion dysfunction 1 month post-RT (14). Furthermore, it has been demonstrated that the regional liver venous perfusion dysfunction is associated with overall liver function (30). An alternative reoptimization strategy could be reoptimization of irradiation geometry based on local normal tissue damage (31); however, it is questionable whether the changes would be detectable early enough to allow modification of already started treatment regimen. Imaging as a biomarker Imaging biomarkers are characteristics that can be objec- tively imaged as indicators of normal biological processes, pathogenic processes, or pharmacologic responses to thera- peutic interventions. Imaging biomarkers as surrogate end- points are imaging biomarkers that are intended to substitute for clinical endpoints. Surrogate endpoints are expected to predict clinical benefit (or harm or lack of benefit or harm) based on epidemiologic, therapeutic, pathophysio- logic, or other scientific evidence. Imaging biomarkers should be discussed in the context of molecular biomarkers, which are described in detail else- where (see Bentzen et al., this issue). Molecular biomarkers have biophysical properties, which allow their measurements in biological samples, such as plasma, serum, cerebrospinal fluid, or biopsy samples. Molecular biomarkers can detect molecular and cellular changes with high sensitivity but might not be very specific. For example, the hematocrit or other blood counts can be a sensitive measure of marrow function. However, they can also be affected by dysfunction caused by other conditions (e.g., bowel disease or malnutrition affecting hematocrit). Further, molecular markers lack spatial informa- tion. Thus, they may be useful in the realm of whole organ irradiation (e.g., blood counts for total body irradiation or liver function tests for whole liver irradiation) but may not be sensitive for regional organ effects. Similar limitations hold for molecular biomarkers obtained from biopsy samples, which sample only few points in the organ, thus being unable to assess the regional organ response heterogeneity. On the contrary, imaging has the unique potential for detecting the spatial distribution of the tissue damage that can lead to organ dysfunction. Common to imaging and molecular biomarkers (32) is that they may beused to identify patients at increased or decreased risk for radiation treatment-related injury. In some settings, imaging and molecular biomarkers may be synergis- tic, and their combined use may overcome inherent limita- tions of each single approach, thereby increasing overall sensitivity and specificity of the assessment. Multiple obstacles lie in the path toward establishment of imaging biomarkers as surrogate endpoints for assessment and prediction of clinical injury. Challenges for quantitative imaging are discussed in the next section. Other obstacles in- clude unknown temporal dynamics of RT-induced injury, un- derstanding of normal biology, and the relationship between early normal tissue damage and late symptomatic organ dys- function. In addition, RT is often combined with chemother- apy and molecular targeted therapies; normal tissue toxicity can result from either modality separately or through a syner- gistic effect of combined therapies. New knowledge about the mechanisms of normal tissue toxicity and potential inhi- bition of the effects, for example, with anti-inflammatory compounds (e.g., inhibitors of prostaglandin and leukotriene formation, NFkB and interleukin [IL]-1 signaling) might sig- nificantly affect RT-induced toxicity management. Monitor- ing induction, resolution, and mitigation of radiation-induced toxicity will be essential in the development of clinically suc- cessful normal tissue preserving strategies. Molecular imag- ing might be particularly useful to study and monitor these changes. However, much work still needs to be done before relevant molecular probes are developed to explore fully the potential that molecular imaging offers for questions relevant to human clinical imaging. Need for quantitative imaging of normal tissue toxicity Imaging modalities and techniques, primarily developed with clinical diagnostic application in mind, are often not quantitative enough to raise imaging to the level of a bio- marker. Imaging, although it has a quantitative physical ba- sis, is often burdened with significant uncertainties, preventing characterization of small changes that are charac- teristic of moderate normal tissue injury. It is important that quantification is ensured through the whole procedure— from image acquisition and image reconstruction to image analysis. The assessment of imaging as either a biomarker or surrogate endpoint also requires quantitative clinical end- points. However, whereas imaging endpoints are usually continuous, most clinical endpoints are dichotic. Using a con- tinuous variable for measurement of an organ function or stage of injury could improve statistical power for correlative analysis relating imaging to clinical events, thereby reducing the number of patients required for studies. Although qualita- tive diagnostic imaging does not carry the same value as quantitative imaging, it can be useful in the diagnosis of nor- mal tissue effects (e.g., esophageal stricture seen on barium swallow, cerebral edema, on CT/MRI). Clearly, these problems call for a wide cooperative effort among various governmental, professional, and industrial en- tities. Some of these efforts have already begun. Initial efforts started within individual professional societies: Radiological Society of North America, American College of Radiology, American Association of Physicists in Medicine, Society of Nuclear Medicine, International Society for Magnetic Reso- nance in Medicine; however, it was soon realized that the problems are too significant to be solved by a single profes- sional society. The first organized effort was initiated by Na- tional Cancer Institute (NCI) and Association of American Cancer Institutes in 2003. It lead to the formation of Image Response Assessment Teams (IRAT) with the purpose to fa- cilitate development of multidisciplinary teams in NCI-des- ignated comprehensive cancer centers to advance the role of imaging in assessment of response to therapy. The IRAT project’s primary objective was to increase collaboration be- tween imaging scientists and oncology investigators to en- hance the use of quantitative anatomic, functional, and S142 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 143. molecular imaging endpointsin clinical therapeutic trials. The IRAT initiative is currently being augmented with the ef- forts within Clinical and Translational Science Award, partic- ularly the Imaging Working Group. The second large effort was a workshop, ‘‘Imaging as a Biomarker: Standards for Change Measurements in Therapy,’’ organized by National Institute of Standards and Technology in 2006. It included the U.S. Food and Drug Administration, Pharmaceutical Re- search and Manufacturers of America, National Institutes of Health, academia, and societies. Key summary points from this workshop were the following: (1) variability is too high in the multicenter trials that use imaging, (2) standards for imaging clinical trials are lacking, and (3) sharing of im- aging data is inadequate partially because of insufficient in- frastructure and underdeveloped processes. In 2008, the Quantitative Imaging Biomarkers Alliance between drug and equipment industries and imaging societies has been formed to develop and advance standards for the use of vol- umetric CT, FDG-PET, and DCE-MRI in clinical trials. More organized efforts following from these initiatives are under- way, warranting a significant shift from qualitative to quanti- tative imaging in the future. Although these efforts are important in making imaging quantitative and more useful, they do not specifically address or consider RT-induced normal tissue toxicity imaging as an endpoint. To make normal tissue imaging more successful, a more coherent effort should be initiated between all inter- ested parties: clinicians, physicists, radiobiologists, radiolo- gists, their representative societies (such as American Society for Therapeutic Radiology and Oncology, European Society for Therapeutic Radiology and Oncology, American Association of Physicists in Medicine, Radiation Research Society, and cooperative clinical trial groups such as Radia- tion Therapy Oncology Group and European Organization for Research and Therapy of Cancer). For example, a cross- society task group could be formed to systematically ap- proach normal tissue imaging, prepare normal tissue imaging guidance documents, and share the expertise between the in- terested parties. More collaborative clinical trials focusing on normal tissue imaging, as main or secondary endpoints, should be initiated, optimally within one of the cooperative groups. CONCLUSIONS Imaging has been used successfully to assess radiation-in- duced injury within several organs. The extent and severity of normal tissue damage has also been successfully related to clinically observed changes in global organ dysfunction. Be- cause current assessment of normal tissue damage and organ dysfunction mostly relies on established anatomic and func- tional imaging techniques, the full potential of discovering and applying imaging biomarkers has not been explored. Use of molecular imaging, although potentially much more powerful in identifying radiation-induced injury, has yet to be thoroughly investigated. New knowledge and understand- ing of the onset, dynamics and resolution of RT-induced in- jury mechanisms will likely lead to development of more specific molecular imaging techniques. There are many ques- tions that make application of imaging to normal tissue as- sessment challenging: we do not know when to image and what to image and how imaging changes correlate to the clin- ically observed effects. In addition, establishing imaging as a biomarker, particularly rising it to the level of surrogate endpoints of clinically relevant outcome, is still relatively weak. The answers to these questions will only be obtained by performing clinical trials that focus on normal tissue injury and include imaging as an investigative modality as well as one of the endpoints. The importance of well-designed clin- ical trials in which normal tissue injury is a clearly defined endpoint is paramount. In addition, preclinical studies of RT-induced normal tissue injury can greatly help understand- ing complicated pathophysiology. As we better understand the mechanisms of RT injury elucidated by such studies, we will be able to plan radiotherapeutic management more rationally to minimize treatment-related complications and intervene in injury processes to improve outcomes and qual- ity of life for our patients. The establishment of imaging as a biomarker holds great promise for realization of these goals. REFERENCES 1. Rodemann HP, Blaese MA. Responses of normal cells to ioniz- ing radiation. Semin Radiat Oncol 2007;17:81–88. 2. Marks LB. The pulmonary effects of thoracic irradiation. Oncol- ogy 1994;8:89–106. discussion 100, 103. 3. Dawson LA, Ten Haken RK. Partial volume tolerance of the liver to radiation. Semin Radiat Oncol 2005;15:279–283. 4. Lawrence TS, Robertson JM, Anscher MS, et al. Hepatic toxic- ity resulting from cancer treatment. Int J Radiat Oncol Biol Phys 1995;31:1237–1248. 5. Vos MJ, Hoekstra OS, Barkhof F, et al. Thallium-201 single- photon emission computed tomography as an early predictor of outcome in recurrent glioma. J Clin Oncol 2003;21:3559– 3565. 6. Fan M, Marks LB, Hollis D, et al. Can we predict radiation- induced changes in pulmonary function based on the sum of pre- dicted regional dysfunction? J Clin Oncol 2001;19:543–550. 7. Fan M, Marks LB, Lind P, et al. Relating radiation-induced re- gional lung injury to changes in pulmonary function tests. Int J Radiat Oncol Biol Phys 2001;51:311–317. 8. Seppenwoolde Y, De Jaeger K, Boersma LJ, et al. Regional differences in lung radiosensitivity after radiotherapy for non- small-cell lung cancer. International Journal of Radiation Oncology Biology Physics 2004;60:748–758. 9. Marks LB, Yu X, Prosnitz RG, et al. The incidence and func- tional consequences of RT-associated cardiac perfusion defects. Int J Radiat Oncol Biol Phys 2005;63:214–223. 10. Seddon B, Cook A, Gothard L, et al. Detection of defects in myocardial perfusion imaging in patients with early breast can- cer treated with radiotherapy. Radiother Oncol 2002;64:53–63. 11. Marks LB, Zhou S, Yu X. The impact of irradiated left ventric- ular volume on the incidence of radiation-induced cardiac per- fusion changes. Int J Radiat Oncol Biol Phys 2003;57. Imaging for assessment of normal tissue effects d R. JERAJ et al. S143
- 144. 12. Marks LB,Prosnitz RG, Hardenbergh PH. Functional conse- quences of radiation (RT)-induced perfusion changes in patients with left-sided breast cancer. Int J Radiat Oncol Biol Phys 2002; 54:3–4. 13. Prosnitz RG, Hubbs JL, Evans ES, et al. Prospective assessment of radiotherapy-associated cardiac toxicity in breast cancer pa- tients: Analysis of data 3 to 6 years after treatment. Cancer 2007;110:1840–1850. 14. Cao Y, Platt JF, Francis IR, et al. The prediction of radiation- induced liver dysfunction using a local dose and regional venous perfusion model. Med Phys 2007;34:604–612. 15. Munden RF, Erasmus JJ, Smythe WR, et al. Radiation injury to the liver after intensity-modulated radiation therapy in patients with mesothelioma: An unusual CT appearance. AJR Am J Roentgenol 2005;184:1091–1095. 16. Hahn CA, Zhou SM, Dunn RH, et al. Dose-dependent effects of radiation therapy on cerebral blood flow, metabolism and neu- rocognitive dysfunction. Int J Radiat Biol Phys 2005;62(Suppl. 1):S67. 17. Rutkowski T, Tarnawski R, Sokol M, et al. 1H-MR spectros- copy of normal brain tissue before and after postoperative radio- therapy because of primary brain tumors. Int J Radiat Oncol Biol Phys 2003;56:1381–1389. 18. Usenius T, Usenius JP, Tenhunen M, et al. Radiation-induced changes in human brain metabolites as studied by 1H nuclear magnetic resonance spectroscopy in vivo. Int J Radiat Oncol Biol Phys 1995;33:719–724. 19. Waldrop SM, Davis PC, Padgett CA, et al. Treatment of brain tumors in children is associated with abnormal MR spectro- scopic ratios in brain tissue remote from the tumor site. AJNR Am J Neuroradiol 1998;19:963–970. 20. Buus S, Grau C, Munk OL, et al. 11C-methionine PET, a novel method for measuring regional salivary gland function after ra- diotherapy of head and neck cancer. Radiother Oncol 2004;73: 289–296. 21. Zhang L, Murata Y, Ishida R, et al. Functional evaluation with intravoxel incoherent motion echo-planar MRI in irradiated sal- ivary glands: A correlative study with salivary gland scintigra- phy. J Magn Reson Imaging 2001;14:223–229. 22. Brush J, Lipnick SL, Phillips T, et al. Molecular mechanisms of late normal tissue injury. Semin Radiat Oncol 2007;17:121– 130. 23. Atwood T, Payne VS, Zhao W, et al. Quantitative magnetic res- onance spectroscopy reveals a potential relationship between ra- diation-induced changes in rat brain metabolites and cognitive impairment. Radiat Res 2007;168:574–581. 24. Atwood T, Robbins ME, Zhu JM. Quantitative in vivo proton MR spectroscopic evaluation of the irradiated rat brain. J Magn Reson Imaging 2007;26:1590–1595. 25. Darby SC, McGale P, Taylor CW, et al. Long-term mortality from heart disease and lung cancer after radiotherapy for early breast cancer: Prospective cohort study of about 300,000 women in US SEER cancer registries. Lancet Oncol 2005;6: 557–565. 26. Muryama S, Akamine T, Sakai S, et al. Risk factor of radiation pneumonitis: Assessment with velocity-encoded cine magnetic resonance imaging of pulmonary artery. J Comput Assist Tomogr 2004;28:204–208. 27. Guerrero T, Johnson V, Hart J, et al. Radiation pneumonitis: Local dose versus [18F]-fluorodeoxyglucose uptake response in irradiated lung. Int J Radiat Oncol Biol Phys 2007;68: 1030–1035. 28. Hart JP, McCurdy MR, Ezhil M, et al. Radiation pneumonitis: Correlation of toxicity with pulmonary metabolic radiation response. Int J Radiat Oncol Biol Phys 2008;71:967–971. 29. Hassaballa HA, Cohen ES, Khan AJ, et al. Positron emission tomography demonstrates radiation-induced changes to nonir- radiated lungs in lung cancer patients treated with radiation and chemotherapy. Chest 2005;128:1448–1452. 30. Cao Y, Pan C, Balter JM, et al. Liver function after irradiation based on computed tomographic portal vein perfusion imaging. Int J Radiat Oncol Biol Phys 2008;70:154–160. 31. Zhang G, Dilling TJ, Stevens CW, et al. Functional lung imag- ing in thoracic cancer radiotherapy. Cancer Control 2008;15: 112–119. 32. Fleckenstein K, Gauter-Fleckenstein B, Jackson IL, et al. Using biological markers to predict risk of radiation injury. Semin Radiat Oncol 2007;17:89–98. S144 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 145. QUANTEC: VISION PAPER BIOMARKERSAND SURROGATE ENDPOINTS FOR NORMAL-TISSUE EFFECTS OF RADIATION THERAPY: THE IMPORTANCE OF DOSE–VOLUME EFFECTS SØREN M. BENTZEN, PH.D., D.SC.,*y MATTHEW PARLIAMENT, M.D.,z JOSEPH O. DEASY, PH.D.,x ADAM DICKER, M.D., PH.D.,y{ WALTER J. CURRAN, M.D.,{k JACQUELINE P. WILLIAMS, PH.D.,** AND BARRY S. ROSENSTEIN, PH.D.yy *Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, WI; y Radiation Therapy Oncology Group, Philadelphia, PA; z Cross Cancer Institute and University of Alberta, Edmonton, Alberta, Canada; x Mallinckrodt Institute of Radiology, Washington University Medical Center, St. Louis, MO; { Jefferson Medical College of Thomas Jefferson University, Philadelphia, PA; k Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA; **University of Rochester Medical Center, Rochester, NY; yy Department of Radiation Oncology, Mount Sinai School of Medicine and NYU School of Medicine, New York, NY Biomarkers are of interest for predicting or monitoring normal tissue toxicity of radiation therapy. Advances in molecular radiobiology provide novel leads in the search for normal tissue biomarkers with sufficient sensitivity and specificity to become clinically useful. This article reviews examples of studies of biomarkers as predictive markers, as response markers, or as surrogate endpoints for radiation side effects. Single nucleotide polymor- phisms are briefly discussed in the context of candidate gene and genomewide association studies. The importance of adjusting for radiation dose distribution in normal tissue biomarker studies is underlined. Finally, research priorities in this field are identified and discussed. Ó 2010 Elsevier Inc. Biomarkers, Normal tissue effects, Predictive factors, Toxicity, Dose distribution, Single nucleotide polymor- phisms, Surrogate endpoints, Radiogenomics. PATIENT-TO-PATIENT VARIABILITY IN NORMAL TISSUE RESPONSE TO RADIATION Any group of patients will exhibit a range of normal tissue effects in response to an identical course of radiation therapy. It has long been debated whether this is mainly the result of a deterministic variation in radioresponsiveness (1) or a ran- dom (stochastic) variation in the induction and processing of damage (2). Unique insights into this question have come from studies of the inter- and intrapatient variability in early and late side effects in two separately irradiated fields in a large population of patients (3–5). For example, one study estimated that as much as 81% of the total variation in the de- velopment of skin telangiectasia was attributable to determin- istic effects (3). It has also been shown that the within-patient correlations between the occurrence of two late endpoints, fi- brosis and telangiectasia, or between early and late endpoints appear to be low (4, 5). These findings provide strong support for the hypotheses that (1) there are biological determinants of the risk of normal tissue toxicity that varies among individ- uals and (2) these factors are likely to be specific for a given radiation pathogenesis. It is noteworthy, in the QUANTEC (QUantitative Analysis of Normal Tissue Effects in the Clinic) context, that the studies cited have analyzed skin and subcutaneous endpoints where a relatively well-defined reference dose can be assigned to the tissue of interest in a specific patient (6) because of the simple field techniques used. In contrast, modern radiation therapy techniques typi- cally give rise to a broad range of absorbed doses in the tis- sues and organs of interest. Although much of the theoretical discussion has focused on the hypothetical existence of a distinct subpopulation of individuals with a marked increase in radioresponsiveness, clinical data seem not to support this hypothesis (7). A sub- group of patients expressing a given radiation side effect at Reprint requests to: Søren M. Bentzen, Ph.D., D.Sc., University of Wisconsin School of Medicine and Public Health, Department of Human Oncology, K4/316 Clinical Science Center, 600 Highland Avenue, Madison, WI 53792. Tel: (608) 265-8572; Fax: (608) 263-9947; E-mail: bentzen@humonc.wisc.edu This work was funded in part by the Varian Visiting Professor- ship Grant to the Radiation Therapy Oncology Group and with fed- eral funds from the United States Department of Health and Human Services under Grant No. CA21661, CA 37422, and CA32115. The authors acknowledge support by Alberta Cancer Research Institute Operating Grant No. 22175 (MP); Department of the Army Grant No. PC074201, W81XWH-08-1-0529; American Cancer Society Research Scholar Grant RSGT-05-200-01-CCE (BSR); Grant Nos. 5 U19 AI067733-04 and 1 RC1 AI081244-01 (JPW); National Cancer Institute Grant No. CA85181 (JOD). Conflict of interest: none. Received Feb 25, 2009, and in revised form Aug 21, 2009. Accepted for publication Aug 29, 2009. S145 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S145–S150, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.08.076
- 146. a relatively lowdose would give rise to a ‘‘bump’’ at the foot of the sigmoid clinical dose–incidence curve for normal tis- sue reactions, an effect that has not been evident in a relatively large clinical series. This appears to imply that this hypothet- ical hyperresponsive clinical phenotype must either have a very low prevalence or they cannot be far separated from the majority of cases in terms of responsiveness. Taken together, the studies cited are consistent with a hy- pothesis promulgating considerable interpatient variability in radioresponsiveness for a specific endpoint but reflective of a relatively broad continuum of varying responsiveness rather than a distinct subpopulation of sensitive individuals. Stratification of patients according to the risk of toxicity could potentially guide modality selection or interventions to mitigate this risk in high-risk individuals or allow intensi- fication of therapy in low-risk individuals. Also, biological variability in radioresponsiveness is likely to be a major con- founding factor in dose–response and dose–volume analyses, associated with a loss of statistical resolution and potentially causing problems with model identification. PROPOSED TERMINOLOGY: BIOMARKERS AND SURROGATE ENDPOINTS A biomarker is a measurable characteristic of a biological system that is indicative of normal function or disease state of the system or its response to an external factor such as a ther- apeutic intervention. Although the literature on biomarkers in cancer biology and tumor therapy outcome is rich and rapidly expanding (8), the study of biomarkers in normal-tissue ra- diobiology is a research field in its infancy. The development of new high-throughput assays as well as advances in molec- ular radiation pathology (9) are likely to boost research on toxicity biomarkers in the next 5 to 10 years (10). There is currently no general consensus on the appropriate terminology for biomarkers relevant to normal-tissue radia- tion research, but we propose distinguishing between three main classes of biomarkers: predictive factors, response markers, and surrogate endpoints. Predictive factors are biological or clinical factors (but not treatment-related factors) observable at baseline, i.e., before the start of therapy, that are statistically associated with the probability of a given outcome of a specific treatment in an individual. In the case of normal tissue side effects, these are often called risk factors or protective factors. This is consistent with the definition in Okunieff et al. (11). The dis- tinction between predictive and prognostic markers is of ma- jor importance in tumor biology (8). The analogous distinction for normal tissue risk factors would be between markers associated with poor tolerance to any (effective) therapy vs. markers predicting excess risk of toxicity after a specific therapy. Although some factors could potentially be in the former group—performance status, for example— most factors studied so far are modality-specific and are therefore likely to be predictive rather than prognostic. Note that Okunieff et al. (11) essentially defined a prognostic marker as a predictive marker assessed after the start of ther- apy. However, this definition seems to be at variance with the traditional use of this term in cancer research. Response markers are defined here as therapy-related changes in bio- markers that are mechanistically related to treatment outcome at the individual-patient level. These are sometimes referred to as direct markers of the underlying pathologic process (12). In the case of normal tissue toxicity, these markers would ideally reflect a deterministic step in the radiation path- ogenesis of a specific side effect. Response markers may be used for guiding therapy intensity or interventions for toxic- ity in an individual patient. Endpoints are health state characteristics that are used to assess treatment outcome in a population of patients. Clinical endpoints are symptoms, signs, or functional measures of dis- ease or toxicity. Clinical tumor endpoints are desirable treat- ment outcomes, reflecting the therapeutic aim, such as local tumor control or progression-free survival. Clinical normal- tissue endpoints are side effects affecting the patient’s health-related quality of life. Surrogate endpoints are measur- able biological effects that can be used as an early indicator of the effect of therapy on a given clinical endpoint in a popula- tion of patients. A response marker may serve as a surrogate endpoint. However, a surrogate endpoint might not necessar- ily be mechanistically related to the occurrence of the clinical endpoint in an individual (discussed later). It is noteworthy that markers associated with a disease state may not necessarily be valid surrogate endpoints. One example is the Cardiac Arrhythmia Suppression Trial in which clinical development of encainide and flecainide, de- spite demonstrating efficacy in suppressing arrhythmia after myocardial infarctions, were discontinued because of excess mortality compared with patients receiving a placebo (13). Another example is low hemoglobin concentration in cancer patients, a biomarker shown to be associated with increased disease burden and poor therapeutic outcome. Administra- tion of erythropoietin led to the desired increase in hemoglo- bin concentration but proved to be associated with a worse outcome in randomized placebo-controlled trials (14). PREDICTIVE MARKERS Predictive markers, assessed at baseline, i.e., before the start of therapy, are aimed at selecting cases for a specific type of therapy or for changing radiotherapy dose-fraction- ation prescription or planned dose distributions. In vitro radiosensitivity of normal human skin fibroblasts looked promising as a clinical radiosensitivity assay in the early 1980s. However, when large confirmatory studies were conducted, a significant association was not found (15). Cytokines and growth factors as predictive factors The possible predictive value of cytokines and growth fac- tors, involved in damage response and tissue remodeling as- sessed at baseline, have also been investigated in a number of studies. One example is transforming growth factor b-1 (TGF-b1), a strongly profibrotic, multifunctional cytokine (9) that can be activated from its latent form by ionizing S146 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 147. radiation. This activationhas been demonstrated within an hour after doses as low as 0.1 Gy. Li et al. (16) showed a sta- tistically significant association between the level of TGF-b1 in preradiotherapy plasma samples and subsequent develop- ment of radiation fibrosis in 91 early-stage breast cancer patients, thus demonstrating that this is a potential predictive marker for this side effect. Baseline plasma levels of a number of proinflammatory cy- tokines have been studied as predictive markers for radiation side effects by the group at University of Rochester. In one study, these investigators found that interleukin (IL)-1a and IL-6 were elevated in 13 patients who went on to develop symptomatic radiation pneumonitis compared with 11 patients who did not (17). The predictive power of IL-6 was slightly higherthanthatof IL-1a; however,the positive (PPV)and neg- ative(NPV)predictivevaluesforIL-6wereonly80%and47%, respectively. The relatively disappointing results with such phenotypic assays have motivated studies into genotypic as- says as an alternative in the post–Human Genome Project era. Genetic variations Advances in molecular biology, particularly with the ad- vent of high-throughput assays, have stirred interest in radio- genomics, the study of the possible link between genotypic variation and radiation therapy toxicity. It has long been known that some rare genetic syndromes, such as Nijmegen breakage syndrome and ataxia telangiectasia (AT), are asso- ciated with hyper-radiosensitivity in vitro as well as in the clinic (9). In particular, the ATM gene, mutated in patients with AT, has been intensively studied as a candidate gene of interest in radiogenomics. Although individuals who are homozygous for ATM mutations, which generally cause truncation of the encoded protein, show dramatic radiation hypersensitivity, the very low incidence of AT (1 per 40,000 live births) means that this syndrome cannot account for the normal tissue toxicities observed in a general popula- tion of patients receiving radiotherapy. The relative contribu- tion of patients who are heterozygous for ATM protein truncation mutations to the spectrum of radiation reactions seen in an unselected population of patients remains unclear. Recently, radiogenomic interest has focused on single nu- cleotide polymorphisms (SNPs). These genetic variants rep- resent substitutions in which an alternate base pair is present at a particular nucleotide location. The prevalence of SNPs is roughly 1 in every 1,000 nucleotides in the human genome. Until recently, use of the term SNP was restricted to polymor- phisms present in 1% of the population. However, data- bases such as the dbSNP of the National Center for Biotechnology Information, U.S. National Library of Medi- cine, do not use a lower bound on the minor allele frequency in defining what constitutes a SNP. SNPs have been inten- sively studied in disease susceptibility (18, 19) and pharma- cogenetics (20) studies, and it is reasonable to hypothesize that they may also affect the induction and processing of damage from ionizing radiation. Two approaches are being pursued to investigate the association of SNPs with the devel- opment of adverse normal tissue effects after radiotherapy: candidate gene studies and genomewide association studies (GWASs). Candidate genes are those for which their function suggests that they may be mechanistically involved in some aspect of radiation damage induction, repair, or damage pro- cessing and tissue remodeling. Typically, candidate gene studies concentrate on SNPs causing nonconservative amino acid changes in the final gene product or SNPs located in reg- ulatory regions, possibly affecting gene expression or protein secretion rates. In a recent review, Alsner et al. (21) summa- rized data from no less than 39 studies, albeit some of them reporting on an extended or different set of SNPs as a previ- ously reported patient series. Although a majority of these studies have found encouraging associations between selected SNPs and radiation toxicity, no SNPs have yet been unequivocally established as associated with a specific radiation reaction. GWASs take a different approach: the association between alleles of different linked SNPs in a population, the so-called linkage disequilibrium, means that a relatively manageable subset of tag SNPs can capture most of the genetic variation in a region. This technology has led to the recent explosion in publication of disease susceptibility studies (22), looking at a quarter or half a million SNPs in thousands of cases and controls. However, although a number of GWAS are in prog- ress in the setting of radiation therapy side effects, so far none have been published. What kind of resolution is required on the risk scale? It can be argued (9) that SNPs conveying an odds ratio of less than $2 are unlikely to be of practical use in modifying radiation therapy, in view of the many other risk factors that have been identified. This means that GWASs to identify SNPs associated with the development of radia- tion-induced normal tissue toxicities require fewer subjects (a few thousands rather than tens of thousands) to achieve a particular statistical power compared with most disease as- sociation studies. An important added advantage of the radio- therapy patient studies is that the environmental agent, ionizing radiation, and the doses to which the subjects are ex- posed are known. This means, however, that both dosimetric and dose–volume variability must be carefully controlled be- cause these will be confounders in a study of biological asso- ciations. RESPONSE MARKERS Response markers are of interest partly because they could serve as individualized in vivo dosimeters for biologically ef- fective dose and partly because they could form the basis for biological adaptive radiotherapy. As an example, the study from the University of Rochester (17) measured weekly levels of IL-1a and IL-6 during fractionated radiotherapy and tested whether changes in the level of these cytokines 1–5 weeks after the start of therapy, relative to baseline levels, showed stronger correlation with ultimate outcome than the baseline values themselves. However, the authors concluded that this was not the case. In clinical studies, a normalization of plasma TGF-b1 levels toward the end of a course of radiotherapy yielded Biomarkers and dose distribution d S. M. BENTZEN et al. S147
- 148. a PPV of90% for identifying patients who did not develop radiation pneumonitis (23). This formed the hypothesis un- derlying a subsequent dose-escalation study in 38 patients with inoperable non–small cell lung cancer (24). This study showed that patients with normalization of TGF-b1 levels to- ward the end of radiotherapy could be dose escalated from 73.6 to 80 Gy (8 patients) or 86.4 Gy (6 patients). However, the authors concluded that long-term survivors had a ‘‘signif- icant risk’’ of developing severe treatment-related complica- tions. Evans and colleagues (25) reassessed the value of TGF-b1 as a response marker and concluded interestingly that this marker was only associated with radiation pneumo- nitis in a subgroup of patients with unfavorable dose–volume metrics. This illustrates the importance of controlling for dose distribution as a potentially important confounder in this kind of study, particularly when assessing such radiation sensitive organs as the lung. A further illustration of the concepts introduced here is pro- vided by the recent study by Zhao et al. (26), who did not find an association between radiation-induced lung toxicity (RILT, defined as pneumonitis or fibrosis) and plasma TGF- b1 at baseline in 165 patients with non–small cell lung cancer. In a subset of 102 cases, plasma TGF-b1 concentration was measured 4 weeks into the course of fractionated radiother- apy. This value was not significantly associated with the risk of RILT, whereas the ratio between the TGF-b1 level dur- ing and before RT showed a significant association with sub- sequent RILT. Using the terminology proposed here, we would conclude that baseline TGF-b1 level is not a predictive factor for RILT and that the TGF-b1 level duringradiotherapy is not a response marker. However, the change in the TGF-b1 level relative to baseline is a response marker in Zhao’s study. Why distinguish between response markers and predictive markers? There are basic differences between factors that are given at baseline and that can predict the risk of radiotherapy effects even before the first dose fraction is delivered and biomarkers that are induced by the radiation and therefore are biological ‘‘responses’’ in themselves that may precede a subsequent clinical effect. Genetic differences are obvi- ously not responses; elevated cytokine markers after the start of RT obviously are. The two classes of biomarkers differ in terms of study design methodology, biological significance, and potential use in clinical management. SURROGATE ENDPOINTS FOR NORMAL TISSUE EFFECTS Surrogate endpoints for efficacy have attracted consider- able interest in drug development trials (27). Surrogate toxic- ity endpoints are of great potential interest in radiation oncology trials, especially early surrogates of late radiation ef- fects. An example is the use of increased low-grade toxicity as an indicator of increased severe toxicity, that can be seen as a surrogate endpoint. Although in some cases lower-grade toxicity may progress into higher-grade toxicity (28), this is not obligatory. The aim of using lower-grade toxicity as a sur- rogate for higher-grade toxicity is partly to gain a lead time in assessing toxicity but, in particular, to improve statistical res- olution by increasing the number of events. Another example is confluent mucositis after cytotoxic treatment for head and neck cancer, which is a clinical endpoint in its own right but may also be seen as a useful surrogate endpoint reflecting treatment intensity with respect to other early toxicities. It is correlated with, but not mechanistically related to, the clinical endpoints of pain and dysphagia (29). Validation of surrogacy requires demonstration of a statistical association between changes in the clinical endpoint and changes in the surrogate endpoint in a population of patients (30). Functional and mo- lecular imaging data are also examples of biomarkers that are of potential interest as normal tissue response markers or sur- rogate endpoints (see the article in this issue by Jeraj et al.). DOSE DISTRIBUTION AND BIOMARKERS Modern radiotherapy techniques have deliberately given rise to a range of absorbed doses in nontarget tissues. This is in contrast to target volume dose distributions for which the vast majority of current treatment plans prescribe a uni- form dose distribution with the aim of delivering it within a relatively narrow tolerance band. The intricacy of separating dose distribution and treatment intensity from biomarker analysis is illustrated by Evans et al. (25) who noted that plasma TGF-b1 level has been shown to be correlated with mean lung dose (MLD) in patients receiv- ing radiation therapy for lung cancer and that the tumor itself may produce TGF-b1. The observation that larger tumors are more likely to be treated with plans characterized by a higher MLD completes the circle. All of this will obviously con- found the possible relationship between plasma TGF-b1 level and the clinical incidence of radiation pneumonitis. Dose–volume metrics and predictive markers add variabil- ity in toxicity outcome data that will reduce the statistical power to detect an association between these factors and out- come. Studies are emerging that correct for dosimetric and patient-related risk factors when trying to link SNPs with a clinical phenotype (31, 32). The candidate gene SNP study from the Cross Cancer Institute (33) is illustrative in this con- text. This group looked for an association between 49 SNPs in 24 candidate genes vs. Grade 2+ rectal and bladder toxicity in a series of 83 patients receiving definitive radiotherapy for prostate cancer. Ranked in order of statistical significance the three most significant predictors were (1) rectal D30 75 Gy; (2) XRCC3 AG, 50 untranslated region 4541; and (3) age at diagnosis $60 years. Ranked in order of the magnitude of the hazard ratio, the same three factors topped the list, but the or- der was (1) XRCC3 AG, 50 untranslated region 4541; (2) age at diagnosis $60 years; and (3) rectal D30 75 Gy. In a multivariate Cox proportional hazards model, age at diag- nosis and D30 were included in each of the best and second best subsets of four and five predictors, whereas the XRCC3 AG SNP was not selected for inclusion in any of these four models. One or two among a set of four other SNPs were included in at least one of the four models; one of these, ERCC2 GA, Asp711 Asp was nonsignificant S148 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 149. (p = 0.08)in univariate analysis but was significant (p = 0.02) in a model including age at diagnosis, mean bladder dose, rectal D30, and the LIG 4 TC, Asp568 Asp SNP. Although the inclusion or exclusion of specific covariates in Cox models using stepwise selection should be interpreted with great care, these data do illustrate how SNPs selected without adjustment for dose–volume metrics can be selected under a ‘‘wrong’’ model. It is also worth noting that the dose–vol- ume metrics appeared more robust as an explanatory variable in this particular study. From the perspective of estimating dose–volume relationships, the rectal D30 showed greater significance and a larger hazard ratio in two of the four models adjusting for selected SNPs. Caveats in the Cross Cancer Institute are the large number of SNPs studied in a rel- atively small number of patients, increasing the risk of spuri- ous false-positive findings, and the decision to pool rectal and bladder toxicities in the analysis. Although it may be a reason- able assumption to test whether these depend on common SNPs, the relevant dose–volume metrics for the two organs will not generally be the same. It should also be noted that the plan is only a surrogate of what was actually delivered, and ultimately the most valid dose distribution would be a cu- mulative one comprising the actual dose from every fraction. That type of data is only starting to be collected on a small scale; see the article in this issue by Jaffray et al. Despite these limitations, the Canadian study provides an interesting example of the interplay between dosimetric and biological risk factors. These relationships should clearly be explored in large independent studies. BIOINFORMATICS AND BIOMARKERS Findings reported in the literature are often inconsistent across studies. An obvious problem is that most studies have modest sample sizes in relation to the realistic magnitude of likely effect sizes. Other reasons for conflicting findings be- tween studies are a high likelihood of false-positive findings due to (1) multiple comparisons, i.e., high dimensionality of the genomic data; (2) the testing of data-generated hypotheses in the same data set; and (3) overfitting, i.e., the use of too many covariates in a predictive model relative to the number of events being analyzed. All of these issues can lead to false associations and reduce the generalizability of the findings to independent data sets (15). A number of strategies have been proposed to reduce these problems (34) including improved study reporting, assay quality assurance, high-precision do- simetry, and improved toxicity scoring (15). Prospectively planned studies, with independent training and test data sets with large sample sizes will be required to achieve a balance between discovering novel associations on one hand and re- ducing the false-positive rate on the other (15, 35). RESEARCH PRIORITIES As mentioned earlier, dose distribution and biomarkers are mutually confounding factors in many of the studies con- ducted to date. From a QUANTEC perspective, adjusting for biological and patient-related factors will lead to stronger dose–volume effect relationships. From a biomarker discov- ery perspective, adjustment for dose–volume effects will im- prove the statistical power to detect biological predictive factors with a specific effect size. Discovery of response markers would typically involve mechanistic studies in patients who develop a specific radiation effect, but also, in this case, an understanding of the relationship between local and organ-level effects would typically have to be estab- lished. Likewise, one first screen for surrogate toxicity endpoints could be to prove dose–response and volume–re- sponse sensitivity. Several national and international bio- banks have been set up specifically aimed at association studies with radiation therapy effects (36). Much has been learned from the first generation of radiogenomics studies. Moving on to the second generation of studies, we propose the following priorities: 1. Large prospective studies to identify associations between specific radiation effect endpoints and candidate predic- tive markers or GWASs with careful adjustment for dose–volume relationships and other risk factors: stan- dardized scoring of the grade of reaction with adequate follow-up time in case of late effects and prospective stor- ing of the full three-dimensional dose matrix should be re- quired from all participating centers. Such trials are under consideration within the Radiation Therapy Oncology Group (RTOG). 2. Training set/validation set designs with prospective validation in truly independent populations. 3. High throughput methodology for mass screening of potential predictive factors, response markers, and surro- gate endpoints. 4. Discovery of surrogate endpoints of late side effects to be used in early clinical trials of new combined modality therapies. 5. Development of data analysis strategies that allow correc- tion for the confounding effects of dose distribution as well as patient- and treatment-related risk factors. One of the keys to success in the coming 5 years will be to expand the number of cases in normal-tissue-effect biomarker studies. This is likely to require large collaborative networks of investigators or studies within the RTOG or other multicen- ter groups. At the same time, a more rigorous application of training/validation set designs will be required to address the problem of overfitting and high false-positive rates. REFERENCES 1. Holthusen H. Erfahrungen u¨ber die Vertra¨glichkeitsgrenze fu¨r Ro¨ntgenstrahlen und deren Nutzanwendung zur Verhu¨tung von Scha¨den. Strahlentherapie 1936;57:254–269. 2. Munro TR, Gilbert CW. The relation between tumour lethal doses and the radiosensitivity of tumour cells. Br J Radiol 1961;34:246–251. Biomarkers and dose distribution d S. M. BENTZEN et al. S149
- 150. 3. Safwat A,Bentzen SM, Turesson I, Hendry JH. Deterministic rather than stochastic factors explain most of the variation in the expression of skin telangiectasia after radiotherapy. Int J Ra- diat Oncol Biol Phys 2002;52:198–204. 4. Bentzen SM, Overgaard M. Relationship between early and late normal-tissue injury after postmastectomy radiotherapy. Radio- ther Oncol 1991;20:159–165. 5. Bentzen SM, Overgaard M, Overgaard J. Clinical correlations between late normal-tissue endpoints after radiotherapy: Impli- cations for predictive assays of radiosensitivity. Eur J Cancer 1993;29A:1373–1376. 6. Bentzen SM, Christensen JJ, Overgaard J, Overgaard M. Some methodological problems in estimating radiobiological parame- ters from clinical data. Alpha/beta ratios and electron RBE for cutaneous reactions in patients treated with postmastectomy radiotherapy. Acta Oncol 1988;27:105–116. 7. Bentzen SM. Potential clinical impact of normal-tissue intrinsic radiosensitivity testing. Radiother Oncol 1997;43:121–131. 8. Bentzen SM, Buffa FM, Wilson GD. Multiple biomarker tissue microarrays: Bioinformatics and practical approaches. Cancer Metastasis Rev 2008;27:481–494. 9. Bentzen SM. Preventing or reducing late side effects of radia- tion therapy: Radiobiology meets molecular pathology. Nat Rev Cancer 2006;6:702–713. 10. Amundson SA, Grace MB, McLeland CB, et al. Human in vivo radiation-induced biomarkers: Gene expression changes in radiotherapy patients. Cancer Res 2004;64:6368–6371. 11. Okunieff P, Chen Y, Maguire DJ, Huser AK. Molecular markers of radiation-related normal tissue toxicity. Cancer Me- tastasis Rev 2008;27:363–374. 12. Cohn JN. Introduction to surrogate markers. Circulation 2004; 109(Suppl. 1):IV20–IV21. 13. Echt DS, Liebson PR, Mitchell LB, et al. Mortality and morbidity inpatientsreceivingencainide,flecainide,orplacebo.TheCardiac Arrhythmia Suppression Trial. N Engl J Med 1991;324:781–788. 14. Crawford J. Erythropoietin: High profile, high scrutiny. J Clin Oncol 2007;25(9):1021–1023. 15. Bentzen SM. From cellular to high-throughput predictive assays in radiation oncology: Challenges and opportunities. Semin Radiat Oncol 2008;18:75–88. 16. Li C, Wilson PB, Levine E, et al. TGF-beta1 levels in pre-treat- ment plasma identify breast cancer patients at risk of developing post-radiotherapy fibrosis. Int J Cancer 1999;84:155–159. 17. Chen Y, Hyrien O, Williams J, et al. Interleukin (IL)-1A and IL- 6: Applications to the predictive diagnostic testing of radiation pneumonitis. Int J Radiat Oncol Biol Phys 2005;62:260–266. 18. Easton DF, Pooley KA, Dunning AM, et al. Genome-wide as- sociation study identifies novel breast cancer susceptibility loci. Nature 2007;447:1087–1093. 19. Wellcome Trust Case Control Consortium. Genome-wide asso- ciation study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007;447:661–678. 20. Roses AD. Genome-based pharmacogenetics and the pharma- ceutical industry. Nat Rev Drug Discov 2002;1:541–549. 21. Alsner J, Andreassen CN, Overgaard J. Genetic markers for pre- diction of normal tissue toxicity after radiotherapy. Semin Ra- diat Oncol 2008;18:126–135. 22. Grant SF, Hakonarson H. Microarray technology and applica- tions in the arena of genome-wide association. Clin Chem 2008;54:1116–1124. 23. Anscher MS, Kong FM, Andrews K, et al. Plasma transforming growth factor beta1 as a predictor of radiation pneumonitis. Int J Radiat Oncol Biol Phys 1998;41:1029–1035. 24. Anscher MS, Marks LB, Shafman TD, et al. Risk of long-term complications after TFG-beta1-guided very-high-dose thoracic radiotherapy. Int J Radiat Oncol Biol Phys 2003;56(4):988– 995. 25. Evans ES, Kocak Z, Zhou SM, et al. Does transforming growth factor-beta1 predict for radiation-induced pneumonitis in pa- tients treated for lung cancer? Cytokine 2006;35:186–192. 26. Zhao L, Wang L, Ji W, et al. Elevation of plasma TGF-beta1 during radiation therapy predicts radiation-induced lung toxic- ity in patients with non-small-cell lung cancer: A combined analysis from Beijing and Michigan. Int J Radiat Oncol Biol Phys 2009;74:1385–1390. 27. Le Tourneau C, Lee JJ, Siu LL. Dose escalation methods in phase I cancer clinical trials. J Natl Cancer Inst 2009;101: 708–720. 28. Bentzen SM, Thames HD, Overgaard M. Latent-time estima- tion for late cutaneous and subcutaneous radiation reactions in a single-follow-up clinical study. Radiother Oncol 1989;15: 267–274. 29. Bentzen SM, Saunders MI, Dische S, Bond SJ. Radiotherapy- related early morbidity in head and neck cancer: Quantitative clinical radiobiology as deduced from the CHART trial. Radio- ther Oncol 2001;60:123–135. 30. Tang PA, Bentzen SM, Chen EX, Siu LL. Surrogate end points for median overall survival in metastatic colorectal cancer: Literature-based analysis from 39 randomized con- trolled trials of first-line chemotherapy. J Clin Oncol 2007; 25(29):4562–4568. 31. Yuan X, Liao Z, Liu Z, et al. Single nucleotide polymorphism at rs1982073:T869C of the TGFbeta1 gene is associated with the risk of radiation pneumonitis in patients with non-small-cell lung cancer treated with definitive radiotherapy. J Clin Oncol 2009;27:3370–3378. 32. Cesaretti JA, Stock RG, Atencio DP, et al. A genetically deter- mined dose–volume histogram predicts for rectal bleeding among patients treated with prostate brachytherapy. Int J Radiat Oncol Biol Phys 2007;68:1410–1416. 33. Damaraju S, Murray D, Dufour J, et al. Association of DNA re- pair and steroid metabolism gene polymorphisms with clinical late toxicity in patients treated with conformal radiotherapy for prostate cancer. Clin Cancer Res 2006;12:2545–2554. 34. McCarthy MI, Abecasis GR, Cardon LR, et al. Genome-wide association studies for complex traits: Consensus, uncertainty and challenges. Nat Rev Genet 2008;9:356–369. 35. Barnett GC, West CM, Dunning AM, et al. Normal tissue reac- tions to radiotherapy: Towards tailoring treatment dose by genotype. Nat Rev Cancer 2009;9:134–142. 36. West CM, McKay MJ, Holscher T, et al. Molecular markers predicting radiotherapy response: Report and recommendations from an International Atomic Energy Agency technical meet- ing. Int J Radiat Oncol Biol Phys 2005;62:1264–1273. S150 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 151. QUANTEC: VISION PAPER IMPROVINGNORMALTISSUE COMPLICATION PROBABILITY MODELS: THE NEED TO ADOPT A ‘‘DATA-POOLING’’ CULTURE JOSEPH O. DEASY, PH.D.,* SØREN M. BENTZEN, PH.D.,y ANDREW JACKSON, PH.D.,z RANDALL K. TEN HAKEN, PH.D.,x ELLEN D. YORKE, PH.D.,k LOUIS S. CONSTINE, M.D.,z ASHISH SHARMA, PH.D.,{ AND LAWRENCE B. MARKS, M.D.** From the *Department of Radiation Oncology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; y Department of Human Oncology, University of Wisconsin School of Medicine, Madison, WI; z Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY; x Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; k Department of Radiation Oncology, University of Rochester Cancer Center, Rochester, NY; { Center for Comprehensive Informatics, Emory University, Atlanta, GA; and **Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried out effectively in a few normal tissue complication probability studies and should become a common strategy. Ó 2010 Elsevier Inc. NTCP, Normal tissue complication probability models, Data sharing, Data reuse, Data pooling. THE CURRENT PACE OF PROGRESS IN NORMAL TISSUE COMPLICATION PROBABILITY MODELING: STEADY, BUT SLOW Progress in radiation oncology should accelerate with an improved understanding of how treatment decisions affect outcomes. Key elements to improving predictive models of normal tissue toxicity include: discovering new factors (e.g., dosimetric, anatomic, biological) that influence risk and validating evolving models with increasingly compre- hensive datasets. In the face of biological complexity and measurement uncertainties, of course, models will never have perfect predictive power. Despite a large number of dose-volume-outcome publica- tions, made possible by the revolution in three-dimensional treatment planning, progress in normal tissue complication probability (NTCP) modeling to date has been modest. The QUANTEC reviews, though helpful, have demonstrated the limited accuracy of existing risk prediction models. New publications often take one step forward (identifying new factors or mathematical models), and one-half step back (raising issues of why different conclusions are reached compared to previous ‘‘solid’’ publications). A good exam- ple of this is radiation pneumonitis: some studies see a clear risk difference between upper and lower lung irradiation, some do not, and still others don’t look for the effect (see the review in this issue). Some of these discordant findings are likely due to a low statistical power resulting from a low absolute incidence of recorded toxicities. Nevertheless, there are also many examples in the QUANTEC reviews where large studies find contrasting results, including contrasting causative factors. Statistical power issues, as well as correct risk-factor identification issues, could poten- tially be reduced if we could pool data from much larger populations of patients. Another example of unexplained variations between models is xerostomia. One carefully-studied dataset (1) shows little late salivary reduction at mean doses below $40 Gy, whereas most other reports (see the xerostomia review in this issue) show some reduction in function at lower mean doses (15–20 Gy). This difference is probably related to dose–volume/location factors that are current un- known, but without actually doing a combined analysis based on the full dose distributions there is little chance of resolving Reprint requests to: Joe Deasy, Ph.D., Professor, Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, St. Louis, MO 63110. Tel: (314) 362-1420; Fax: (314) 362-8521; E-mail: jdeasy@radonc.wustl.edu Acknowledgment—Development of this statement was partially sup- ported by NIH grant CA85181 (JOD). Received April 6, 2009, and in revised form June 23, 2009. Accepted for publication June 24, 2009. S151 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S151–S154, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.06.094
- 152. the issue. Noveldose–volume metrics, that may require full access to the three-dimensional treatment planning data, are often proposed as a result of new research (e.g., the weighted center of the dose distribution as a risk factor in radiation pneumonitis) (2). Another problem, not solved by data pool- ing is that many of the studies use different measured end- points (e.g., whole-mouth vs. single gland salivary function). The same principles hold true for tissue complica- tion probability (TCP) modeling. Recent analyses of dose– volume factors affecting lung and prostate local control required the full dose distribution characteristics (3, 4). Inter-report comparisons of NTCP modeling results are often problematic due to differences in patient cohorts, treat- ment techniques, complication reporting methods, analysis methods, and models tested (Fig. 1). Currently, it is virtually impossible to revisit previously published, high-quality data- sets to assess such issues raised in the later studies. Reports can be made more comparable by using only standard models, but this would impede progress: the ‘‘best’’ dose– volume model is never known a priori and the most common currently used models (e.g., the Lyman-Kutcher-Burman model) are clearly oversimplified. Hence, modeling results are often not reconciled, and under our current way of doing things, the resulting literature is destined to continue to be a collection of conflicting and incomplete results. DATA SHARING TODAY Unfortunately, the typical method of dealing with radio- therapy data used for NTCP or TCP analyses today is illus- trated in Fig. 2. The ‘‘trash can,’’ of course, is typically a set of computer tapes or disks that simply gather dust. In many cases storage media have deteriorated over time or the device for reading these may no longer be available. This occurs despite a commitment on the part of the NIH to emphasize the need for effective data sharing. Reports of the use of existing databases reused for NTCP modeling projects are limited. THE CASE FOR DATA POOLING An excellent illustration of the value of data sharing is the pooled analysis of pneumonitis data and dose–volume histo- grams for 540 patients from five institutions in the United States and Europe published by Kwa et al. more than 10 years ago (5). This study allowed the comparison of alternative NTCP models fitted to the dataset and provided a powerful argument for mean lung dose as a simple and useful metric for this clinical endpoint. The study also carefully analyzed some of the issues relating to the pooling of data from multi- ple studies and showed how institutional differences in the incidence of pneumonitis remained even in the final model. Searching for other causative factors will often require full access to the treatment planning data, however. NTCP models are meant to have a wide range of applicabil- ity.Ideally,then,NTCPmodelingshouldincludedatasetsgath- ered for a wide range of treatment techniques. This was shown tobecrucial,forexample,intheradiationpneumonitisexample of Bradley et al., which combined three-dimensional institu- tional and Radiation Therapy Oncology Group (RTOG) clini- cal trial 93-11 data to arrive at a single model that well- described pneumonitis risk for many types of irradiation pat- terns (6). Combining datasets would normally be expected to increase the generalizability/applicability of the resulting model to a wider range of patient and dose distribution charac- teristics, and would shed light on important differences be- tween datasets. Data pooling could also provide crucial statistical power in probing causative factors for rare, yet life- threatening,complications.Ofcourse,thevalueofdatapooling depends critically on data quality: adding unreliable data to re- liabledataisnotprogress.Datacollectionqualityassuranceand adherence to objective standards remain key issues. Difficulties analyzing and modeling multidimensional datasets are ubiquitous in science, and are not limited to radiation oncology. Other areas in science are shifting to curation, reconciliation, and accrual of valuable datasets (this is in addition to the traditional work product of published individual reports). Many editorials, reports, and letters have Fig. 1. Why does normal tissue complication probability (NTCP) modeling frequently lead to incompatible results? The current para- digm consists of applying a range of evolving methods (models tested, structures included, etc. to datasets that at least partially differ in patient, disease, and treatment characteristics). This inevitably leads to inconsistent results and impedes the validation of NTCP models for broad clinical use. It will be necessary to pool data to escape this trap. Fig. 2. ‘‘The current (data-loss) paradigm.’’ Data are effectively lost to the wider scientific community after publication. Capturing key datasets in query-able data repositories would accelerate the discov- ery of causative factors and increase the accuracy of parameter esti- mates. S152 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 153. detailed the expectedadvantages of, and obstacles to (7), moving to a ‘‘data sharing culture’’ (8, 9). Advantages of data sharing further include the ability to replicate results, re- fine methods (10), address new questions with the same data (11), and make research more efficient (12). THE NEED FOR EVOLVING MODELS The clinical scenario being studied is never static: ‘‘base- line’’ treatments, adjuvant systemic therapies, RT dose delivery methods (e.g., stereotactic body radiotherapy, proton therapy), and desired doses/targets/fractionation schemes, each evolve. Thus, relevant databases will need to contain broad clinical data, and dose–volume models will need to be continuously updated and adapted to new treatment condi- tions. Accessible NTCP/TCP data repositories should include key institutional datasets data from Phase III clinical trials representing the systematic study of the relationships be- tween idealized data from prospective trials—often con- ducted in centers of excellence. However, such repositories should also contain data recorded during routine conditions to make the results as widely applicable as possible. IS RADIATION ONCOLOGY DATA SHARING FEASIBLE? Yes. The Image-guided Therapy Center at Washington Uni- versity stores clinical trial treatment planning data for all the re- cent RTOG three-dimensional–based trials. Datasets from the prostate cancer three-dimensional conformal radiotherapy trial 94-06 and the lung cancer dose escalation trial 93-11 have been exported and used for extensive NTCP modeling (6, 13). Al- though technically cumbersome, data sharing has moved for- ward, even for these complicated treatment planning datasets. The American College of Radiology’s web-accessible data warehouse and the National Biomedical Imaging Archive (14), for example, are powerful data repositories that will support reuse of imaging datasets. As part of an ongoing data sharing program, RTOG clinical trial 0522 data and American College of Radiology Imaging Network (ACRIN) data from a companion trial are being exported to the Na- tional Cancer Institute Imaging Archive database, including both Fluorine-18-deoxyglucose-positron emission tomogra- phy (FDG-PET) and digital imaging and communications in medicine (DICOM-RT) data objects. Washington Univer- sity has similarly developed a web-based database architec- ture to store myriad datasets, including fully archived treatment planning datasets with open-source viewing tools. Publicly accessible datasets do not necessarily need to be shared in a single massive data warehouse. Data repositories can potentially be decentralized so long as common data for- mats are used and the appropriate middleware is available. In addition, software is now freely available that allows conversions into a vendor-neutral archive file from a wide range of commercial and academic treatment planning systems (15). The same software system (computational environment for radiotherapy research) has extensive tools to review and analyze this format on personal computers. DISCOVERABLE DATABASES The inability to be able to query for the existence of an archive can often be just as big a roadblock as it is to obtain access to the data itself. We envision that institutional data- bases could become discoverable for the sake of contributing to universal queries with anonymized summaries of available data. In this way (as a fictitious example), a resident at Medical School A could make a universal query, and learn that Medical School B had 86 cases relevant to radiation proctitis after proton therapy, and that the cases included dose distributions, outcomes (with 13 responders), and computed tomography images. At this point, no protected health information of detailed data values would be shared, only aggregate ‘‘inventory’’ summaries of available data. Such a system, linking together discoverable databases, would be the key motivator to move to the next step and begin the relatively more cumbersome process of contacting the appropriate researchers and beginning the institutional review board process. The National Cancer Institute’s caBIG program has made significant progress in this area through the use of an architec- ture paradigm wherein individual datasets are kept under in- stitutional control yet made discoverable (16, 17). A remote user can query multiple datasets across institutions. These ‘‘grid services’’ are also very sensitive to the security needs of multi-institutional access. After users have discovered the appropriate datasets, the data custodians/investigators could be contacted about obtaining research approval. The grid infrastructure would then provide the researcher with a single ‘‘virtual’’ archive, customized using their credentials and privileges, from which they can get their data. The caGrid effort thus provides one potential solution to the problem of a universal query of datasets that could be pooled. OBSTACLES TO DATA POOLING There are significant administrative and professional issues involved in regulating access to data while still expediting re- search. Biomedical on the one hand, cooperative trial groups need to protect the opportunity of researchers/physicians who generated the data to get a ‘‘first crack’’ at data analysis and publication, whereas the larger societal need is to maximize the benefit of the entire process for scientific/clinical advance- ment. A compromise is needed. We suggest that cooperative groups grant wider access to anonymized data after some set time after publication of the original envisioned analyses. Fur- ther citations and data reuse would only increase the value of the original investment in the clinical trial. Despite our enthusiasm, it needs to be said that data pooling is not a panacea to NTCP modeling problems, espe- cially because differences in datasets can obscure the looked- for effects. In addition to the added cost of keeping data in us- able formats, other obstacles to fully leveraging archived data include variations in: outcome reporting and analysis (RTOG vs. Common Terminology Criteria for Adverse Events scale vs. institutional scales), the prevalence of known or unknown comorbidities, dose calculation algorithms (older methods Data pooling to improve NTCP models d J. O. DEASY et al. S153
- 154. vs. convolution orMonte Carlo), setup procedures, contour- ing policies, etc. (See reviews by Bentzen et al. and Jackson et al. in this issue). Some limitations of current NTCP studies can be over- come by a greater reliance on collaboration, for example as part of multi-institutional trials. Nonetheless, making such data discoverable and available for pooled analyses is still su- perior to one-time use, especially considering the probability that the models are likely to change. RECOMMENDATIONS Apart from the practical issues discussed previously, progress in making the archiving of key datasets the norm in radiation oncology research will require cooperation from major grant-funded stakeholders, including individual investigators, cooperative groups, and journal editors. Despite these (surmountable) obstacles, creating a culture of data reuse in the radiation oncology research community will have long-term advantages and would very likely lead to improved radiation oncology outcomes. A complete shift to making data archiving a requirement for publishing is ar- guably problematic because of technical costs. To maximize the use and relevance of clinical trials data, cooperative groups may want to adopt a policy of anonymizing clinical trials data and making the data publicly accessible after a rea- sonable delay. This delay would enable publication of all the investigator-driven, planned studies. Digital data, unlike tissue specimens, do not become depleted with use, and so less access management would be required. For these reasons, we encourage the establishment of key databanks of linked treatment planning, imaging, and outcomes data. Costs associated with data curation/quality assurance, ano- nymization, access policy, data verification, data format con- version, and data extraction of course need to be considered by funding agencies. Potentially, discoverable databases could be conveniently queried for linked lists of data includ- ing outcomes, images, dose, tissue samples, and previously conducted bio-array results. Much of the software and asso- ciated standards required to do this has been developed. In contrast to a data pooling culture, our current ‘‘data loss’’ paradigm leaves NTCP and TCP modeling in a Sisy- phean cycle: rolling a slightly different boulder up a slightly different hill, over and over. We need to escape from this trap and gain the advantages of data sharing. Converting to a data reuse paradigm will require changes in operation by cooper- ative groups, institutional investigators, and journal. Infor- matics support will be crucial. Many groups across the sciences have already called for a wholesale change in pro- cess that supports data reuse. Some scientific journals, espe- cially in genomics-related areas, already require submission of supporting datasets with research articles. However, adop- tion of policies to ‘‘publish the data’’ has been much slower in fields dealing with sensitive health information. If the radiation oncology world were to adopt a data reuse policy, progress toward improved NTCP models (and other types of treatment effect comparisons) would accelerate, new factors relevant to outcomes would be identified, and the road block to consensus would be surmountable. It is only by making published datasets available for ongoing combined analyses that we can hope to produce powerful and validated models of quantitative normal tissue effects in the clinic. REFERENCES 1. Li Y, Taylor JM, Ten Haken RK, et al. The impact of dose on parotid salivary recovery in head and neck cancer patients treated with radiation therapy. Int J Radiat Oncol Biol Phys 2007;67:660–669. 2. Hope AJ, Lindsay PE, El Naqa I, et al. Clinical, dosimetric, and location-related factors to predict local control in non- small cell lung cancer. Int J Radiat Oncol Biol Phys 2005; 63: S231. 3. Mu Y, Hope AJ, Lindsay P, et al. Statistical modeling of tumor control probability for non-small-cell lung cancer radiotherapy. Int J Radiat Oncol Biol Phys 2008;72: S448. 4. van Herk M, Witte MG, Heemsbergen WD, et al. Relation be- tween dose outside the prostate next term and failure free sur- vival in the Dutch previous term prostate next term cancer trial. Int J Radiat Oncol Biol Phys 2008;72: S65. 5. Kwa SL, Lebesque JV, Theuws JC, et al. Radiation pneumonitis as a function of mean lung dose: An analysis of pooled data of 540 patients. Int J Radiat Oncol Biol Phys 1998;42:1–9. 6. Bradley JD, Hope A, El Naqa I, et al. A nomogram to predict radiation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data. Int J Radiat Oncol Biol Phys 2007;69:985–992. 7. Colditz GA. Constraints on data sharing experience from the Nurses’ Health Study. Epidemiology 2009;20:169–171. 8. Piwowar HA, Chapman W. Envisioning a biomedical data reuse registry. AMIA Annu Symp Proc 2008:1097. 9. Parr CS, Cummings MP. Data sharing in ecology and evolution. Trends Ecol Evol 2005;20:362–363. 10. HernanMA,WilcoxAJ.Epidemiology,datasharing,andthechal- lenge of scientific replication. Epidemiology 2009;20:167–168. 11. Van Horn JD, Ishai A. Mapping the human brain: New insights from fMRI data sharing. Neuroinformatics 2007;5:146–153. 12. Koslow SH. Sharing primary data: A threat or asset to discov- ery? Nat Rev Neurosci 2002;3:311–313. 13. Tucker SL, Dong L, Bosch WR, et al. Fit of a generalized Ly- man normal-tissue complication probability (NTCP) model to Grade $2 late rectal toxicity data from patients treated on pro- tocol RTOG 94-06 next term. Int J Radiat Oncol Biol Phys 2007;69:S8–S9. 14. National Biomedical Imaging Archive. Available online at: https://cabig.nci.nih.gov/tools/NCIA. Accessed March 24, 2009. 15. Deasy JO, Blanco AI, Clark VH. CERR: A computational envi- ronment for radiotherapy research. Med Phys 2003;30:979–985. 16. Saltz J, Kurc T, Hastings S, et al. e-Science, caGrid, and trans- lational biomedical research. Computer 2008;41:58–64. 17. Oster S, Langella S, Hastings S, et al. caGrid 1.0: An enterprise grid infrastructure for biomedical research. J Am Med Inform Assoc 2008;15:138–149. S154 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 155. QUANTEC: VISION PAPER THELESSONS OF QUANTEC: RECOMMENDATIONS FOR REPORTING AND GATHERING DATAON DOSE–VOLUME DEPENDENCIES OF TREATMENT OUTCOME ANDREW JACKSON, PH.D.,* LAWRENCE B. MARKS, M.D.,y SØREN M. BENTZEN, PH.D., D.SC.,z AVRAHAM EISBRUCH, M.D.,x ELLEN D. YORKE, PH.D.,* RANDAL K. TEN HAKEN, PH.D.,x LOUIS S. CONSTINE, M.D.,k AND JOSEPH O. DEASY, PH.D.{ From the *Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY; y Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC; z Department of Human Oncology, University of Wisconsin Medical School, Madison, WI; x Department of Radiation Oncology, University of Michigan, Ann Arbor, MI; k Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY; and { Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO The 16 clinical articles in this issue review the dose–volume dependence of toxicities of external beam radiotherapy. They are limited by the difficulty of synthesizing results from different publications. The major problems stem from incomplete reporting of results and use of incompatible or ambiguous endpoints. Here we specify these problems; give recommendations to authors, editors, and reviewers on standards of reporting; and provide methods of defining endpoints suitable for the dose–volume analysis of toxicity. Adopting these recommendations will facilitate meta-analysis and increase the utility of individual studies of the dependence of complications on dose distributions. Ó 2010 Elsevier Inc. Normal tissue toxicity, Statistical reporting standards, Endpoint definition. REQUIREMENTS FOR FUTURE QUANTEC EFFORTS Severe normal tissue complications are, by good medical practice, relatively uncommon. Investigations of their causes will inevitably be plagued by the small numbers of events in individual series. It is therefore important to be able to combine complication data from different institutions and protocols. This can be achieved in two ways: by the direct combination of raw data (i.e., pooling of dose distribution and outcome information); or by combination of published results (literature-based meta-analysis). The initial efforts of QUANTEC have concentrated on the second approach (the data-pooling paper by Deasy et al. in this issue discusses the first). In the process of gathering and analyzing the pub- lished data for the papers in this issue, the limitations of existing journal articles as sources for meta-analysis have be- come apparent. They fall into two major categories: first, the low and uneven standards of reporting results; and second, the difficulty of defining common and meaningful clinical endpoints. 1. REPORTING STANDARDS AND STATISTICAL REQUIREMENTS FOR LITERATURE-BASED META-ANALYSIS The Consolidated Standards of Reporting Trials (CON- SORT) statement provides a model for good practice in re- porting clinical results (http://www.consort-statement.org/). Guidelines based on these standards have been created for ra- diotherapy by Bentzen (1); however, as noted by Trotti and Bentzen, the CONSORT guidelines are lacking in specifics when dealing with the scope and severity of the adverse effects of radiotherapy (2). Typically, papers on the dose–volume dependence of com- plications are not written to maximize their utility for either clinical application or subsequent meta-analysis. The reme- dies for these defects are often simple. Common failures and specific remedies are given in the following sections. Where possible, examples of these failures (sometimes from our own publications) are cited in the heading, and cita- tions to solutions are given in the following text. To clarify Reprint requests to: Andrew Jackson, Ph.D., Department of Med- ical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, New York 10021. Tel: (212) 639-7685 Fax: (212) 717-3010; E-mail: jacksona@mskcc.org Acknowledgment—Partially supported by NIH grant 85181 (J.O.D.), NIH grant CA69579 (L.B.M.), and a grant from the Lance Armstrong Foundation (L.B.M.). Received March 26, 2009, and in revised form Aug 6, 2009. Accepted for publication Aug 13, 2009. S155 Int. J. Radiation Oncology Biol. Phys., Vol. 76, No. 3, Supplement, pp. S155–S160, 2010 Copyright Ó 2010 Elsevier Inc. Printed in the USA. All rights reserved 0360-3016/10/$–see front matter doi:10.1016/j.ijrobp.2009.08.074
- 156. the examples, citationsare given to the relevant locations, fig- ures, and tables where appropriate. 1A. Lack of basic statistical data on incidence of toxicity (see reference (3): Methods and Materials—Criteria for Radiation Myelopathy). Wherever relevant, both the number of subjects and the number of events should be reported (see reference (4): Figure 1, and reference (5): p. 735). Alterna- tively, when an estimate of incidence is given, the standard error should also be supplied. For late complications, when the Kaplan-Meier method is used, the follow-up time at which the estimate is made should be given. If a minimum follow-up time is used, this cutoff should be specified. 1B. Lack of numerical labeling of response histograms (see reference (6): Figure 9). Where responses are shown as functions of a dosimetric variable, using quartile or similar plots, the numerical range and median of the variable should be supplied for each group (see reference (7): Table 4, and reference (8): Table 4). 1C. Complication rates as functions of differences of abso- lute variables (see reference (9): Figure 2). Where a scientific point may require a response rate as a function of the differ- ence between two variables (e.g., the dose difference between the ipsilateral and contralateral ears), the corresponding response rate as a function of an absolute variable should also be supplied (e.g., the absolute dose to the ipsilateral ear). 1D. Lack of model parameter estimates and their standard errors (see reference (10): p. 698–609). Where clinical and dose–volume variables of a predictive model are found to be significantly correlated with complications, best fit parameters and their confidence intervals should be given, so the response function can be reconstructed (see reference (11): Table 1). 1E. Lack of complication rates associated with constraints (see reference (12): p. 689–690). When dose–volume histo- grams or other constraints are derived, the observed compli- cation rate for treatments above and below the constraint should be stated (see reference (4): Figure 1, and reference (13)). These are expected to depend on the degree to which the constraints are violated or respected, respectively, and to vary for constraints at different dose levels. 1F. Lack of goodness of fit. Although models may be fit and result in statistically significant correlation with outcome, their quality as descriptions of the data is rarely reported. Goodness of fit statistics should be stated (such as the chi-squared test on binned complication data (see refer- ence (14): p. 887–888, Figure 6, and Table 4)), because they indicate when models provide adequate fits to data or when alternative models should be considered. Various tests of goodness of fit have been proposed for Cox proportional hazards models (15–18). 1G. Lack of receiver-operating characteristic curves or other discrimination statistics. It is useful to know if a model efficiently discriminates between responders and nonre- sponders. Plots of predicted versus observed incidence of toxicity are helpful for graphical testing of model perfor- mance. If the model is used as a binary classifier the area un- der the receiver-operating characteristic curve should be calculated to summarize the model’s ability to discriminate responders from nonresponders throughout the range of cut points (see reference (19): Figure 5b); the false- and true- positive ratios display the costs and benefits of imposing clinical constraints. Spearman’s rank correlation coefficient (see reference (6): Table 6), and Kendall’s tau (see reference (14): p. 888 and Figure 7) may also be used to assess the strength of correlation and the ability of a model to segregate responders from nonresponders. 1H. Dose–volume histograms including only partial volumes (see reference (20): p. 693, section on conformal plan evaluation). Segmentation guidelines vary. Some publications relied on planning systems that did not allow overlapping structures, or did not include parts of a structure outside the dose computation grid. Preferably, data used for NTCP analyses should include the full organ volume (see reference (19): p. 107, paragraph 2). When this is not possi- ble, either a standard method of normalization, or absolute volumes should be used (see reference (21): p. 63 Methods and Materials paragraph 2, and Table 1). A clear statement of the definition of the organ volume should be given, paying close attention to such issues as length of linear structures included (e.g., rectum), inclusion or otherwise of the lumen for tubular or cavitary structures (e.g., rectum, bladder), inclusion or otherwise of any overlap with planning target volume, clinical target volume, or gross target volume. 1I. Complication rates as functions of novel variables (see reference (22): Figure 3). Fragmentation of the literature results when response rates are presented only as a function of a novel variable (e.g., dose–surface histograms, or mea- sures of dose to the circumference of tubular structures). This can be mitigated if the corresponding response rate func- tion for a standard variable is also supplied (see reference (23): Table 2, and Figures 3 and 4) or if the relationship between the variables is well understood (see reference (24): Figure 4). Without the basic reporting of statistics and treatment variables recommended in items 1A–E, a study cannot be included in a meta-analysis; items 1F and 1 G allow its qual- ity to be assessed, and help decide if it should be included; items 1H and 1I help insure that studies are compatible. Other good research practices (not rising to the level of requirements) include: tests of models reported by others to be statistically significant; tables or graphs of the correlations between dosimetric variables—this can make it obvious whether a dataset really has the ability to discriminate between, say V20 and mean dose as predictors of radiation pneumonitis (see reference (25): Figures 5 and 6); the robust- ness of a fit to statistical variation of the patients included can be assessed using cross-validation and bootstraps techniques (see reference (19): p. 109 paragraph 1, reference (26): p. 16 section 2.2.4. and Figure 6, and reference (27): Figure 5 and p. 987 section on statistical analysis), choice of the most robust fit helps to avoid overfitting. Recommendations on reporting standards and statistical requirements for Referees and Editors The responsibility for accurate and sufficient reporting lies primarily with authors; however, reviewers and editors of S156 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 157. submitted papers shouldconsider these criteria when judging the suitability of a paper for publication. The requirement of brevity is in conflict with that of complete reporting, and a pri- ority of journals is for concise papers establishing a single scientific point; nevertheless, authors, editors, and reviewers need to keep in mind the specific priorities of this branch of clinical science. As reviewers and editors, we will ask for revisions to articles that do not follow the recommendations in items 1A–1I, because the clinical utility of papers comply- ing with these requests would be greatly increased. The requirement for comprehensive reporting. The sim- ple expedients given above will allow a reader to critically appraise the validity of a modeling study, and facilitate the statistical synthesis of data from multiple published studies. However, there is a need they do not address: the need for data to be analyzed and presented comprehensively. Individ- ual studies may give dose volume constraints, or perform model fits, but results from different studies cannot be com- bined unless the same dose–volume constraints or model pa- rameters are considered. This can be addressed only partly by diligently exploring the models used by previous authors, as the fundamental difficulty lies in the large number of dose– volume variables to be tested. To address this problem through the literature requires adoption and creation of tools for comprehensive reporting such as dose–volume and Equivalent Uniform Dose (EUD) Atlases of Complication Incidence (4, 13). We also recommend that journals allow re- porting comprehensive supplementary material in electronic form. Alternatively, repositories of validated dose distribu- tion, patient characteristics, and outcome data may address this matter (see Deasy et al. in this issue). If such a data base were created, tools such as the EUD Atlases of Compli- cation Incidence would still be useful for the comprehensive display of the data. In any kind of retrospective pooling of data from multiple studies, recently discovered clinical or treatment-related risk factors may not be available in older datasets. Such factors can be strong confounders of dose–volume response relation- ships, and pooling the outcome of studies without adjusting for them may not be justifiable. The development of side ef- fects after cancer therapy is inherently multifactorial and much of the variability in response is currently unexplained by dosimetric factors alone. Another obstacle, described in the following sections, is that many studies use different def- initions of endpoints. 2. ENDPOINT DEFINITIONS Many endpoints are used to classify normal tissue injury, including patient symptoms (e.g., shortness of breath), for- mal clinical/functional assessments (e.g., quality of life tools, exercise testing), laboratory tests (e.g., pulmonary function tests, blood counts), and imaging (e.g., CT density). The majority of studies use symptoms to assess toxicity. Authors should make every effort to analyze standard end- points. However, the commonly used clinical grading systems may not be ideal for providing quantitative data for the QUANTEC projects for several reasons. 2A. Most grading systems separate acute and late compli- cation at one point in time. In specific cases, the timing of this division may not be appropriate. The classic example that does not fit easily into the early-late scheme is radiation pneumonitis which may occur up to $6 months posttreat- ment. Unless this is recognized prospectively, pneumonitis cases occurring after the acute cutoff time need to be retro- spectively reassigned by careful examination of individual cases. The use of actuarial statistical methods may be re- quired (28). 2B. Toxicities are grouped into grades. Typically: Grade 0: no change; Grade 1: changes of no clinical significance; Grade 2: changes requiring outpatient treatment; Grade 3: changes requiring hospitalization; Grade 4: life-threatening changes; Grade 5: lethal changes. Toxicity scales vary in the way these definitions are applied (e.g., prescription of steroids for radiation pneumonitis is considered Grade 2 by the South Western Oncology Group, but Grade 3 by the Ra- diation Therapy Oncology Group). Their clinical application is often subjective, and related to the physician’s clinical practice and perception of the severity of the event. For ex- ample, it is often not clear if and when patients should be started on medications (Grade 2) or admitted to the hospital (Grade 3). The use of a standard toxicity reporting system is needed. For each of the organ-specific papers, the authors make recommendations regarding the scoring and grading of toxicity. 2C. Various symptoms referable to a single organ are of- ten grouped together. Thus, dose–volume responses based on clinical grade alone are super-positions of responses from different complications, and in consequence, broader and shallower than that of any one constituent. For example, the response of the bladder may reflect a global organ effect (e.g., reduced capacity and resultant urinary frequency) or a focal effect (e.g., bleeding due to local ulceration). The dose–volume relationships for these two types of response are likely to be different. Nevertheless, these symptoms are grouped together in most scoring systems used to assess blad- der injury. Particular signs and symptoms may not indicate a specific pathogenesis without further workup. Similarly, there may be circumstances where different symptoms originate from damage to different portions of an organ, and the superposition of responses seen in any individual clinical series will depend on the probability of irradiation of the different regions. For example, Heemsber- gen (29) and Peeters (30) examined rectal complications of prostate radiotherapy using patient-reported symptoms. They identified several distinct endpoints in patients treated on a prostate dose escalation trial, and analyzed their dose– volume and regional dependence separately. Bleeding and soiling were associated with irradiation of different regions of the rectal wall. Thus, analysis of a portmanteau endpoint such as the = Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer Grade 2 rectal complications, will produce a response function that The lessons of QUANTEC d A. JACKSON et al. S157
- 158. is an unpredictablesuperposition of the responses for bleed- ing, incontinence, increased stool frequency, and increased mucous discharge. Where possible, it is preferred to report the data in a more granular fashion (i.e., with the different endpoints reported separately), as well as in the aggregate form. 2D. Symptoms are not always easily attributable to specific organs. For example, shortness of breath can result from injury to the lung, heart, and trachea, as well as anemia from bone marrow effects. Thus, a modest degree of lung in- jury, along with anemia, can result in a relatively high degree of shortness of breath. Should that be scored as a low-grade lung and bone marrow effect, or a high-grade lung effect? Further, the presence and grade of toxicity may be related to concurrent clinical factors unrelated to treatment (e.g., pre- existing anemia or pre-RT lung disease may make patients more prone to developing dyspnea). Studies considering such endpoints should at least acknowledge this issue, and, where possible, report the information concerning the con- founding factors (e.g., considering and reporting anemia con- current with dyspnea). Because toxicity may occur, at least in part, because of pre-RT conditions, scoring systems that ac- knowledge the contribution of such baseline factors may also be useful in dose–volume/outcome studies. 2E. The number of different endpoints for a single compli- cation is large. Aside from the differences in the grades of complication analyzed, published results use different grad- ing schema, and it is often not possible to combine these cleanly. Discussion and recommendations for endpoint definition In contrast with the statistical issues, those related to end- point definition are challenging and complex. The requirement that endpoints be objective and quantita- tive naturally leads to those based on functional imaging and testing (see Jeraj et al. in this issue). Nevertheless, for such tests to be useful, they must be related to clinically relevant outcomes. It is important to separate symptoms into coherent disease entities when attempting to associate functional imaging studies with clinical outcome. Failure to eliminate complica- tions arising from confounding disease entities will obscure the correlations between measures of functional change and their clinical consequences. A proper understanding of the causes and anatomical origins of distinct clinical complica- tions is also important in this regard. As an example, pre- and posttreatment studies of saliva collected from head-and-neck patients have had sporadic success in establishing that this endpoint is related to xerosto- mia. Studies vary in the way saliva is collected: stimulated vs. unstimulated flow; from the parotids alone (31, 32) vs. whole mouth (33, 34). They also vary in the degree to which the whole mouth is involved in the treatment. Xerostomia is not totally determined by the parotid gland function; other glands in the oral cavity (particularly the submandibular and sublingual glands) produce watery or sticky saliva (35). Therefore, the degree to which parotid dose or parotid function correlates with the incidence of xerostomia may de- pend on the dose to the rest of the oral cavity (36–38). A num- ber of pre- and posttreatment imaging studies of the function of the parotid and other glands of the oral cavity are currently underway and may resolve this issue. We therefore recommend that grading schemes based on symptoms of coherent clinical syndromes (rather than organ specific collections of disparate symptoms) be used for dose– volume toxicity studies. Where necessary, these may need to be developed, with the aid of our biological and anatomical understanding of the causes and usual timing of the onset of these complications. Standard coalescing scoring systems (e.g., that of the Radiation Therapy Oncology Group) may provide a useful way to summarize the data; however, the un- derlying discrete symptom-specific information should be re- tained. This may facilitate studies to determine the pathophysiological cause of complications. The SOMA-late effects normal tissues (SOMA-LENT) sys- tem (39–43) was devised to specifically address four different ways to quantify toxicity; based on Subjective findings (e.g., symptoms of shortness of breath), Objective findings (e.g., changes in respiratory rate), Management interventions (e.g., the institution of steroids or oxygen), and Analytic data (e.g., pulmonary function tests or blood gas results). Findings ineachofthesefourdomainsareindependentlyquantified.These granular data, in each of the four domains, can be combined, in either a predetermined or situation-specific manner, to generate a global toxicity score. Thus the SOMA-LENT system has the flexibility to be applicable in a wide variety of clinical scenarios. As demonstrated in the Netherlands Cancer Institute’s stud- ies of rectal complications, patient-reported symptom check- lists may be helpful. In this regard, the National Cancer Institute is developing patient reported versions of the Common Terminology Criteria for Adverse Events (CTCAE) symptom items (https://wiki.nci.nih.gov/display/ CTMS/Task+2+-+Develop+PRO-CTCAE+items). Currently, some 27 items are listed at the website (e.g., erectile dysfunc- tion, dyspnea). In addition, the National Institutes of Health is developing Patient-Reported Outcomes Measurement Infor- mation System (PROMIS), a databank of validated patient-re- ported instruments (http://www.nihpromis.org/default.aspx). In some cases, determining the appropriate endpoints to ana- lyze for separate dose–volume outcome correlates is a key part of the research project itself. To address the complex problems outlined here, there is a need for a peer-reviewed central repository of dose–volume constraint standards. This might include atlases, contouring standards, endpoint definitions, grading schemes, and toxic- ity data/rates for a variety of common situations. Expert working groups would need to be formed and maintained with the charge of overseeing the repository and keeping it up to date. These needs will require specific infrastructure solutions, such as the databanks outlined in Deasy et al. in this issue. Advanced imaging and other quantitative metrics afford a unique opportunity to systematically relate dose–volume variables with outcome. Carefully defined objective S158 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010
- 159. endpoints are requiredfor the success of such projects. Studies of this kind, together with the recent explosion in radiotherapy planning and delivery tools, leading to more diversity in dose distributions, may provide an exciting time when the complex responses of normal tissues to radiation can be better understood. REFERENCES 1. Bentzen S. Towards evidence based radiation oncology: Improving the design, analysis, and reporting of clinical out- come studies in radiotherapy. Radiother Oncol 1998;46:5–18. 2. Trotti A, Bentzen S. The need for adverse effects reporting stan- dards in oncology clinical trials. J Clin Oncol 2004;22:19–22. 3. Wong C, Van Dyk J, Milosevic M, et al. Radiation myelopathy following single courses of radiotherapy and retreatment. Int J Radiat Oncol Biol Phys 1994;30:575–581. 4. Jackson A, Yorke E, Rosenzweig K. The atlas of complication incidence: A proposal for a new standard for reporting the results of radiotherapy protocols. Semin Radiat Oncol 2006; 16:260–268. 5. Schultheiss TE. Spinal cord radiation tolerance. Int J Radiat Oncol Biol Phys 1994;30:735–736. 6. Hope AJ, Lindsay PE, Naqa IE, et al. Modeling radiation pneu- monitis risk with clinical, dosimetric, and spatial parameters. Int J Radiat Oncol Biol Phys 2006;65:112–124. 7. Hernando ML, Marks LB, Bentel GC, et al. Radiation-induced pulmonary toxicity: A dose-volume histogram analysis in 201 patients with lung cancer. Int J Radiat Oncol Biol Phys 2001; 51:650–659. 8. Kong F-M, Hayman J, Griffith K, et al. Final toxicity results of a radiation-dose escalation study in patients with non-small-cell lung cancer (NSCLC): Predictors for radiation pneumonitis and fibrosis. Int J Radiat Oncol Biol Phys 2006;65:1075–1086. 9. Pan CC, Eisbruch A, Lee JS, et al. Prospective study of inner ear radiation dose and hearing loss in head-and-neck cancer patients. Int J Radiat Oncol Biol Phys 2005;61:1393–1402. 10. Jackson A, Skwaarchuk MW, Zelefsky MJ, et al. Late rectal bleeding after conformal radiotherapy of prostate cancer (II): Volume effects and dose-volume histograms. Int J Rad Oncol Biol Phys 2001;49:685–698. 11. Tucker SL, Liu HH, Wang S, et al. Dose-volume modeling of the risk of postoperative pulmonary complications among esophageal cancer patients treated with concurrent chemoradio- therapy followed by surgery. Int J Radiat Oncol Biol Phys 2006; 66:754–761. 12. Jackson A. Partial organ irradiation of the rectum. Seminars Radiat Oncol 2001;11:215–223. 13. Jackson A, Yorke ED, Rosenzweig KE, et al. EUD and dose- volume based atlases of complication incidence: A proposal for new standards in reporting results of treatment protocols [abstract]. ASTRO 2006 Philadelphia, PA; 2006., Int J Radiat Oncol Biol Phys 2006;66(S3):S124-125 14. Jackson A, Ten Haken RK, Robertson JM, et al. Analysis of clinical complication data for radiation hepatitis using a parallel architecture model. Int J Radiat Oncol Biol Phys 1995;31:883– 891. 15. Wei LJ. Testing goodness of fit for proportional hazards model with censored observations. J Am Stat Assoc 1984;79:649–652. 16. Hae H, Lee S. Comparison of goodness of fit tests for the cox proportional hazards model. Comm Stat Simulat Comput 2000;29:187–206. 17. Le C, Zelterman D, Le C. Goodness of fit tests for proportional hazards regression models. Biometrical J 1992;34:557–566. 18. Schoenfeld D. Chi-squared goodness-of-fit tests for the propor- tional hazards regression model. Biometrika 1980;67:145–153. 19. Skwarchuk M, Jackson A, Zelefsky M, et al. Late rectal toxicity after conformal radiotherapy of prostate cancer (I): Multivariate analysis and dose-response. Int J Radiat Oncol Biol Phy 2000; 47:103–113. 20. Storey MR, Pollack A, Zagars G, et al. Complications from radiotherapy dose escalation in prostate cancer: Preliminary results of a randomized trial. Int J Radiat Oncol Biol Phys 2000;48:635–642. 21. Kupelian P, Reddy C, Carlson T, et al. Dose/volume relation- ship of late rectal bleeding after external beam radiotherapy for localized prostate cancer: Absolute or relative rectal volume? Cancer J Sci Am 2002;8:62–66. 22. Fenwick JD, Khoo VS, Nahum AE, et al. Correlations between dose-surface histograms and the incidence of long-term rectal bleeding following conformal or conventional radiotherapy treatment of prostate cancer. Int J Radiat Oncol Biol Phys 2001;49:473–480. 23. Koper PC, Heemsbergen WD, Hoogeman MS. Impact of volume and location of irradiated rectum wall on rectal blood loss after radiotherapy of prostate cancer. Int J Radiat Oncol Biol Phys 2004;58:1072–1082. 24. Garcia-Vincente F, Zapatero A, Floriano A, et al. Statistical analysis of dose-volume and dose-wall histograms for rectal toxicity following 3D-CRT in prostate cancer. Med Phys 2005;32:2503–2509. 25. Yorke ED, Jackson A, Rosenzweig KE, et al. Correlation of dosimetric factors and radiation pneumonitis for non-small- cell lung cancer patients in a recently completed dose escalation study. Int J Radiat Oncol Biol Phys 2005;63:672–682. 26. Levegrun S, Jackson A, Zelefsky M, et al. Risk group dependence of dose response for biopsy outcome after three- dimensional conformal radiation therapy of prostate cancer. Radiother Oncol 2002;63:11–26. 27. Bradley J, Hope A, Naqa IE, et al. A nomogram to predict radi- ation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data. Int J Radiat Oncol Biol Phys 2007; 69:985–992. 28. Tucker S, Liu H, Liao Z, et al. Analysis of radiation pneumoni- tis risk using a generalized Lyman model. Int J Radiat Oncol Biol Phys 2008;72:568–574. 29. Heemsbergen WD, Hoogeman MS, Hart GA, et al. Gastrointes- tinal toxicity and its relation to dose distributions in the anorec- tal region of prostate cancer patients treated with radiotherapy. Int J Radiat Oncol Biol Phys 2005;61:1011–1018. 30. Peeters ST, Lebesque JV, Heemsbergen WD. Localized volume effects for late rectal and anal toxicity after radiotherapy for prostate cancer. Int J Radiat Oncol Biol Phys 2006;64:1151– 1161. 31. Eisbruch A, Ten Haken RK, Kim HM, et al. Dose, volume, and function relationships in parotid salivary glands following con- formal and intensity-modulated irradiation of head and neck cancer. Int J Radiat Oncol Biol Phys 1999;45:577–587. 32. Schilstra C, Meertens H. Calculation of the uncertainty in com- plication probability for various dose-response models, applied to the parotid gland. Int J Radiat Oncol Biol Phys 2001;50:147– 158. 33. Blanco AI, Chao KS, Naqa IE. Dose-volume modeling of salivary function in patients with head-and-neck cancer receiv- ing radiotherapy. Int J Radiat Oncol Biol Phys 2005;62:1055– 1069. 34. Chao KS, Deasy JO, Markman J, et al. A prospective study of salivary function sparing in patients with head-and-neck cancers receiving intensity-modulated or three-dimensional radiation therapy: Initial results. Int J Radiat Oncol Biol Phys 2001;49:907–916. The lessons of QUANTEC d A. JACKSON et al. S159
- 160. 35. Eisbruch A,Ship JA, Kim HM, et al. Partial irradiation of the parotid gland. Semin Radiat Oncol 2001;11:234–239. 36. Jellema AP, Doornaert P, Slotman BJ, et al. Does radiation dose to the salivary glands and oral cavity predict patient-rated xero- stomia and sticky saliva in head and neck cancer patients treated with curative radiotherapy? Radiother Oncol 2005;77:164–171. 37. Saarilahti K, Kouri M, Collan J, et al. Erratum to ‘‘sparing of the submandibular glands by intensity modulated radiotherapy in the treatment of head and neck cancer’’ [Radiother. Oncol. 78 (2006) 270–275]. Radiother Oncol 2006;80:107–108. 38. Saarilahti K, Kouri M, Collan J, et al. Sparing of the submandib- ular glands by intensity modulated radiotherapy in the treatment of head and neck cancer. Radiother Oncol 2006;78:270–275. 39. LENT SOMA Tables: Table of contents 1995. Radiother Oncol 1995;35:17–60. 40. Overgaard J, Bartelink H. About tolerance and quality. An im- portant notice to all radiation oncologists. Radiother Oncol 1995;35:1–3. 41. Pavy J-J, Denekamp J, Letschert J, et al. EORTC late effects working group. Late effect toxicity scoring: The SOMA scales. Radiother Oncol 1995;35:11–15. 42. Rubin P, Constine LS, Fajardo LF, et al. RTOG late effects working group: Overview of late effects normal tissues (LENT) scoring system. Radiother Oncol 1995;35:9–10. 43. Denekamp J, Bartelink H, Rubin P, et al. Correction for the use of the SOMA LENT tables. Radiother Oncol 1996;39:191. S160 I. J. Radiation Oncology d Biology d Physics Volume 76, Number 3, Supplement, 2010