Stevens et al, Continuous monitoring of prostate position using stereoscopic and monoscopic kV image guidance

Continuous monitoring of prostate position using stereoscopic and monoscopic kV
image guidance
M. Tynan R. Stevens, Dave D. Parsons, and James L. Robar
Citation: Medical Physics 43, 2558 (2016); doi: 10.1118/1.4947295
View online: http://dx.doi.org/10.1118/1.4947295
View Table of Contents: http://scitation.aip.org/content/aapm/journal/medphys/43/5?ver=pdfcov
Published by the American Association of Physicists in Medicine
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Continuous monitoring of prostate position using stereoscopic
and monoscopic kV image guidance
M. Tynan R. Stevens, Dave D. Parsons, and James L. Robar
Department of Medical Physics, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada and Nova
Scotia Cancer Centre, QEII Health Science Centre, Halifax, Nova Scotia B3H 2Y9, Canada
(Received 18 November 2015; revised 29 March 2016; accepted for publication 9 April 2016;
published 27 April 2016)
Purpose: To demonstrate continuous kV x-ray monitoring of prostate motion using both stereoscopic
and monoscopic localizations, assess the spatial accuracy of these techniques, and evaluate the dose
delivered from the added image guidance.
Methods: The authors implemented both stereoscopic and monoscopic fiducial localizations using
a room-mounted dual oblique x-ray system. Recently developed monoscopic 3D position estimation
techniques potentially overcome the issue of treatment head interference with stereoscopic imaging
at certain gantry angles. To demonstrate continuous position monitoring, a gold fiducial marker was
placed in an anthropomorphic phantom and placed on the Linac couch. The couch was used as a
programmable translation stage. The couch was programmed with a series of patient prostate motion
trajectories exemplifying five distinct categories: stable prostate, slow drift, persistent excursion,
transient excursion, and high frequency excursions. The phantom and fiducial were imaged using
140 kVp, 0.63 mAs per image at 1 Hz for a 60 s monitoring period. Both stereoscopic and monoscopic
3D localization accuracies were assessed by comparison to the ground-truth obtained from the Linac
log file. Imaging dose was also assessed, using optically stimulated luminescence dosimeter inserts
in the phantom.
Results: Stereoscopic localization accuracy varied between 0.13±0.05 and 0.33±0.30 mm,
depending on the motion trajectory. Monoscopic localization accuracy varied from 0.2±0.1 to
1.1±0.7 mm. The largest localization errors were typically observed in the left–right direction. There
were significant differences in accuracy between the two monoscopic views, but which view was
better varied from trajectory to trajectory. The imaging dose was measured to be between 2 and
15 µGy/mAs, depending on location in the phantom.
Conclusions: The authors have demonstrated the first use of monoscopic localization for a room-
mounted dual x-ray system. Three-dimensional position estimation from monoscopic imaging per-
mits continuous, uninterrupted intrafraction motion monitoring even in the presence of gantry
rotation, which may block kV sources or imagers. This potentially allows for more accurate treatment
delivery, by ensuring that the prostate does not deviate substantially from the initial setup position.
C 2016 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4947295]
Key words: stereoscopic, monoscopic, intrafraction motion, prostate cancer, x-ray imaging
1. INTRODUCTION
The accurate delivery of external beam radiation therapy
depends on precise localization of the anatomy to be irradiated.
While planning CT and pretreatment imaging are routinely
used for patient setup, this cannot account for intrafraction
motion observed for many internal organs like the prostate.
Indeed, prostate motion of more than 1 cm is not uncommon,
and for most patients, the prostate will spend at least 5% of
the treatment fraction more than 4 mm from the expected
location.1
These deviations from the setup position can affect
the dosimetric outcomes of treatment, as it has been shown
that motion of 5 mm can result in a 10% reduction of the 100%
dose coverage.2
Although prostate motion is not always large
enough to produce serious dosimetric impact, intrafraction
motion monitoring can help avoid this possibility altogether.
An additional consideration regarding intrafraction motion
is the impact of this positional uncertainty on planning target
volume (PTV) margins. PTV margins must be made large
enough to ensure that the prescribed dose to the clinical target
volume (CTV) is maintained despite systematic and random
variations in treatment delivery.3
However, smaller PTV
margins are desirable in order to reduce the dose delivered to
healthy tissue, particularly for nearby organs-at-risk (OARs).
The widely used formula of van Herk et al.3
for calculating
PTV margins contains terms for both systematic preparation
errors and random variations throughout treatment. Thus,
knowledge of intrafraction motion can be used to reduce PTV
margins by accounting for a substantial component of random
variance,4
for example, by gating treatment or dynamically
updating couch5,6
or MLC positions.7–9
The impact of intrafraction motion is especially important
to consider given the recent interest in hypofractionated
radiotherapy of prostate tumors.10,11
Hypofractionation is an
attractive option for prostate tumors because the generally
accepted α/β ratio of prostate tumors is low compared to
2558 Med. Phys. 43 (5), May 2016 0094-2405/2016/43(5)/2558/11/$30.00 © 2016 Am. Assoc. Phys. Med. 2558

2559 Stevens, Parsons, and Robar: Stereoscopic and monoscopic imaging for prostate motion monitoring 2559
the surrounding organs-at-risk,12
which allows for improved
tumor cell kill with potentially fewer adverse effects. Whereas
it is typically assumed that position deviations average out
across fractions (i.e., contribute to random variation only),3
this assumption is invalid in hypofractionated treatment due to
the small number of fractions. It is thus especially important to
employ motion monitoring in hypofractionated treatment, in
order to achieve the desired tumor control and OAR sparing.
There are several techniques available for intrafraction mo-
tion monitoring, including implanted RF transponders,7,13,14
stereoscopic x-ray imaging,15–17
or monoscopic imaging.18–22
Stereoscopic techniques include kV/MV imaging using the
on-board imager (OBI) and MV beam’s eye view,17
and room-
mounted dual16
or quad23,24
kV imaging. These techniques
usually rely on implanted gold fiducial markers as prostate
surrogates. Stereoscopic kV/MV imaging has the advantage of
widespread availability; however, the fiducial markers can be
obstructedintheMVimagesbymovementsoftheMLCleaves,
and the changing view-angle can result in variable fiducial
overlap with other fiducials or bony anatomy. Room-mounted
kV systems are not affected by MLC positions and provide
a constant view angle, which makes it easier to ensure no
overlap of fiducials. However, dual kV room-mounted systems
frequently have one of their tube/detector pairs blocked by the
gantry at certain angles as it rotates around the patient (Fig. 1).
While this shortcoming is addressed by quad kV systems like
that used by Shimizu et al.,23
these systems have not been
widely adopted.
The intermittent blocking of one x-ray tube/detector by
the treatment head has presented a substantial challenge in the
implementation of intrafraction motion monitoring with room-
mounted systems, as 3D location cannot be exactly determined
from a single 2D image perspective. However, techniques for
monoscopic localization of fiducial markers have recently
been developed for OBI systems.19,22
While monoscopic
imagingonlyprovidesabsolutelocalizationintwodimensions,
F. 1. Gantry angle restrictions for our room-mounted stereoscopic imaging
system. When the gantry angle is in the red-shaded zones, the treatment head
blocks one of the two stereo x-ray panels (1 and 2) or sources (3 and 4). For
the green-shaded angles, both panels have unobstructed views of isocenter.
The exact angles available for stereo imaging will vary from setup to setup.
correlations between prostate motion in the anterior–posterior
andinferior–superiordirectionscanbeusedinordertoperform
an informed estimate of the unresolved dimension. Although
3D position estimation from monoscopic imaging is naturally
less accurate than stereoscopic localization, it can achieve sub-
mm accuracy,19
and therefore is a substantial improvement on
no intrafraction monitoring.
While monoscopic localization has been demonstrated for
OBIsystems,toourknowledgenostudieshaveinvestigatedthe
use of monoscopic localization for room-mounted kV systems.
We therefore aim to demonstrate monoscopic localization
using a room-mounted kV system. This technique alleviates
the issue of restricted gantry angles, enabling uninterrupted
intrafraction motion monitoring for room-mounted systems. In
this work, we demonstrate the accuracy of the monoscopic and
stereoscopic localization technique in phantom by comparison
with a ground-truth trajectory and assess the extra dose
delivered by the added kV imaging.
2. METHODS
We evaluated monoscopic localization accuracy using a
room-mounted dual kV imaging system. We identified three
motion monitoring schemes: (1) full stereoscopic localization,
(2) monoscopic localization (using either x-ray sources, see
Fig. 1), and (3) no imaging. In all cases, the gantry was
parked at zero degrees to prevent image obstruction, and
monoscopic image series were created retrospectively. The
no imaging scenario represents a worst case, as only the initial
setup position is known. For each scheme, we evaluated the
accuracy by comparison with prescribed phantom motion and
determined the extra imaging dose delivered for the purpose
of motion monitoring.
2.A. Motion phantom
A cylindrical gold fiducial marker (1 × 5 mm) was fixed
between two layers of an anthropomorphic phantom (ATOM
Dosimetry Phantoms, Norfolk, VA) at the approximate loca-
tion of the prostate gland (Fig. 2). The phantom was placed
on the treatment couch of the linear accelerator (Varian STx,
Varian Medical Systems, Inc.), and the alignment lasers were
used to place the fiducial marker initially at isocenter. The
Linac couch was utilized as a programmable translation stage
using Developer Mode, with real prostate motion trajectories
implemented from published Calypso-based patient data.21
Five unique trajectories of approximately 1 min duration
were implemented, including stable prostate position, slow
drift, transient excursion, persistent excursion, and frequent
excursions.21,22
For each motion trajectory, a log file of the
couch positions produced by the Linac was collected as the
ground-truth locations.
2.B. Image acquisition and analysis
Monoscopicandstereoscopicx-rayimagingwasperformed
using a room-mounted dual kV system (ExacTrac, Brainlab
Medical Physics, Vol. 43, No. 5, May 2016

F. 2. Experimental setup: (a) A fiducial marker (x) was fixed between two slabs of the anthropomorphic phantom. The phantom also contained several inserts
for optically stimulated luminescent dosimeters. (b) The phantom was placed on the Linac couch, which was used as a programmable translation stage, and
the fiducial motion was imaged using the room-mounted x-ray system. The couch motion and image data were temporally coregistered using a microcomputer
equipped with an accelerometer and two field diodes.
AG, Feldkirchen, Germany). This system consists of two x-
ray sources embedded in the floor of the treatment room,
and two ceiling mounted flat panel detectors, providing
orthogonal oblique image projections with approximately
13.5 cm field of view at isocenter (Fig. 3). Continuous images
were acquired at a rate of 1 Hz throughout each motion
trajectory, resulting in 60 images per experiment. The x-
ray tubes were set to deliver 0.63 mAs per acquisition at
a tube potential of 140 kVp, to provide adequate fiducial
contrast.
The fiducial markers were automatically detected from the
x-ray images using a maximum convolution approach.25,26
For
this purpose, a 64×64 pixel convolution kernel was created
with the central pixels set to 1, surrounded by a 1 pixel
border with a negative value, determined such that the summed
pixel value of the entire kernel is zero. When convolved with
an image, this kernel thus produces zero for features much
larger than the central kernel area, and maximal values for
features the same size and orientation as this central region.
To optimize the detection process, the angle and size of the
fiducial marker in the two projections were determined from
an initial image acquisition pair. As the acquisition geometry
is constant for room-mounted systems, this projected shape is
consistent from image to image. For each image projection, the
point of maximum convolution was taken as the image location
of the fiducial marker (i.e., [i1,j1] and [i2,j2] in Fig. 3). From the
detected image locations of the fiducials, patient coordinates
for the fiducial markers were computed via both stereoscopic
and monoscopic approaches (see the Appendix for detailed
calculations).
In order to relate the fiducial locations determined by
imaging to the known couch positions obtained from the
Linac log file, a common temporal frame of reference is
required. A custom microcomputer was built for this purpose
(Fig. 2), which included an accelerometer to detect the couch
motion, and two field diode inputs to monitor the x-ray output.
Continuous recording from each of these three devices was
performed throughout each motion monitoring experiment.
With this system, the exact timing of image acquisition
with respect to the motion trajectories was determined by
coregistering the onset of movement in the accelerometer
data to the Linac log file. The localization accuracy was
assessed by the root-mean-square (RMS) localization er-
ror (averaged across all imaging time-points), using the
Linac log file positions as ground-truth. Significance of
accuracy differences was assessed using a paired t-test of
the accuracy versus time for each localization method and
trajectory.

F. 3. The x-ray imaging geometry is specified by the spherical coordinates
of the image sources and detectors, parameterized by the polar angle “Θ,”
azimuthal angle “Φ,” source to axis (isocenter) distance (SAD), and axis to
detector distance (ADD). The image coordinate systems can be specified in
terms of pixel locations ([i1, j1] and [i2, j2]) or mm relative to the projection
of isocenter ([xim1, yim1] and [xim2, yim2], respectively). The above geometry
is then used to convert image locations to patient or room coordinates ([xp,
yp, zp]).
2.C. Measurement of imaging dose
We assessed the dose associated with the additional kV im-
ages required for motion monitoring, as any additional patient
dose represents an important consideration when adopting this
technique. For this purpose, optically stimulated luminescent
dosimeters (OSLDs, Landauer Nanodots, Chicago, IL) were
placed in prefabricated inserts at various locations in the
phantom slabs immediately above and below the fiducial
marker [Fig. 2(a)]. The OSLDs were cross-calibrated against
an ion chamber (Exradin A12, Standard Imaging, Middleton,
WI) calibrated for the same kVp and half-value layer following
TG-61.ToachievesufficientsignalontheOSLDs,thephantom
was exposed to 50 acquisitions from a single x-ray tube
operating at 140 kVp and 40 mAs. The dose from the other
tube and from stereoscopic acquisitions was then inferred by
symmetry.
2.D. MV scatter
The experiments described above were performed with the
MV treatment beam off, in order to exclude the influence of
MV scatter on accuracy of fiducial detection in the images, and
subsequently 3D localization. To ensure that the methods used
are viable in situ, we evaluated reproducibility of the fiducial
detection with the treatment beam on, using a 5×5 cm2
field
and a dose rate of 500 MU/min. We tested the two worst-case-
scenarios for MV scatter: gantry at 180◦
(when the beam is
most pointed toward the detectors) and 90◦
(where the lateral
dimension of the patient creates the most scatter). For each
gantry angle, we collected 20 images at four different kV mAs
settings (0.63, 1.0, 1.2, and 1.6 mAs). The variance in the
detected fiducial location across the 20 images was assessed
for each mAs and gantry angle pairing.
3. RESULTS
3.A. Localization accuracy
The results of motion monitoring using stereoscopic or
monoscopic imaging are shown in Fig. 4 for the various
classes of prostate motion. Stereoscopic imaging produced
very accurate localization, with less than 0.4 mm RMS error
for all five trajectories (Fig. 5). The highest RMS error for the
stereoscopic localization was for the “persistent excursion”
trajectory (0.34 ± 0.30 mm), for which there was a brief
localization error around the time of the excursion. This
error was the largest in the left–right direction, with a peak
3D mislocalization of 1.8 mm. In the trajectories with rapid
prostate motion (e.g., frequent excursions), the imaging rate
of 1 Hz can be insufficient to sample the full dynamics. While
this typically only results in small interpolation errors, higher
imaging frequency may be desirable.
Monoscopic localization also produced sub-mm accuracy
on average in 3D, in all but one case (tube 1, transient
excursion trajectory). In this case, the RMS error was only
marginally larger than 1 mm (1.1 ± 0.7 mm), largely due to
an underestimation of the excursion amplitude around t = 41 s
[Fig. 4(d)], and an overestimation of motion in the left–right
direction at the same time. A similar underestimation of
motion in the ant/post and sup/inf directions, accompanied
by a mislocalization in the left/right direction was observed
using tube 2 in the slow drift trajectory [Fig. 4(b)]. The
largest error in monoscopic localization was approximately
4 mm (tube 1, transient excursion at 41 s), but still accounted
for the majority of the relatively large (∼12 mm) and rapid
(∼5 s) excursion at that point in the trajectory. In general,
monoscopic imaging accurately detected most of the motion
in all trajectories.
For all trajectories, stereoscopic imaging produced signif-
icantly better localization accuracy than no imaging (p
< 0.001). For monoscopic imaging, all but the stable prostate
trajectory produced significantly better localization than no
imaging (p < 0.001), with no difference in the case of the stable
prostate. Stereoscopic localization was significantly more
accurate than monoscopic at the p < 0.001 level except for
the persistent excursion trajectory, which was only significant
at p < 0.05 for monoscopic tube 2. While there were significant
differences in the accuracy of the two views for monoscopic
localization, the superior view varied between trajectories.
3.B. Imaging dose
The imaging dose per mAs delivered by a single x-
ray tube is shown in Fig. 6 for a number of locations in
the slab above and below the fiducial marker. The peak
dose (15.3 ± 0.1 µGy/mAs) was observed at the posterior
of the phantom, nearest to the beam entry point. Dose was
significantly higher (p < 0.001) in the slab below the fiducial

F. 4. Actual and reconstructed fiducial marker trajectories for a variety of prostate trajectories. Examples of (top to bottom) stable prostate, slow drift, persistent
excursions, transient excursions, and high frequency excursions are shown.
(i.e.,closertothegantry),asthebeamsenterfromthisdirection
(see Fig. 3). The oblique orientation of the x-ray sources
also causes the strong dose gradient in the anterior/posterior
direction shown in Fig. 6.
The protocol in this study used 0.63 mAs per image,
resulting in 37% lower dose per image than what is shown
in Fig. 6. This was the lowest mAs setting available on
our x-ray system and produced sufficient image quality to
identify the fiducial markers. During stereoscopic imaging,
when both x-ray tubes are firing, the dose will be equivalent
to about 1.26 mAs per image pair. The total dose delivered is
proportional to the number of images acquired, which itself is
the product of imaging frequency and fraction duration. Using
1 Hz imaging as in this study, a 3 min VMAT plan would result
in a peak dose of 5.4 ± 0.1 mGy in the case of stereoscopic
imaging (worst-case-scenario).
3.C. MV scatter
With the MV beam on, it was necessary to increase
the kV tube current in order to clearly resolve the fiducial
in the images (Fig. 7). For kV tube current of 1.2 mAs
or greater, the fiducial was detected in the images with
perfect reproducibility. Although difficult to see in the raw
images, scatter was more problematic with the gantry at
90◦
than 180◦
, due to the thicker lateral dimension of the
phantom.
4. DISCUSSION
To our knowledge, this is the first report of monoscopic
motion monitoring, with estimate of 3D position, using a
room-mounted kV x-ray system. This avoids the most serious

F. 5. Accuracy of the motion monitoring techniques. The 25th to 75th per-
centiles are indicated by the boxes, with the median error shown by the white
lines. The whiskers end at the 5th and 95th percentiles, with outliers shown
with circles. For the slowly moving prostates (stable, drift, and persistent
excursions), the no imaging case results in large median errors, whereas for
the prostates with rapid dynamics (transient and frequent excursions), the
largest deviations appear as outliers. All three motion monitoring techniques
accurately account for the majority of the prostate motion.
pitfall of motion monitoring using room-mounted systems,
i.e., blocking of the x-ray tubes by the Linac treatment
head. Both stereoscopic motion and monoscopic motion
monitoring successfully reduced the intrafraction positional
uncertainty for this simulated prostate treatment. Although by
definition stereoscopic localization is capable of producing
more accurate results, monoscopic localization was able to
account for the majority of prostate motion, significantly
reducing position uncertainty. The knowledge of actual pros-
tate position throughout treatment can be used as feed-forward
to dynamic MLC (Refs. 7–9) or couch position updates5,6
in order to increase the accuracy and conformality of dose
delivery.
Our monoscopic error localization errors ranged from 0.2
to 1.1 mm RMS, with a maximum of 3.8 mm. For comparison,
stereoscopic localization errors ranged from 0.1 to 0.3 mm
RMS, with a maximum of 1.8 mm. Previous studies using
the same monoscopic localization algorithm for OBI imaging
systems found approximately 0.35 mm RMS error, with a
3.6 mm maximum error.20
Using a dynamically updated prob-
ability density function (PDF), slightly smaller RMS error was
achievable (0.22 mm),20
depending on the prostate trajectory.
A study by Poulsen et al.21
using the same prostate trajectories
as in our study found a mean RMS error of 0.3–1.0 mm, with
a maximum localization error of 2 mm. The main competitive
technique is implanted electromagnetic transponders, with
reported localization accuracy of 0.4–1.5 mm.1,7,13
Overall,
the monoscopic localization accuracy of this study com-
pares favorably with those reported previously in the litera-
ture, and the stereoscopic accuracy exceeds other available
methods.
ThepotentialimpactoftheintrafractionmonitoringonPTV
margins(MPTV)canbeestimatedusingtheformulaofvanHerk
et al.:3
MPTV = 2.5Σ+0.7σ, where Σ and σ are the systematic
and random setup variances respectively, including both inter-
fraction and intrafraction errors (e.g., σ =
√
(σ2
inter +σ2
intra)).
The potential margin reductions (∆M) afforded by resolving
intrafraction motion are thus ∆M = 0.7(σ −σmonitored), where
σmonitored includes interfraction random error, as well as the
residual variance unaccounted for by intrafraction motion
monitoring (i.e., σmonitored =
√
(σ2
inter + σ2
residual)). Taking the
value of σinter = (1.4 mm LR, 1.6 mm AP, 1.4 mm SI)
for initial setup using fiducial marker surrogates from Tanyi
et al.,4
the PTV margin reduction made possible by accounting
for intrafraction motion ranges from negligible in the stable
prostate case to (0, 1.5, 0.6 mm) in the case of the persistent
excursion. For the four relatively dynamic prostate trajectories
investigated, there was no difference between the margin
reduction for monoscopic (0, 1.1, 0.5 mm) and stereoscopic (0,
1.2, 0.5 mm) motion monitoring on average. Importantly, the
largest margin reduction was observed in the AP direction,
which is the direction of one of the principal OARs for
prostate treatment—the rectal wall. These margin reductions
would need to be facilitated by either restrictive motion
gating tolerances or (preferably) highly accurate tracking
mechanisms, such as the dynamic MLC system proposed by
Poulsen et al.8
There are several inherent advantages of the room-mounted
x-ray system compared to the OBI. With the room-mounted
system, a pretreatment imaging period (i.e., with the gantry
parked at vertical) can be used to build a patient-specific PDF
under the same geometry as will be used for monitoring.
This direct measurement of motion variance/covariance is
more efficient than the alternative probabilistic techniques
needed in the OBI case.20
Furthermore, there is also no sag
or flex corrections needed to compensate for the change in
isocenter/imager relationships as the gantry rotates. Finally,
the constant view angle simplifies the problem of detecting
the fiducial markers in the images, as there is no change in
the projection geometry, and likewise no substantial changes
in fiducial overlap with other fiducials or with background
anatomy. While both of these fiducial detection issues can be
overcome via sophisticated detection strategies [e.g., see the
work of Feldelius et al. 2011 (Ref. 27) and 2014 (Ref. 28)], the
added complexities will reduce overall sensitivity/specificity
of detection.
An additional consideration regarding imaging geometry is
that not all motions are equally important from a dosimetric
perspective. Due to the rapid fall off of typical beam profiles,

F. 6. Dose per mAs at the locations of the OSLD dosimeters in the phantom slabs above (a) and below (b) the fiducial marker. Peak dose was observed at the
posterior aspect of the phantom in the slice below the fiducial marker (i.e., closer to the gantry), due to the beam entry angle.
motion perpendicular to the beam’s-eye-view (BEV) is more
detrimental to target coverage than motion along the BEV.29,30
In the case of OBI imaging, motion along the BEV is always
resolved directly, whereas one of the axes perpendicular to
BEV is not directly observable. In the case of the room-
mounted geometry, the monoscopic image plane is at an angle
to the BEV, such that both perpendicular axes are partially
resolved. Alternatively, in-line or BEV imaging in theory is
capable of resolving all off-axis motion directly, but suffers
from MLC blockage and poor MV image contrast. A poten-
tially useful development is in-line kilovoltage imaging;31,32
however, in order to achieve the desired energy spectrum,
special Linac targets must be used, preventing this technique
from being employed during treatment. We are currently
investigating a rapidly switching target system to overcome
this issue,33
with one of the potential applications being
intrafraction imaging.
It is worth pointing out that for each trajectory, the
localization method with the highest error represents a
worst-case-scenario. In practice, gantry rotation during the
treatment fraction would necessitate toggling the tube used
for monoscopic imaging as the treatment head rotates (i.e.,
quadrants 1 and 3 versus 2 and 4 in Fig. 1), and indeed
would allow for periods of stereoscopic monitoring around
each of the cardinal angles. Thus the accuracy obtained
in a realistic implementation would be somewhere in the
middle of the range shown in Fig. 6. The added information
afforded by the intermittent stereoscopic imaging opportu-
nities could potentially be used to improve the monoscopic
localization model and should be investigated in future
studies.
In general, the monoscopic localization technique was
highly accurate in the sup/inf and ant/post directions, with
the largest errors occurring in the lateral direction. This result
is likely due to a combination of two factors: (1) motion
in the left/right directions is much less correlated with the
other two dimensions and is thus less certain to infer from the
2D measurement, and (2) the geometry of the room-mounted
imaging system is such that (unlike the lab-frame covariance
matrix), the rotated covariance matrix has no near-zero entries.
Because of this latter point, variance in the sup/inf and ant/post
directions tends to get projected somewhat into the lateral
dimension.
The added dose to patients of approximately 5 mGy per
fraction is low in the context of a typical 2 Gy fraction. Over
the course of a typically fractionated treatment, this could add
up to as much as 20 cGy, or 10% of a single fraction dose,
assuming conventional fractionation. This result is comparable
to previous estimates of 10–15 cGy from 1 Hz imaging over the
course of a VMAT treatment using OBI imaging.34
The only
published data on ExacTrac imaging dose available estimate
0.551 mGy entrance dose per image at 140 kVp and 15 mAs,35
or equivalently 37 µGy/mAs. This is about 2.5 times our
observed dose at the depth of the rectum, which is consistent
with the PDD at this depth and energy.36
Any increase in the image rate or treatment time changes
to the imaging technique (kVp or mAs), or added pretreat-
ment imaging can increase the imaging dose. However, in
hypofractionatedtreatment,thetotaltreatmenttimeistypically
reduced, which lowers the relative contribution of imaging
dose for a fixed image frequency.34
Thus hypofractionated
regimens are not only the best candidate for prostate motion

F. 7. Reproducibility of fiducial detection in the presence of MV scatter, for gantry angles of (a) 90◦ and (b) 180◦. A small ROI of representative raw images
around the fiducial marker is shown in the top rows of (a) and (b). The mean ± standard deviation of the detected fiducial location (xi, yi) was determined from
20 replications of the images at each of four tube current levels (bottom rows). At 0.63 mAs, the fiducials are obscured by the MV scatter contribution, resulting
in unreliable fiducial detection. For 1.2 mAs or higher, the fiducial is reliably detected at both gantry angles.
monitoring, but benefit the most from the added localization
certainty.
In this study, we initially ignored the influence of MV
scatter on image quality, and subsequently on the accuracy
of fiducial detection and localization. It has previously been
shown for OBI imaging that accurate fiducial detection is
achievable even at high MV dose rates,27,28
and the increased
isocenter-to-detector distance of the ceiling mounted panels
should further reduce the added scatter noise. Nonetheless,
the presence of MV scatter noise necessitated increased
mAs to maintain adequate image quality. Our results suggest
that tube current of approximately 1.2 mAs would produce
sufficient image quality for typical MV dose rates and field
sizes. While this would approximately double the imaging
dose, the result would still only represent 0.5% of a typical
treatment fraction and could in principle be accounted for
during treatment planning. Additionally, the dose estimates
above were produced using the conservative assumption of
constant stereoscopic imaging, which in practice would be
reduced by almost half given the large range of gantry angles
for which monoscopic imaging would be used. A more
sophisticated approach would be to modulate the kV imaging
technique as a function of gantry angle and (MLC-modulated)
field size in order to provide constant image quality while
minimizing accumulated dose, but this is outside the scope of
this paper.

F. 8. Illustration of (a) stereoscopic and (b) monoscopic localization
schemes employed (shown in 2D for simplicity of illustration). Stereoscopic
localization finds the intersection point (black circle) of the ray lines con-
necting the detected image locations (i1,i2) of the fiducials (grey filled
circles) with the corresponding source locations (s1 and s2, respectively).
Monoscopic localization finds the maximum likelihood position (black cir-
cle) along the single ray line connecting the detected image location and
source point using a PDF derived from the motion covariances (Px, y).
Monolocalization and stereolocalization modes can be toggled in real time
depending on which imaging panels have an unobstructed view of the fiducial
markers.
5. CONCLUSION
We have implemented both stereoscopic and monoscopic
motion monitorings using a room-mounted kV imaging
system. The availability of both localization modes allows
continuous 3D localization despite the wide range of angles
over which the treatment head may obstruct one of the x-
ray tubes and detectors. The motion monitoring accuracy
rivals that available with other published methods and is
superior when stereoscopic views are available. Accurate
intrafraction prostate localization is especially beneficial for
hypofractionated treatment where movement of the target
volume can have critical dosimetric impact.
ACKNOWLEDGMENTS
The authors would like to acknowledge financial support
from Varian Medical Systems and technical support from
Brainlab AG. Lee MacDonald provided guidance on using
developer mode for driving motion trajectories and Dr.
Mike Sattarivand who contributed details on the geometry
of their specific ExacTrac system setup. The authors also
recognize valuable contribution from machinist John Noddin
for creating the custom OSLD inserts for their phantom
experiments.
APPENDIX: LOCALIZATION CALCULATIONS
1. Stereoscopic localization
To find patient coordinates (r = [xp,yp,zp]) of the fiducial
marker using stereoscopic localization (rstereo), the method of
Brost et al.15
is followed. Using the geometry shown in Fig. 3,
the image locations (p1 = [i1,j1,0] and p2 = [i2,j2,0], in pixels)
are first converted to room coordinates (d1 = [xd1,yd1,zd1]
and d2 = [xd2,yd2,zd2] respectively). For example, for the first
detector,
d1 = R·[(p1 −po1)◦dp]+do1 = R·

xim1
yim1
0

+do1, (A1)
where R is the rotation matrix that aligns unit vectors in
the detector plane with the room coordinate system (see
Fig. 3), po1 = [io1,jo1,0] is the pixel coordinates of the projected
isocenter, dp = [dx,dy,0] is the vector of pixel dimensions,
and do1 = [xo1,yo1,zo1] are the room coordinate for the pro-
jectedisocenter(i.e.,ADD∗
[cos Θ cos Φ, cos Θ sin Φ, cos Θ]).
Points (r1 = [xp1,yp1,zp1]) on the line connecting the de-
tected point with the source location (s1 = [xs1,ys1,zs1]
= SAD∗
[−cos Θ cos Φ, −cos Θ sin Φ, −cos Θ]) can then be
parameterized as
r1 = d1 +m1(s1 −d1) = d1 +m1a1, (A2)
where m1 governs the distance along the ray line from the
detector. Likewise for the line connecting the second detector
and source,
r2 = d2 +m2a2. (A3)
The location of the fiducial marker is the point at which these
two lines intersect (Fig. 8), and thus
d1 +m1a1 = d2 +m2a2 (A4)
or equivalently
d = A·

m1
−m2

, (A5)
where d = d2 −d1 and A = [a1,a2]. In practice the two ray lines
willnotintersectperfectlyduetofinitemeasurementprecision;
however, an approximate solution to this equation is given by
finding the pseudo-inverse for A A†
,
A†
= AT
·A
−1
·AT
, (A6)
yielding

m1
−m2

= A†
d. (A7)
The values of m1 and m2 are then used to estimate the two
(ideally equivalent) world points (r1 and r2), and the mean of
these is used as the final stereoscopic localization rstereo.
2. Monoscopic localization
The algorithm employed for 3D localization from mono-
scopic imaging relies on a priori information in the form
of motion covariances “C” (Fig. 8), which can be obtained
directly from stereoscopic localization pretreatment, or from

published population averages,19
C =

varx covx y covxz
covx y vary covyz
covxz covyz varz

=

0.3163 −0.0775 0.0114
−0.0775 2.4733 1.5051
0.0114 1.5051 1.8820

mm2
. (A8)
This covariance matrix can be used to determine a Gaussian
PDF for the fiducial locations (P(x,y,z)),
P(x,y,z) =

det(C−1)
8π3
e−rTC−1r/2
(A9)
or in the coordinate system rotated to be parallel to the image
plane,
Prot(xrot,yrot,zrot) =

det(C−1)
8π3
e−rT
rotR−1C−1Rrrot/2
. (A10)
Identifying the matrix elements of the rotated covariance as
R−1
C−1
R =

Arot Drot/2 Erot/2
Drot/2 Brot Frot/2
Erot/2 Frot/2 Crot

. (A11)
Poulsen et al.19
showed that the expectation value for the
position along the axis perpendicular to the imaging plane
(⟨zrot⟩) is
⟨zrot⟩ = SAD

Arot
( xim
SDD
)2
+ Brot
( yim
SDD
)2
+ Drot
ximyim
SDD2
− Erot
xim
2·SDD
−Frot
yim
2·SDD

σ2
, (A12)
where SDD is the source-to-detector distance (i.e., SDD =
SAD+ADD) and σ is the standard deviation,
σ =

Arot
( xim
SDD
)2
+ Brot
( yim
SDD
)2
+Crot
+ Drot
ximyim
SDD2
−Erot
xim
SDD
−Frot
yim
SDD
−1/2
. (A13)
By appropriately scaling the image coordinates ([xim,yim])
according to zrot, we obtain the (rotated) 3D location of the
fiducial marker (rrot = [xrot,yrot,zrot]),
xrot = xim(SAD− zrot)/(SAD+ADD), (A14)
yrot = yim(SAD− zrot)/(SAD+ADD). (A15)
Finally, the monoscopic localization coordinates (rmono) are
obtained by applying the rotation matrix (i.e., rmono = R·rrot).
1H. S. Li, I. J. Chetty, C. A. Enke, R. D. Foster, T. R. Willoughby, P. A.
Kupellian, and T. D. Solberg, “Dosimetric consequences of intrafraction
prostate motion,” Int. J. Radiat. Oncol. 71(3), 801–812 (2008).
2S. Hossain, P. Xia, C. Chuang, L. Verhey, A. R. Gottschalk, G. Mu, and L.
Ma, “Simulated real time image guided intrafraction tracking-delivery for
hypofractionated prostate IMRT,” Med. Phys. 35(9), 4041–4048 (2008).
3M. van Herk, P. Remeijer, C. Rasch, and J. V. Lebesque, “The probability
of correct target dosage: Dose-population histograms for deriving treatment
margins in radiotherapy,” Int. J. Radiat. Oncol. Biol. Phys. 47(4), 1121–1135
(2000).
4J. A. Tanyi, T. He, P. A. Summers, R. G. Mburu, C. M. Kato, S. M. Rhodes,
A. Y. Hung, and M. Fuss, “Assessment of planning target volume margins for
intensity-modulated radiotherapy of the prostate gland: Role of daily inter-
and intrafraction motion,” Int. J. Radiat. Oncol. 78(5), 1579–1585 (2010).
5W. D. D’Souza, S. A. Naqvi, and C. X. Yu, “Real-time intra-fraction-motion
tracking using the treatment couch: A feasibility study,” Phys. Med. Biol.
50(17), 4021–4033 (2005).
6P. Qiu, W. D. D’Souza, T. J. McAvoy, and K. J. Ray liu, “Inferential modeling
and predictive feedback control in real-time motion compensation using the
treatment couch during radiotherapy,” Phys. Med. Biol. 52(19), 5831–5854
(2007).
7A. Sawant, R. L. Smith, R. B. Venkat, L. Santanam, B. Cho, P. Poulsen,
H. Cattell, L. J. Newell, P. Parikh, and P. J. Keall, “Toward submillimeter
accuracy in the management of intrafraction motion: The integration of real-
time internal position monitoring and multileaf collimator target tracking,”
Int. J. Radiat. Oncol. 74(2), 575–582 (2009).
8P. R. Poulsen, W. Fledelius, B. Cho, and P. Keall, “Image-based dynamic
multileaf collimator tracking of moving targets during Intensity-modulated
arc therapy,” Int. J. Radiat. Oncol. 83(2), e265–e271 (2012).
9P. J. Keall, H. Cattell, D. Pokhrel, S. Dieterich, K. H. Wong, M. J. Murphy,
S. S. Vedam, K. Wijesooriya, and R. Mohan, “Geometric accuracy of a
real-time target tracking system with dynamic multileaf collimator tracking
system,” Int. J. Radiat. Oncol. 65(5), 1579–1584 (2006).
10W. R. Lee, “Prostate cancer and the hypofractionation hypothesis,” J. Clin.
Oncol. 31(31), 3849–3851 (2013).
11N.-S. Hegemann, M. Guckenberger, C. Belka, U. Ganswindt, F. Manapov,
and M. Li, “Hypofractionated radiotherapy for prostate cancer,” Radiat.
Oncol. 9(1), 275–290 (2014).
12S. M. Bentzen and M. A. Ritter, “The α/β ratio for prostate cancer: What is
it, really?,” Radiother. Oncol. 76(1), 1–3 (2005).
13T. R. Willoughby, P. A. Kupelian, J. Pouliot, K. Shinohara, M. Aubin, M.
Roach, L. L. Skrumeda, J. M. Balter, D. W. Litzenberg, S. W. Hadley, J. T.
Wei, and H. M. Sandler, “Target localization and real-time tracking using the
Calypso 4D localization system in patients with localized prostate cancer,”
Int. J. Radiat. Oncol. 65(2), 528–534 (2006).
14T. Mate, D. Krag, J. Wright, and S. Dimmer, “A new system to perform
continuous target tracking for radiation and surgery using non-ionizing alter-
nating current electromagnetics,” Int. Congr. Ser. 1268, 425–430 (2004).
15A. Brost, N. Strobel, L. Yatziv, W. Gilson, B. Meyer, J. Hornegger, J. Lewin,
and F. Wacker, “Accuracy of x-ray image-based 3D localization from two
C-arm views: A comparison between an ideal system and a real device,”
Proc. SPIE 7261, 72611Z (2009).
16M. S. Hoogeman, J. J. Nuyttens, P. C. Levendag, and B. J. M. Heijmen,
“Time dependence of intrafraction patient motion assessed by repeat stereo-
scopic imaging,” Int. J. Radiat. Oncol. 70(2), 609–618 (2008).
17R. D. Wiersma, W. Mao, and L. Xing, “Combined kV and MV imaging
for real-time tracking of implanted fiducial markers,” Med. Phys. 35(4),
1191–1198 (2008).
18J. Adamson and Q. Wu, “Prostate intrafraction motion evaluation using kV
fluoroscopy during treatment delivery: A feasibility and accuracy study,”
Med. Phys. 35(5), 1793–1806 (2008).
19P. R. Poulsen, B. Cho, K. Langen, P. Kupelian, and P. J. Keall, “Three-
dimensional prostate position estimation with a single x-ray imager utiliz-
ing the spatial probability density,” Phys. Med. Biol. 53(16), 4331–4353
(2008).
20P. R. Poulsen, B. Cho, and P. J. Keall, “Real-time prostate trajectory esti-
mation with a single imager in arc radiotherapy: A simulation study,” Phys.
Med. Biol. 54(13), 4019–4035 (2009).
21P. R. Poulsen, B. Cho, A. Sawant, and P. J. Keall, “Implementation of a new
method for dynamic multileaf collimator tracking of prostate motion in arc
radiotherapy using a single kV imager,” Int. J. Radiat. Oncol. 76(3), 914–923
(2010).
22J. A. Ng, J. T. Booth, P. R. Poulsen, W. Fledelius, E. S. Worm, T. Eade, F.
Hegi, A. Kneebone, Z. Kuncic, and P. J. Keall, “Kilovoltage intrafraction
monitoring for prostate intensity modulated arc therapy: First clinical re-
sults,” Int. J. Radiat. Oncol. 84(5), e655–e661 (2012).
23S. Shimizu, H. Shirato, K. Kitamura, N. Shinohara, T. Harabayashi, T.
Tsukamoto, T. Koyanagi, and K. Miyasaka, “Use of an implanted marker
and real-time tracking of the marker for the positioning of prostate and
bladder cancers,” Int. J. Radiat. Oncol. Biol. Phys. 48(5), 1591–1597
(2000).

24K. Kitamura, H. Shirato, Y. Seppenwoolde, T. Shimizu, Y. Kodama, H.
Endo, R. Onimaru, M. Oda, K. Fujita, S. Shimizu, and K. Miyasaka, “Tu-
mor location, cirrhosis, and surgical history contribute to tumor movement
in the liver, as measured during stereotactic irradiation using a real-time
tumor-tracking radiotherapy system,” Int. J. Radiat. Oncol. 56(1), 221–228
(2003).
25A. Nederveen, J. Lagendijk, and P. Hofman, “Detection of fiducial gold
markers for automatic on-line megavoltage position verification using a
marker extraction kernel (MEK),” Int. J. Radiat. Oncol. Biol. Phys. 47(5),
1435–1442 (2000).
26E. J. Harris, H. A. McNair, and P. M. Evans, “Feasibility of fully automated
detection of fiducial markers implanted into the prostate using electronic
portal imaging: A comparison of methods,” Int. J. Radiat. Oncol. 66(4),
1263–1270 (2006).
27W. Fledelius, E. Worm, U. V. Elstrøm, J. B. Petersen, C. Grau, M. Høyer,
and P. R. Poulsen, “Robust automatic segmentation of multiple implanted
cylindrical gold fiducial markers in cone-beam CT projections,” Med. Phys.
38(12), 6351–6361 (2011).
28W. Fledelius, E. Worm, M. Høyer, C. Grau, and P. R. Poulsen, “Real-time
segmentation of multiple implanted cylindrical liver markers in kilovolt-
age and megavoltage x-ray images,” Phys. Med. Biol. 59(11), 2787–2800
(2014).
29S. Nill, J. Unkelbach, L. Dietrich, and U. Oelfke, “Online correction for
respiratory motion: Evaluation of two different imaging geometries,” Phys.
Med. Biol. 50(17), 4087–4096 (2005).
30Y. Suh, S. Dieterich, and P. J. Keall, “Geometric uncertainty of 2D projec-
tion imaging in monitoring 3D tumor motion,” Phys. Med. Biol. 52(12),
3439–3454 (2007).
31Y. Dzierma, F. G. Nuesken, N. P. Licht, and C. Ruebe, “Dosimetric prop-
erties and commissioning of cone-beam CT image beam line with a carbon
target,” Strahlenther. Onkol. 189(7), 566–572 (2013).
32J. Rottmann, P. Keall, and R. Berbeco, “Real-time soft tissue motion esti-
mation for lung tumors during radiotherapy delivery,” Med. Phys. 40(9),
091713 (7pp.) (2013).
33R. I. Berbeco, A. Detappe, P. Tsiamas, D. Parsons, M. Yewondwossen, and
J. Robar, “Low Z target switching to increase tumor endothelial cell dose
enhancement during gold nanoparticle-aided radiation therapy,” Med. Phys.
43(1), 436–442 (2016).
34J. K. Crocker, J. A. Ng, P. J. Keall, and J. T. Booth, “Measurement of patient
imaging dose for real-time kilovoltage x-ray intrafraction tumour posi-
tion monitoring in prostate patients,” Phys. Med. Biol. 57(10), 2969–2980
(2012).
35M. J. Murphy, J. Balter, S. Balter, J. A. BenComo, I. J. Das, S. B. Jiang,
C.-M. Ma, G. H. Olivera, R. F. Rodebaugh, K. J. Ruchala, H. Shirato,
and F.-F. Yin, “The management of imaging dose during image-guided
radiotherapy: Report of the AAPM Task Group 75,” Med. Phys. 34(10),
4041–4063 (2007).
36D. Parsons and J. L. Robar, “An investigation of kV CBCT image quality and
dose reduction for volume-of-interest imaging using dynamic collimation,”
Med. Phys. 42(9), 5258–5269 (2015).

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