Evolution of Fractionation and Conventional Fractionation in Radiotherapy
EVOLUTION OF FRACTIONATION
DR NIKHIL SEBASTIAN
From the very
beginning of RT
crude with low
So delivery of a
dose would require
Single fraction RT
became possible in
1914 after the
The following ten
years was a period
of uncertainty about
the proper way to
2 schools of
treatments to be
Argued that a single
necessary to cure
tumor cells were
active- Better able
to recover from
The recovery will
favor tumor cells if
dose is not applied
in the first
regaud to justify
He showed that a
ram's testis could not
be sterilized by a
But sterilization was
without damage to
The reasoning was
FRACTIONATION OF RADIATION
PRODUCED BETTER TUMOR CONTROL
FOR A GIVEN LEVEL OF NORMAL
TISSUR TOXICITY THAN A SINGLE
Henry Coutard published his excellent
results with fractionated RT in 1932.
The effect of rdaiation is based on the
difference in cell kinetics between normal
cells and tumor cells.
When a given dose is split into fractions,
the biological effect always decreases for
both tumor cells and normal cells.
nt within the
Most imp of all 4Rs in terms of rationale for
The capability of a tissue type to repair SLD
is indicated by its a/b value
Low a/b (high b) --> high capability of repair
Normal tissue --> low a/b
Tumor cells --> high a/b
a/b represnts curviness of the survival curve.
Tumor cell-->High a/b --> starighter curve.
Late reacting N tissue--> low a/b--> curvier
The survival curves for normal tissue and
tumor cells cross at 2to 5 Gy.
Below the cross over normal tissue has
increased survival. Above --> the reverse.
So delivery of dose >5Gy is destructive to N
tissue than tumor cells.
But doses >5 Gy is required for tumor cell kill.
One- To deliver high doses to tumor alone and
avoiding the normal tissues by techniques like
Two- To fractionate....
RT, if sufficient time
is allowed btw #, all
would be repaired
fraction (SF) for
treatment would be
Hence the shape of
the CSC would
repeat for each #.
If the dose for each
# is below the cross
over value, there is
cell damage and
death with each
fraction. Hence the
from each other.
The optimal dpf is
that which produces
max separation of
the 2 curves.
This ocurs at
around 50% of the
cross over dose.
So optimal dpf is 1 to
All cancers contain dividing cells at a much
faster rate than normal tissue.
During a course of RT there s considerable
repopulation of cancer cells.
Longer the course of RT, the more difficult it
becomes to control tumor without
exceeding normal tissue tolerances.
Faster rates of division kicks in after 1st 2
to 4 weekd of fractionated XRT.
The repopulation principle dictates that a
course of RT should not be overly
But it is not entirely detrimental. Acutely
respomding normal tissues need to
repopulate during a course of RT to avoid
exceeding acute tolerance.
Hence fractionation must be such that it
does not allow too much time for excessive
repopulation, but at the same time not
treating so fast that a/c tolernace is
O2 – most powerful radiation sensitizer.
Hypoxic cells relatively rdaioresisitant
3 times more dose- would exceed N tisssue
When time givenbtw exposures-->
decrease in the no of hypoxic cells--> can
be handled by a dose without exceeding
Cells surviving single dose of treatment –
partially synchronized with over abundance
of cells in the S phase.
If the 2nd dose is delivered after some
time, the remaining cells will be most
sensitive if the they have travelled over the
time to M phase.
This radiation induced partial
synchronization is known as reassortment
Though theoretically possible, no practical
advantage has been demonstrated becaus
Hence potential effects of redistribution are
generally ignored while deisgning
The parameters that determine the N tissue
Overall treatment time
Dose per fraction
Frequency of fractions.
The intensity of acute reactions reflect the
balance btw the rate of celll killing and the
rate of regeneration by surviving cells.
This depends primarily on rate of dose
accumulation ( frequency).
Late reactions are determined more by the
fraction size. It has lesser impact on acute
After a/c reactions peak, further trtmt-->
longer duartion to heal--> late injury.
Importance of tdf models
1. to calculate new total dose required to
keep biological effectiveness when
conventional frcationation is altered.
2. to compare diff trtmt techniques that
differ in no of #, dpf, and overall trtmt time.
3. To strive for optimal fractionation
Attempts to relate tumor and N tissue
effects to overall time and total dose started
early 20th century.
Isoeffect curves are a set of curves which
relate total dose to overall trtmt time for
definite effects of radiation.
He showed that isoeffect curves on a log-
llog plot formed straight lines.
So same slope,
Total dose for an
isoeffect prop to T
raise to 0.33
CUBE ROOT LAW
He summarized a
body of clinical data
in which erythema,
skin danage and
tumor control of
skin cells, were
trtmt times from 1 to
Isoeffect curve for tumor control had a
smaller slope, m=0.22.
This means as the traetment time is
increased, tumor control comes closer to
the maximum tolerated skin dose.
i.e. Tumor control can be achieved with
less normal tissue damage.
D prop to cubic root of N0
T prop to N
When T and N changed
Frank Ellis, British, 1969
Cube root law was the result of biological effect that were
functions of N and T
N was about twice as imp as T in influencing the dose at
which the skin reactions occured.
D= NSD. T 0.11. N 0.24
This correlated well with Strandquist’s data. i.e. For
traeting once a day, everyday. T0.11
By not treating on weekends this will be reduced to T0.33
The constant NSD is Nominal Standard
NSD is a constant of proportionality which
can be thought of as a bioeffective dose i.e.
dose corrected for time and fractionation.
NSD= D. T-0.11
Unit of NSD is RET( Roentgen Eqquivalent
NSD can be used to compare two
Limitaitions of Elllis formula
Was based on early Xray damage to skin & for trtmt
upto 6 weeks. So cannot be applied for:
2.For other normal tissue effects that limit maximum
3.For n<4 or >30
4.For high Let rdaiation.
5.Not linearly additive
6.Does not allow for explanation of important
differences btw early and late effects in fr. RT.
Fe plot- Douglas and Fowler.
Showed that the total dose required to
produce a constant effect was related to
dose per fraction.
The xponent of N, 0.24 does not predict the
severe late damage that occur with large
Time factor is underestimated for tumor and
acutely responding tissues but
overestimated for late reacting tissues.
Partial tolerance- Winston et al
NSD is not linearly additive- complex
Partial tolerance PT = N/ Ntol . NSD
N= No of # actually delivered
Ntol= No of # required to reach full tolerance.
Partial tolerance reflects the biological effect
of a regimen which does not take the tissue
to tolerance levels.
PT prop to N. hence linearly additive.
CRE- Kirk et al
The biological effect can be described from the original
strandquists plot without introducing NSD or PT.
Cumulative radiation effect= NSD at tolerance levels.
CRE= D. N-0.24
d(dpf) = D/N ; x(avg time btw #)= T/N
CRE= d. N0.65
CRE prop N0.65
Hence linearly additive
Unit of CRE is reu (radiation effect unit)
Though CRE avoids the use of PT, it is still
TDF factor- orton and ellis
TDF factor is derived from the basic NSD
TDF= N. d1.538
TDF independent of NSD
For a fixed d and x TDF is a lineara fraction of
N and hence linearly additive.
TDF tables are available for rapid solution of
In split course regimes, overall effect= sum of
Allowance must be made for the repopulation
during the break- Decay factor.
Decay factor is applied to initial TDF to
calculate TDF after a break.
Decay factor = [T/T+R]0.11
T= time from beginning of RT to break.
R= rest interval in days.
Thus effectiveness of a split course regime =
Experimental evidence suggested the
importance of dpf implied that underlying
cell survival curve was of linear quadratic
LQ model of fractionation is a direct derivation
from LQ survival curves.
It is a mechanistic model based on the
mechanism of R interaction with biological
systems. Hence it can be applied to a crude
range of fractionation.
According to this model biological
effectiveness of fractionated RT is
E= n [ad+ bd2
=a. nd. [1+d/a/b]
E/a= D [1+ d/a/b]
= Dose x relative effectiveness.
The term E/a is termed Biological effective
BED is the dose which when delivered in an infinitely
large number of infinitely small dpf produce the
biological end point in question.
BED is a single value indiacting biological
effectiveness in a frcationated regimen.
This model has gained popularity over other models
because it is simple and tissue specific.
Early and late effcts are separately estimated.
The a/b values of early and late effects are different.
A particular slide catching your eye?
Clipping is a handy way to collect important slides you want to go back to later.