1. EVOLUTION OF FRACTIONATION
AND
CONVENTIONAL
FRACTIONATION
DR NIKHIL SEBASTIAN

2. 
From the very
beginning of RT
treatments were
fractionated.

Primitive Xray
machines were
crude with low
output.

So delivery of a
single tumoricidal
dose would require
Single fraction RT
became possible in
1914 after the
invention of
coolidge cathode
tube.
High output
Adjustable tube
current
Reproducible

3. 
The following ten
years was a period
of uncertainty about
the proper way to
fractionate.

2 schools of
thought
ERLANGEN
PARIS

4. Erlangen

He believed
fractionated
treatments to be
inferior

Argued that a single
dose was
necessary to cure
cancer

BERGONIE
TRIBONDEAU
LAW
Rapidly growing
tumor cells were
metablocally more
active- Better able
to recover from
injury.
The recovery will
favor tumor cells if
the tumoricidal
dose is not applied
in the first
treatment.

5. Paris school

Usedradiobiological
experments of
regaud to justify
fractionation.

He showed that a
ram's testis could not
be sterilized by a
single fraction
without causing
significant skin
reaction.
But sterilization was
possible with
fractionated Rt
without damage to
scrotal skin.
The reasoning was
wrong. But
conclusion stood
valid.

6. 
FRACTIONATION OF RADIATION
PRODUCED BETTER TUMOR CONTROL
FOR A GIVEN LEVEL OF NORMAL
TISSUR TOXICITY THAN A SINGLE
LARGE DOSE.

Henry Coutard published his excellent
results with fractionated RT in 1932.

7. RATIONALE FOR
FRACTIONATION

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.

8. Sparing
effect
Repair Repopulation
of surviving
clonogenic
cells
Re-
oxygenation
Redistributi
on or
reassortme
nt within the
cell cycle
Lethal
effects

9. Survival curve- cross over

10. REPAIR

Most imp of all 4Rs in terms of rationale for
#n

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

11. 
a/b represnts curviness of the survival curve.

Tumor cell-->High a/b --> starighter curve.

Late reacting N tissue--> low a/b--> curvier
survival curves.

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.

12. 
So delivery of dose >5Gy is destructive to N
tissue than tumor cells.

But doses >5 Gy is required for tumor cell kill.

2 ways:

One- To deliver high doses to tumor alone and
avoiding the normal tissues by techniques like
SRS.

Two- To fractionate....

13. 
With fractionated
RT, if sufficient time
is allowed btw #, all
sub lethally
damaged cells
would be repaired
before next
exposure.

So surviving
fraction (SF) for
each succesive
treatment would be
identical.
Hence the shape of
the CSC would
repeat for each #.
If the dose for each
# is below the cross
over value, there is
increased tumor
cell damage and
death with each
fraction. Hence the
curves separate
from each other.

15. 
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
2.5 Gy.

16. REPOPULATION

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.

17. 
The repopulation principle dictates that a
course of RT should not be overly
prolonged.

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

18. REOXYGENATION

O2 – most powerful radiation sensitizer.

Hypoxic cells relatively rdaioresisitant

3 times more dose- would exceed N tisssue
tolerance.

When time givenbtw exposures-->
decrease in the no of hypoxic cells--> can
be handled by a dose without exceeding
tolerance.

19. REDISTRIBUTION

20. 
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
os redistribition.

21. 
Though theoretically possible, no practical
advantage has been demonstrated becaus
eof redistribution..

Hence potential effects of redistribution are
generally ignored while deisgning
fractionation.

22. TDF models...

The parameters that determine the N tissue
tolerance are:

Overall treatment time

Total dose

Dose per fraction

Frequency of fractions.

23. 
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
recations.

After a/c reactions peak, further trtmt-->
longer duartion to heal--> late injury.

24. Acute reaction Rate of dose
accumulation
(frequency)
Fraction size (dpf)Late reaction

25. 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
regimen.

26. Strandquist plot

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.

27. Lines parallel.

So same slope,
m=0.33

Total dose for an
isoeffect prop to T
raise to 0.33

CUBE ROOT LAW

28. COHEN

He summarized a
body of clinical data
in which erythema,
skin danage and
tumor control of
skin cells, were
documented for
trtmt times from 1 to
40 days.

29. 
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

30. When T and N changed
separately?

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
x T0.24
= T0.35.

By not treating on weekends this will be reduced to T0.33

31. The constant NSD is Nominal Standard
Dose.
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
.N-0.24
Unit of NSD is RET( Roentgen Eqquivalent
Therapy).
NSD can be used to compare two
fractionation regimes.

32. Limitaitions of Elllis formula
Was based on early Xray damage to skin & for trtmt
upto 6 weeks. So cannot be applied for:
1.Late effects.
2.For other normal tissue effects that limit maximum
dose.
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.

33. 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
dpf.
Time factor is underestimated for tumor and
acutely responding tissues but
overestimated for late reacting tissues.

34. Partial tolerance- Winston et al
NSD is not linearly additive- complex
calculations.
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.

35. 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
. T-0.11
d(dpf) = D/N ; x(avg time btw #)= T/N
CRE= d. N0.65
. X-0.11
CRE prop N0.65
CRE1/0.65
prop N
CRE1.538
prop N
Hence linearly additive

36. Unit of CRE is reu (radiation effect unit)
Though CRE avoids the use of PT, it is still
mathematically complex.

37. TDF factor- orton and ellis
TDF factor is derived from the basic NSD
equation.
TDF= N. d1.538
. X-0.169
. 10-3
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
NSD problem.

38. In split course regimes, overall effect= sum of
TDF factors.
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.

39. Thus effectiveness of a split course regime =
TDF1 [T/T+R]0.11
+ TDF2
Experimental evidence suggested the
importance of dpf implied that underlying
cell survival curve was of linear quadratic
form.

40. LQ model
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
expressed as:

41. E= n [ad+ bd2
]
=nd[a+bd]
=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
Dose (BED)

42. 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.