EVOLUTION OF FRACTIONATION AND

CONVENTIONAL FRACTIONATION

DR NIKHIL SEBASTIAN

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 several days.

Single fraction RT became possible in 1914 after the invention of coolidge cathode tube.

High output

Adjustable tube current

Reproducible exposures.

The following ten years was a period of uncertainty about the proper way to fractionate.

2 schools of thought

ERLANGEN

PARIS

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.

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.

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.

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.

Sparing effect

Repair Repopulation of surviving clonogenic cells

Re-oxygenation

Redistribution or reassortment within the cell cycle

Lethal effects

Survival curve- cross over

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

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.

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....

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.

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.

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.

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 exceeded.

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.

REDISTRIBUTION

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.

Though theoretically possible, no practical advantage has been demonstrated becaus eof redistribution..

Hence potential effects of redistribution are generally ignored while deisgning fractionation.

TDF models...

The parameters that determine the N tissue tolerance are:

Overall treatment time Total dose 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 recations.

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

Acute reaction Rate of dose accumulation (frequency)

Fraction size (dpf)Late reaction

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.

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.

Lines parallel. So same slope,

m=0.33 Total dose for an

isoeffect prop to T raise to 0.33

CUBE ROOT LAW

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.

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 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

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.

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.

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.

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.

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

Unit of CRE is reu (radiation effect unit)

Though CRE avoids the use of PT, it is still mathematically complex.

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.

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.

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.

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:

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)

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.