Extracting patient-specific radiobiological parameters for adaptive radiotherapy of lung cancer

An Tai, Elizabeth Gore, X. Allen Li

Medical College of Wisconsin, Milwaukee

Oct. 6, 2012 Milwaukee, WI 1

Introduction

A 5-year control rate of 12%, 35% and a 5-year overall survival rate of 4%,22% for lung cancer patients receiving 63-69, 74-84 Gy in 2.1 Gy/fx Kong, FM et al IJROBP 2005;63:324-333.

Mean decreases in CT and PET NSCLC volumes were 26% and 44%, respectively at 40-50 Gy. Kong FM et al IJROBP 2009; 73, 1228–1234

RTOG 1106 was initiated to replan after 50 Gy based on mid-PET/CT escalating dose to as high as OARs can tolerate (<86 Gy)

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Comparison of pre- and dur-images for RTOG 1106

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CT1GTV= 132 cc; CT2GTV=96 GTV ----- reduced by 27%

PET1GTV=84 cc; PET2GTV=39 ----- reduced by 54%

Allow dose escalation to 80.4 Gy

The strategy currently used is to adapt the treatment to the morphologic changes during treatment.

Is it possible to include tumor radiobiological information of an individual patient into the adaptive plan ?

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Cell survival curves and in-vivo radiobiological parameters

2M A MD D

S e

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The 1st treatment The last treatment

Daily IGRT provides an opportunity to probe the radiobiological properties

of a tumor.

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Tumor volume regression data acquired during RT may be

used to extract individualized radiobiological parameters for a

patient such that the radiobiological properties of a tumor can

be considered in the adaptive plan

An assumption:

A model including 4 Rs –

repair,repopulation,reassortment and reoxygenation

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Td

eS)

/1(

Reassortment and reoxygenation ---- redistribution

of radiosensitive and radioresistant cells in tumor

during RT

The first 2 Rs have been included in the LQ model

We propose that tumor cells comprise both radiosensitive

and radioresistant components and a dynamic equilibrium

exists between these two components before RT.

Two-compoment model:

Model formulism

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The tumor cells are divided into 4 groups after 1st radiation treatment. They are:

(1) percentage of survived radiosensitive cells

(2) percentage of survived radioresistant cells

(3) percentage of damaged radiosensitive cells

(4) percentage of damaged radioresistant cells

These terms can be calculated using the LQ model.

sS1

rS1sD1rD1

rr

ss

ddr

dds

ShD

ShD

heS

ehS

rr

ss

11

11

)(

1

)(

1

1

)1(

h

rsrs DDSSV 11111

hSS

fSrs

r

11

1 )1(

is the fraction of radioresistant cells before treatment

By assuming that there is a proportional relationship between tumor cells

and its volume, the percentage volume after the 1st fraction is

The cells tend to reestablish equilibrium through a transition of the radioresistant cells

into the radiosensitive cells by a constant fraction f . The f can be calculated by

.

Chvetsov A, et al IJROBP 2009, 75:595-602

Eq. 1

Model formulism

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.

)(

1

)/2(ln

12 )(ddrtTss ssd eSfeSS

)(

12 )1( ddrr rreSfS

)1)(()(

1

)/2(ln

1

)/2(ln

12

ddrtTstTss ssdDis eSfeSeDD

)1()1( )(

1

)/2(ln

12

ddrtTrr rrDis eSfeDD

Two time scales : radiosensitive cells proliferate and the damaged cells disintegrate

following an exponential function with a half life of Td and TDis, respectively. The four terms

in Eq.(1) after the 2nd fraction

where Δt is the time between two fractions. The percentage volume after the completion of n

fractions can be obtained through following iterative equations

)(

1

)/2(ln

1 )(ddr

n

tTs

n

s

nssd eSfeSS

)(

1)1( ddr

n

r

nrreSfS

)1)(()(

1

)/2(ln

1

)/2(ln

1

ddr

n

tTs

n

tTs

n

s

nssdDis eSfeSeDD

)1()1( )(

1

)/2(ln

1

ddr

n

tTr

n

r

nrrDis eSfeDD

Data Fitting and predictions

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rs rrs r2

Another parameter, r, similar to oxygen enhancement ratio (OER), to link the parameters α

and β of radiosensitive and radioresistant cells

Our study shows that the 4 parameters, αs, h, Td and TDis in the model are more crucial in the

determination of the lung volume change. We therefore fix αs/βs=10 Gy and r=3.0 in the data

fitting (Hall EJ and Giaccia AJ Radiobiology for the radiologist. 6th ed. Philadelphia (PA) Lippincott Williams & Wilkins, 2006.

p.86. )

Patients Tumor size (cc)

TNM Dose (Gy)

Treatment time (day)

a 32 T1NXM0 60 58

b 15 T1N0M0 65 54

c 19 T1N0M0 60 50

d 15 metastases 28 22

Patient list: daily images were acquired with TOMO

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How can PET help ?

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.

r

n

s

n

r

n

s

n

CT

n DDSSV r

n

s

n

PET

n SSV

The Metabolic volume on PET does not depend on the

disintegration process, in contrast to the density

volume on CT DisT

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PET with FMISO may help to determine the h parameter

PET may also be used to detect the double-time of a tumor

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Model fitting of lung volume changes on PET/CT

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h=0.5 ( Int. J. Rad Onco Biol Phys 36 (1996) 417)

Fig. 1: Percentage tumor volume by PET/CT following 50 (patient 1-4) or 60 Gy (patient 5 and 6) in 2 Gy per fraction. Only those patients whose tumor volumes are reduced by more than 30% on PET are selected.

patient 1 2 3 4 5 6

αs

(Gy-1) 0.047 0.037 0.052 0.040 0.031 0.091

Td

(day) 16.9 14.5 17.6 15.5 14.0 26.0

TDis

(day) 18.8 3.6 13.4 4.0 5.4 90.0

Milwaukee, WI

An Example of using extracted parameters – BED calculation

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patient 1 2 3 4 5 6

d (Gy) 6.4 4.9 6.7 5.5 4.3 8.5

If the adaptive boost plan would like to be delivered in 3 fractions

(patient 1-4) or 2 fractions (patient 5 and 6) such that the final doses

are biologically equivalent to treat the patients to a total dose of 80 Gy

in 2 Gy per fraction.

Conclusions

(1) The lung tumor volume change observed using PET/CT in the early part of IGRT may be used to predict individual tumor volume regression, providing useful information for the adaptive radiotherapy in the remaining of the treatment.

(2) Significant variations of the model parameters were found among patients.

(3) The remaining optimal treatment may adapt to the patient radiobiological properties.

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Thank you