A radiobiological database produced by the BIANCA model to predict the biological effectiveness - PowerPoint Presentation

Slide1

A radiobiological database produced by the BIANCA model to predict the biological effectiveness of

hadrontherapy

beams

Mario Carante

, John Telloand Francesca Ballarini

mariopietro.carante01@ateneopv.it

15th NRM, Varenna 2018

University of Pavia and INFN, Italy

Slide2

Healthy

tissue

Healthy

tissue

Tumour

Spread Out

Bragg

Peak

Slide3

Physical

dose (

Gy)Biological dose

(GyRBE*)Depth (mm)Dose (Gy)

0 50 100 150 200 250

0.5 1 1.5 2 2.5 3 3.5 4

Carbon

 

Physical

dose and

biological

dose

Slide4

Energy

depositions

D N A

Chromosome

Nucleus

Cell

DNA Cluster

Lesions

(CL)

Lethal

chromosome

aberrations

Cell

death

The BIANCA model

BI

ophysical

AN

alysis

of

C

ell

death

and

chromosome

A

berrations

Version

developed

within

the INFN

"

ETHICS"

project

Slide5

Yield

of DNA Cluster

Lesions (CL)

Mainly dependent on particle

type

and energy

(

tuned for each

radiation

quality

and

kept

unvaried

with

varying dose)

Only two adjustable

parameters:

Model

parameters

Chromosome

fragment

un-

rejoining

probability

(f)

Mainly

dependent

on the target

cell

features

(



fixed

by

comparison

with

photon

data

and

kept

unvaried

with

varying

LET)

Slide6

Protons

Increasing

CLs

Dose (

Gy

)

Surviving

fraction

LET

(

keV

/µm)

7.7

11.0

17.8

27.6

(Carante and Ballarini 2016,

Frontiers

in

Oncology

)

Exp

data from Belli et al 1998,

Folkard

et al 1996

V79

cells

Slide7

He

ions

V79

cells

Increasing

CLs

Dose (

Gy

)

Surviving

fraction

LET

(

keV

/µm)

18.6

29.9

50.0

73.9

90.8

Exp

. data

fits

from

Furusawa

et al 2000

Simulations

Exp

. data

fits

16 LET

values

:

18.6

-

90.8

keV

/µm

(Carante et al. 2018,

Physics

in Medicine and

Biology

)

Slide8

C

ions

V79

cells

Increasing

CLs

Surviving

fraction

Dose (

Gy

)

LET

(

keV

/µm)

22.5

102

137

360

Exp

. d

ata

fits

from

Furusawa

et al 2000

Surviving

fraction

Dose (

Gy

)

LET

(

keV

/µm)

31

78.5

206

Simulations

Exp

.

data fits

28 LET

values

: 22.5 – 502

keV

/µm

(Carante et al. 2018,

Physics

in Medicine and

Biology

)

Slide9

LET (

keV

/µm)

CL/

µm

Protons

He

ions

CL/

µm

LET (

keV

/µm)

CL/

µm

LET (

keV

/µm)

Carbon

ions

CL/µm

yield

well

fitted

by a 2

parameter

linear-

quadratic

function

(y=aL+bL

2

)

before

the over-

killing

region

CLs

as

a

function

of LET (V79

cells

)

Slide10

LQ

fits

of simulated

survival curves

Surviving

fraction

Dose (

Gy

)

Protons

(

example

at

15

keV

/µm)

Simulations

LQ

fit

We

perform

simulations

for the

different

particles

(up to

now

: p, He, C)

at

many

LET

values

, and

we

fit

them

with a Linear-

Quadratic

function

S=

exp

(

-

α

D-

β

D

2) (

α, β

)

Slide11

α

and

β

for protonsLET (

keV/µm)

Alpha Beta

LET (

keV

/µm)

Alpha Beta

We

obtain

a set of

many

α

and

β

points

as

a

function

of LET

β

values

β

fit

α

values

α

fit

Unpublished

Slide12

α

and

β for

helium ions

LET (keV

/µm)

Alpha Beta

LET (

keV

/µm)

Alpha Beta

We

obtain

a set of

many

α

and

β

points

as

a

function

of LET

β

values

β

fit

α

values

α

fit

Unpublished

Slide13

α

and

β

for carbon ionsLET (

keV/µm)

Alpha Beta

LET (

keV

/µm)

Alpha Beta

For

every

LET

value

we

have

α

and

β

β

values

β

fit

α

values

α

fit

Unpublished

Slide14

Interface with FLUKA

 

 

Fluka

3D dose

profile

Particle

LET

Dose

For

mixed

fields

We

provide

tables

of

α

and

β

values

for

different

ions

within

a wide

energy

range

Slide15

Biological

profile

for protons

Depth (cm)

Relative

quantities

Dose

Cell

death

V79

cells

(

low

α

/

β

ratio)

Preliminary,

unpublished

Slide16

α

and

β for

chromosome aberrations

LET (

keV

/µm)

Alpha Beta

β

values

β

fit

α

values

α

fit

These

kind

of

aberrations

may

induce

secondary

tumors

(

healty

tissue

damage

)

Protons

Dose (

Gy

)

Aberrations

/

cell

Preliminary,

unpublished

Slide17

Biological

profile

for protons

Depth (cm)

Relative

quantities

Dose

Aberrations

V79

cells

(

low

α

/

β

ratio)

Preliminary,

unpublished

Slide18

AG

cells

(high α/β

ratio)

Dose

Cell

death

Biological

profile

for

protons

Depth (cm)

Relative

quantities

Preliminary,

unpublished

Slide19

Acknowledgments

Funding:

INFN

(projects “ETHICS” and “MC-INFN/FLUKA”)FLUKA collaboration

A.

Ferrari, A.

Mairani e G.

Aricò for cooperation and useful discussions

Slide20

Backup

Slide21

Physical

dose (

Gy)

Biological dose(GyRBE*)Depth (mm)Dose (Gy)

0 50 100 150 200 250

0.5 1 1.5 2 2.5 3 3.5 4

Carbon

Which

biological

effect

?

Dose (

Gy

)

Fraction

of

surviving

cells

 

Slide22

Protons

Normal

cells (AG) ->

normal

tissue

Increasing

CLs

Surviving

fraction

Dose (

Gy

)

LET

(

keV

/µm)

1.1

4.0

7.0

11.9

18.0

22.6

(Carante and Ballarini 2016,

Frontiers

in

Oncology

)

Exp

data from

Chaudary

et al 2014

Slide23

LET (

keV

/µm)

CL/µm

All

Protons

Helium

ions

Moving

from

one

particle

to

another

?

Carbon

ions

Slide24

LET (

keV

/µm)

CL/µm

Carbon

ions

T

he

overkilling

region

A

function

of the

form

: y=

c·arctg

(aL+bL

2

)

works

better

Slide25

α

and

β

for protonsLET (

keV/µm)

Alpha Beta

LET (

keV

/µm)

Alpha Beta

We

obtain

a set of

many

α

and

β

points

and

we

fit

them

β

values

β

fit

α

values

α

fit

Slide26

α

and

β for

helium ions

LET (

keV/µm)

Alpha Beta

β

values

β

fit

α

values

α

fit

We

use a+bx

+

cx

2

for

α

and a+bx

-

cx

2

for

β

Slide27

α

and

β

for carbon ions

LET (keV

/µm)

Alpha Beta

For

every

LET

value

we

have

α

and

β

β

values

β

fit

α

values

α

fit

Slide28

LET (

keV

/µm)

CL/µm

Protons

CL/µm V79

LQ

fit V79

Moving

from

one

cell

line to

another

CL/µm AG

X 2.9

Slide29

LET (

keV

/µm)

CL/µm

Helium

ions

CL/µm V79

LQ

fit

V79

Moving

from

one

cell

line to

another

CL/µm AG

X 1.5

Slide30

LET (

keV

/µm)

CL/µm

Carbon

ions

CL/µm V79

LQ

fit V79

Moving

from

one

cell

line to

another

CL/µm AG

X 1.3

Slide31

Goal 2:

predictions

for other

cell

lines

LET (

keV

/µm)

CL/

µm

Protons

Helium

ions

LET (

keV

/µm)

CL/

µm

Carbon

ions

LET (

keV

/µm)

CL/

µm

May

the

multiplying

factors

be

derived

from the

differences

in

radiosensitivity

to

photon

exposure

?

 

With the

calibration

curves

for V79

cells

and the

photon

survival

curve for

another

cell

line

, BIANCA

could

predict

the

response

of

that

line to

charged

particles

at

any

LET

Slide32

Proton

fits

LET (

keV

/µm)

CL/

µm

Linear

CL/

µ

m

LQ

fit

LET (

keV

/µm)

Quadratic

Slide33

Helium

fits

LET (

keV

/µm)

CL/

µm

Linear

CL/

µ

m

LQ

fit

LET (

keV

/µm)

Quadratic

Slide34

Carbon

fits

LET (

keV

/µm)

CL/

µm

Linear

CL/

µ

m

LQ

fit

LET (

keV

/µm)

Quadratic

Slide35

Biological

profile

for protonsDepth (cm)

Dose (

Gy

)

Dose*RBE

Dose*1.1

Dose

Slide36

α

and

β

for protonsLET (

keV/µm)

Alpha Beta

LET (

keV

/µm)

Alpha Beta

We

obtain

a set of

many

α

and

β

points

and

we

fit

them

β

values

β

fit

α

values

α

fit

α

β

Giovannini et al 2015

Slide37

FLUKA input

Slide38

Bolzer

et al 2015

Reality

Simulations

Photons

:

CLs

distributed

uniformly

in the

cell

nucleus

S

L

ight

ions

(

like

p

and He

of

low

energy

):

CLs

distributed

along

the

particle

traversals

<n> = D



S/(0.16



LET)

h

S

’

> S

H

eavier

ions

(

like

C):

Delta

rays

Targets and

irradiation

Cell

nucleus

with the

various

chromosomes

Slide39

R

max [

μm]=0.05E[MeV

/u]1.7(Scholz and Kraft, 1992; Kiefer and Straatch, 1986)

Radial

shift

r

(nm)

p

(r)