il metodo monte carlo in radioterapia - pratica clinica e strumenti tecnologici 1 monte carlo...

Il metodo Monte Carlo in radioterapia - pratica clinica e strumenti tecnologici 1

Monte Carlo simulation for treatment planning in conventional radiotherapy and

in hadrontherapy

Faiza Bourhaleb

Dipartimento di fisica sperimentale

Università degli studi di Torino


index

• General description of a Monte Carlo for Treatment Planning

• Monte Carlo validations.• Practical example of treatment planning

with MC: modeling and verification in hadrontherapy.

• Radiobiology and Monte Carlo.• Conclusion


General description of a Monte Carlo for Treatment Planning


Beamline modeling

Patient data

Optimized TP

ANCOD++

Analytical TPS MC of the TP

Patient modeling

MC for BDL

Scoring

Cutoffs

General description of a MC for TP verification

Particles Transport

12

3

4


• GEANT3 / GEANT4 • Fluka / Fluka++• EGS / EGS4• MCNP / MCNPX• ETRAN• ITS• PENELOPE• VMC (Voxel Monte Carlo) / VCM++

4 Phases of a MC =>

Packages used for Monte Carlo use to verify the TPS


• Electron and Photons: Physics is very similar in most MC codes for

electrons and photons transport.Multiple scattering for e- is very important.

• Proton and Carbon ion: Physics is similar but for carbon ion the nuclear

interaction and so the fragmentation are very important.

(Scattering + stragling effects)

Particle transport modeling


• Read and conversion CT• 3D construction CT input HU

Density+ Tissues specification

PS: beam type dependent

Patient modeling


• Primary sourceUpper part: components remaining Fixed (Patient not depending).It is modeled only oncePhase space file

• Secondary sourceThe phase space file is used as input for the transport of patient dependent beam modifiers Virtual Source Model (parameterization of a phase space file consisting of several sub-sources particle generator for MC )

Primary Source

Secondary Source

Beam Line Modeling


• Limitation on the voxel grid for the simulation

• Conversion to water-equivalent

• Cutoffs (Energies, histories, particles considered…..)

Scoring / Cutoffs


Validation of the Monte Carlo simulation


• Light ion fragmentation reactions– Attenuate the primary beam– Lead to a build up of low Z reaction products– Long range fragments deposit dose beyond maximum

range of carbon beam

• Treatment planning – Physical beam model must consider fragmentation in

addition to scattering and ionization

Fragmentation of light ion


• Analytical– Transport equation based on experimental

cross sections in water (GSI)

• Monte Carlo– Increased interest for treatment planning

exploiting parallel computing techniques

Fragmentation of light ion


– PHITS (JAERI-Japan) (Particle and Heavy Ion Transport code System)

– SHIELD-HIT (Karolinska / Russian Acad. Of Sciences)

– FLUKA

– GEANT4 (4.6.2)• Binary cascade model of light ion fragmentation

Use of GEANT4 to simulate light ion fragmentation experiments for the purpose of verification

Codes handling fragmentation


• Simulation of simple water tank

• Physical beam model used in treatment

planning – Energy deposition w. depth for carbon beams in

water– Extensively validated with experimental data (GSI)

Test 1

depth


Test 1


Schall et al 1996 (GSI)

– Fragmentation of light ion beams in water

– Yield of fragments (Z > 4) with depth

Test 2


Ionisation Chambers90% Ar, 10% CH4, 1 atm t=50cm

E detector

670 MeV/u

Target

1o beam diagnostics

H2Ot=0-25 cm

Test 2


C12

46%

Test 2


Gunzert-Marx et al 2003 (GSI)

– Fragmentation of a carbon beam in water

– Spectroscopy of light fragments (A < 4)

Test 3


Water t=13 cm

NE102 t=9mm

BaF2

t=14.5cm

E-E detector

3m

C12

200 MeV/u

Target

Test 3


neutrons protons

deuterons

Test 3

tritons


helium-3alpha


Practical example of Monte Carlo for treatment planning in hadrontherapy: modeling and verification.


Hadron beams


Scanning magnets

Scanning magnets

SynchrotonSynchroton

LinacLinac

Carbon source

Carbon source

Proton source

Proton source

Monitoring system Monitoring system

Z

Ec

d E/ d

z

Active scan tecnique


• Simulation with GEANT4 for the beam delivery line consisting of :– monitoring system

– Ripple filter

Modeling of Beam Delivery Line


look-up tables of the inv. PS from MC

Proton beamsCarbon ion beams

Modeling of Beam Delivery Line


Patient modeling and conversion

this work = Jäkel et al.

Maximum number of materials are defined.

PS: We usually use the CT resolution for the simulation different from the TP matrix.simulation.


• Parameters of a specific TP optimized to use as input for the MC TP– Positions of the sources– Kinetic energies for single beams– Direction of the Field– Angles of single beams– Optimized Fluences

Treatment planning verification


Carbon Ion beams Proton beams

Treatment planning verification


Radiobiology and Monte Carlo simulation


Dos

e [G

y]

Depth [mm]

TRiP (GSI)


Sampling data inside a MC code using the LEM (or an hybrid)

Principles of Local Effect Model (LEM)

• Biological effect completely determined by the local distribution of dose inside the cell nucleus

• Homogeneous cell nucleus with constant density and radiosensitivity

• Locally, the effect of ions can be evaluated using the X-ray Linear Quadratic model:


Alpha

Carbon ions



What we can do with MC for the Radiobiological part?

N

Depth [mm]Ed [keV]

Depth [mm]

Ed [

keV

]


• “Data – Flow”

MC simulations

(Geant)

Ion tracks

Kraft/Scholz model

(RBEsoft)

Survival curves

(α,β)

Analytical functions

Lookup tables

TPS

(Ancod++)

RBE



Radiobiology modeling

TP with the biological optimization how can we verify??



Conclusion


MC for hadron beams with Geant4 fully validated Experiments of ion fragmentation in tissue

substitutes useful for further verification studies

MC for radiobiology Biological Monte Carlo Treatment Planning (BMCTP)!?


References• The Dosimetry of Ionizing Radiation, edited by Kase, Bjärngard, and Attix, Academic Press,

1990.• Dr. Schardt and Dr. Gunzert-Marx of GSI for experimental details and data• Dr. J.P. Wellisch and Dr. G. Folger of the GEANT4 hadronic physics group • Sven O. Groezinger of GSI for carbon therapy images• M. Kraemer et al (TRiP)• M. Scholz et al for the Local effect Model (LEM)• A treatment planning code for inverse planning and 3D-optimization in hadrontherapy. (F

Bourhaleb et al) paper in preparation…

Knowledge

F. Marchetto2, Iwan Cornellius, Andrea Attili2, Roberto Cirio2, Cristiana Peroni1

1 Dipartimento di fisica sperimentale, Università di Torino

2 Istituto Nazionale di Fisica Nucleare (INFN), Torino.


Thanks for your attention


Model Verification

• Simulate fragmentation experiments• Schall (GSI): Fragment yields (Z>4) for

varying thickness water target• Matsufuji (NIRS): fragment yields (Z>1)

for varying thickness PMMA target• Gunzert-Marx (GSI): fragment

spectroscopy and angular dependence (n,p,d,t,He-3,)


G4 Ion Physics

• G4MultipleScattering

• G4ionIonisation

• G4HadronInelasticProcess

• G4TripathiCrossSection

• G4IonsShenCrossSection

• G4BinaryLightIonReaction


Schall et.al. 1996

• Beam : C-12 676 AMeV

• Target : H2O (variable thickness, t)

• Detection system : Ionisation Chamber f(E)

• Information : N(Z,t) /No


1. Results & Discussion

Xpeak mm Epeak % Eint %

GEANT4 2.0 4 4.1

SHIELD-HIT 2.0 N/A 3.0

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