Geant4 review from the aspect of a gate developer and user Nicolas Karakatsanis

Geant4 review from the aspect of a GATE developer and user

• Nicolas Karakatsanis

Contents

• Tracking in parameterized volumes

• Performance of Geant4 with large voxelized phantoms

• Profiling of GATE-GEANT4 performance

• Variance Reduction Techniques with GEANT4

• GEANT4 implementation of the ion source

• Radioactive Decay Module

• Dosimetry in GEANT4

• Further suggestions from the medical community

Tracking in parameterized volumes

• In SPECT a detector is typically made of a scintillator capturing gammas emitted from a patient tracer.

• In front of such a detector is a lead block with circa 150.000 air holes

• In parallel beam applications all these holes have an identical form and are aligned along a rectangular grid.

• We can model such a parallel beam collimator using arrays (repeaters) or using Geant4 replicas.

• Both options are available in GATE but for distributed computing only replicas are used since building the geometry goes fast (almost no overhead on a cluster).

Tracking in parametrized volumes

• However also applying

• Fan collimators (oriented towards a focal line)
• cone beam collimators (oriented towards a focal spot)

• Hence, every individual hole has another form/orientation

• which can be pre-calculated and described in a closed analytical expression

• To model such collimators

• GATE uses G4 parametrised volumes.
• Building the geometry goes fast and flawless.
• The tracking however is multiple orders slower
• probably because every time a particle hits the collimator every form and distance is recalculated.

Tracking in parametrized volumes

• Temporary solution

• Design of a "flying hole array“
• only takes the 20 neighbouring holes around the interaction site into account.
• Limitation if the energy of the gammas increases
• because then can travel through many of the lead lamella, crossing over multiple holes (not known before how many holes)

• Question

• How to increase calculation speed in an application with more than 10^4 parametrized inserts in one volume
• Contact: Steven Staelens : [e-mail]

Performance of Geant4 with large voxelized phantoms

• Problem:

• The simulation time for a voxelized phantom in GATE is prohibitive (dependent on the number of total voxels).
• This is a bottleneck in GATE when using voxelized phantom.

• Question

• Couldn't some implementation in Geant4 reduce this computing time?

Performance of Geant4 with large voxelized phantoms

• Our analysis:

• Geant4 forces one step in material region boundary
• This feature could be one of most important (if not the most important) factors that affects simulation speed when using large voxelised phantoms
• Because G4 is dealing with each voxel as a different material region

• Possible solution

• If the material in one voxel is the same as that in its neighboring voxel,
• Treat those two voxels as one region (no region boundary between those two voxels)
• Check that condition for all voxels

Performance of Geant4 with large voxelized phantoms

• Possible solution (..continue)

• Create an option in stepping function
• to test if the material in next region is the same as current one.
• If yes
• no boundary is applied here and
• a normal step is taken
• A flag can turn on/off the previous option

Performance of Geant4 with large voxelized phantoms

• Solution developed in GATE

• A compressedMatrix phantom object can be used instead of the parameterizedBoxMatrix
• generate a compressed phantom where voxel size is variable
• All adjacent voxels of the same material are fused together to form the largest possible rectangular voxel.
• A compressed phantom uses
• less memory and also
• less CPU
• It is possible to exclude regions in the phantom from being compressed through the use of an "exclude list" of materials

• Question

• Using compressedMatrix phantom
• reduce the CPU time but only by maybe 30%.
• A more efficient way to track particles in a voxelized geometry is welcomed

• Contact: Richard Taschereau: [e-mail]

Profiling of GATE-Geant4 performance

• Profiling tools

• Grpof and Valgrind (GNU profiling tools)

• Profiling results indicate

• Use of voxelized maps
• degrade Geant4 performance
• Significant increase of the computation time consumed by the method
• CLHEP :: Hep3vector G4ThreeVector
• which is used by the Geant4 class
• G4ParameterizedNavigation
• Geant4 navigation follows a voxel-to-voxel approach
• =>time-consuming approach
• Possible Solutions
• Need for optimization
• Merging of neighboring voxels with similar attributes
• Definition of maps using ray-tracing techniques
• Abandon discrete maps definition – introduce volume rendering

Profiling of GATE-Geant4 performance

Profiling of GATE-Geant4 performance

• Further questions from the medical community

• Profiling results indicate bottleneck caused by the G4 Navigator
• Will it be possible for GATE to define its own navigator that would inherit properties from the G4 navigator?

Current VRT Implementations

• Variance Reduction Techniques (VRTs)

• Importance sampling
• Photon splitting
• Russian roulette
• Weight window sampling
• Weight roulette
• Scoring

• A number of VRT implementations are already available in Geant4, but

• Some of the Geant4 classes can be optimized more,
• Further classes implementing VRTs could be developed

Suggested VRTs for Geant4

• Alternative photon splitting technique for G4

• If the first photon of the annihilation pair is detected
• => second photon splits into multiple photons with equal weights and total weight sum of 1
• Degree of splitting depends on the probability of detection
• Probability is dependent on axial position and emission angle
• Therefore geometrical importance sampling is based on axial position and emission angle
• Therefore prior knowledge of the geometry of the detector systems is required
• High detection probability => photon splits into a small number of secondary photons
• Low detection probability => photon splits into a large number of secondary photons
• Result
• Accuracy is not affected
• 3 – 4 times increase in efficiency of the application

Suggested VRTs for Geant4

• Alternative photon–splitting technique for G4 (…continue)

• Second photon-splitting – avoid adding noise to scatter estimation
• If the first photon is detected without having undergone Compton interaction
• Second photon splits at the annihilation point
• Else if the second photon is detected
• First photon splits at the Compton interaction point
• Else
• No coincidence is recorded
• Repeat previous steps for each event

• Addition photon transport algorithms could be implemented

• Delta scattering including energy discrimination

• Flags implementation

• user can easily activate or not the various VRT options

Suggested actions regarding VRTs

• Collaboration between

• GATE VRTs workgroup
• Geant4 VRTs workgroup

• Aim of collaboration

• Determination of the existing G4 classes need to be optimized
• Determination of further G4 classes possibly needed to be implemented
• Implementation of GATE-specific classes within the Geant4 framework
• Publication of a GATE-specific patch for Geant4

• Suggested VRTs for Geant4 follow:

• Implementation of flags (probably at GATE) for each one of the following VRTs
• => VRTs should be activated or deactivated by the user

• Contact: Nicolas Karakatsanis : [e-mail]

GEANT4 – VRTs implementation

• Further questions regarding VRTs implementation at Geaant4

• Are there any validation data regarding the variance reduction techniques currently available in Geant4?
• Are people actually using them?
• Who are the persons involved in
• the developments of VRT and
• the validation of these techniques?

G4 implementation of the Ion source

• G4 Ion source implementation problem

• Too many memory leaks
• => leading to abnormal termination of lengthy simulations

RDM (radioactive decay module)

• Is it efficient, in terms of computational time, for instance when considering sources such as

• Fluorine 18 or
• Iodine 124 ?

• Computational problems arise when

• we have to simulate billions of such decays

Dosimetry with GEANT4

• Comparisons between GEANT4 and other codes in the past indicate

• always some discrepancies between GEANT and the other MC codes, like EGS4 (more or less the gold standard)

• When performing "Rogers' > experiment" using GATE(GEANT4), EGS and MCNP,

• observe differences in absorbed dose at boundaries between materials.
• Therefore problem seems to be associated with both
• the set of low energy processes used and
• particle transport

Dosimetry with GEANT4

• Problem

• Option between two sets of low energy processes viz. "Penelope" and "low > energy“
• A little bewildering
• Both sets yield different results
• The simple user have to pick the one that is "right" for him
• Suggestion
• Only one is necessary -> the "right“ one
• Question
• Which set of low energy processes should be chosen for dosimetry purpose?
• Any data regarding the validation of absorbed dose as calculated using Geant4?

Using G4 for medical applications – Further suggestions

• Build-in Profiling features (time-profiling)

• a verbose option could display the average time (and RAM ?) spent for
• each physical processes,
• for the stepping process,
• for the navigation part and
• for the initialisation part

• Makefile management improvement

• Cmake management tool
• easier maintenance and smoother linking of third-party libraries
• especially important for medical applications, often linked with other software or libraries (e.g. image management)

Using G4 for medical applications – Further suggestions

• Voxelized scene

• a bug with the Nested parameterisation?
• David Sarrut exchanged mail with G4 developer community
• slight differences with conventional parameterisations
• not a problem due to roundoff error or machine precision
• probably a problem which occurs in some infrequent situation (particle moving along boundary ...)
• A class managing a 3D matrix of objects (voxels) should be useful for
• image management,
• 3D distribution of measurables for example
• deposit dose but also
• any other measurable such as Beta+ emitters
• different from the way such matrix is represented for navigation (parameterized volume, G4Boxs or other)
• 3D managing class characteristics
• Fast voxel access
• voxel spacing management
• capabilities to store any object type
• visualization features, storing, retrieving...
• David Sarrut is ready to help build such class

Using G4 for medical applications – Further suggestions

• The documentation on the facrange (facgeom and related) parameters seems important for medical application users

• “Wiki” documentation

• cooperative community-build documentation in a “wiki” format
• interesting way to improve the documentation, particularly in the developer section
• “Wiki” technology is now well known and mature
• allows any user to modify and improve the on-line documentation
• Our experience shows that
• is very efficient and
• it also encourages information exchange in the community

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Aim

• calculate doses from extended source distributions in homogeneous media
• averaging doses over finite volumes

• Basic Method

• Calculate dose-point-kernels in an infinite water medium
• Definition: radial distributions of dose around isotropic point sources of electrons or beta emitters.

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• L. Maigne, C.O. Thiam

• Laboratoire de Physique Corpusculaire, 24 avenue des Landais, 63177 AUBIERE cedex

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Method

• In Monte Carlo simulations, the dose around a point source is obtained by
• scoring the energy deposited in thin concentric spherical shells around the source per particle decay
• Dose estimation techniques exist for photons
• the linear track length kerma estimator of Williamson estimates the kerma by scoring tracks crossing a volume
• But no alternatives for electrons

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• where:

• r is the radial distance to the middle of the spherical shells
• rE the nominal CSDA range
• ρ the density of the medium
• D(r,E) the dose per incident particle at distance r

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of G4 Versions (50keV, 100keV)

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of G4 Versions (1MeV, 2MeV)

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of G4 Versions (3MeV, 4MeV)

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Conclusion

• High discrepancies between G4.5 and G4.6, G4.6 and G4.7 =>
• Possible cause: Multiple scattering implementation?

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of Geant4 with other MC calculations ( kinetic energy = 50keV, 100keV )

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of Geant4 with other MC calculations ( kinetic energy = 1MeV, 2MeV )

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Comparison of Geant4 with other MC calculations ( kinetic energy = 3MeV, 4MeV )

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Conclusion

• High discrepancies between Geant4.8 and other MC packages (around 10%)
• Possible reason: still undefined

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Study of G4example TestEm5
• Transmission of electrons through a thin layer of water (1.02 mm).
• Layer at 1.273 cm from the monoenergetic electron source
• World filled with air.
• Energy of electrons is 4 MeV.
• One million of electrons have been generated

Beta Ray Point Source Distributions Using GEANT4 – Comparative Study

• Plotted

• the space angle of transmitted electrons at the exit of the water layer and
• the projected angle on the y and z direction of the same scattering angle
• (Note: cut-off value in range for electrons is 0.0043 mm, equivalent to 1 keV in air and 2 keV in water medium)

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• L. Maigne, C.O. Thiam

• Laboratoire de Physique Corpusculaire, 24 avenue des Landais, 63177 AUBIERE cedex

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Source capsule

• 0.05 mm thick titanium tube,
• density of 4.54 g.cm^-3

• Radioactive seed core

• cylindrical ceramic shell
• outer and inner diameters of 0.60 and 0.22 mm
• length of 3.50 mm
• density of 2.88 g.cm^-3 (Alumina Al2O3)
• Uniform activity distribution of 10^-22 MBq of 125-I

• Gold marker (inside the radioactive seed core)

• density of 19.32 g.cm^-3,
• 0.17 mm diameter
• Length of 3.5 mm long
• permits radiographic localisation of the seed

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• 2D dose distribution around cylindrically symmetric sources, the dose rate at point (r,θ) can be written as

• Line source model

• The radial dose function g(r)
• accounts for the effects of absorption and scatter in the medium along the transverse axis of the source
• 2D anisotropy function F(r, theta)
• describes the variation in dose as a function of polar angle relative to the transverse plane

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Considering the 125-I brachytherapy sources, the simulations were performed in liquid water

• 1 476 000 gamma particles were generated for each simulations

• Cut applied on the electrons is 1 meter

• High enough because the maximum range of secondary electrons is small comparing to the recovering ring dimensions.

• The cut on X-rays is fixed to 1 keV

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Comparison of G4 Standard / Low Energy

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Comparison of G4 Versions (Low-Energy package)

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Comparisons with other MC and measurements (low-energy package)

Dosimetric characteristics of an I125 Brachytherapy Source Using Geant4 – A comparative study

• Conclusions

• Little discrepancies between Standard and Low Energy packages (7%),
• Better agreement between Low-energy package and other MC
• => to be explained
• Good agreement between G4 versions
• Good agreement with other Monte Carlo and measurements