Geant4 review from the aspect of a gate developer and user Nicolas Karakatsanis
tarix 14.05.2018 ölçüsü 496 b. #50415
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 : steven.staelens@ugent.be 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: RTaschereau@mednet.ucla.edu 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 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 : knicolas@mail.ntua.gr 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 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 Good agreement between G4 versions Good agreement with other Monte Carlo and measurements Dostları ilə paylaş:
