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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TH-A-19A-08: Intel Xeon Phi Implementation of a Fast Multi-Purpose Monte Carlo Simulation for Proton Therapy

Purpose: Recent studies have demonstrated the capability of graphics processing units (GPUs) to compute dose distributions using Monte Carlo (MC) methods within clinical time constraints. However, GPUs have a rigid vectorial architecture that favors the implementation of simplified particle transport algorithms, adapted to specific tasks. Our new, fast, and multipurpose MC code, named MCsquare, runs on Intel Xeon Phi coprocessors. This technology offers 60 independent cores, and therefore more flexibility to implement fast and yet generic MC functionalities, such as prompt gamma simulations. Methods: MCsquare implements several models and hence allows users to make their own tradeoff between speed and accuracy. A 200 MeV proton beam is simulated in a heterogeneous phantom using Geant4 and two configurations of MCsquare. The first one is the most conservative and accurate. The method of fictitious interactions handles the interfaces and secondary charged particles emitted in nuclear interactions are fully simulated. The second, faster configuration simplifies interface crossings and simulates only secondary protons after nuclear interaction events. Integral depth-dose and transversal profiles are compared to those of Geant4. Moreover, the production profile of prompt gammas is compared to PENH results. Results: Integral depth dose and transversal profiles computed by MCsquare and Geant4 are within 3%. The production of secondaries from nuclear interactions is slightly inaccurate at interfaces for the fastest configuration of MCsquare but this is unlikely to have any clinical impact. The computation time varies between 90 seconds for the most conservative settings to merely 59 seconds in the fastest configuration. Finally prompt gamma profiles are also in very good agreement with PENH results. Conclusion: Our new, fast, and multi-purpose Monte Carlo code simulates prompt gammas and calculates dose distributions in less than a minute, which complies with clinical time constraints. It has been successfully validated with Geant4. This work has been financialy supported by InVivoIGT, a public/private partnership between UCL and IBA.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

SU-E-T-22: A Deterministic Solver of the Boltzmann-Fokker-Planck Equation for Dose Calculation

Purpose: The Boltzmann-Fokker-Planck equation (BFPE) accurately models the migration of photons/charged particles in tissues. While the Monte Carlo (MC) method is popular for solving BFPE in a statistical manner, we aim to develop a deterministic BFPE solver based on various state-of-art numerical acceleration techniques for rapid and accurate dose calculation. Methods: Our BFPE solver is based on the structured grid that is maximally parallelizable, with the discretization in energy, angle and space, and its cross section coefficients are derived or directly imported from the Geant4 database. The physical processes that are taken into account are Compton scattering, photoelectric effect, pair production for photons, and elastic scattering, ionization and bremsstrahlung for charged particles.While the spatial discretization is based on the diamond scheme, the angular discretization synergizes finite element method (FEM) and spherical harmonics (SH). Thus, SH is used to globally expand the scattering kernel and FFM is used to locally discretize the angular sphere. As a Result, this hybrid method (FEM-SH) is both accurate in dealing with forward-peaking scattering via FEM, and efficient for multi-energy-group computation via SH. In addition, FEM-SH enables the analytical integration in energy variable of delta scattering kernel for elastic scattering with reduced truncation error from the numerical integration based on the classic SH-based multi-energy-group method. Results: The accuracy of the proposed BFPE solver was benchmarked against Geant4 for photon dose calculation. In particular, FEM-SH had improved accuracy compared to FEM, while both were within 2% of the results obtained with Geant4. Conclusion: A deterministic solver of the Boltzmann-Fokker-Planck equation is developed for dose calculation, and benchmarked against Geant4. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT 4

Purpose: This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and GEANT4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field. Methods: A stand-alone version of the Elekta™ GPUMCD algorithm, to be used within the Monaco treatment planning system to model dose for the Elekta™ magnetic resonance imaging (MRI) Linac, was compared against GEANT4 (v10.1). This was done in the presence or absence of a 1.5 T static magnetic field directed orthogonally to the radiation beam axis. Phantoms with material compositions of water, ICRU lung, ICRU compact-bone, and titanium were used for this purpose. Beams with 2 MeV monoenergetic photons as well as a 7 MV histogrammed spectrum representing the MRI Linac spectrum were emitted from a point source using a nominal source-to-surface distance of 142.5 cm. Field sizes ranged from 1.5 × 1.5 to 10 × 10 cm{sup 2}. Dose scoring was performed using a 3D grid comprising 1 mm{sup 3} voxels. The production thresholds were equivalent for both codes. Results were analyzed based upon a voxel by voxel dose difference between the two codes and also using a volumetric gamma analysis. Results: Comparisons were drawn from central axis depth doses, cross beam profiles, and isodose contours. Both in the presence and absence of a 1.5 T static magnetic field the relative differences in doses scored along the beam central axis were less than 1% for the homogeneous water phantom and all results matched within a maximum of ±2% for heterogeneous phantoms. Volumetric gamma analysis indicated that more than 99% of the examined volume passed gamma criteria of 2%—2 mm (dose difference and distance to agreement, respectively). These criteria were chosen because the minimum primary statistical uncertainty in dose scoring voxels was 0.5%. The presence of the magnetic field affects the dose at the interface depending upon the density of the material on either sides of the interface. This effect varies with the field size. For example, at the water-lung interface a 33.94% increase in dose was observed (relative to the D{sub max}), by both GPUMCD and GEANT4 for the field size of 2 × 2 cm{sup 2} (compared to no B-field case), which increased to 47.83% for the field size of 5 × 5 cm{sup 2} in the presence of the magnetic field. Similarly, at the lung-water interface, the dose decreased by 19.21% (relative to D{sub max}) for a field size of 2 × 2 cm{sup 2} and by 30.01% for 5 × 5 cm{sup 2} field size. For more complex combinations of materials the dose deposition also becomes more complex. Conclusions: The GPUMCD algorithm showed good agreement against GEANT4 both in the presence and absence of a 1.5 T external magnetic field. The application of 1.5 T magnetic field significantly alters the dose at the interfaces by either increasing or decreasing the dose depending upon the density of the material on either side of the interfaces.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Improvements in simulation of multiple scattering effects in ATLAS fast simulation

Fast ATLAS Tracking Simulation (Fatras) package was verified on single layer geometry with respect to full simulation with GEANT4. Fatras hadronic interactions and multiple scattering simulation were studied in comparison with GEANT4. Disagreement was found in multiple scattering distributions of primary charged particles (μ, π, e). A new model for multiple scattering simulation was implemented in Fatras. The model was based on R. Frühwirth’s mixture models. New model was tested on single layer geometry and a good agreement with GEANT4 was achieved. Also a comparison of reconstructed tracks’ parameters was performed for Inner Detector geometry, and Fatras with new multiple scattering model proved to have better agreement with GEANT4. New model of multiple scattering was added as a part of Fatras package in the development release of ATLAS software—ATHENA.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Fusion Neutron Generator

The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example. The FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons – neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed “fusion-to-thermal neutron converters” in the literature. The code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. The physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.

Martin, NicholasP. [Idaho National Laboratory (INL↗
DOE OSTI2013

TOPAS Tool for Particle Simulation

TOPAS lets users simulate the passage of subatomic particles moving through any kind of radiation therapy treatment system, can import a patient geometry, can record dose and other quantities, has advanced graphics, and is fully four-dimensional (3D plus time) to handle the most challenging time-dependent aspects of modern cancer treatments.TOPAS unlocks the power of the most accurate particle transport simulation technique, the Monte Carlo (MC) method, while removing the painstaking coding work such methods used to require. Research physicists can use TOPAS to improve delivery systems towards safer and more effective radiation therapy treatments, easily setting up and running complex simulations that previously used to take months of preparation. Clinical physicists can use TOPAS to increase accuracy while reducing side effects, simulating patient-specific treatment plans at the touch of a button. TOPAS is designed as a “user code” layered on top of the Geant4 Simulation Toolkit. TOPAS includes the standard Geant4 toolkit, plus additional code to make Geant4 easier to control and to extend Geant4 functionality. TOPAS aims to make proton simulation both “reliable” and “repeatable.” “Reliable” means both accurate physics and a high likelihood to simulate precisely what the user intended to simulate, reducing issues of wrong units, wrong materials, wrong scoring locations, etc. “Repeatable” means not just getting the same result from one simulation to another, but being able to easily restore a previously used setup and reducing sources of error when a setup is passed from one user to another. TOPAS control system incorporates key lessons from safety management, proactively removing possible sources of user error such as line-ordering mistakes In control files. TOPAS has been used to model proton therapy treatment examples including the UCSF eye treatment head, the MGH stereotactic alignment in radiosurgery treatment head and the MGH gantry treatment heads in passive scattering and scanning modes, and has demonstrated dose calculation based on patient-specific CT data.

Perl, Joseph↗
DOE OSTI2023

Improving The Simulation Of Muons In The Rock Around The NOvA Near Detector

This thesis investigates the viability of the PROPOSAL lepton propagation tool as an alternative to the commonly used GEANT4 simulation for muon propagation within the NOvA experiment. The main objectives of this research were twofold: first, to validate the accuracy of PROPOSAL data in simulating rock muons when compared to GEANT4 data; second, to explore the practical application of transporting cosmic muons through the NOvA rock region using PROPOSAL. Additionally, an 1D analysis was conducted to determine the optimal altitude at which to hand over the simulation task from PROPOSAL to GEANT4, should we choose to use PROPOSAL for rock simulations and GEANT4 for detector simulations in the NOvA experiment. By thoroughly examining these aspects, this study aims to contribute to the advancement of muon simulation techniques and their implementation in high-energy experiments such as NOvA.

Parvez, Radwan↗
DOE OSTI2022

Simulation of the spatial shift in detector response for polarized protons within a calorimeter

Measurement of the helicity dependent elastic electron-proton scattering cross section provides a key means of investigating parity violation within the proton. However, such measurements exhibit potential instrumental effects associated with the detection of polarized recoiled protons. In particular, spin-orbit interactions within a massive detector induce a systematic spatial shift in the detector signal. In this study, we determine the size of this shift using the Geant4 simulation toolkit. For a typical hadron calorimeter, we found a polarization dependent shift on the order of 0.01-0.1 mm, multiple orders of magnitude smaller than the typical spatial resolution seen in hadronic calorimeters. Additionally, we provide the custom modifications required of the Geant4 source code to implement the quasi-elastic scattering of polarized protons incident on nuclei in the detector. The modifications are readily extendable to generic matter sources, and can be used for the study of additional spin dependent observables in Geant4.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Thick target neutron yields from Beryllium, Carbon, Tungsten, and Lead targets irradiated by 26.7 MeV/nucleon 4 H e ions

The angular and energy distributions of secondary neutrons produced from 26.7 MeV/nucleon 4 He ions, stopping in thick Be, C, W and Pb targets are measured by the time of flight method. The GEANT4, PHITS, and FLUKA Monte Carlo simulation codes with different physics models are employed to simulate the neutron yields and the results are compared with the experimental data. For the thick Be and C targets, GEANT4 with INCL++ reproduces the experimental data reasonably well. Whereas PHITS with JQMD-2.0 overestimates the neutron yields at intermediate energies and FLUKA with PEANUT underestimated the neutron yields at intermediate energies. For W and Pb targets, FLUKA with PEANUT physics model agree with experimental data best. PHITS with JQMD-2.0 overestimates the neutron yield at intermediate energies at 0°, and GEANT4 with INCL++ underestimates the neutron yield at intermediate energies at three angles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

A broadband gamma-ray spectrometry using novel unfolding algorithms for characterization of laser wakefield-generated betatron radiation

We present a high-flux, broadband gamma-ray spectrometry capable of characterizing the betatron radiation spectrum over the photon energy range from 10 keV to 20 MeV with respect to the peak photon energy, spectral bandwidth, and unique discrimination from background radiations, using a differential filtering spectrometer and the unfolding procedure based on the Monte Carlo code GEANT4. These properties are experimentally verified by measuring betatron radiation from a cm-scale laser wakefield accelerator (LWFA) driven by a 1-PW laser, using a differential filtering spectrometer consisting of a 15-filter and image plate stack. The gamma-ray spectra were derived by unfolding the photostimulated luminescence (PSL) values recorded on the image plates, using the spectrometer response matrix modeled with the Monte Carlo code GEANT4. The accuracy of unfolded betatron radiation spectra was assessed by unfolding the test PSL data simulated with GEANT4, showing an ambiguity of less than 20% and clear discrimination from the background radiation with less than 10%. The spectral analysis of betatron radiation from laser wakefield-accelerated electron beams with energies up to 3 GeV revealed radiation spectra characterized by synchrotron radiation with the critical photon energy up to 7 MeV. The gamma-ray spectrometer and unfolding method presented here facilitate an in-depth understanding of betatron radiation from LWFA process and a novel radiation source of high-quality photon beams in the MeV regime.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Photon detection probability prediction using one-dimensional generative neural network

Abstract Photon detection is important for liquid argon detectors for direct dark matter searches or neutrino property measurements. Precise simulation of photon transport is widely used to understand the probability of photon detection in liquid argon detectors. Traditional photon transport simulation, which tracks every photon using the Geant4 simulation toolkit, is a major computational challenge for kilo-tonne-scale liquid argon detectors and GeV-level energy depositions. In this work, we propose a one-dimensional generative model which efficiently generates features using an O u t e r P r o d u c t -layer. This model bypasses photon transport simulation and predicts the number of photons detected by particular photon detectors at the same level of detail as the Geant4 simulation. The application to simulating photon detection systems in kilo-tonne-scale liquid argon detectors demonstrates this novel generative model is able to reproduce Geant4 simulation with good accuracy and 20 to 50 times faster. This generative model can be used to quickly predict photon detection probability in huge liquid argon detectors like ProtoDUNE or DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Accelerating accurate simulations of calorimeter showers with normalizing flows and probability density distillation

Recently, we introduced caloflow, a high-fidelity generative model for GEANT4 calorimeter shower emulation based on normalizing flows. Here, we present caloflow v2, an improvement on our original framework that speeds up shower generation by a further factor of 500 relative to the original. The improvement is based on a technique called probability density distillation, originally developed for speech synthesis in the machine learning literature, and which we develop further by introducing a set of powerful new loss terms. We demonstrate that caloflow v2 preserves the same high fidelity as the original using qualitative (average images, histograms of high-level features) and quantitative (classifier metric between geant4 and generated samples) measures. The result is a generative model for calorimeter showers that matches the state of the art in speed (a factor of 10 4 faster than GEANT4) and greatly surpasses the previous state of the art in fidelity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

WE-A-17A-04: Development of An Ultra-Fast Monte Carlo Dose Engine for High Dose Rate Brachytherapy

Purpose: Current clinical brachytherapy dose calculations are based on AAPM TG43 guidelines, which approximate the patient geometry as a large water phantom. This ignores heterogeneities and tends to overestimate skin dose. Although Monte Carlo (MC) dose calculations have been recognized as the most accurate method, its associated long computational time is a major bottleneck for routine clinical applications. This work aims to develop a GPU-based ultra-fast MC dose engine (gBMC) for HDR brachytherapy to provide clinical users with accurate sub-minute dose calculations. Methods: Standard photon transport with discrete events including: Compton scattering, Rayleigh scattering and Photoelectric effect, was implemented. Secondary electrons were transported under the continuous slowing down approximation. To reduce the GPU thread divergence, photons and electrons were separately transported. Transport of photons was grouped according to energy. The source model in gBMC can be either a phase-space file generated using Geant4 or a parameterized source model. This dose engine was validated against TG43 in a water phantom and against Geant4 calculations in heterogeneous patient geometries. Results: A phase space file was generated for the Varian VS2000 Ir-192 source. In a water phantom, the calculated radial dose function was within 0.6% of the TG43 calculations for radial distances from 1 cm to 20 cm. The anisotropy functions were within 1% for radial distances from 1 cm to 20 cm except for polar angles larger than 173°. Local point-dose differences were within 2%. In a Mammosite breast cancer case with 22 dwell locations, gBMC and Geant4 isodose lines compared well. The computation time was about 28 seconds using the phase-space file source and 20 seconds using the parameterized source to simulate 1 billion particles, yielding less than 1% statistical uncertainty. Conclusion: The gBMC dose engine makes it possible to use fast and accurate MC dose calculations for clinical work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-C-204-04: Patient Specific Proton Stopping Powers Estimation by Combining Proton Radiography and Prior-Knowledge X-Ray CT Information

Purpose: The material relative stopping power (RSP) uncertainty is the highest contributor to the range uncertainty in proton therapy. The purpose of this work is to develop a robust and systematic method that yields accurate, patient specific, RSP by combining 1) pre-treatment x-ray CT and 2) daily proton radiograph of the patient. Methods: The method is formulated as a linear least-square optimization problem (min||Ax-B||2). The parameter A represents the pathlength crossed by the proton in each material. The RSPs for the materials (water equivalent thickness (WET)/physical thickness) are denoted by x. B is the proton radiograph expressed as WET crossed. The problem is minimized using a convex-conic optimization algorithm with xi<xi+1 constraint. The Gammex RMI-465 phantom, with 13 material inserts, is used to investigate the optimal RSPs. The proton radiograph (B) is produced using Geant4 simulation. The matrix A is computed by calculating proton trajectories through the CT with the cubic-spline approach. Geant4 RSPs are used as reference and the clinical HU-RSP calibration curve is used as comparison. The convergence is investigated as a function of the number of angles and protons used. The radiographs angle which yield the most accurate RSPs are investigated. Results: Optimization with 9 angles and 104 protons/angle yields precise RSP (<0.75%) for all materials, except plastic lung (1.5%). Average deviation relative to Geant4 RSP is 0.5% and 3.5% using HU-RSP. Using more than two angles or more than 4×103 proton does not further increase the RSP estimate accuracy. The insert distance to the beam initial plane is related to the RSP error for this insert material. Specific filters are applied on the proton angle and energy loss to remove nuclear interaction artefacts. Conclusion: The proposed formulation of the problem with prior knowledge x-ray CT demonstrates serious potential to increase the accuracy of present RSP estimates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-499: Initial Developments of An OpenCL-Based Cross-Platform Monte Carlo Dose Engine for Carbon Ion Therapy

Purpose Dose calculation is of critical importance for carbon ion therapy. Monte Carlo (MC) simulation is considered to be the most accurate method for calculation of absorbed dose and of all the more fundamental physical quantities related to biological effects. The long computation time, however, limits its routine clinical applications. We have recently started developing a fast MC package, gCMC for carbon therapy on a parallel processing platform, e.g. GPU, aiming at achieving sufficient efficiency to enable MC in clinically important tasks. This abstract reports our progress. Methods gCMC was developed in OpenCL environment. Our initial developments focused on water material. gCMC supported carbon ion transport in the energy range of 1–450 MeV/u. A Class II condensed history algorithm was implemented for charged particle transport simulations with stopping power computed via Bethe-Bloch equation. Energy straggling and multiple scattering were modeled. Total cross section of nuclear interaction was extracted from Geant4. At present, nuclear interaction events were sampled but transports of secondary particles were not included. Results We tested cases with a homogeneous water phantom and a pencil carbon ion beam with energy of 200–400 MeV/u. When only electro-magnetic channel was included, dose/fluence difference between gCMC and Geant4 results averaged within 10% isodose line was <0.5% of the maximum dose/fluence. After enabling nuclear interactions without transporting secondary particles, dose and fluence agreed with the corresponding results computed by Geant4 with <1% difference. Due to the support for multiple platforms of OpenCL, gCMC was executable on NVidia and AMD GPUs, and Intel CPUs. It took ∼50 sec to transport 107 200MeV/u source carbon ions on an NVidia Titan GPU card. Conclusion Preliminary studies have demonstrated the accuracy and efficiency of gCMC. With further developments in near future, gCMC will potentially achieve clinically acceptable fast and accurate MC simulations for carbon ion therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-554: Monte Carlo Calculation of Source Terms and Attenuation Lengths for Neutrons Produced by 50–200 MeV Protons On Brass

Purpose: We used TOPAS (TOPAS wraps and extends Geant4 for medical physicists) to compare Geant4 physics models with published data for neutron shielding calculations. Subsequently, we calculated the source terms and attenuation lengths (shielding data) of the total ambient dose equivalent (TADE) in concrete for neutrons produced by protons in brass. Methods: Stage1: The Bertini and Binary nuclear models available in Geant4 were compared with published attenuation at depth of the TADE in concrete and iron. Stage2: Shielding data of the TADE in concrete was calculated for 50– 200 MeV proton beams on brass. Stage3: Shielding data from Stage2 was extrapolated for 235 MeV proton beams. This data was used in a point-line-source analytical model to calculate the ambient dose per unit therapeutic dose at two locations inside one treatment room at the Francis H Burr Proton Therapy Center. Finally, we compared these results with experimental data and full TOPAS simulations. Results: At larger angles (∼130o) the TADE in concrete calculated with the Bertini model was about 9 times larger than that calculated with the Binary model. The attenuation length in concrete calculated with the Binary model agreed with published data within 7%±0.4% (statistical uncertainty) for the deepest regions and 5%±0.1% for shallower regions. For iron the agreement was within 3%±0.1%. The ambient dose per therapeutic dose calculated with the Binary model, relative to the experimental data, was a ratio of 0.93±0.16 and 1.23±0.24 for two locations. The analytical model overestimated the dose by four orders of magnitude. These differences are attributed to the complexity of the geometry. Conclusion: The Binary and Bertini models gave comparable results, with the Binary model giving the best agreement with published data at large angle. Shielding data we calculated using the Binary model is useful for fast shielding calculations with other analytical models. This work was supported by National Cancer Institute Grant R01CA140735.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

SU-E-T-764: Track Repeating Algorithm for Proton Therapy Applied to Intensity Modulated Proton Therapy for Head-And-Neck Patients

Purpose: To determine the suitability of fast Monte Carlo techniques for dose calculation in particle therapy based on track-repeating algorithm for Intensity Modulated Proton Therapy, IMPT. The application of this technique will make possible detailed retrospective studies of large cohort of patients, which may lead to a better determination of Relative Biological Effects from the analysis of patient data. Methods: A cohort of six head-and-neck patients treated at the University of Texas MD Anderson Cancer Center with IMPT were utilized. The dose distributions were calculated with the standard Treatment Plan System, TPS, MCNPX, GEANT4 and FDC, a fast track-repeating algorithm for proton therapy for the verification and the patient plans. FDC is based on a GEANT4 database of trajectories of protons in a water. The obtained dose distributions were compared to each other utilizing the g-index criteria for 3mm-3% and 2mm-2%, for the maximum spatial and dose differences. The γ-index was calculated for voxels with a dose at least 10% of the maximum delivered dose. Dose Volume Histograms are also calculated for the various dose distributions. Results: Good agreement between GEANT4 and FDC is found with less than 1% of the voxels with a γ-index larger than 1 for 2 mm-2%. The agreement between MCNPX with FDC is within the requirements of clinical standards, even though it is slightly worse than the comparison with GEANT4.The comparison with TPS yielded larger differences, what is also to be expected because pencil beam algorithm do not always performed well in highly inhomogeneous areas like head-and-neck. Conclusion: The good agreement between a track-repeating algorithm and a full Monte Carlo for a large cohort of patients and a challenging, site like head-and-neck, opens the path to systematic and detailed studies of large cohorts, which may yield better understanding of biological effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-BRC-06: OpenCL-Based Cross-Platform Monte Carlo Simulation Package for Carbon Ion Therapy

Purpose: Monte Carlo (MC) simulation is considered to be the most accurate method for calculation of absorbed dose and fundamental physical quantities related to biological effects in carbon ion therapy. Its long computation time impedes clinical and research applications. We have developed an MC package, goCMC, on parallel processing platforms, aiming at achieving accurate and efficient simulations for carbon therapy. Methods: goCMC was developed under OpenCL framework. It supported transport simulation in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history algorithm was employed for charged particle transport with stopping power computed via Bethe-Bloch equation. Secondary electrons were not transported with their energy locally deposited. Energy straggling and multiple scattering were modeled. Production of secondary charged particles from nuclear interactions was implemented based on cross section and yield data from Geant4. They were transported via the condensed history scheme. goCMC supported scoring various quantities of interest e.g. physical dose, particle fluence, spectrum, linear energy transfer, and positron emitting nuclei. Results: goCMC has been benchmarked against Geant4 with different phantoms and beam energies. For 100 MeV/u, 250 MeV/u and 400 MeV/u beams impinging to a water phantom, range difference was 0.03 mm, 0.20 mm and 0.53 mm, and mean dose difference was 0.47%, 0.72% and 0.79%, respectively. goCMC can run on various computing devices. Depending on the beam energy and voxel size, it took 20∼100 seconds to simulate 10{sup 7} carbons on an AMD Radeon GPU card. The corresponding CPU time for Geant4 with the same setup was 60∼100 hours. Conclusion: We have developed an OpenCL-based cross-platform carbon MC simulation package, goCMC. Its accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon therapy.

60 APPLIED LIFE SCIENCES↗