A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation

Individualized dose calculation for internal exposure on radionuclide intake: GPU acceleration approach

Objective. The rapid and accurate assessment of internal exposure dose is a crucial safeguard for personnel health and safety. This study aims to investigate a precise and efficient GPU Monte Carlo simulation approach for internal exposure dose calculation. It directly calculates doses from common radioactive nuclides intake, like60Co for occupational exposure, allowing personalized assessments.Approach. This study developed a GPU-accelerated Monte Carlo program for internal exposure on radionuclide intake, successfully realizing photoelectronic coupled transport, nuclide simulation, and optimized acceleration. The generation of internal irradiation sources and sampling methods were achieved, along with the establishment of a personalized phantom construction process. Three irradiation scenarios were simulated to assess computational accuracy and efficiency, and to investigate the influence of posture variations on internal dose estimations.Main results. Using the International Commission on Radiological Protection (ICRP) voxel-type phantom, the internal dose of radionuclides in individual organs was calculated, exhibiting relative deviation of less than 3% in comparison to organ dose results interpolated by Specific Absorbed Fractions in ICRP Publication 133. Employing the Chinese reference phantom for calculating internal irradiation dose from the intake of various radionuclides, the use of GPU Monte Carlo program significantly shortened the simulation time compared to using CPU programs, by a factor of 150-500. Internal dose estimation utilizing a seated Chinese phantom revealed up to a 75% maximum difference in organ dose compared to the same phantom in a standing posture.Significance. This study presents a rapid GPU-based simulation method for internal irradiation doses, capable of directly simulating dose outcomes from nuclide intake and accommodating individualized phantoms for more realistic and expeditious calculations tailored to specific internal irradiation scenarios. It provides an effective and feasible tool for precisely calculating internal irradiation doses in real-world scenarios.

Performance evaluation of Monaco radiotherapy treatment planning system using CIRS Thorax Phantom: Dosimetric assessment of flattened and non-flattened photon beams

Aim

The present study was undertaken to evaluate the performance of different algorithms for flattening filter-free (FFF) and flattened (FF) photon beams in three different in-homogeneities.

Materials and Method

Computed tomography (CT) image sets of the CIRS phantom maintained in the SAD setup by placing the ionization chamber in the lung, bone, and tissue regions, respectively, were acquired. The treatment planning system (TPS) calculated and the ionization chamber measured the doses at the center of the chamber (in the three mediums) were recorded for the flattened and non-flattened photon beams.

Results

The results were reported for photon energies of 6 MV, 10 MV, 15 MV, 6 FFF, and 10 FFF of field sizes 5 × 5 cm2, 10 × 10 cm2, and 15 × 15 cm2. In the bone inhomogeneity, the pencil beam algorithm predicted that the maximum dose variation was 4.88% of measured chamber dose in 10-MV photon energy for the field size 10 × 10 cm2. In water inhomogeneity, both the collapsed cone and Monte Carlo algorithm predicted that the maximum dose variation was ± 3% of measured chamber dose in 10-MV photon energy for the field size 10 × 10 cm2 and in 10-MV FFF photon energy for the field size 5 × 5 cm2, whereas in lung inhomogeneity, the pencil beam algorithm predicted that the highest dose variation was - 6.9% of measured chamber dose in 10-MV FFF photon energy for the field size 5 × 5 cm2.

Conclusion

FF and FFF beams performed differently in lung, water, and bone mediums. The assessment of algorithms was conducted using the anthropomorphic phantom; therefore, these findings may help in the selection of appropriate algorithms for particular clinical settings in radiation delivery.

GPU-accelerated Monte Carlo simulation of electron and photon interactions for radiotherapy applications

Objective. The Monte Carlo simulation software is a valuable tool in radiation therapy, in particular to achieve the needed accuracy in the dose evaluation for the treatment plans optimisation. The current challenge in this field is the time reduction to open the way to many clinical applications for which the computational time is an issue. In this manuscript we present an innovative GPU-accelerated Monte Carlo software for dose valuation in electron and photon based radiotherapy, developed as an update of the FRED (Fast paRticle thErapy Dose evaluator) software.Approach. The code transports particles through a 3D voxel grid, while scoring their energy deposition along their trajectory. The models of electromagnetic interactions in the energy region between 1 MeV-1 GeV available in literature have been implemented to efficiently run on GPUs, allowing to combine a fast tracking while keeping high accuracy in dose assessment. The FRED software has been bench-marked against state-of-art full MC (FLUKA, GEANT4) in the realm of two different radiotherapy applications: Intra-Operative Radio Therapy and Very High Electron Energy radiotherapy applications.Results. The single pencil beam dose-depth profiles in water as well as the dose map computed on non-homogeneous phantom agree with full-MCs at 2% level, observing a gain in processing time from 200 to 5000.Significance. Such performance allows for computing a plan with electron beams in few minutes with an accuracy of ∼%, demonstrating the FRED potential to be adopted for fast plan re-calculation in photon or electron radiotherapy applications.

A phase space model of a Versa HD linear accelerator for application to Monte Carlo dose calculation in a real-time adaptive workflow

PURPOSE

This study aims to develop and validate a simple geometric model of the accelerator head, from which a particle phase space can be calculated for application to fast Monte Carlo dose calculation in real-time adaptive photon radiotherapy. With this objective in view, the study investigates whether the phase space model can facilitate dose calculations which are compatible with those of a commercial treatment planning system, for convenient interoperability.

MATERIALS AND METHODS

A dual-source model of the head of a Versa HD accelerator (Elekta AB, Stockholm, Sweden) was created. The model used parameters chosen to be compatible with those of 6-MV flattened and 6-MV flattening filter-free photon beams in the RayStation treatment planning system (RaySearch Laboratories, Stockholm, Sweden). The phase space model was used to calculate a photon phase space for several treatment plans, and the resulting phase space was applied to the Dose Planning Method (DPM) Monte Carlo dose calculation algorithm. Simple fields and intensity-modulated radiation therapy (IMRT) treatment plans for prostate and lung were calculated for benchmarking purposes and compared with the convolution-superposition dose calculation within RayStation.

RESULTS

For simple square fields in a water phantom, the calculated dose distribution agrees to within ±2% with that from the commercial treatment planning system, except in the buildup region, where the DPM code does not model the electron contamination. For IMRT plans of prostate and lung, agreements of ±2% and ±6%, respectively, are found, with slightly larger differences in the high dose gradients.

CONCLUSIONS

The phase space model presented allows convenient calculation of a phase space for application to Monte Carlo dose calculation, with straightforward translation of beam parameters from the RayStation beam model. This provides a basis on which to develop dose calculation in a real-time adaptive setting.

Simulation of Gamma-Ray Transmission Buildup Factors for Stratified Spherical Layers

Deterministic particle transport codes usually take into account scattered photons with correct attenuation laws and application of buildup factor to incident beam. Transmission buildup factors for adipose, bone, muscle, and skin human tissues, as well as for various combinations of these media for point isotropic photon source with energies of .15, 1.5 and 15 MeV, for different thickness of layers, were carried out using Geant4 (version 10.5) simulation toolkit. Also, we performed the analysis of existing multilayered shield fitting models (Lin and Jiang, Kalos, Burke and Beck) of buildup factor and the proposition of a new model. We found that the model combining those of Burke and Beck, for low atomic number (Z) followed by high Z materials and Kalos 1 for high Z followed by low Z materials, accurately reproduces simulation results with approximated deviation of 3 ± 3%, 2 ± 2%, and 3 ± 2% for 2, 3, and 4 layers, respectively. Since buildup factors are the key parameter for point kernel calculations, a correct study can be of great interest to the large community of radiation physicists, in general, and to medical imaging and radiotreatment physicists, especially.

High-throughput, accurate Monte Carlo simulation on CPU hardware for PET applications

Monte Carlo simulations (MCS) represent a fundamental approach to modelling the photon interactions in Positron Emission Tomography (PET). A variety of PET-dedicated MCS tools are available to assist and improve PET imaging applications. Of these, GATE has evolved into one of the most popular software for PET MCS because of its accuracy and flexibility. However, simulations are extremely time-consuming. The use of graphics processing units (GPU) has been proposed as a solution to this, with reported acceleration factors about 400-800. These factors refer to GATE benchmarks performed on a single CPU core. Consequently, CPU-based MCS can also be easily accelerated by one order of magnitude or beyond when exploiting multi-threading on powerful CPUs. Thus, CPU-based implementations become competitive when further optimisations can be achieved. In this context, we have developed a novel, CPU-based software called the PET Physics Simulator (PPS), which combines several efficient methods to significantly boost the performance. PPS flexibly applies GEANT4 cross-sections as a pre-calculated database, thus obtaining results equivalent to GATE. This is demonstrated for an elaborated PET scanner with 3-layer block detectors. All code optimisations yield an acceleration factor of  20 (single core). Multi-threading on a high-end CPU workstation (96 cores) further accelerates the PPS by a factor of 80. This results in a total speed-up factor of 1600, which outperforms comparable GPU-based MCS by a factor of  2. Optionally, the proposed method of coincidence multiplexing can further enhance the throughput by an additonal factor of 15. The combination of all optimisations corresponds to an acceleration factor of  24000. In this way, the PPS can simulate complex PET detector systems with an effective throughput of photon pairs in less than 10 milliseconds.

A Comparison between Electron Gamma Shower, National Research Council/Easy Particle Propagation (EGSnrc/Epp) and Monte Carlo N-Particle Transport Code (MCNP) in Simulation of the INTRABEAM ® System with Spherical Applicators

BACKGROUND

Online Monte Carlo (MC) treatment planning is very crucial to increase the precision of intraoperative radiotherapy (IORT). However, the performance of MC methods depends on the geometries and energies used for the problem under study.

OBJECTIVE

This study aimed to compare the performance of MC N-Particle Transport Code version 4c (MCNP4c) and Electron Gamma Shower, National Research Council/easy particle propagation (EGSnrc/Epp) MC codes using similar geometry of an INTRABEAM^® system.

MATERIAL AND METHODS

This simulation study was done by increasing the number of particles and compared the performance of MCNP4c and EGSnrc/Epp simulations using an INTRABEAM^® system with 1.5 and 5 cm diameter spherical applicators. A comparison of these two codes was done using simulation time, statistical uncertainty, and relative depth-dose values obtained after doing the simulation by each MC code.

RESULTS

The statistical uncertainties for the MCNP4c and EGSnrc/Epp MC codes were below 2% and 0.5%, respectively. 1e9 particles were simulated in 117.89 hours using MCNP4c but a much greater number of particles (5e10 particles) were simulated in a shorter time of 90.26 hours using EGSnrc/Epp MC code. No significant deviations were found in the calculated relative depth-dose values for both in the presence and absence of an air gap between MCNP4c and EGSnrc/Epp MC codes. Nevertheless, the EGSnrc/Epp MC code was found to be speedier and more efficient to achieve accurate statistical precision than MCNP4c.

CONCLUSION

Therefore, in all comparisons criteria used, EGSnrc/Epp MC code is much better than MCNP4c MC code for simulating an INTRABEAM^® system.

Monte Carlo simulation of coherently scattered photons based on the inverse-sampling technique

The acceptance-rejection technique has been widely used in several Monte Carlo simulation packages for Rayleigh scattering of photons. However, the models implemented in these packages might fail to reproduce the corresponding experimental and theoretical results. The discrepancy is attributed to the fact that all current simulations implement an elastic scattering model for the angular distribution of photons without considering anomalous scattering effects. In this study, a novel Rayleigh scattering model using anomalous scattering factors based on the inverse-sampling technique is presented. Its performance was evaluated against other simulation algorithms in terms of simulation accuracy and computational efficiency. The computational efficiency was tested with a general-purpose Monte Carlo package named Particle Transport in Media (PTM). The evaluation showed that a Monte Carlo model using both atomic form factors and anomalous scattering factors for the angular distribution of photons (instead of the atomic form factors alone) produced Rayleigh scattering results in closer agreement with experimental data. The comparison and evaluation confirmed that the inverse-sampling technique using atomic form factors and anomalous scattering factors exhibited improved computational efficiency and performed the best in reproducing experimental measurements and related scattering matrix calculations. Furthermore, using this model to sample coherent scattering can provide scientific insight for complex systems.