Technical Note: GATE‐RTion: a GATE/Geant4 release for clinical applications in scanned ion beam therapy

Beam monitor chamber calibration of a synchro-cyclotron high dose rate per pulse pulsed scanned proton beam

Objective. Ionization chambers, mostly used for beam calibration and for reference dosimetry, can show high recombination effects in pulsed high dose rate proton beams. The aims of this paper are: first, to characterize the linearity response of newly designed asymmetrical beam monitor chambers (ABMC) in a 100-226 MeV pulsed high dose rate per pulse scanned proton beam; and secondly, to calibrate the ABMC with a PPC05 (IBA Dosimetry) plane parallel ionization chamber and compare to calibration with a home-made Faraday cup (FC).Approach. The ABMC response linearity was evaluated with both the FC and a PTW 60019 microDiamond detector. Regarding ionometry-based ABMC calibration, recombination factors were evaluated theoretically, then numerically, and finally experimentally measured in water for a plane parallel ionization chamber PPC05 (IBA Dosimetry) throughkssaturation curves. Finally, ABMC calibration was also achieved with FC and compared to the ionometry method for 7 energies.Main results. Linearity measurements showed that recombination losses in the new ABMC design were well taken into account for the whole range of the machine dose rates. The two-voltage-method was not suitable for recombination correction, but Jaffé's plots analysis was needed, emphasizing the current IAEA TRS-398 reference protocol limitations. Concerning ABMC calibration, FC based absorbed dose estimation and PPC05-based absorbed dose estimation differ by less than 6.3% for the investigated energies.Significance.So far, no update on reference dosimetry protocols is available to estimate the absorbed dose in ionization chambers for clinical high dose rate per pulse pulsed scanned proton beams. This work proposes a validation of the new ABMC design, a method to take into account the recombination effect for ionometry-based ABMC calibration and a comparison with FC dose estimation in this type of proton beams.

UMC-PET: a fast and flexible Monte Carlo PET simulator

Objective.The GPU-based Ultra-fast Monte Carlo positron emission tomography simulator (UMC-PET) incorporates the physics of the emission, transport and detection of radiation in PET scanners. It includes positron range, non-colinearity, scatter and attenuation, as well as detector response. The objective of this work is to present and validate UMC-PET as a a multi-purpose, accurate, fast and flexible PET simulator.Approach.We compared UMC-PET against PeneloPET, a well-validated MC PET simulator, both in preclinical and clinical scenarios. Different phantoms for scatter fraction (SF) assessment following NEMA protocols were simulated in a 6R-SuperArgus and a Biograph mMR scanner, comparing energy histograms, NEMA SF, and sensitivity for different energy windows. A comparison with real data reported in the literature on the Biograph scanner is also shown.Main results.NEMA SF and sensitivity estimated by UMC-PET where within few percent of PeneloPET predictions. The discrepancies can be attributed to small differences in the physics modeling. Running in a 11 GB GeForce RTX 2080 Ti GPU, UMC-PET is ∼1500 to ∼2000 times faster than PeneloPET executing in a single core Intel(R) Xeon(R) CPU W-2155 @ 3.30 GHz.Significance.UMC-PET employs a voxelized scheme for the scanner, patient adjacent objects (such as shieldings or the patient bed), and the activity distribution. This makes UMC-PET extremely flexible. Its high simulation speed allows applications such as MC scatter correction, faster SRM estimation for complex scanners, or even MC iterative image reconstruction.

Proposing a Clinical Model for RBE Based on Proton Track-End Counts

PURPOSE

In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts.

METHODS AND MATERIALS

We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE.

RESULTS

Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track end model identified the same biological hotspots as predicted by LETd-based radiobiological models of proton RBE.

CONCLUSIONS

These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LETd-based models in terms of information provided while also offering superior statistical properties.

Technical note: In silico benchmarking of the linear energy transfer-based functionalities for carbon ion beams in a commercial treatment planning system

BACKGROUND

The increasing number of studies dealing with linear energy transfer (LET)-based evaluation and optimization in the field of carbon ion radiotherapy (CIRT) indicates the rising demand for LET implementation in commercial treatment planning systems (TPS). Benchmarking studies could play a key role in detecting (and thus preventing) computation errors prior implementing such functionalities in a TPS.

PURPOSE

This in silico study was conducted to benchmark the following two LET-related functionalities in a commercial TPS against Monte Carlo simulations: (1) dose averaged LET (LET_d ) scoring and (2) physical dose filtration based on LET for future LET-based treatment plan evaluation and optimization studies.

METHODS

The LET_d scoring and LET-based dose filtering (in which the deposited dose can be separated into the dose below and above the user specified LET threshold) functionalities for carbon ions in the research version RayStation (RS) 9A-IonPG TPS (RaySearch Laboratories, Sweden) were benchmarked against GATE/Geant4 simulations. Pristine Bragg peaks (BPs) and cuboid targets, positioned at different depths in a homogeneous water phantom and a setup with heterogeneity were used for this study.

RESULTS

For all setups (homogeneous and heterogeneous), the mean absolute (and relative) LET_d difference was less than 1 keV/ μ $\umu$ m (3.5%) in the plateau and target and less than 2 keV/ μ $\umu$ m (8.3%) in the fragmentation tail. The maximum local differences were 4 and 6 keV/ μ $\umu$ m, respectively. The mean absolute (and relative) physical dose differences for both low- and high-LET doses were less than 1 cGy (1.5%) in the plateau, target and tail with a maximum absolute difference of 2 cGy.

CONCLUSIONS

No computation error was found in the tested functionalities except for LET_d in lateral direction outside the target, showing the limitation of the implemented monochrome model in the tested TPS version.

GPU accelerated Monte Carlo scoring of positron emitting isotopes produced during proton therapy for PET verification

Objective.Verification of delivered proton therapy treatments is essential for reaping the many benefits of the modality, with the most widely proposedin vivoverification technique being the imaging of positron emitting isotopes generated in the patient during treatment using positron emission tomography (PET). The purpose of this work is to reduce the computational resources and time required for simulation of patient activation during proton therapy using the GPU accelerated Monte Carlo code FRED, and to validate the predicted activity against the widely used Monte Carlo code GATE.Approach.We implement a continuous scoring approach for the production of positron emitting isotopes within FRED version 5.59.9. We simulate treatment plans delivered to 95 head and neck patients at Centrum Cyklotronowe Bronowice using this GPU implementation, and verify the accuracy using the Monte Carlo toolkit GATE version 9.0.Main results.We report an average reduction in computational time by a factor of 50 when using a local system with 2 GPUs as opposed to a large compute cluster utilising between 200 to 700 CPU threads, enabling simulation of patient activity within an average of 2.9 min as opposed to 146 min. All simulated plans are in good agreement across the two Monte Carlo codes. The two codes agree within a maximum of 0.95σon a voxel-by-voxel basis for the prediction of 7 different isotopes across 472 simulated fields delivered to 95 patients, with the average deviation over all fields being 6.4 × 10^-3σ.Significance.The implementation of activation calculations in the GPU accelerated Monte Carlo code FRED provides fast and reliable simulation of patient activation following proton therapy, allowing for research and development of clinical applications of range verification for this treatment modality using PET to proceed at a rapid pace.

Autonomous digitizer calibration of a Monte Carlo detector model through evolutionary simulation

Simulating the response of a radiation detector is a modelling challenge due to the stochastic nature of radiation, often complex geometries, and multi-stage signal processing. While sophisticated tools for Monte Carlo simulation have been developed for radiation transport, emulating signal processing and data loss must be accomplished using a simplified model of the electronics called the digitizer. Due to a large number of free parameters, calibrating a digitizer quickly becomes an optimisation problem. To address this, we propose a novel technique by which evolutionary algorithms calibrate a digitizer autonomously. We demonstrate this by calibrating six free parameters in a digitizer model for the ADAC Forte. The accuracy of solutions is quantified via a cost function measuring the absolute percent difference between simulated and experimental coincidence count rates across a robust characterisation data set, including three detector configurations and a range of source activities. Ultimately, this calibration produces a count rate response with 5.8% mean difference to the experiment, improving from 18.3% difference when manually calibrated. Using evolutionary algorithms for model calibration is a notable advancement because this method is novel, autonomous, fault-tolerant, and achieved through a direct comparison of simulation to reality. The software used in this work has been made freely available through a GitHub repository.

The OpenGATE ecosystem for Monte Carlo simulation in medical physics

This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume, Actors, Digitizer). The main source code repositories are detailed together with the automated compilation and tests processes (Continuous Integration). We then described how the OpenGATE collaboration managed the collaborative development of about one hundred developers during almost 20 years. The impact of GATE on medical physics and cancer research is then summarized, and examples of a few key applications are given. Finally, future development perspectives are indicated.

Technical note: Impact of beamline-specific particle energy spectra on clinical plans in carbon ion beam therapy

PURPOSE

The Local Effect Model version one (LEM I) is applied clinically across Europe to quantify the relative biological effectiveness (RBE) of carbon ion beams. It requires the full particle fluence spectrum differential in energy in each voxel as input parameter. Treatment planning systems (TPSs) use beamline-specific look-up tables generated with Monte Carlo (MC) codes. In this study, the changes in RBE weighted dose were quantified using different levels of details in the simulation or different MC codes.

METHODS

The particle fluence differential in energy was simulated with FLUKA and Geant4 at 500 depths in water in 1-mm steps for 58 initial carbon ion energies (between 120.0 and 402.8 MeV/u). A dedicated beam model was applied, including the full description of the Nozzle using GATE-RTionV1.0 (Geant4.10.03p03). In addition, two tables generated with FLUKA were compared. The starting points of the FLUKA simulations were phase space (PhS) files from, firstly, the Geant4 nozzle simulations, and secondly, a clinical beam model where an analytic approach was used to mimic the beamline. Treatment plans (TPs) were generated with RayStation 8B (RaySearch Laboratories AB, Sweden) for cubic targets in water and 10 clinical patient cases using the clinical beam model. Subsequently, the RBE weighted dose was re-computed using the two other fluence tables (FLUKA PhS or Geant4).

RESULTS

The fluence spectra of the primary and secondary particles simulated with Geant4 and FLUKA generally agreed well for the primary particles. Differences were mainly observed for the secondary particles. Interchanging the two energy spectra (FLUKA vs. GEANT4) to calculate the RBE weighted dose distributions resulted in average deviations of less than 1% in the entrance up to the end of the target region, with a maximum local deviation at the distal edge of the target. In the fragment tail, larger discrepancies of up to 5% on average were found for deep-seated targets. The patient and water phantom cases demonstrated similar results.

CONCLUSION

RBE weighted doses agreed well within all tested setups, confirming the clinical beam model provided by the TPS vendor. Furthermore, the results showed that the open source and generally available MC code Geant4 (in particular using GATE or GATE-RTion) can also be used to generate basic beam data required for RBE calculation in carbon ion therapy.

Estimate of the Biological Dose in Hadrontherapy Using GATE

For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D10 for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic ions. These two models were used to create databases of survival fraction coefficients for several ion types (hydrogen, carbon, helium and oxygen) and for energies ranging from 0.1 to 400 MeV/n. We calculated α values as a function of LET with the mMKM and the NanOx models, and compared these with the literature. In order to estimate the biological dose for SOBPs, these databases were used with a Monte Carlo toolkit. We considered GATE, an open-source software based on the GEANT4 Monte Carlo toolkit. We implemented a tool, the BioDoseActor, in GATE, using the mMKM and NanOx databases of cell survival predictions as input, to estimate, at a voxel scale, biological outcomes when treating a patient. We modeled the HIBMC 320 MeV/u carbon-ion beam line. We then tested the BioDoseActor for the estimation of biological dose, the relative biological effectiveness (RBE) and the cell survival fraction for the irradiation of the HSG cell line. We then tested the implementation for the prediction of cell survival fraction, RBE and biological dose for the HIBMC 320 MeV/u carbon-ion beamline. For the cell survival fraction, we obtained satisfying results. Concerning the prediction of the biological dose, a 10% relative difference between mMKM and NanOx was reported.

Fixed Beamline Optimization for Intensity Modulated Carbon-Ion Therapy

A major obstacle for the adoption of heavy ion therapy is the cost and technical difficulties to construct and maintain a rotational gantry. Many heavy ion treatment facilities instead choose to construct fixed beamlines as a compromise, which we propose to mitigate with optimized treatment couch angle. We formulate the integrated beam orientation and scanning spot optimization problem as a quadratic cost function with a group sparsity regularization term. The optimization problem is efficiently solved using fast iterative shrinkage-thresholding algorithm (FISTA). To test the method, we created the fixed beamline plans with couch rotation (FBCR) and without couch rotation (FB) for intensity modulated carbon-ion therapy (IMCT) and compared with the ideal scenario where both the couch and gantry have 360 degrees of freedom (GCR). FB, FBCR, and GCR IMCT plans were compared for ten pancreas cases. The FBCR plans show comparable PTV coverage and OAR doses for each pancreas case. In conclusion, the dosimetric limitation of fixed beams in heavy ion radiotherapy may be largely mitigated with integrated beam orientation optimization of the couch rotation.

Towards harmonizing clinical linear energy transfer (LET) reporting in proton radiotherapy: a European multi-centric study

BACKGROUND

Clinical data suggest that the relative biological effectiveness (RBE) in proton therapy (PT) varies with linear energy transfer (LET). However, LET calculations are neither standardized nor available in clinical routine. Here, the status of LET calculations among European PT institutions and their comparability are assessed.

MATERIALS AND METHODS

Eight European PT institutions used suitable treatment planning systems with their center-specific beam model to create treatment plans in a water phantom covering different field arrangements and fulfilling commonly agreed dose objectives. They employed their locally established LET simulation environments and procedures to determine the corresponding LET distributions. Dose distributions D1.1 and DRBE assuming constant and variable RBE, respectively, and LET were compared among the institutions. Inter-center variability was assessed based on dose- and LET-volume-histogram parameters.

RESULTS

Treatment plans from six institutions fulfilled all clinical goals and were eligible for common analysis. D1.1 distributions in the target volume were comparable among PT institutions. However, corresponding LET values varied substantially between institutions for all field arrangements, primarily due to differences in LET averaging technique and considered secondary particle spectra. Consequently, DRBE using non-harmonized LET calculations increased inter-center dose variations substantially compared to D1.1 and significantly in mean dose to the target volume of perpendicular and opposing field arrangements (p < 0.05). Harmonizing LET reporting (dose-averaging, all protons, LET to water or to unit density tissue) reduced the inter-center variability in LET to the order of 10-15% within and outside the target volume for all beam arrangements. Consequentially, inter-institutional variability in DRBE decreased to that observed for D1.1.

CONCLUSION

Harmonizing the reported LET among PT centers is feasible and allows for consistent multi-centric analysis and reporting of tumor control and toxicity in view of a variable RBE. It may serve as basis for harmonized variable RBE dose prescription in PT.

A Monte Carlo study of different LET definitions and calculation parameters for proton beam therapy

The strongin vitroevidence that proton Relative Biological Effectiveness (RBE) varies with Linear Energy Transfer (LET) has led to an interest in applying LET within treatment planning. However, there is a lack of consensus on LET definition, Monte Carlo (MC) parameters or clinical methodology. This work aims to investigate how common variations of LET definition may affect potential clinical applications. MC simulations (GATE/GEANT4) were used to calculate absorbed dose and different types of LET for a simple Spread Out Bragg Peak (SOBP) and for four clinical PBT plans covering a range of tumour sites. Variations in the following LET calculation methods were considered: (i) averaging (dose-averaged LET (LET_d) & track-averaged LET); (ii) scoring (LET_dto water, to medium and to mass density); (iii) particle inclusion (LET_dto all protons, to primary protons and to particles); (iv) MC settings (hit type and Maximum Step Size (MSS)). LET distributions were compared using: qualitative comparison, LET Volume Histograms (LVHs), single value criteria (maximum and mean values) and optimised LET-weighted dose models. Substantial differences were found between LET values in averaging, scoring and particle type. These differences depended on the methodology, but for one patient a difference of ∼100% was observed between the maximum LET_dfor all particles and maximum LET_dfor all protons within the brainstem in the high isodose region (4 keVμm^-1and 8 keVμm^-1respectively). An RBE model using LET_dincluding heavier ions was found to predict substantially different LET-weighted dose compared to those using other LET definitions. In conclusion, the selection of LET definition may affect the results of clinical metrics considered in treatment planning and the results of an RBE model. The authors' advocate for the scoring of dose-averaged LET to water for primary and secondary protons using a random hit type and automated MSS.

NRG Oncology Survey of Monte Carlo Dose Calculation Use in US Proton Therapy Centers

Purpose/Objective(s)

Monte Carlo (MC) dose calculation has appeared in primary commercial treatment-planning systems and various in-house platforms. Dual-energy computed tomography (DECT) and metal artifact reduction (MAR) techniques complement MC capabilities. However, no publications have yet reported how proton therapy centers implement these new technologies, and a national survey is required to determine the feasibility of including MC and companion techniques in cooperative group clinical trials.

Materials/Methods

A 9-question survey was designed to query key clinical parameters: scope of MC utilization, validation methods for heterogeneities, clinical site-specific imaging guidance, proton range uncertainties, and how implants are handled. A national survey was distributed to all 29 operational US proton therapy centers on 13 May 2019.

Results

We received responses from 25 centers (86% participation). Commercial MC was most commonly used for primary plan optimization (16 centers) or primary dose evaluation (18 centers), while in-house MC was used more frequently for secondary dose evaluation (7 centers). Based on the survey, MC was used infrequently for gastrointestinal, genitourinary, gynecology and extremity compared with other more heterogeneous disease sites (P < .007). Although many centers had published DECT research, only 3/25 centers had implemented DECT clinically, either in the treatment-planning system or to override implant materials. Most centers (64%) treated patients with metal implants on a case-by-case basis, with a variety of methods reported. Twenty-four centers (96%) used MAR images and overrode the surrounding tissue artifacts; however, there was no consensus on how to determine metal dimension, materials density, or stopping powers.

Conclusion

The use of MC for primary dose calculation and optimization was prevalent and, therefore, likely feasible for clinical trials. There was consensus to use MAR and override tissues surrounding metals but no consensus about how to use DECT and MAR for human tissues and implants. Development and standardization of these advanced technologies are strongly encouraged for vendors and clinical physicists.

Technical note: GAMMORA, a free, open-source, and validated GATE-based model for Monte-Carlo simulations of the Varian TrueBeam

PURPOSE

Monte Carlo (MC) is the reference computation method for medical physics. In radiotherapy, MC computations are necessary for some issues (such as assessing figures of merit, double checks, and dose conversions). A tool based on GATE is proposed to easily create full MC simulations of the Varian TrueBeam STx.

METHODS

GAMMORA is a package that contains photon phase spaces as a pre-trained generative adversarial network (GAN) and the TrueBeam's full geometry. It allows users to easily create MC simulations for simple or complex radiotherapy plans such as VMAT. To validate the model, the characteristics of generated photons are first compared to those provided by Varian (IAEA format). Simulated data are also compared to measurements in water and heterogeneous media. Simulations of 8 SBRT plans are compared to measurements (in a phantom). Two examples of applications (a second check and interplay effect assessment) are presented.

RESULTS

The simulated photons generated by the GAN have the same characteristics (energy, position, and direction) as the IAEA data. Computed dose distributions of simple cases (in water) and complex plans delivered in a phantom are compared to measurements, and the Gamma index (3%/3mm) was always superior to 98%. The feasibility of both clinical applications is shown.

CONCLUSIONS

This model is now shared as a free and open-source tool that generates radiotherapy MC simulations. It has been validated and used for five years. Several applications can be envisaged for research and clinical purposes.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

Monte Carlo computation of 3D distributions of stopping power ratios in light ion beam therapy using GATE-RTion

PURPOSE

This paper presents a novel method for the calculation of three-dimensional (3D) Bragg-Gray water-to-detector stopping power ratio (s_w,det ) distributions for proton and carbon ion beams.

METHODS

Contrary to previously published fluence-based calculations of the stopping power ratio, the s_w,det calculation method used in this work is based on the specific way GATE/Geant4 scores the energy deposition. It only requires the use of the so-called DoseActor, as available in GATE, for the calculation of the s_w,det at any point of a 3D dose distribution. The simulations are performed using GATE-RTion v1.0, a dedicated GATE release that was validated for the clinical use in light ion beam therapy.

RESULTS

The Bragg-Gray water-to-air stopping power ratio (s_w,air ) was calculated for monoenergetic proton and carbon ion beams with the default stopping power data in GATE-RTion v1.0 and the new ICRU90 recommendation. The s_w,air differences between the use of the default and the ICRU90 configuration were 0.6% and 5.4% at the physical range (R₈₀ - 80% dose level in the distal dose fall-off) for a 70 MeV proton beam and a 120 MeV/u carbon ion beam, respectively. For protons, the s_w,det results for lithium fluoride, silicon, gadolinium oxysulfide, and the active layer material of EBT2 (radiochromic film) were compared with the literature and a reasonable agreement was found. For a real patient treatment plan, the 3D distributions of s_w,det in proton beams were calculated.

CONCLUSIONS

Our method was validated by comparison with available literature data. Its equivalence with Bragg-Gray cavity theory was demonstrated mathematically. The capability of GATE-RTion v1.0 for the s_w,det calculation at any point of a 3D dose distribution for simple and complex proton and carbon ion plans was presented.

Automated Monte-Carlo re-calculation of proton therapy plans using Geant4/Gate: implementation and comparison to plan-specific quality assurance measurements

OBJECTIVES

Software re-calculation of proton pencil beam scanning plans provides a method of verifying treatment planning system (TPS) dose calculations prior to patient treatment. This study describes the implementation of AutoMC, a Geant4 v10.3.3/Gate v8.1 (Gate-RTion v1.0)-based Monte-Carlo (MC) system for automated plan re-calculation, and presents verification results for 153 patients (730 fields) planned within year one of the proton service at The Christie NHS Foundation Trust.

METHODS

A MC beam model for a Varian ProBeam delivery system with four range-shifter options (none, 2 cm, 3 cm, 5 cm) was derived from beam commissioning data and implemented in AutoMC. MC and TPS (Varian Eclipse v13.7) calculations of 730 fields in solid-water were compared to physical plan-specific quality assurance (PSQA) measurements acquired using a PTW Octavius 1500XDR array and PTW 31021 Semiflex 3D ion chamber.

RESULTS

TPS and MC showed good agreement with array measurements, evaluated using γ analyses at 3%, 3 mm with a 10% lower dose threshold:>94% of fields calculated by the TPS and >99% of fields calculated by MC had γ ≤ 1 for>95% of measurement points within the plane. TPS and MC also showed good agreement with chamber measurements of absolute dose, with systematic differences of <1.5% for all range-shifter options.

CONCLUSIONS

Reliable independent verification of the TPS dose calculation is a valuable complement to physical PSQA and may facilitate reduction of the physical PSQA workload alongside a thorough delivery system quality assurance programme.

ADVANCES IN KNOWLEDGE

A Gate/Geant4-based MC system is thoroughly validated against an extensive physical PSQA dataset for 730 clinical fields, showing that clinical implementation of MC for PSQA is feasible.

Evaluation of GATE-RTion (GATE/Geant4) Monte Carlo simulation settings for proton pencil beam scanning quality assurance

PURPOSE

Geant4 is a multi-purpose Monte Carlo simulation tool for modeling particle transport in matter. It provides a wide range of settings, which the user may optimize for their specific application. This study investigates GATE/Geant4 parameter settings for proton pencil beam scanning therapy.

METHODS

GATE8.1/Geant4.10.3.p03 (matching the versions used in GATE-RTion1.0) simulations were performed with a set of prebuilt Geant4 physics lists (QGSP_BIC, QGSP_BIC_EMY, QGSP_BIC_EMZ, QGSP_BIC_HP_EMZ), using 0.1mm-10mm as production cuts on secondary particles (electrons, photons, positrons) and varying the maximum step size of protons (0.1mm, 1mm, none). The results of the simulations were compared to measurement data taken during clinical patient specific quality assurance at The Christie NHS Foundation Trust pencil beam scanning proton therapy facility. Additionally, the influence of simulation settings was quantified in a realistic patient anatomy based on computer tomography (CT) scans.

RESULTS

When comparing the different physics lists, only the results (ranges in water) obtained with QGSP_BIC (G4EMStandardPhysics_Option0) depend on the maximum step size. There is clinically negligible difference in the target region when using High Precision neutron models (HP) for dose calculations. The EMZ electromagnetic constructor provides a closer agreement (within 0.35 mm) to measured beam sizes in air, but yields up to 20% longer execution times compared to the EMY electromagnetic constructor (maximum beam size difference 0.79 mm). The impact of this on patient-specific quality assurance simulations is clinically negligible, with a 97% average 2%/2 mm gamma pass rate for both physics lists. However, when considering the CT-based patient model, dose deviations up to 2.4% are observed. Production cuts do not substantially influence dosimetric results in solid water, but lead to dose differences of up to 4.1% in the patient CT. Small (compared to voxel size) production cuts increase execution times by factors of 5 (solid water) and 2 (patient CT).

CONCLUSIONS

Taking both efficiency and dose accuracy into account and considering voxel sizes with 2 mm linear size, the authors recommend the following Geant4 settings to simulate patient specific quality assurance measurements: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (in the phantom and range-shifter) and 10 mm (world); best agreement to measurement data was found for QGSP_BIC_EMZ reference physics list at the cost of 20% increased execution times compared to QGSP_BIC_EMY. For simulations considering the patient CT model, the following settings are recommended: No step limiter on proton tracks; production cuts of 1 mm for electrons, photons and positrons (phantom/range-shifter) and 10 mm (world) if the goal is to achieve sufficient dosimetric accuracy to ensure that a plan is clinically safe; or 0.1 mm (phantom/range-shifter) and 1 mm (world) if higher dosimetric accuracy is needed (increasing execution times by a factor of 2); most accurate results expected for QGSP_BIC_EMZ reference physics list, at the cost of 10-20% increased execution times compared to QGSP_BIC_EMY.