A Monte Carlo pencil beam scanning model for proton treatment plan simulation using GATE/GEANT4

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.

Evaluation of monte carlo to support commissioning of the treatment planning system of new pencil beam scanning proton therapy facilities

Objective. To demonstrate the potential of Monte Carlo (MC) to support the resource-intensive measurements that comprise the commissioning of the treatment planning system (TPS) of new proton therapy facilities.Approach. Beam models of a pencil beam scanning system (Varian ProBeam) were developed in GATE (v8.2), Eclipse proton convolution superposition algorithm (v16.1, Varian Medical Systems) and RayStation MC (v12.0.100.0, RaySearch Laboratories), using the beam commissioning data. All models were first benchmarked against the same commissioning data and validated on seven spread-out Bragg peak (SOBP) plans. Then, we explored the use of MC to optimise dose calculation parameters, fully understand the performance and limitations of TPS in homogeneous fields and support the development of patient-specific quality assurance (PSQA) processes. We compared the dose calculations of the TPSs against measurements (DDTPSvs.Meas.) or GATE (DDTPSvs.GATE) for an extensive set of plans of varying complexity. This included homogeneous plans with varying field-size, range, width, and range-shifters (RSs) (n= 46) and PSQA plans for different anatomical sites (n= 11).Main results. The three beam models showed good agreement against the commissioning data, and dose differences of 3.5% and 5% were found for SOBP plans without and with RSs, respectively. DDTPSvs.Meas.and DDTPSvs.GATEwere correlated in most scenarios. In homogeneous fields the Pearson's correlation coefficient was 0.92 and 0.68 for Eclipse and RayStation, respectively. The standard deviation of the differences between GATE and measurements (±0.5% for homogeneous and ±0.8% for PSQA plans) was applied as tolerance when comparing TPSs with GATE. 72% and 60% of the plans were within the GATE predicted dose difference for both TPSs, for homogeneous and PSQA cases, respectively.Significance. Developing and validating a MC beam model early on into the commissioning of new proton therapy facilities can support the validation of the TPS and facilitate comprehensive investigation of its capabilities and limitations.

Deep learning-based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy

BACKGROUND

Plan verification is one of the important steps of quality assurance (QA) in carbon ion radiotherapy. Conventional methods of plan verification are based on phantom measurement, which is labor-intensive and time-consuming. Although the plan verification method based on Monte Carlo (MC) simulation provides a more accurate modeling of the physics, it is also time-consuming when simulating with a large number of particles. Therefore, how to ensure the accuracy of simulation results while reducing simulation time is the current difficulty and focus.

PURPOSE

The purpose of this work was to evaluate the feasibility of using deep learning-based MC denoising method to accelerate carbon-ion radiotherapy plan verification.

METHODS

Three models, including CycleGAN, 3DUNet and GhostUNet with Ghost module, were used to denoise the 1 × 106 carbon ions-based MC dose distribution to the accuracy of 1 × 108 carbon ions-based dose distribution. The CycleGAN's generator, 3DUNet and GhostUNet were all derived from the 3DUNet network. A total of 59 cases including 29 patients with head-and-neck cancers and 30 patients with lung cancers were collected, and 48 cases were randomly selected as the training set of the CycleGAN network and six cases as the test set. For the 3DUNet and GhostUNet models, the numbers of training set, validation set, and test set were 47, 6, and 6, respectively. Finally, the three models were evaluated qualitatively and quantitatively using RMSE and three-dimensional gamma analysis (3 mm, 3%).

RESULTS

The three end-to-end trained models could be used for denoising the 1 × 106 carbon ions-based dose distribution, and their generalization was proved. The GhostUNet obtained the lowest RMSE value of 0.075, indicating the smallest difference between its denoised and 1 × 108 carbon ions-based dose distributions. The average gamma passing rate (GPR) between the GhostUNet denoising-based versus 1 × 108 carbon ions-based dose distributions was 99.1%, higher than that of the CycleGAN at 94.3% and the 3DUNet at 96.2%. Among the three models, the GhostUNet model had the fewest parameters (4.27 million) and the shortest training time (99 s per epoch) but achieved the best denoising results.

CONCLUSION

The end-to-end deep network GhostUNet outperforms the CycleGAN, 3DUNet models in denoising MC dose distributions for carbon ion radiotherapy. The network requires less than 5 s to denoise a sample of MC simulation with few particles to obtain a qualitative and quantitative result comparable to the dose distribution simulated by MC with relatively large number particles, offering a significant reduction in computation time.

Treatment planning of scanned proton beams in RayStation

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

A systematic approach for calibrating a Monte Carlo code to a treatment planning system for obtaining dose, LET, variable proton RBE and out-of-field dose

Objective. While integration of variable relative biological effectiveness (RBE) has not reached full clinical implementation, the importance of having the ability to recalculate proton treatment plans in a flexible, dedicated Monte Carlo (MC) code cannot be understated . Here we provide a step-wise method for calibrating dose from a MC code to a treatment planning system (TPS), to obtain required parameters for calculating linear energy transfer (LET), variable RBE and in general enabling clinical realistic research studies beyond the capabilities of a TPS.Approach. Initially, Pristine Bragg peaks (PBP) were calculated in both the Eclipse TPS and the FLUKA MC code. A rearranged Bortfeld energy-range relation was applied to the initial energy of the beam to fine-tune the range of the MC code at 80% dose level distal to the PBP. The energy spread was adapted by dividing the TPS range by the MC range for dose level 80%-20% distal to the PBP. Density and relative proton stopping power were adjusted by comparing the TPS and MC for different Hounsfield units. To find the relationship of dose per primary particle from the MC to dose per monitor unit in the TPS, integration was applied to the area of the Bragg curve. The calibration was validated for spread-out Bragg peaks (SOBP) in water and patient treatment plans. Following the validation, variable RBE were calculated using established models.Main results.The PBPs ranges were within ±0.3mm threshold, and a maximum of 5.5% difference for the SOBPs was observed. The patient validation showed excellent dose agreement between the TPS and MC, with the greatest differences for the lung tumor patient.Significance. Aprocedure for calibrating a MC code to a TPS was developed and validated. The procedure enables MC-based calculation of dose, LET, variable RBE, advanced (secondary) particle tracking and more from treatment plans.

Development and validation of an optimal GATE model for proton pencil-beam scanning delivery

OBJECTIVE

To develop and validate a versatile Monte Carlo (MC)-based dose calculation engine to support MC-based dose verification of treatment planning systems (TPSs) and quality assurance (QA) workflows in proton therapy.

METHODS

The GATE MC toolkit was used to simulate a fixed horizontal active scan-based proton beam delivery (SIEMENS IONTRIS). Within the nozzle, two primary and secondary dose monitors have been designed to enable the comparison of the accuracy of dose estimation from MC simulations with respect to physical QA measurements. The developed beam model was validated against a series of commissioning measurements using pinpoint chambers and 2D array ionization chambers (IC) in terms of lateral profiles and depth dose distributions. Furthermore, beam delivery module and treatment planning has been validated against the literature deploying various clinical test cases of the AAPM TG-119 (c-shape phantom) and a prostate patient.

RESULTS

MC simulations showed excellent agreement with measurements in the lateral depth-dose parameters and spread-out Bragg peak (SOBP) characteristics within a maximum relative error of 0.95 mm in range, 1.83% in entrance to peak ratio, 0.27% in mean point-to-point dose difference, and 0.32% in peak location. The mean relative absolute difference between MC simulations and measurements in terms of absorbed dose in the SOBP region was 0.93% ± 0.88%. Clinical phantom studies showed a good agreement compared to research TPS (relative error for TG-119 planning target volume PTV-D95 ∼ 1.8%; and for prostate PTV-D95 ∼ -0.6%).

CONCLUSION

We successfully developed a MC model for the pencil beam scanning system, which appears reliable for dose verification of the TPS in combination with QA information, prior to patient treatment.

A simple method to import CAD mesh format models in FLUKA

BACKGROUND

Monte Carlo (MC) code FLUKA possesses widespread usage and accuracy in the simulation of particle beam radiotherapy. However, the conversion from computer-aided design (CAD) mesh format models to FLUKA readable geometries could not be implemented directly and conveniently. A simple method was required to be developed.

PURPOSE

The present study proposed a simple method to voxelize CAD mesh format files by using a Python-based script and establishing geometric models in FLUKA.

METHODS

Five geometric models including cube, sphere, cone, ridge filter (RGF), and 1D-Ripple Filter (1D-RiFi) were created and exported as CAD mesh format files (.stl). An open-source Python-based script was used to convert them into voxels by endowing X, Y, and Z (following the Cartesian coordinates system) of solid materials in the three-dimensional (3D) grid. A FLUKA (4-2.2, CERN) predefined routine was used to establish the voxelized geometry model (VGM), while Flair (3.2-1, CERN) was used to build the direct geometry model (DGM) in FLUKA for comparison purposes. Uniform carbon ion radiation fields 8×8 cm3 and 4×4 cm3 were generated to transport through the five pairs of models, 2D and 3D dose distributions were compared. The integral depth dose (IDD) in water of three different energy levels of carbon ion beams transported through 1D-RiFis were also simulated and compared. Moreover, the volume between CAD mesh and VGMs, as well as the computing speed between FLUKA DGMs and VGMs were simultaneously recorded.

RESULTS

The volume differences between VGMs and CAD mesh models were not more than 0.6%. The maximum mean point-to-point deviation of IDD distribution was 0.7% ± 0.51% (mean ± standard deviation). The 3D dose Gamma-index passing rates were never lower than 97% with criteria of 1%-1 mm. The difference in computing CPU time was 2.89% ± 0.22 on average.

CONCLUSIONS

The present study proposed and verified a Python-based method for converting CAD mesh format files into VGMs and establishing them in FLUKA simply as well as accurately.

Extended in-field and out-of-field validation of a compact Monte Carlo model of an IBA PROTEUS®ONE proton beam in TOPAS/GEANT4

Objective:This study evaluates a compact Monte Carlo (MC) model of a pencil beam scanning clinical proton beam using TOPAS to estimate the dose out-of-field (OOF). Compact modelling means that the model starts from a pristine proton beam at the nozzle exit, customised based on acceptance and commissioning data, instead of modelling the full treatment head and room.Approach: First, in-field validation tests were performed. Then, the OOF dose was validated in an RW3 phantom with bubble detectors for personal neutron dosimetry (measuring the neutron dose equivalent) and thermoluminiescent detectors (measuring the absorbed dose by protons and gammas). Measurements were performed at 15 and 35 cm from the distal edge of the field for five different irradiation plans, covering different beam orientations, proton energies and a 40 mm range shifter. TOPAS simulations were performed with QGSP Binary Cascade HP (BIC) and QGSP Bertini HP (Bertini) hadron physics lists.Main results: In-field validation shows that MC simulations agree with point dose measurements within -2.5 % and +1.5 % at locations on- and off-axis and before, in and after the Bragg peak or plateau. The gamma passing rate 2%/3mm of four simulated treatment plans compared to the dose distribution calculated by the TPS exceeds 97 % agreement score. OOF dose simulations showed an average overestimation of 27 % of the neutron dose equivalent for the BIC hadron physics list and an average underestimation of 20 % for the Bertini hadron physics list. The simulated absorbed dose of protons and gammas showed a systematic underestimation which was on average 21 % and 51 % for BIC and Bertini respectively.Significance: Our study demonstrates that a compact MC model can reliably produce in-field data, while out-of-field dose data are within the uncertainties of the detector systems and MC simulations nuclear models, and do so with shorter modelling and faster calculation time.

Commissioning dose computation model for proton source in pencil beam scanning therapy by convolution neural networks

Objective. Proton source model commissioning (PSMC) is critical for ensuring accurate dose calculation in pencil beam scanning (PBS) proton therapy using Monte Carlo (MC) simulations. PSMC aims to match the calculated dose to the delivered dose. However, commissioning the 'nominal energy' and 'energy spread' parameters in PSMC can be challenging, as these parameters cannot be directly obtained from solving equations. To efficiently and accurately commission the nominal energy and energy spread in a proton source model, we developed a convolution neural network (CNN) named 'PSMC-Net.'Methods. The PSMC-Net was trained separately for 33 energies (E, 70-225 MeV with a step of 5 MeV plus 226.09 MeV). For eachE, a dataset was generated consisting of 150 source model parameters (15 nominal energies ∈ [E,E+ 1.5 MeV], ten spreads ∈ [0, 1]) and the corresponding 150 MC integrated depth doses (IDDs). Of these 150 data pairs, 130 were used for training the network, 10 for validation, and 10 for testing.Results. The source model, built by 33 measured IDDs and 33 PSMC-Nets (cost 0.01 s), was used to compute the MC IDDs. The gamma passing rate (GPRs, 1 mm/1%) between MC and measured IDDs was 99.91 ± 0.12%. However, when no commissioning was made, the corresponding GPR was reduced to 54.11 ± 22.36%, highlighting the tremendous significance of our CNN commissioning method. Furthermore, the MC doses of a spread-out Bragg peak and 20 patient PBS plans were also calculated, and average 3D GPRs (2 mm/2% with a 10% threshold) were 99.89% and 99.96 ± 0.06%, respectively.Significance. We proposed a nova commissioning method of the proton source model using CNNs, which made the PSMC process easy, efficient, and accurate.

The effect of voxelization in Monte Carlo simulation to validate Bragg peak characteristics for a pencil proton beam

Background

The purpose of this research was to show how the Bragg peak (BP) characteristics were affected by changing the voxel size in longitudinal and transverse directions in Monte Carlo (MC) simulations by using Geant4 and to calculate BP characteristics accurately by considering the voxel size effect for 68 MeV and 235.81 MeV.

Materials and methods

Different interpolation techniques were applied to simulation data to find the closest results to the experimental data.

Results

When the x-size of the voxel was increased 2 times at low energy, the maximum dose increase in the entrance and plateau regions were 17.8% and 17%, respectively, while BP curve shifted to the shallower region, resulting in a 0.5 mm reduction in the curable tumor width (W_80pd). At high energy, the maximum dose increase at the entrance and plateau regions were 0.4% and 0.6%, respectively, while it was observed that W_80pd did not change. When the y-z sizes of the voxel were increased 2 times at low energy, the maximum dose reduction at the entrance and plateau regions was 3.4%, but no change was observed in W_80pd. At high energy, when the y-z sizes of the voxel were increased 2.2 times, the maximum dose reduction at the entrance and plateau regions were 8.9% and 9.1%, respectively, while W_80pd increased by 0.5 mm. When linear, cubic spline, and Akima interpolations were applied to the simulation data, it was found that the results closest to the experimental data were obtained for Akima interpolations for both energies.

Conclusion

it has been shown that the voxel size effect for the longitudinal direction was more effective at low energy than at high energy. However, the voxel size effect for the transverse direction was more effective for high energy.

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.

ProTheRaMon - a GATE simulation framework for proton therapy range monitoring using PET imaging

OBJECTIVE

This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland.

APPROACH

The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user's needs and specific settings of a given proton therapy facility and PET scanner design.

MAIN RESULTS

ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized.

SIGNIFICANCE

We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github.

Direct mapping from PET coincidence data to proton-dose and positron activity using a deep learning approach

Objective. Obtaining the intrinsic dose distributions in particle therapy is a challenging problem that needs to be addressed by imaging algorithms to take advantage of secondary particle detectors. In this work, we investigate the utility of deep learning methods for achieving direct mapping from detector data to the intrinsic dose distribution. Approach. We performed Monte Carlo simulations using GATE/Geant4 10.4 simulation toolkits to generate a dataset using human CT phantom irradiated with high-energy protons and imaged with compact in-beam PET for realistic beam delivery in a single-fraction (∼2 Gy). We developed a neural network model based on conditional generative adversarial networks to generate dose maps conditioned on coincidence distributions in the detector. The model performance is evaluated by the mean relative error, absolute dose fraction difference, and shift in Bragg peak position. Main results. The relative deviation in the dose and range of the distributions predicted by the model from the true values for mono-energetic irradiation between 50 and 122 MeV lie within 1% and 2%, respectively. This was achieved using 105 coincidences acquired five minutes after irradiation. The relative deviation in the dose and range for spread-out Bragg peak distributions were within 1% and 2.6% uncertainties, respectively. Significance. An important aspect of this study is the demonstration of a method for direct mapping from detector counts to dose domain using the low count data of compact detectors suited for practical implementation in particle therapy. Including additional prior information in the future can further expand the scope of our model and also extend its application to other areas of medical imaging.

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.

Determination of Integral Depth Dose in Proton Pencil Beam Using Plane-parallel Ionization Chambers

Purpose

This study aimed to determine the integral depth-dose curves and assess the geometric collection efficiency of different detector diameters in proton pencil beam scanning.

Materials and Methods

The Varian ProBeam Compact spot scanning system was used for this study. The integral depth-dose curves with a proton energy range of 130 to 220 MeV were acquired with 2 types of Bragg peak chambers: 34070 with 8-cm diameter and 34089 with 15-cm diameter (PTW), multi-layer ionization chamber with 12-cm diameter (Giraffe, IBA Dosimetry), and PeakFinder with 8-cm diameter (PTW). To assess geometric collection efficiency, the integral depth-dose curves of 8- and 12-cm chamber diameters were compared to a 15-cm chamber diameter as the largest detector.

Results

At intermediate depths of 130, 150, 190, and 220 MeV, PTW Bragg peak chamber type 34089 provided the highest integral depth-dose curves followed by IBA Giraffe, PTW Bragg peak chamber type 34070, and PTW PeakFinder. Moreover, PTW Bragg peak chamber type 34089 had increased geometric collection efficiency up to 3.8%, 6.1%, and 3.1% when compared to PTW Bragg peak chamber type 34070, PTW PeakFinder, and IBA Giraffe, respectively.

Conclusion

A larger plane-parallel ionization chamber could increase the geometric collection efficiency of the detector, especially at intermediate depths and high-energy proton beams.

The influence of beam optics asymmetric distribution on dose in scanning carbon-ion radiotherapy

Purpose

To quantify the influence of beam optics asymmetric distribution on dose.

Methods

Nine reference cubic targets and corresponding plans with modulation widths (M) of 3, 6, and 9 cm and with center depths (CDs) of 6, 12, and 24 cm were generated by the treatment planning system (TPS). The Monte Carlo code FLUKA was used for simulating the dose distribution from the aforementioned original plans and the dose perturbation by varying ±5%, ±15%, ±20%, ±25%, and ±40% in spot full width half maximum to the X‐direction while keeping consistent in the Y‐direction. The dosimetric comparisons in dose deviation, γ‐index analysis, lateral penumbra, and flatness were evaluated.

Results

The largest 3D absolute mean deviation was 15.0% ± 20.9% (mean ± standard deviation) in M3CD6, whereas with the variation from −15% to +20%, the values were below 5% for all cube plans. The lowest 2D γ‐index passing rate was 80.6% with criteria of 2%–2 mm by a +40% variation in M3CD6. For the M9CD24 with a −40% variation, the maximum 1D dose deviations were 5.6% and 15.7% in the high‐dose region and the edge of the radiation field, respectively. The maximum deviations of penumbra and flatness were 3.4 mm and 11.4%, respectively.

Conclusions

The scenario of beam optics asymmetric showed relatively slight influence on the global dose distribution but severely affected dose on the edge of the radiation field. For scanning carbon‐ion therapy facilities, beam spot lateral profile settings in TPS base data should be properly handled when beam optics asymmetry variation is over 15%.

Validation and testing of a novel pencil-beam model derived from Monte Carlo simulations in carbon-ion treatment planning for different scenarios

PURPOSE

The calculation ability of the newly-proposed accurate beam model, the double Gaussian-logistic (DG-L) model, was validated in both homogeneous and heterogeneous phantoms to provide helpful information for its future application in clinical carbon-ion treatment planning system (TPS).

METHODS

MatRad was used as the new algorithm test platform. Based on Monte Carlo (MC) method, the basic database in matRad was generated, then comparative dosimetric analyses between the single Gaussian (SG), double Gaussian (DG) and DG-L models against the MC recalculations were performed on the treatment plans of a cubic water phantom, a TG119 phantom and a liver patient scenario. Absolute dose differences, dose-volume histograms (DVHs) and global γ-index analyses derived from the treatment plans were evaluated.

RESULTS

Calculated with the DG-L model, the deviations of the target dose coverage (D₉₅) for the cubic water phantom, the TG119 phantom and the liver patient case against the MC recalculations could be reduced from -2.5%, -4.6% and -6.4% to -0.3%, -2.0% and -4.5% respectively compared to the SG model, while the γ pass rates (3%/3mm) could be enhanced from 98.0%, 90.6% and 90.1% to 99.8%, 95.7% and 91.6%, respectively. The novel beam model also shows improved performance compared with the DG model, without substantially increasing the computation time.

CONCLUSIONS

The DG-L model could effectively improve the dose calculation accuracy and mitigate the delivered dose deficiency in target volumes compared to the SG and DG models. The lateral heterogeneities should be considered for its future implementation in a clinical TPS.

Development and validation of an automatic commissioning tool for the Monte Carlo dose engine in myQA iON

Independent dose verification with Monte Carlo (MC) simulations is an important feature of proton therapy quality assurance (QA). However, clinical integration of such tools often generates an additional and complex workload for medical physicists. The preparation of the necessary clinical inputs, such as the machine beam model, should therefore be automated. In this work, a methodology for automatic MC commissioning has been devised, validated, and developed into a MATLAB tool for the users of myQA iON, the recent QA platform of IBA Dosimetry. With this workflow, all necessary parameters can easily be tuned using dedicated optimization methods. For the geometrical beam parameters (phase space), the assumption of a single or double Gaussian is made. To model the energy spectrum, a Gaussian function is assumed and parameters are optimized using either MC simulations or a library of pre-computed Bragg peaks. For the absolute dose calibration, commissioning fields can be reproduced with the dose engine to retrieve the necessary parameters. We discuss in a first time the tool efficiency and show that one can optimize all parameters in less than 4 min per energy with excellent accuracy. We then validate a beam model obtained with the tool by simulating homogeneous spread-out Bragg peaks (SOBPs) and patient QA plans previously measured in water. An average range agreement of 0.29 ± 0.34 mm is achieved for the SOBPs while 3%/3 mm local gamma passing rates reach 99.3% on average over all 62 measured patient QA planes, which is well within clinical tolerances.

Biodistribution and internal radiation dosimetry of a companion diagnostic radiopharmaceutical, [68Ga]PSMA-11, in subcutaneous prostate cancer xenograft model mice

[⁶⁸Ga]PSMA-11 is a prostate-specific membrane antigen (PSMA)-targeting radiopharmaceutical for diagnostic PET imaging. Its application can be extended to targeted radionuclide therapy (TRT). In this study, we characterize the biodistribution and pharmacokinetics of [⁶⁸Ga]PSMA-11 in PSMA-positive and negative (22Rv1 and PC3, respectively) tumor-bearing mice and subsequently estimated its internal radiation dosimetry via voxel-level dosimetry using a dedicated Monte Carlo simulation to evaluate the absorbed dose in the tumor directly. Consequently, this approach overcomes the drawbacks of the conventional organ-level (or phantom-based) method. The kidneys and urinary bladder both showed substantial accumulation of [⁶⁸Ga]PSMA-11 without exhibiting a washout phase during the study. For the tumor, a peak concentration of 4.5 ± 0.7 %ID/g occurred 90 min after [⁶⁸Ga]PSMA-11 injection. The voxel- and organ-level methods both determined that the highest absorbed dose occurred in the kidneys (0.209 ± 0.005 Gy/MBq and 0.492 ± 0.059 Gy/MBq, respectively). Using voxel-level dosimetry, the absorbed dose in the tumor was estimated as 0.024 ± 0.003 Gy/MBq. The biodistribution and pharmacokinetics of [⁶⁸Ga]PSMA-11 in various organs of subcutaneous prostate cancer xenograft model mice were consistent with reported data for prostate cancer patients. Therefore, our data supports the use of voxel-level dosimetry in TRT to deliver personalized dosimetry considering patient-specific heterogeneous tissue compositions and activity distributions.

Monte Carlo framework for commissioning a synchrotron-based discrete spot scanning proton beam system and treatment plan verification

This study aimed to develop a Monte Carlo (MC) framework for commissioning the narrow proton beams (spot size sigma, 5.2 mm 2 mm at isocenter for 69.4 MeV-221.3 MeV for the main beam option and 4.1 mm 1.3 mm for the minibeam option respectively) of a synchrotron-based proton therapy system and design an independent absolute dose calculation engine for intensity-modulated proton treatments. A proton therapy system (Hitachi PROBEAT-V) was simulated using divergent and convergent beam models at the nozzle entrance. The innovative source weighting scheme for the MC simulation with TOPAS (TOol for PArticle Simulations) was implemented using dose output data for the absolute dose calculations. The results of the MC simulation were compared to the experimental data, analyzed and used to commission the treatment planning system. Two MC models, divergent and convergent beams were implemented. The convergent beam model produced a high level of agreement when MC and measurements were analyzed. The beam ellipticity did not result in significant differences between MC simulated and treatment planning system calculated doses. A model of a synchrotron-based spot scanning proton therapy system has been developed and implemented in the TOPAS MC transport code framework. The dose computation engine is useful for treatment plan verification with primary and minibeam beam option.

Empirical quenching correction in radiochromic silicone-based three-dimensional dosimetry of spot-scanning proton therapy

Background and purpose

Three-dimensional dosimetry of proton therapy (PT) with chemical dosimeters is challenged by signal quenching, which is a lower dose-response in regions with high ionization density due to high linear-energy-transfer (LET) and dose-rate. This study aimed to assess the viability of an empirical correction model for 3D radiochromic silicone-based dosimeters irradiated with spot-scanning PT, by parametrizing its LET and dose-rate dependency.

Materials and methods

Ten cylindrical radiochromic dosimeters (Ø50 and Ø75 mm) were produced in-house, and irradiated with different spot-scanning proton beam configurations and machine-set dose rates ranging from 56 to 145 Gy/min. Beams with incident energies of 75, 95 and 120 MeV, a spread-out Bragg peak and a plan optimized to an irregular target volume were included. Five of the dosimeters, irradiated with 120 MeV beams, were used to estimate the quenching correction factors. Monte Carlo simulations were used to obtain dose and dose-averaged-LET (LET_d) maps. Additionally, a local dose-rate map was estimated, using the simulated dose maps and the machine-set dose-rate information retrieved from the irradiation log-files. Finally, the correction factor was estimated as a function of LET_d and local dose-rate and tested on the different fields.

Results

Gamma-pass-rates of the corrected measurements were >94% using a 3%-3 mm gamma analysis and >88% using 2%-2 mm, with a dose deviation of <5.6 ± 1.8%. Larger dosimeters showed a 20% systematic increase in dose-response, but the same quenching in signal when compared to the smaller dosimeters.

Conclusion

The quenching correction model was valid for different dosimeter sizes to obtain relative dosimetric maps of complex dose distributions in PT.

Proton FLASH: passive scattering or pencil beam scanning?

This study focused on a direct comparison of dose delivery efficiency between two proton FLASH delivery modes: passive scattering and pencil beam scanning (PBS). Monte-Carlo simulation of the beamline was performed using the Geant4 package. Two proton energies (63 and 230 MeV) were selected, targeting for shallow and deep-seated tumors, respectively. Two irradiation field sizes were selected: 13 × 13 mm² and 50 × 50 mm². For each delivery mode, two cases were investigated: shoot-through and Bragg peak, yielding a total of 4 delivery scenarios. For the passive scattering mode, the impact on dose rate by multiple components along the beamline were investigated, including ridge-filter, scatterer, range shifter and collimator. A quantitative comparison among four scenarios was made in terms of field size, dose, dose rate and treatment plan quality (dose volume histogram). For the 230 MeV case, the dose rate (for 1 nA current) is 0.05 Gy s^-1 (passive with Bragg peak, field size: 50 × 50 mm²) and 2.6 Gy s^-1 (PBS with shoot-through). Dose rate comparison is made between passive scattering and PBS as the delivery changes from spot-layer to shoot-through. In conclusion, the study successfully established a benchmark reference for dose rate performance for different scenarios, taking into account components along the beamline, field size and beam current. The results allow us to predict and compare the required beam current to yield a dose rate sufficiently high, above the threshold of the FLASH effect.

Fast MCsquare-Based Independent Dose Verification Platform for Pencil Beam Scanning Proton Therapy

PURPOSE

To commission MCsquare (a multi-cores CPU-based dose calculation engine) for pencil beam scanning (PBS) proton therapy, integrate it into RayStation treatment plan system (TPS) to create a dedicated platform for fast independent dose verification.

METHOD

A MCsquare-based independent dose verification platform (MC2InRS) was developed to realize automatic dose re-calculation for clinical use, including data preparation, dose calculation, 2D/3D gamma analysis. MCsquare was commissioned based on in-air lateral dose profiles, integrated depth dose, and the absolute dose of different beam energies for Proteus®ONE. MC2InRS was validated with measurement data using various targets and depths in a water phantom. This study also investigated 15 clinical cases to demonstrate the feasibility and effectiveness of MC2InRS platform in clinic practice.

RESULTS

Between simulation and measurement, the distal range differences at 80% (R80) and 20% (R20) dose levels for each energy were below 0.05 mm, and 0.1 mm, respectively, and the absolute dose differences were below 0.5%. 29 out of 36 QA planes reached a 100% gamma passing rate (GPR) for 2%/2mm criteria, and a minimum of 98.3% gamma was obtained in water phantom between simulation and measurement. For the 15 clinical cases investigated, the average 2D GPR (2%/2mm) was 95.4%, 99.3% for MCsquare vs. measurement, MCsquare vs. TPS, respectively. The average 3D GPR (2%/2mm) was 98.9%, 95.3% for MCsquare vs. TPS in water, and computed tomography (CT), respectively.

CONCLUSION

MC2InRS, a fast, independent dose verification platform, has been developed to perform dose verification with high accuracy and efficiency for Pencil Bream Scanning (PBS). Its potential to be applied in routine clinical practice has also been discussed.

Computer-assisted beam modeling for particle therapy

Purpose

To develop a computer‐driven and thus less user‐dependent method, allowing for a simple and straightforward generation of a Monte Carlo (MC) beam model of a scanned proton and carbon ion beam delivery system.

Methods

In a first step, experimental measurements were performed for proton and carbon ion energies in the available energy ranges. Data included depth dose profiles measured in water and spot sizes in air at various isocenter distances. Using an automated regularization‐based optimization process (AUTO‐BEAM), GATE/Geant4 beam models of the respective beam lines were generated. These were obtained sequentially by using least square weighting functions with and without regularization, to iteratively tune the beam parameters energy, energy spread, beam sigma, divergence, and emittance until a user‐defined agreement was reached. Based on the parameter tuning for a set of energies, a beam model was semi‐automatically generated. The resulting beam models were validated for all centers comparing to independent measurements of laterally integrated depth dose curves and spot sizes in air. For one representative center, three‐dimensional dose cubes were measured and compared to simulations. The method was applied on one research as well as four different clinical beam lines for proton and carbon ions of three different particle therapy centers using synchrotron or cyclotron accelerator systems: (a) MedAustron ion therapy center, (b) University Proton Therapy Dresden, and (c) Center Antoine Lacassagne Nice.

Results

Particle beam ranges in the MC beam models agreed on average within 0.2 mm compared to measurements for all energies and beam lines. Spot sizes in air (full‐width at half maximum) at all positions differed by less than 0.4% from the measurements. Dose calculation with the beam model for the clinical beam line at MedAustron agreed better than 1.7% in absolute dose for a representative clinical case treated with protons. For protons, beam model generation, including geometry creation, data conversion, and validation, was possible within three working days. The number of iterations required for the optimization process to converge, was found to be similar for all beam line geometries and particle types.

Conclusion

The presented method was demonstrated to work independently of the beam optics behavior of the different beam lines, particle types, and geometries. Furthermore, it is suitable for non‐expert users and requires only limited user interaction. Beam model validation for different beam lines based on different beam delivery systems, showed good agreement.

Using Geant4 Monte Carlo toolkit to evaluate a low power X-ray tube generator configuration

Monte Carlo technique has been widely used as an important tool to develop new irradiation equipment, prototype medical equipment parts, and test methodologies for dosimetry. In this manuscript, we present a methodology to design a low power X-ray tube generator using the Geant4 Monte Carlo toolkit. The simulations were performed considering a large number of variables, namely, the material composition of the target track, the window thickness, and the air pressure of the X-ray tube. The X-ray production was simulated considering monoenergetic electron beams impinging on targets of tungsten and copper with incident kinetic energies ranging from 20 keV to 60 keV and initial divergences from 5° to 30°. For the polyenergetic emission, a conservative approach with Gaussian energy distribution was adopted. The analysis indicates that among the evaluated parameters, the incident kinetic energy, and the target material produced the most notable changes in the spectra shape and conversion efficiency (CE), significantly impacting the X-ray tube design. The studies provide a reliable methodology to explore general configurations for X-ray tube generators, defining the best geometry, material compositions, and thicknesses to be used on spectroscopy applications.

Producing a Beam Model of the Varian ProBeam Proton Therapy System using TOPAS Monte Carlo Toolkit

PURPOSE

A Geant4-based TOPAS Monte Carlo toolkit was utilized to model a Varian ProBeam proton therapy system, with the aim of providing an independent computational platform for validating advanced dosimetric methods.

MATERIALS AND METHODS

The model was tested for accuracy of dose and linear energy transfer (LET) prediction relative to the commissioning data, which included integral depth dose (IDD) in water and spot profiles in air measured at varying depths (for energies of 70 to 240 MeV in increments of 10 MeV, and 242 MeV), and absolute dose calibration. Emittance was defined based on depth-dependent spot profiles and Courant-Snyder's particle transport theory, which provided spot size and angular divergence along the inline and crossline plane. Energy spectra were defined as Gaussian distributions that best matched the range and maximum dose of the IDD. The validity of the model was assessed based on measurements of range, dose to peak difference, mean point to point difference, spot sizes at different depths, and spread-out Bragg peak (SOBP) IDD and was compared to the current treatment planning software (TPS).

RESULTS

Simulated and commissioned spot sizes agreed within 2.5%. The single spot IDD range, maximum dose, and mean point to point difference of each commissioned energy agreed with the simulated profiles generally within 0.07 mm, 0.4%, and 0.6%, respectively. A simulated SOBP plan agreed with the measured dose within 2% for the plateau region. The protons/MU and absolute dose agreed with the current TPS to within 1.6% and exhibited the greatest discrepancy at higher energies.

CONCLUSIONS

The TOPAS model agreed well with the commissioning data and included inline and crossline asymmetry of the beam profiles. The discrepancy between the measured and TOPAS-simulated SOBP plan may be due to beam modeling simplifications of the current TPS and the nuclear halo effect. The model can compute LET, and motivates future studies in understanding equivalent dose prediction in treatment planning, and investigating scintillation quenching.

Cellular S-value evaluation based on real human cell models using the GATE MC package

Exploring the spatial distribution of the energy loss of ionising radiation at the subcellular level is indispensable for evaluating the radiobiological effects of targeted radionuclide therapy accurately. Believing that S-values are important for obtaining the target dose, the Committee on Medical Internal Radiation Dose (MIRD) proposed a method to obtain the cellular dosimetric parameter. However, most available data on cellular S-values were calculated based on simple geometric models, such as ellipsoids or spheres, which do not accurately reflect biological reality. To investigate the influence of the cellular model on S-values, calculations were performed for two kinds of polygon-surface phantom models of realistic, individual human cells, the lung epithelial cell model (the B2B Phantom model) and the hepatocyte model (the Liver Phantom model), using the Monte Carlo (MC) software package GATE. To analyse the influence of cell geometry on the final S-value, the differences in the S-values between the realistic cell models and simple geometric sphere and ellipsoid models with similar volumes were calculated and compared for six different combinations of source and target regions. The irradiation conditions were 0.01-1.10 MeV monoenergetic electron sources and the Auger electronic therapy nuclides Ga-67, Tc-99m, In-111, I-125 and Tl-201, which are commonly used in nuclear medicine. The S-values calculated in this study are different from the results of the simple geometry models proposed by previous researchers. Two more precise polygon-surface phantom models of realistic, individual human cells were used, which provided more accurate information about the cell dose and will be very useful for the diagnostic application of radiotherapy in the future.

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.

Development of a Monte Carlo beam model for raster scanning proton beams and dosimetric comparison

PURPOSE

To develop a Monte Carlo (MC) beam model for raster scanning proton beams for dose verification purposes.

METHODS AND MATERIALS

MC program FLUKA was used in the model. The nominal energy, momentum spread and beam angular distribution in the model were determined by matching the simulation profiles with the measured integral depth dose (IDD) and in air spot size. Dosimetric comparison was done by comparing the measured and simulated dose distributions. The 1 D dose profile of cubic Spread Out Bragg Peak (SOBP) plans, and the 2 D dose distribution of previously treated breast cancer patients' clinical plans were measured by using Pinpoint chambers and 2 D array ionization chambers, respectively. Corresponding DICOM plan information was utilized for MC simulation.

RESULTS

The MC results showed good agreement with measurements for the SOBP plans. The absolute comparison of the absorbed dose difference between the MC and the measurement was 0.93%±0.88%. For the patient plans, the overall passing rate of the gamma index analysis (γ-PR) between the MC simulation and measurement with the 2%-2 mm criteria was 97.78%, and only 1 case had a γ-PR less than 90%. With the 3%-3 mm criteria, γ-PR was never below 99% for all cases with and without the range shifter.

CONCLUSIONS

This work described a method for adapting a MC simulation model for a raster scanning proton beam. The good concordance between the simulations and measurements shows that the MC model is an accurate and reliable method. It has the potential to be used for patient specific quality assurance (PSQA) to reduce the beam time for the measurements in water.

The practical radius of a pencil beam in proton therapy

The central Gaussian shaped high dose region of a pencil beam (PB) in light ion beam therapy (LIBT) is enveloped by a low dose region causing non-negligible field size effects and impairs the dose calculation accuracy considerably if the low dose envelope is not well modeled. The purpose of this study was to calculate the practical radius, R_c, at which a PB does not influence a field more than a certain accuracy level. Lateral dose profiles of proton beams in water were simulated using GATE/Geant4. Those lateral dose profiles were integrated numerically and used to calculate field size factors (FSFs). The R_c was then determined such, that the lateral dose at radii exceeding R_c can be neglected without compromising the FSF of a 20cm×20cm field more than a desired accuracy level c. The practical radius R_c yielding c=0.5% was compared to the frequently applied concept of full width at a ratio x of the maximum (FWxM). The sensitivity to variations of the beam width was tested by increasing the initial beam width σ_C of the clinical beam model by 0.5 and 1mm, respectively. Neglecting the dose at radii exceeding R_c resulted in the desired FSF accuracy, whereas using the FW0.01%M cut resulted in varying accuracy. In order to yield a constant FSF accuracy, the ratio x in FWxM ranged from 0.003% to 0.065% of the maximum. In contrast to R_c, FWxM was sensitive to variations of the initial beam width. The maximum R_c over all depths was less than 7cm for the low(62.4MeV) and medium(148.2MeV) proton energy beam, which suggests that a plane parallel ionization chamber exceeding that radius is sufficient to acquire laterally integrated depth dose distributions for those energies. However, this holds not true for the highest energy (252.7MeV) or when including a range shifter (RaShi). The values of R_c are specific to our beam line configuration as the maximum R_c was depending on both, the scattering material in the Nozzle as well as the distance of the air-gap between Nozzle and phantom.

Technical Note: Integrating an open source Monte Carlo code "MCsquare" for clinical use in intensity-modulated proton therapy

PURPOSE

To commission an open source Monte Carlo (MC) dose engine, "MCsquare" for a synchrotron-based proton machine, integrate it into our in-house C++-based I/O user interface and our web-based software platform, expand its functionalities, and improve calculation efficiency for intensity-modulated proton therapy (IMPT).

METHODS

We commissioned MCsquare using a double Gaussian beam model based on in-air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread-out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++-based dose calculation code and web-based second check platform "DOSeCHECK." We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well-benchmarked GPU-accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)-related model-dependent biological dose calculation.

RESULTS

Differences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients' geometries using an inexpensive CPU workstation (Intel Xeon E5-2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.

CONCLUSIONS

MCsquare was successfully commissioned for a synchrotron-based proton beam therapy delivery system and integrated into our web-based second check platform. After adopting CT resampling and implementing LET model-dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo-based and LET-guided robust optimization in IMPT, which will be done in the future studies.

A Monte Carlo model for organ dose reconstruction of patients in pencil beam scanning (PBS) proton therapy for epidemiologic studies of late effects

Significant efforts such as the Pediatric Proton/Photon Consortium Registry (PPCR) involving multiple proton therapy centers have been made to conduct collaborative studies evaluating outcomes following proton therapy. As a groundwork dosimetry effort for the late effect investigation, we developed a Monte Carlo (MC) model of proton pencil beam scanning (PBS) to estimate organ/tissue doses of pediatric patients at the Maryland Proton Treatment Center (MPTC), one of the proton centers involved in the PPCR. The MC beam modeling was performed using the TOPAS (TOol for PArticle Simulation) MC code and commissioned to match measurement data within 1% for range, and 0.3 mm for spot sizes. The established MC model was then tested by calculating organ/tissue doses for sample intracranial and craniospinal irradiations on whole-body pediatric computational human phantoms. The simulated dose distributions were compared with the treatment planning system dose distributions, showing the 3 mm/3% gamma index passing rates of 94%-99%, validating our simulations with the MC model. The calculated organ/tissue doses per prescribed doses for the craniospinal irradiations (1 mGy Gy^-1 to 1 Gy Gy^-1) were generally much higher than those for the intracranial irradiations (2.1 μGy Gy^-1 to 0.1 Gy Gy^-1), which is due to the larger field coverage of the craniospinal irradiations. The largest difference was observed at the adrenal dose, i.e. ∼3000 times. In addition, the calculated organ/tissue doses were compared with those calculated with a simplified MC model, showing that the beam properties (i.e. spot size, spot divergence, mean energy, and energy spread) do not significantly influence dose calculations despite the limited irradiation cases. This implies that the use of the MC model commissioned to the MPTC measurement data might be dosimetrically acceptable for patient dose reconstructions at other proton centers particularly when their measurement data are unavailable. The developed MC model will be used to reconstruct organ/tissue doses for MPTC pediatric patients collected in the PPCR.

Pitfalls in the beam modelling process of Monte Carlo calculations for proton pencil beam scanning

OBJECTIVE

Monte Carlo (MC) simulations substantially improve the accuracy of predicted doses. This study aims to determine and quantify the uncertainties of setting up such a MC system.

METHODS

Doses simulated with two Geant4-based MC calculation codes, but independently tuned to the same beam data, have been compared. Different methods of MC modelling of a pre-absorber have been employed, either modifying the beam source parameters (descriptive) or adding the pre-absorber as a physical component (physical).

RESULTS

After the independent beam modelling of both systems in water (resulting in excellent range agreement) range differences of up to 3.6/4.8 mm (1.5% of total range) in bone/brain-like tissues were found, which resulted from the use of different mean water ionisation potentials during the energy tuning process. When repeating using a common definition of water, ranges in bone/brain agreed within 0.1 mm and gamma-analysis (global 1%,1mm) showed excellent agreement (>93%) for all patient fields. However, due to a lack of modelling of proton fluence loss in the descriptive pre-absorber, differences of 7% in absolute dose between the pre-absorber definitions were found.

CONCLUSION

This study quantifies the influence of using different water ionisation potentials during the MC beam modelling process. Furthermore, when using a descriptive pre-absorber model, additional Faraday cup or ionisation chamber measurements with pre-absorber are necessary.

ADVANCES IN KNOWLEDGE

This is the first study quantifying the uncertainties caused by the MC beam modelling process for proton pencil beam scanning, and a more detailed beam modelling process for MC simulations is proposed to minimise the influence of critical parameters.

Automatic phase space generation for Monte Carlo calculations of intensity modulated particle therapy

Monte Carlo (MC) is generally considered as the most accurate dose calculation tool for particle therapy. However, a proper description of the beam particle kinematics is a necessary input for a realistic simulation. Such a description can be stored in phase space (PS) files for different beam energies. A PS file contains kinetic information such as energies, positions and travelling directions for particles traversing a plane perpendicular to the beam direction. The accuracy of PS files plays a critical role in the performance of the MC method for dose calculations. A PS file can be generated with a set of parameters describing analytically the beam kinematics. However, determining such parameters can be tedious and time consuming. Thus, we have developed an algorithm to obtain those parameters automatically and efficiently. In this paper, we presented such an algorithm and compared dose calculations using PS automatically generated for the Shanghai Proton and Heavy Ion Center (SPHIC) with measurements. The gamma-index for comparing calculated depth dose distributions (DDD) with measurements are above 96.0% with criterion 0.6%/0.6 mm. For each single energy, the mean difference percentage between calculated lateral spot sizes at 5 different locations along beam direction and measurements are below 3.5%.

Advancing proton minibeam radiation therapy: magnetically focussed proton minibeams at a clinical centre

Proton minibeam radiation therapy (pMBRT) is a novel therapeutic strategy that has proven to significantly increase dose tolerances and sparing of normal tissue. It uses very narrow proton beams (diameter ≤1 mm), roughly one order of magnitude smaller than state-of-the-art pencil beams. The current implementation of pMBRT with mechanical collimators is suboptimal as it is inflexible, decreases efficiency and produces additional secondary neutrons. As a potential solution, we explore in this article minibeam generation through magnetic focussing and investigate possibilities for the integration of such a technique at existing clinical centres. For this, a model of the pencil beam scanning (PBS) nozzle and beam at the Orsay Proton Therapy Centre was established and Monte Carlo simulations were performed to determine its focussing capabilities. Moreover, various modifications of the nozzle geometry were considered. It was found that the PBS nozzle in its current state is not suitable for magnetic minibeam generation. Instead, a new, optimised nozzle design has been proposed and conditions necessary for minibeam generation were benchmarked. In addition, dose simulations in a water phantom were performed which showed improved dose distributions compared to those obtained with mechanical collimators.

Benchmarking a GATE/Geant4 Monte Carlo model for proton beams in magnetic fields

Purpose

Magnetic resonance guidance in proton therapy (MRPT) is expected to improve its current performance. The combination of magnetic fields with clinical proton beam lines poses several challenges for dosimetry, treatment planning and dose delivery. Proton beams are deflected by magnetic fields causing considerable changes in beam trajectories and also a retraction of the Bragg peak positions. A proper prediction and compensation of these effects is essential to ensure accurate dose calculations. This work aims to develop and benchmark a Monte Carlo (MC) beam model for dose calculation of MRPT for static magnetic fields up to 1 T.

Methods

Proton beam interactions with magnetic fields were simulated using the GATE/Geant4 toolkit. The transport of charged particle in custom 3D magnetic field maps was implemented for the first time in GATE. Validation experiments were done using a horizontal proton pencil beam scanning system with energies between 62.4 and 252.7 MeV and a large gap dipole magnet (B = 0–1 T), positioned at the isocenter and creating magnetic fields transverse to the beam direction. Dose was measured with Gafchromic EBT3 films within a homogeneous PMMA phantom without and with bone and tissue equivalent material slab inserts. Linear energy transfer (LET) quenching of EBT3 films was corrected using a linear model on dose‐averaged LET method to ensure a realistic dosimetric comparison between simulations and experiments. Planar dose distributions were measured with the films in two different configurations: parallel and transverse to the beam direction using single energy fields and spread‐out Bragg peaks. The MC model was benchmarked against lateral deflections and spot sizes in air of single beams measured with a Lynx PT detector, as well as dose distributions using EBT3 films. Experimental and calculated dose distributions were compared to test the accuracy of the model.

Results

Measured proton beam deflections in air at distances of 465, 665, and 1155 mm behind the isocenter after passing the magnetic field region agreed with MC‐predicted values within 4 mm. Differences between calculated and measured beam full width at half maximum (FWHM) were lower than 2 mm. For the homogeneous phantom, measured and simulated in‐depth dose profiles showed range and average dose differences below 0.2 mm and 1.2%, respectively. Simulated central beam positions and widths differed <1 mm to the measurements with films. For both heterogenous phantoms, differences within 1 mm between measured and simulated central beam positions and widths were obtained, confirming a good agreement of the MC model.

Conclusions

A GATE/Geant4 beam model for protons interacting with magnetic fields up to 1 T was developed and benchmarked to experimental data. For the first time, the GATE/Geant4 model was successfully validated not only for single energy beams, but for SOBP, in homogeneous and heterogeneous phantoms. EBT3 film dosimetry demonstrated to be a powerful dosimetric tool, once the film response function is LET corrected, for measurements in‐line and transverse to the beam direction in magnetic fields. The proposed MC beam model is foreseen to support treatment planning and quality assurance (QA) activities toward MRPT.