Improved efficiency in Monte Carlo simulation for passive-scattering proton therapy

Implementation of a double scattering nozzle for Monte Carlo recalculation of proton plans with variable relative biological effectiveness

A constant relative biological effectiveness (RBE) of 1.1 is currently used in clinical proton therapy. However, theRBEvaries with factors such as dose level, linear energy transfer (LET) and tissue type. MultipleRBEmodels have been developed to account for this biological variation. To enable recalculation of patients treated with double scattering (DS) proton therapy, includingLETand variableRBE, we implemented and commissioned a Monte Carlo (MC) model of a DS treatment nozzle. The main components from the IBA nozzle were implemented in the FLUKA MC code. We calibrated and verified the following entities to experimental measurements: range of pristine Bragg peaks (PBPs) and spread-out Bragg peaks (SOBPs), energy spread, lateral profiles, compensator range degradation, and absolute dose. We recalculated two patients with different field setups, comparing FLUKA vs. treatment planning system (TPS) dose, also obtainingLETand variableRBEdoses. We achieved good agreement between FLUKA and measurements. The range differences between FLUKA and measurements were for the PBPs within ±0.9 mm (83% ⩽ 0.5 mm), and for SOBPs ±1.6 mm (82% ⩽ 0.5 mm). The differences in modulation widths were below 5 mm (79% ⩽ 2 mm). The differences in the distal dose fall off (D80%-D20%) were below 0.5 mm for all PBPs and the lateral penumbras diverged from measurements by less than 1 mm. The mean dose difference (RBE= 1.1) in the target between the TPS and FLUKA were below 0.4% in a three-field plan and below 1.4% in a four-field plan. A dose increase of 9.9% and 7.2% occurred when using variableRBEfor the two patients, respectively. We presented a method to recalculate DS proton plans in the FLUKA MC code. The implementation was used to obtainLETand variableRBEdose and can be used for investigating variableRBEfor previously treated patients.

The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research

PURPOSE

This paper covers recent developments and applications of the TOPAS TOol for PArticle Simulation and presents the approaches used to disseminate TOPAS.

MATERIALS AND METHODS

Fundamental understanding of radiotherapy and imaging is greatly facilitated through accurate and detailed simulation of the passage of ionizing radiation through apparatus and into a patient using Monte Carlo (MC). TOPAS brings Geant4, a reliable, experimentally validated MC tool mainly developed for high energy physics, within easy reach of medical physicists, radiobiologists and clinicians. Requiring no programming knowledge, TOPAS provides all of the flexibility of Geant4.

RESULTS

After 5 years of development followed by its initial release, TOPAS was subsequently expanded from its focus on proton therapy physics to incorporate radiobiology modeling. Next, in 2018, the developers expanded their user support and code maintenance as well as the scope of TOPAS towards supporting X-ray and electron therapy and medical imaging. Improvements have been achieved in user enhancement through software engineering and a graphical user interface, calculational efficiency, validation through experimental benchmarks and QA measurements, and either newly available or recently published applications. A large and rapidly increasing user base demonstrates success in our approach to dissemination of this uniquely accessible and flexible MC research tool.

CONCLUSIONS

The TOPAS developers continue to make strides in addressing the needs of the medical community in applications of ionizing radiation to medicine, creating the only fully integrated platform for four-dimensional simulation of all forms of radiotherapy and imaging with ionizing radiation, with a design that promotes inter-institutional collaboration.

A Monte Carlo based radiation response modelling framework to assess variability of clinical RBE in proton therapy

The clinical implementation of a variable relative biological effectiveness (RBE) in proton therapy is currently controversially discussed. Initial clinical evidence indicates a variable proton RBE, which needs to be verified. In this study, a radiation response modelling framework for assessing clinical RBE variability is established. It was applied to four selected glioma patients (grade III) treated with adjuvant radio(chemo)therapy and who developed late morphological image changes on T1-weighted contrast-enhanced (T1w-CE) magnetic resonance (MR) images within approximately two years of recurrence-free follow-up. The image changes were correlated voxelwise with dose and linear energy transfer (LET) values using univariable and multivariable logistic regression analysis. The regression models were evaluated by the area-under-the-curve (AUC) method performing a leave-one-out cross validation. The tolerance dose TD₅₀ at which 50% of patient voxels experienced toxicity was interpolated from the models. A Monte Carlo (MC) model was developed to simulate dose and LET distributions, which includes variance reduction (VR) techniques to decrease computation time. Its reliability and accuracy were evaluated based on dose calculations of the clinical treatment planning system (TPS) as well as absolute dose measurements performed in the patient specific quality assurance. Morphological image changes were related to a combination of dose and LET. The multivariable models revealed cross-validated AUC values of up to 0.88. The interpolated TD₅₀ curves decreased with increasing LET indicating an increase in biological effectiveness. The MC model reliably predicted average TPS dose within the clinical target volume as well as absolute water phantom dose measurements within 2% accuracy using dedicated VR settings. The observed correlation of dose and LET with late brain tissue damage suggests considering RBE variability for predicting chronic radiation-induced brain toxicities. The MC model simulates radiation fields in patients precisely and time-efficiently. Hence, this study encourages and enables in-depth patient evaluation to assess the variability of clinical proton RBE.

Independent dose verification system with Monte Carlo simulations using TOPAS for passive scattering proton therapy at the National Cancer Center in Korea

For the independent validation of treatment plans, we developed a fully automated Monte Carlo (MC)-based patient dose calculation system with the tool for particle simulation (TOPAS) and proton therapy machine installed at the National Cancer Center in Korea to enable routine and automatic dose recalculation for each patient. The proton beam nozzle was modeled with TOPAS to simulate the therapeutic beam, and MC commissioning was performed by comparing percent depth dose with the measurement. The beam set-up based on the prescribed beam range and modulation width was automated by modifying the vendor-specific method. The CT phantom was modeled based on the DICOM CT files with TOPAS-built-in function, and an in-house-developed C++ code directly imports the CT files for positioning the CT phantom, RT-plan file for simulating the treatment plan, and RT-structure file for applying the Hounsfield unit (HU) assignment, respectively. The developed system was validated by comparing the dose distributions with those calculated by the treatment planning system (TPS) for a lung phantom and two patient cases of abdomen and internal mammary node. The results of the beam commissioning were in good agreement of up to 0.8 mm² [Formula: see text] for B8 option in both of the beam range and the modulation width of the spread-out Bragg peaks. The beam set-up technique can predict the range and modulation width with an accuracy of 0.06% and 0.51%, respectively, with respect to the prescribed range and modulation in arbitrary points of B5 option (128.3, 132.0, and 141.2 mm² [Formula: see text] of range). The dose distributions showed higher than 99% passing rate for the 3D gamma index (3 mm distance to agreement and 3% dose difference) between the MC simulations and the clinical TPS in the target volume. However, in the normal tissues, less favorable agreements were obtained for the radiation treatment planning with the lung phantom and internal mammary node cases. The discrepancies might come from the limitations of the clinical TPS, which is the inaccurate dose calculation algorithm for the scattering effect, in the range compensator and inhomogeneous material. Moreover, the steep slope of the compensator, conversion of the HU values to the human phantom, and the dose calculation algorithm for the HU assignment also could be reasons of the discrepancies. The current study could be used for the independent dose validation of treatment plans including high inhomogeneities, the steep compensator, and riskiness such as lung, head & neck cases. According to the treatment policy, the dose discrepancies predicted with MC could be used for the acceptance decision of the original treatment plan.

Phase Space Generation for Proton and Carbon Ion Beams for External Users' Applications at the Heidelberg Ion Therapy Center

In the field of radiation therapy, accurate and robust dose calculation is required. For this purpose, precise modeling of the irradiation system and reliable computational platforms are needed. At the Heidelberg Ion Therapy Center (HIT), the beamline has been already modeled in the FLUKA Monte Carlo (MC) code. However, this model was kept confidential for disclosure reasons and was not available for any external team. The main goal of this study was to create efficiently phase space (PS) files for proton and carbon ion beams, for all energies and foci available at HIT. PSs are representing the characteristics of each particle recorded (charge, mass, energy, coordinates, direction cosines, generation) at a certain position along the beam path. In order to achieve this goal, keeping a reasonable data size but maintaining the requested accuracy for the calculation, we developed a new approach of beam PS generation with the MC code FLUKA. The generated PSs were obtained using an infinitely narrow beam and recording the desired quantities after the last element of the beamline, with a discrimination of primaries or secondaries. In this way, a unique PS can be used for each energy to accommodate the different foci by combining the narrow-beam scenario with a random sampling of its theoretical Gaussian beam in vacuum. PS can also reproduce the different patterns from the delivery system, when properly combined with the beam scanning information. MC simulations using PS have been compared to simulations, including the full beamline geometry and have been found in very good agreement for several cases (depth dose distributions, lateral dose profiles), with relative dose differences below 0.5%. This approach has also been compared with measured data of ion beams with different energies and foci, resulting in a very satisfactory agreement. Hence, the proposed approach was able to fulfill the different requirements and has demonstrated its capability for application to clinical treatment fields. It also offers a powerful tool to perform investigations on the contribution of primary and secondary particles produced in the beamline. These PSs are already made available to external teams upon request, to support interpretation of their measurements.