Fred: a GPU-accelerated fast-Monte Carlo code for rapid treatment plan recalculation in ion beam therapy

Schiavi, A.; Senzacqua, M.; Pioli, Stefano; Mairani, A.; Magro, Giuseppe; Molinelli, S.; Ciocca, Mario; Battistoni, G.; Patera, V.

doi:10.1088/1361-6560/aa8134

Cited by 58 publications

(72 citation statements)

References 37 publications

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“…Measured and simulated FSFs in this study agreed well with three other studies 4,5,18 for the highest energy, but differences up to 1% were observed for the largest field sizes compared to two other studies 3,11 (see Fig. S3).…”

Section: Discussionsupporting

confidence: 89%

“…In that study, six out of seven planes in an anthropomorphic phantom passed a 90% Gamma index analysis criterion (3%/3 mm) for their MC simulations compared to film measurements, whereas only three out of seven passed using the PB algorithm. Speed optimized MC algorithms dedicated for routine clinical use are usually benchmarked against general purpose MC particle transport algorithms such as FLUKA and Geant4 . The latter are traditionally used during commissioning phase to support basic beam data generation required for treatment planning systems (TPSs) allowing to reduce time consuming measurements …”

Section: Introductionmentioning

confidence: 99%

“…16 Due to the presence of a high dose gradient, misalignment and volume averaging effects limit the significance of the results. 14,17 However, these dose profile validations are useful and necessary to understand more complex situations such as output factors (OFs), which are normalized to a certain field size (typically around 10 cm 4,5,11,16,18 ). OFs such as field size factors (FSFs) and frame factors (FFs) quantify the relative increase of the dose due to increasing field size and are expected to be less sensitive to lateral misalignment due to the symmetry of the field.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of electromagnetic and nuclear scattering models in GATE/Geant4 for proton therapy

et al. 2019

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PurposeThe dose core of a proton pencil beam (PB) is enveloped by a low dose area reaching several centimeters off the central axis and containing a considerable amount of the dose. Adequate modeling of the different components of the PB profile is, therefore, required for accurate dose calculation. In this study, we experimentally validated one electromagnetic and two nuclear scattering models in GATE/Geant4 for dose calculation of proton beams in the therapeutic energy window (62–252 MeV) with and without range shifter (RaShi).MethodsThe multiple Coulomb scattering (MCS) model was validated by lateral dose core profiles measured for five energies at up to four depths from beam plateau to Bragg peak region. Nuclear halo profiles of single PBs were evaluated for three (62.4, 148.2, and 252.7 MeV) and two (97.4 and 124.7 MeV) energies, without and with RaShi, respectively. The influence of the dose core and nuclear halo on field sizes varying from 2–20 cm was evaluated by means of output factors (OFs), namely frame factors (FFs) and field size factors (FSFs), to quantify the relative increase of dose when increasing the field size.ResultsThe relative increase in the dose core width in the simulations deviated negligibly from measurements for depths until 80% of the beam range, but was overestimated by up to 0.2 mm in σ toward the end of range for all energies. The dose halo region of the lateral dose profile agreed well with measurements in the open beam configuration, but was notably overestimated in the deepest measurement plane of the highest energy or when the beam passed through the RaShi. The root‐mean‐square deviations (RMSDs) between the simulated and the measured FSFs were less than 1% at all depths, but were higher in the second half of the beam range as compared to the first half or when traversing the RaShi. The deviations in one of the two tested hadron physics lists originated mostly in elastic scattering. The RMSDs could be reduced by approximately a factor of two by exchanging the default elastic scattering cross sections for protons.ConclusionsGATE/Geant4 agreed satisfyingly with most measured quantities. MCS was systematically overestimated toward the end of the beam range. Contributions from nuclear scattering were overestimated when the beam traversed the RaShi or at the depths close to the end of the beam range without RaShi. Both, field size effects and calculation uncertainties, increased when the beam traversed the RaShi. Measured field size effects were almost negligible for beams up to medium energy and were highest for the highest energy beam without RaShi, but vice versa when traversing the RaShi.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluation of electromagnetic and nuclear scattering models in GATE/Geant4 for proton therapy

et al. 2019

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“…This latter means that the next generation treatment planning systems should incorporate the handling of the uncertainties related with the beam delivery, patient positions, RBE models, etc. GPU‐based TPS could represent a promising solution of these problems . The speed of dose and RBE computations is also a key prerequisite for advanced treatment planning tools such as multicriteria and automatic optimization, and robust optimization, where linearity in dose addition is frequently exploited to speed up calculations; however, this linearity is not given for RBE‐weighted particle dose distributions.…”

Section: Light Ionsmentioning

confidence: 99%

“…GPU-based TPS could represent a promising solution of these problems. [94][95][96] The speed of dose and RBE computations is also a key prerequisite for advanced treatment planning tools such as multicriteria and automatic optimization, and robust optimization, where linearity in dose addition is frequently exploited to speed up calculations; however, this linearity is not given for RBE-weighted particle dose distributions.…”

Section: Light Ionsmentioning

confidence: 99%

Advanced Treatment Planning

et al. 2018

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Treatment planning for protons and heavier ions is adapting technologies originally developed for photon dose optimization, but also has to meet its particular challenges. Since the quality of the applied dose is more sensitive to geometric uncertainties, treatment plan robust optimization has a much more prominent role in particle therapy. This has led to specific planning tools, approaches, and research into new formulations of the robust optimization problems. Tools for solution space navigation and automatic planning are also being adapted to particle therapy. These challenges become even greater when detailed models of relative biological effectiveness (RBE) are included into dose optimization, as is required for heavier ions.

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A GPU‐based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy

Li,

Cheng,

Wang

et al. 2023

J Applied Clin Med Phys

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This paper presents the effort to extend a previously reported code ARCHER, a GPU‐based Monte Carlo (MC) code for coupled photon and electron transport, into protons including the consideration of magnetic fields. The proton transport is modeled using a Class‐II condensed‐history algorithm with continuous slowing‐down approximation. The model includes ionization, multiple scattering, energy straggling, elastic and inelastic nuclear interactions, as well as deflection due to the Lorentz force in magnetic fields. An additional direction change is added for protons at the end of each step in the presence of the magnetic field. Secondary charge particles, except for protons, are terminated depositing kinetic energies locally, whereas secondary neutral particles are ignored. Each proton is transported step by step until its energy drops to below 0.5 MeV or when the proton leaves the phantom. The code is implemented using the compute unified device architecture (CUDA) platform for optimized GPU thread‐level parallelism and efficiency. The code is validated by comparing it against TOPAS. Comparisons of dose distributions between our code and TOPAS for several exposure scenarios, ranging from single square beams in water to patient plan with magnetic fields, show good agreement. The 3D‐gamma pass rate with a 2 mm/2% criterion in the region with dose greater than 10% of the maximum dose is computed to be over 99% for all tested cases. Using a single NVIDIA TITAN V GPU card, the computational time of ARCHER is found to range from 0.82 to 4.54 seconds for 1 × 107 proton histories. Compared to a few hours running on TOPAS, this speed improvement is significant. This work presents, for the first time, the performance of a GPU‐based MC code to simulate proton transportation magnetic fields, demonstrating the feasibility of accurate and efficient dose calculations in potential magnetic resonance imaging (MRI)‐guided proton therapy.

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Fred: a GPU-accelerated fast-Monte Carlo code for rapid treatment plan recalculation in ion beam therapy

Cited by 58 publications

References 37 publications

Evaluation of electromagnetic and nuclear scattering models in GATE/Geant4 for proton therapy

Evaluation of electromagnetic and nuclear scattering models in GATE/Geant4 for proton therapy

Advanced Treatment Planning

A GPU‐based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy

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