A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of non-elastic interactions

TL;DR

This paper presents a GPU-based Monte Carlo simulation for proton transport that incorporates detailed modeling of non-elastic interactions, achieving high accuracy and speed suitable for clinical applications.

Contribution

The authors developed the first GPU Monte Carlo proton transport model with comprehensive nuclear interaction modeling, validated against Geant4, and optimized for clinical use.

Findings

Yields and secondary particle distributions match Geant4 models.

Dose calculations achieve 98% gamma pass rate at 2%-2mm.

Simulation time is approximately 20 seconds for 10 million protons.

Abstract

Purpose: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on GPUs. However, these usually use simplified models for non-elastic (NE) proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and NE collisions. Methods: Using CUDA, we implemented GPU kernels for these tasks: (1) Simulation of spots from our scanning nozzle configurations, (2) Proton propagation through CT geometry, considering nuclear elastic scattering, multiple scattering, and energy loss straggling, (3) Modeling of the intranuclear cascade stage of NE interactions, (4) Nuclear evaporation simulation, and (5) Statistical error estimates on the dose. To validate our MC, we performed: (1) Secondary particle yield calculations in NE collisions, (2) Dose calculations in homogeneous phantoms, (3) Re-calculations of head and neck plans from a commercial treatment planning system (TPS), and compared with Geant4.9.6p2/TOPAS. Results: Yields, energy and angular distributions of secondaries from NE collisions on various nuclei agree well with the Geant4 Bertini and Binary cascade models. The 3D-gamma pass rate at 2\%-2 mm for treatment plan simulations is typically 98\%. The net calculation time on a NVIDIA GTX680 card, including all data transfers, is $\sim$20 s for $1\times10^7$ proton histories. Conclusions: Our GPU-based MC is the first of its kind to include a detailed nuclear model to handle NE interactions of protons with any nucleus. Dosimetric calculations are in very good agreement with Geant4/TOPAS. Our MC is being used to perform fast routine clinical QA of pencil-beam based treatment plans, and has also been adopted as the dose engine in a clinically-applicable MC-based IMPT TPS. The detailed nuclear modeling will allow us to perform very fast linear energy transfer and neutron dose estimates on the GPU.