GPU-based fast Monte Carlo dose calculation for proton therapy

Abstract

Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6–22 s to simulate 10 million source protons to achieve ∼1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.