Browsing by Autor "Daniel C. Maneval"

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<tt>pGPUMCD</tt>: an efficient GPU-based Monte Carlo code for accurate proton dose calculations
(IOP Publishing, 2019) Daniel C. Maneval; Benoı̂t Ozell; Philippe Després
In proton therapy, Monte Carlo simulations are desirable to accurately predict the delivered dose. This paper introduces and benchmarks pGPUMCD, a GPU-based Monte Carlo code implementing the physical processes required for proton therapy applications. In pGPUMCD, the proton transport is carried out in a voxelized geometry with a class II condensed history scheme. For this purpose, the equivalent restricted stopping power formalism (L eq formalism), the Fermi-Eyges scattering theory and the discrete electromagnetic/nuclear interactions were considered. pGPUMCD was compared to Geant4 in a validation study where the physical processes were validated one after the other. Dose differences between pGPUMCD and Geant4 were smaller than 1% in the Bragg peak region and up to 3% in its distal fall-off. Moreover, a voxelwise dose difference below 1% was observed for 99.5% of calculation positions. The pGPUMCD 80% falloff positions matched with those of Geant4 within 0.1%. The pGPUMCD computation times were inversely proportional to the voxel size, with one million protons transported in less than 0.5 s with [Formula: see text] mm3 voxels. pGPUMCD, based on the L eq formalism variance reduction technique, is therefore an attractive candidate for integration in a clinical treatment planning system.