GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources
Reid Townson, Xun Jia, Zhen Tian, Yan Jiang Graves, Sergei Zavgorodni, and Steve B Jiang

TL;DR
This paper introduces a GPU-optimized Monte Carlo dose calculation method using phase-space sources, significantly improving speed and maintaining high accuracy for radiotherapy planning.
Contribution
It presents three innovative phase-space implementation methods, including a novel pre-processing strategy, to enhance GPU-based dose calculations in radiotherapy.
Findings
The PSL method achieves high accuracy with gamma passing rates over 98%.
Dose calculations are completed in seconds on a GPU, vastly faster than traditional CPU methods.
The methods are validated against established simulation tools with excellent agreement.
Abstract
A novel phase-space source implementation has been designed for GPU-based Monte Carlo dose calculation engines. Due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a…
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