BACKGROUND: Preclinical small animal experiments play an indispensable role in proton therapy research. However, accurate dose calculation poses a significant challenge because of the low beam energy and the requirement for submillimeter spatial resolution. Although the Monte Carlo method offers the necessary precision, its high computational cost hinders efficient implementation. PURPOSE: This study aims to develop a GPU-accelerated radiation dose engine for proton radiotherapy (pGARDEN) based on the Monte Carlo method, specifically designed for fast and accurate dose calculation in small animal irradiation. METHODS: In pGARDEN, we optimized the particle transport algorithm to better align with the GPU architecture. Moreover, various acceleration techniques were implemented to boost computational efficiency. To enhance precision, physical parameters, such as energy cutoffs for proton and electron, were tuned to better suit small animal conditions. The performance of pGARDEN was validated against Geant4 simulations and measurements across various beams and phantoms. To demonstrate its practical utility, pGARDEN was applied to calculate a multi-beam proton treatment plan for a lung tumor-bearing mouse model. RESULTS: Compared to Geant4, the engine achieved a > 1000-fold speedup and a 3D gamma passing rate of > 97% with a strict 1%/0.15 mm criterion in all phantom testing scenarios. The integrated depth dose curves and dose profiles showed good agreement with measurements. In the in vivo validation, the 2D gamma passing rates with a 2%/0.3 mm criterion were 95.52% ± 0.74% for the abdomen and 94.18% ± 1.08% for the thorax. Furthermore, pGARDEN calculated the treatment plan with < 1% statistical uncertainty in 4.3 s on an NVIDIA GeForce RTX 4070 Ti GPU, achieving a 100% 3D gamma passing rate with a 2%/0.3 mm criterion. CONCLUSION: pGARDEN can calculate proton dose distribution rapidly and accurately at submillimeter resolution for small animal. It provides a valuable tool for supporting small animal proton radiation experiments, such as the investigation of relative biological effectiveness (RBE) and new therapeutic strategies.
Gong et al. (Fri,) studied this question.