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Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy

机译:在基于GPU的蒙特卡洛粒子传输模拟中对参数化几何进行建模以进行放射治疗

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Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was similar to 3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0.69-1.23 times for photon only transport.
机译:由于通过大规模并行化实现了效率优势,最近在图形处理单元(GPU)平台上进行了蒙特卡洛(MC)粒子传输仿真研究。几乎所有现有的基于GPU的MC软件包都是为体素化的几何体开发的。这些软件包的应用范围受到限制。本文的目的是开发一个用于对参数几何建模的模块,并将其集成到基于GPU的MC仿真中。在我们的模块中,每个连续区域由其边界表面定义,边界表面由二次函数参数化。开发了这种几何形状的粒子导航功能。该模块已整合到两个先前开发的基于GPU的MC软件包中,并在两个示例问题中进行了测试:(1)在近距离放射治疗情况下使用屏蔽圆筒施加器进行低能量光子传输模拟,以及(2)在MeV耦合下的MeV耦合光子/电子传输模拟包含多个不同形状的插入物的幻像。在这两种情况下,计算出的剂量分布与在相应体素化几何形状中计算出的剂量分布非常吻合。平均剂量差异分别为1.03%和0.29%。我们还使用开发的软件包对Varian VS 2000近距离放射治疗源进行了仿真,并生成了一个相空间文件。参数化几何图形下的计算时间取决于存储几何图形数据的存储位置。将数据存储在GPU的共享内存中时,可以实现最高的计算速度。参数化几何图形的合并产生的计算时间大约是相应体素化几何图形的3倍。我们还开发了一种使用辅助索引数组来减少几何计算频率并因此提高效率的策略。使用此策略,根据辅助索引阵列的体素尺寸,计算时间范围为体素化几何图形的1.75-2.03倍,取决于辅助索引阵列的体素尺寸;而对于仅光子传输,计算时间为0.69-1.23倍。

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