Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, USA.
Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA.
Med Phys. 2022 Oct;49(10):6666-6683. doi: 10.1002/mp.15913. Epub 2022 Aug 22.
In proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions.
A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU.
Neutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared.
Integrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries.
VPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.
在质子治疗剂量计算中，与解析计算相比，蒙特卡罗（MC）模拟在准确性上更具优势，但计算时间更长。图形处理单元（GPU）可有效加速 MC 模拟，但在 GPU 线程中可能会出现线程分歧和竞争条件，这会由于核反应中产生的次级粒子而降低计算性能。
提出了一种新的虚拟粒子（VP）MC（VPMC）概念，以避免在 GPU 加速质子 MC 剂量计算中模拟次级粒子，并充分利用 GPU 的计算能力。
忽略从中逃离的中子和伽马射线；沉积电子、重离子和核碎片的剂量；氘的轨迹转换为质子的轨迹。这些粒子，连同初级和次级质子，被认为是实际粒子。初级和次级质子的历史被多个 VP 的历史所取代。每个 VP 对应一个质子（无论是初级还是次级）。通过基于使用 MCsquare 对实际粒子进行模拟的结果生成概率分布函数（PDF），为 VP 开发了连续慢化逼近模型、电离模型和与核相互作用对应的大角度散射事件模型。为了进行有效的计算，这些 PDF 存储在 Compute Unified Device Architecture 纹理中。在体模中和在 13 个代表性患者几何形状中使用 MCsquare 对 TOPAS 和 MCsquare 进行了 VPMC 基准测试。还对 13 名选定患者的特定于患者的质量保证（PSQA）期间从 VPMC 计算的剂量与在水中测量的剂量进行了比较。使用三维伽马分析比较了来自不同方法的剂量，并比较了计算效率。
在同质和非同质体模中，VPMC、TOPAS 和 MCsquare 计算的积分深度剂量和横向剂量分布都非常吻合。在同质体模中，MCsquare 与 TOPAS 之间的 3D-3D 伽马通过率为 2%/2mm 和阈值为 10%，为 98.49%，VPMC 与 TOPAS 之间为 98.31%，在非同质体模中，MCsquare 与 TOPAS 之间为 99.18%，VPMC 与 TOPAS 之间为 98.49%。在患者几何形状中，VPMC 和 MCsquare 之间的 2%/2mm/10%剂量分布的 3D-3D 伽马通过率在患者几何形状中为 98.56±1.09%。在 PSQA 期间，VPMC 计算的剂量分布与二维测量平面剂量分布之间的二维-三维伽马分析，3%/2mm/10%，为 98.91±0.88%。VPMC 计算效率非常高，在患者几何形状中，使用四个 NVIDIA Ampere GPU 为选定的 13 名患者完成计算需要 2.84±2.44s。
VPMC 在质子治疗剂量计算中被发现具有很高的准确性和效率。
