Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit
Full Monte Carlo-Based Biologic Treatment Plan Optimization System for Intensity Modulated Carbon Ion Therapy on Graphics Processing Unit
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DOI：
10.1016/j.ijrobp.2017.09.002
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发表时间：
2018-01-01
影响因子：
7
通讯作者：
Jia, Xun
中科院分区：
文献类型：
--
作者：
Qin, Nan;Shen, Chenyang;Jia, Xun
目的：碳离子治疗的主要好处之一是提高布拉格峰区域的生物有效性。对于强度调制碳离子治疗（IMCT），由于其在模拟物理过程和估计生物效应方面的准确性，希望使用蒙特卡罗（MC）方法来计算每个铅笔束点的特性以制定治疗计划。我们之前开发了goCMC，一个面向图形处理单元（GPU）的MC引擎，用于碳离子治疗。本研究的目的是利用goCMC建立一个生物处理方案优化系统。方法与材料：采用修复-错修-固定模型计算各点线性二次元模型参数的空间分布。开发了一个治疗方案优化模块，以尽量减少处方与实际生物效应之间的差异。我们使用基于梯度的算法来解决优化问题。该系统在客户端-服务器架构下嵌入到Varian Eclipse治疗计划系统中，以实现用户友好的规划环境。我们用一个一维均匀的水病例和3个三维的病人病例对系统进行了测试。结果：我们的系统生成了覆盖目标区域并保留关键结构的生物展开布拉格峰的治疗方案。使用4块NVidia GTX 1080 gpu，前列腺病例（8282个斑点）的计算时间为0.6小时，胰腺病例（3795个斑点）的计算时间为0.2小时，脑部病例（6724个斑点）的计算时间为0.3小时，包括斑点模拟、优化和最终剂量计算。计算时间主要由MC点模拟控制。结论：我们建立了一个IMCT生物治疗方案优化系统，该系统使用快速MC引擎goCMC进行模拟。据我们所知，这是第一次在临床可行的时间框架内实现基于mc的全IMCT逆规划。(C) 2017爱思唯尔公司版权所有。
Purpose: One of the major benefits of carbon ion therapy is enhanced biological effectiveness at the Bragg peak region. For intensity modulated carbon ion therapy (IMCT), it is desirable to use Monte Carlo (MC) methods to compute the properties of each pencil beam spot for treatment planning, because of their accuracy in modeling physics processes and estimating biological effects. We previously developed goCMC, a graphics processing unit (GPU)-oriented MC engine for carbon ion therapy. The purpose of the present study was to build a biological treatment plan optimization system using goCMC.Methods and Materials: The repair-misrepair-fixation model was implemented to compute the spatial distribution of linear-quadratic model parameters for each spot. A treatment plan optimization module was developed to minimize the difference between the prescribed and actual biological effect. We used a gradient-based algorithm to solve the optimization problem. The system was embedded in the Varian Eclipse treatment planning system under a client-server architecture to achieve a user-friendly planning environment. We tested the system with a 1-dimensional homogeneous water case and 3 3-dimensional patient cases.Results: Our system generated treatment plans with biological spread-out Bragg peaks covering the targeted regions and sparing critical structures. Using 4 NVidia GTX 1080 GPUs, the total computation time, including spot simulation, optimization, and final dose calculation, was 0.6 hour for the prostate case (8282 spots), 0.2 hour for the pancreas case (3795 spots), and 0.3 hour for the brain case (6724 spots). The computation time was dominated by MC spot simulation.Conclusions: We built a biological treatment plan optimization system for IMCT that performs simulations using a fast MC engine, goCMC. To the best of our knowledge, this is the first time that full MC-based IMCT inverse planning has been achieved in a clinically viable time frame. (C) 2017 Elsevier Inc. All rights reserved.