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首页> 外文期刊>Physics in medicine and biology. >Automatic commissioning of a GPU-based Monte Carlo radiation dose calculation code for photon radiotherapy
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Automatic commissioning of a GPU-based Monte Carlo radiation dose calculation code for photon radiotherapy

机译：自动调试基于GPU的蒙特卡洛辐射剂量计算代码，用于光子放射治疗

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Monte Carlo (MC) simulation is commonly considered as the most accurate method for radiation dose calculations. Commissioning of a beam model in the MC code against a clinical linear accelerator beam is of crucial importance for its clinical implementation. In this paper, we propose an automatic commissioning method for our GPU-based MC dose engine, gDPM. gDPM utilizes a beam model based on a concept of phase-space-let (PSL). A PSL contains a group of particles that are of the same type and close in space and energy. A set of generic PSLs was generated by splitting a reference phase-space file. Each PSL was associated with a weighting factor, and in dose calculations the particle carried a weight corresponding to the PSL where it was from. Dose for each PSL in water was pre-computed, and hence the dose in water for a whole beam under a given set of PSL weighting factors was the weighted sum of the PSL doses. At the commissioning stage, an optimization problem was solved to adjust the PSL weights in order to minimize the difference between the calculated dose and measured one. Symmetry and smoothness regularizations were utilized to uniquely determine the solution. An augmented Lagrangian method was employed to solve the optimization problem. To validate our method, a phase-space file of a Varian TrueBeam 6 MV beam was used to generate the PSLs for 6 MV beams. In a simulation study, we commissioned a Siemens 6 MV beam on which a set of field-dependent phase-space files was available. The dose data of this desired beam for different open fields and a small off-axis open field were obtained by calculating doses using these phase-space files. The 3D γ-index test passing rate within the regions with dose above 10% of dmax dose for those open fields tested was improved averagely from 70.56 to 99.36% for 2%/2 mm criteria and from 32.22 to 89.65% for 1%/1 mm criteria. We also tested our commissioning method on a six-field head-and-neck cancer IMRT plan. The passing rate of the γ-index test within the 10% isodose line of the prescription dose was improved from 92.73 to 99.70% and from 82.16 to 96.73% for 2%/2 mm and 1%/1 mm criteria, respectively. Real clinical data measured from Varian, Siemens, and Elekta linear accelerators were also used to validate our commissioning method and a similar level of accuracy was achieved.
机译：蒙特卡洛（MC）模拟通常被认为是辐射剂量计算的最准确方法。针对临床线性加速器光束调试MC代码中的光束模型对其临床实施至关重要。在本文中，我们为基于GPU的MC剂量引擎gDPM提出了一种自动调试方法。 gDPM利用基于相空间let（PSL）概念的波束模型。 PSL包含一组相同类型且空间和能量紧密的粒子。通过拆分参考相空间文件生成了一组通用PSL。每个PSL都与一个权重因子相关联，在剂量计算中，颗粒的重量对应于其来源的PSL。预先计算了水中每个PSL的剂量，因此，在给定的一组PSL加权因子下，整个光束在水中的剂量是PSL剂量的加权总和。在调试阶段，解决了优化问题以调整PSL权重，以最大程度地减少计算剂量和测量剂量之间的差异。对称性和平滑度正则化用于唯一确定解决方案。采用增强拉格朗日方法来解决优化问题。为了验证我们的方法，使用了Varian TrueBeam 6 MV光束的相空间文件来生成6 MV光束的PSL。在模拟研究中，我们调试了Siemens 6 MV光束，在该光束上可获得一组取决于场的相空间文件。通过使用这些相空间文件计算剂量，可以获得针对不同开阔场和较小的偏轴开阔场的所需光束的剂量数据。对于2％/ 2 mm的标准，在那些裸眼测试剂量大于dmax剂量10％的区域内，3Dγ指数测试通过率平均从70.56提高到99.36％，对于1％/ 1则从32.22提高到89.65％毫米标准。我们还在六场头颈癌IMRT计划中测试了我们的调试方法。对于2％/ 2 mm和1％/ 1mm的标准，在处方剂量的10％等剂量线内γ指数测试的通过率分别从92.73提高到99.70％和从82.16提高到96.73％。还使用从Varian，Siemens和Elekta线性加速器测得的实际临床数据来验证我们的调试方法，并获得了类似的准确性。

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