A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed‐computing framework.

中文翻译：

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使用蒙特卡洛生成的子束增强体积调制电弧治疗计划的优化

通过将优化过程应用于目标函数，然后精确计算最终的可交付剂量，治疗计划系统（TPS）会产生容积调制电弧治疗（VMAT）计划。但是，在优化步骤中，需要一种快速的剂量计算算法，这会降低其准确性和对目标函数空间的表示。蒙特卡洛（MC）例程被认为是准确性的黄金标准，目前对于实用的全面VMAT优化来说太慢了。因此，我们提出了一种称为增强优化的新颖方法（EO），它以TPS VMAT计划为起点，并应用较小的扰动将解决方案推向更接近真实的目标最小值。扰动由在分布式计算框架上使用MC例程计算的子束剂量矩阵组成。