Tilly David, Holm Åsa, Grusell Erik, Ahnesjö Anders
Medical Radiation Physics, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Medical Physics, Akademiska Hospital, Uppsala, Sweden.
Phys Imaging Radiat Oncol. 2019 Apr 13;10:1-6. doi: 10.1016/j.phro.2019.03.005. eCollection 2019 Apr.
Probabilistic optimization is an alternative to margins for handling geometrical uncertainties in treatment planning of radiotherapy where uncertainties are explicitly incorporated in the optimization. We present a novel probabilistic method based on the same statistical measures as those behind conventional margin based planning.
(PD) was defined as the dose coverage that a treatment plan meet or exceed to a given probability. For optimization, we used the convex measure (EPD) defined as the average dose coverage below a given PD. An iterative method gradually adjusted the constraint tolerance associated with the EPD until the desired target PD was met. It was applied to planning of cervical cancer patients focusing on systematic uncertainty caused by organ deformation. The resulting plans were compared to margin based plans using target and organ at risk PDs.
The EPD tolerance converged in less than ten iterations to produce a PD within 0.1 Gy of the requested. The PD was on average within 0.5% of the requested PD when validated versus independent scenarios. The rectum volume, extracted from the PDs, receiving 90% of the intended target dose was decreased with 16% for the same target PD in comparison to margin based plans.
The proposed probabilistic optimization method enabled prescription of a dose volume histogram metric to a chosen confidence. The probabilistic plans showed improved target dose homogeneity and decreased rectum dose for the same target dose coverage compared to margin based plans.
概率优化是一种在放射治疗计划中处理几何不确定性的替代边界的方法，其中不确定性被明确纳入优化过程。我们提出了一种基于与传统基于边界的计划相同统计量的新型概率方法。
（PD）被定义为治疗计划达到或超过给定概率的剂量覆盖范围。为了进行优化，我们使用了凸测度（EPD），其定义为给定PD以下的平均剂量覆盖范围。一种迭代方法逐渐调整与EPD相关的约束容差，直到满足所需的目标PD。它被应用于宫颈癌患者的计划，重点关注器官变形引起的系统不确定性。使用目标和危及器官的PD将所得计划与基于边界的计划进行比较。
EPD容差在不到十次迭代中收敛，以产生在要求剂量的0.1 Gy范围内的PD。与独立场景验证时，PD平均在要求PD的0.5%以内。与基于边界的计划相比，对于相同的目标PD，从PD中提取的接受90%预期目标剂量的直肠体积减少了16%。
所提出的概率优化方法能够将剂量体积直方图指标规定到选定的置信度。与基于边界的计划相比，概率计划在相同的目标剂量覆盖下显示出更好的目标剂量均匀性和更低的直肠剂量。
