Ferjančič Peter, van der Heide Uulke A, Ménard Cynthia, Jeraj Robert
Department of Medical Physics, Wisconsin Institutes for Medical Research, 1111 Highland Ave, Room 7033, Madison, WI 53705, United States of America.
The Netherlands Cancer Institute, The Netherlands.
Phys Med Biol. 2021 Oct 28;66(21). doi: 10.1088/1361-6560/ac2f8a.
Current radiation therapy (RT) planning guidelines handle uncertainties in RT using geometric margins. This approach is simple to use but oversimplifies complex underlying processes and is cumbersome for non-homogeneous dose prescriptions. In this work, we characterize the performance of a novel probabilistic target definition and planning (PTP) approach, which uses voxel-level tumor likelihood information in treatment plan optimization.We expanded a treatment planning system with probabilistic therapy planning functionality that utilizes non-binary target maps (TM) as voxel-level input to dose plan optimization. Different dose plans were calculated and compared for twelve prostate cancer patients with multiparametric magnetic resonance imaging derived TMs. Dose plans were created using both classical and PTP approaches for uniform and integrated dose boost prescriptions. Dose performance between the different approaches was compared using dose benchmarks on target and organ-at-risk (OAR) volumes.Over all dose metrics, PTP was shown to be comparable to classical planning. For plans of uniform dose prescription, the PTP approach created plans within 1 Gy of the classical planning approach across all dose metrics, with no significant differences ( > 0.2). For plans with the integrated dose boost, PTP plans exhibited higher dose heterogeneity, but still showed target doses comparable to the classical approach, without increasing doses to OAR.In this work we introduce direct incorporation of probabilistic target definition into treatment planning. This treatment planning approach can produce both uniform dose plans and plans with integrated dose boosts that are comparable to ones created using classical dose planning. PTP is a flexible way to optimize external beam radiotherapy, as it is not limited by the use of margins. PTP can produce dose plans equivalent to classical planning, while also allows for greater versatility in dose prescription and direct incorporation of patient target definition uncertainty into treatment planning.
当前的放射治疗（RT）计划指南使用几何边界来处理RT中的不确定性。这种方法使用简单，但过度简化了复杂的潜在过程，并且对于非均匀剂量处方来说很繁琐。在这项工作中，我们描述了一种新型概率靶区定义与计划（PTP）方法的性能，该方法在治疗计划优化中使用体素级肿瘤可能性信息。我们扩展了一个具有概率治疗计划功能的治疗计划系统，该系统利用非二进制靶区图（TM）作为剂量计划优化的体素级输入。针对12例具有多参数磁共振成像衍生TM的前列腺癌患者，计算并比较了不同的剂量计划。使用经典方法和PTP方法创建了用于均匀剂量和综合剂量增加处方的剂量计划。使用靶区和危及器官（OAR）体积的剂量基准比较了不同方法之间的剂量性能。在所有剂量指标上，PTP被证明与经典计划相当。对于均匀剂量处方的计划，PTP方法在所有剂量指标上创建的计划与经典计划方法相差在1 Gy以内，无显著差异（>0.2）。对于具有综合剂量增加的计划，PTP计划表现出更高的剂量异质性，但仍显示出与经典方法相当的靶区剂量，且未增加OAR的剂量。在这项工作中，我们介绍了将概率靶区定义直接纳入治疗计划。这种治疗计划方法可以产生与使用经典剂量计划创建的计划相当的均匀剂量计划和具有综合剂量增加的计划。PTP是优化外照射放疗的一种灵活方法，因为它不受边界使用的限制。PTP可以产生与经典计划等效的剂量计划，同时在剂量处方方面具有更大的通用性，并将患者靶区定义的不确定性直接纳入治疗计划。
