Bai Xuemin, Lim Gino, Grosshans David, Mohan Radhe, Cao Wenhua
Department of Industrial Engineering, University of Houston, Houston, TX, 77004, USA.
Linking Medical Technology, Beijing, 100085, China.
Med Phys. 2020 Sep;47(9):3816-3825. doi: 10.1002/mp.14335. Epub 2020 Jul 13.
Linear energy transfer (LET)-guided methods have been applied to intensity-modulated proton therapy (IMPT) to improve its biological effect. However, using LET as a surrogate for biological effect ignores the topological relationship of the scanning spot to different structures of interest. In this study, we developed an optimization method that takes advantage of the continuing increase in LET beyond the physical dose Bragg peak. This method avoids placing high biological effect values in critical structures and increases biological effect in the tumor area without compromising target coverage.
We selected the cases of two patients with brain tumors and two patients with head and neck tumors who had been treated with proton therapy at our institution. Three plans were created for each case: a plan based on conventional dose-based optimization (DoseOpt), one based on LET-incorporating optimization (LETOpt), and one based on the proposed distal-edge avoidance-guided optimization method (DEAOpt). In DEAOpt, an L -norm sparsity term, in which the penalty of each scanning spot was set according to the topological relationship between the organ positions and the location of the peak scaled LET-weighted dose (c LETxD) was added to a conventional dose-based optimization objective function. All plans were normalized to give the same target dose coverage. Dose (assuming a constant relative biological effectiveness value of 1.1, as in clinical practice), biological effect (c LETxD), and computing time consumption were evaluated and compared among the three optimization approaches for each patient case.
For all four cases, all three optimization methods generated comparable dose coverage in both target and critical structures. The LETOpt plans and DEAOpt plans reduced biological effect hot spots in critical structures and increased biological effect in the target volumes to a similar extent. For the target, the c LETxD and c LETxD in the DEAOpt plans were on average 7.2% and 11.74% higher than in the DoseOpt plans, respectively. For the brainstem, the c LETxD in the DEAOpt plans was on average 33.38% lower than in the DoseOpt plans. In addition, the DEAOpt method saved 30.37% of the computation cost over the LETOpt method.
DEAOpt is an alternative IMPT optimization approach that correlates the location of scanning spots with biological effect distribution. IMPT could benefit from the use of DEAOpt because this method not only delivers comparable biological effects to LETOpt plans, but also is faster.
线性能量传递（LET）引导方法已应用于调强质子治疗（IMPT）以提高其生物学效应。然而，将LET用作生物学效应的替代指标忽略了扫描点与不同感兴趣结构的拓扑关系。在本研究中，我们开发了一种优化方法，该方法利用了在物理剂量布拉格峰之后LET的持续增加。该方法避免在关键结构中放置高生物学效应值，并在不影响靶区覆盖的情况下增加肿瘤区域的生物学效应。
我们选择了在我们机构接受质子治疗的两名脑肿瘤患者和两名头颈部肿瘤患者的病例。为每个病例创建了三个计划：一个基于传统剂量优化（DoseOpt）的计划，一个基于纳入LET优化（LETOpt）的计划，以及一个基于提出的远端边缘回避引导优化方法（DEAOpt）的计划。在DEAOpt中，将一个L范数稀疏项添加到传统的基于剂量的优化目标函数中，其中根据器官位置与峰值缩放LET加权剂量（c LETxD）位置之间的拓扑关系设置每个扫描点的惩罚。所有计划均进行归一化处理，以提供相同的靶区剂量覆盖。对每个患者病例的三种优化方法评估并比较剂量（假设相对生物学效应值恒定为1.1，如临床实践中那样）、生物学效应（c LETxD）和计算时间消耗。
对于所有四个病例，三种优化方法在靶区和关键结构中产生了相当的剂量覆盖。LETOpt计划和DEAOpt计划在类似程度上减少了关键结构中的生物学效应热点，并增加了靶区的生物学效应。对于靶区，DEAOpt计划中的c LETxD和c LETxD分别比DoseOpt计划平均高7.2%和11.74%。对于脑干，DEAOpt计划中的c LETxD比DoseOpt计划平均低33.38%。此外，DEAOpt方法比LETOpt方法节省了30.37%的计算成本。
DEAOpt是一种替代的IMPT优化方法，它将扫描点的位置与生物学效应分布相关联。IMPT可受益于DEAOpt的使用，因为该方法不仅能提供与LETOpt计划相当的生物学效应，而且速度更快。
