Mixed integer programming with dose-volume constraints in intensity-modulated proton therapy.
Mixed integer programming with dose-volume constraints in intensity-modulated proton therapy.
复制标题
调强质子治疗中具有剂量体积限制的混合整数规划。
DOI：
10.1002/acm2.12130
复制
发表时间：
2017
影响因子：
2.1
通讯作者：
Liu,Wei
中科院分区：
文献类型：
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作者：
Zhang,Pengfei;Fan,Neng;Shan,Jie;Schild,StevenE;Bues,Martin;Liu,Wei
背景：在强度调节质子治疗（IMPT）的治疗计划中，我们的目标是将规定的剂量传递到目标，同时最大限度地减少对邻近健康组织的剂量。混合整数规划（MIP）已应用于放射治疗中以生成治疗计划。然而，MIP尚未有效地用于有剂量-体积限制的IMPT治疗计划。在这项研究中，我们将剂量-体积限制纳入MIP模型，以制定IMPT的治疗计划。方法建立具有剂量体积约束的IMPT MIP模型。使用MIP模型为3名患者每人生成两组IMPT治疗方案，共6个方案：一个方案采用有限记忆Broyden-Fletcher-Goldfarb-Shanno （L - BFGS）方法推导，另一个方案采用我们的剂量-体积约束的MIP模型推导。然后，我们通过剂量-体积直方图（DVH）指数比较了这两种方案，以评估具有剂量-体积约束的新MIP模型的性能。此外，我们开发了一个模型，以更有效地找到肿瘤覆盖和正常组织保护之间的最佳平衡。结果与传统的二次规划方法相比，具有剂量-体积约束的MIP模型生成的IMPT治疗方案具有可比较的靶剂量覆盖率、靶剂量均匀性和危及器官（OARs）的最大剂量，而无需任何繁琐的试错过程。观察到桨的平均剂量有一些显著的减少。结论基于剂量-体积约束的MIP模型的治疗方案可以满足桨叶和靶点的所有剂量-体积约束，无需繁琐的试错过程。该模型有可能在不同的治疗计划者之间和跨机构之间自动生成具有一致计划质量的IMPT计划，并以有效的方式更好地保护重要的平行桨。
BackgroundIn treatment planning for intensity‐modulated proton therapy (IMPT), we aim to deliver the prescribed dose to the target yet minimize the dose to adjacent healthy tissue. Mixed‐integer programming (MIP) has been applied in radiation therapy to generate treatment plans. However, MIP has not been used effectively for IMPT treatment planning with dose‐volume constraints. In this study, we incorporated dose‐volume constraints in an MIP model to generate treatment plans for IMPT.MethodsWe created a new MIP model for IMPT with dose volume constraints. Two groups of IMPT treatment plans were generated for each of three patients by using MIP models for a total of six plans: one plan was derived with the Limited‐memory Broyden–Fletcher–Goldfarb–Shanno (L‐BFGS) method while the other plan was derived with our MIP model with dose‐volume constraints. We then compared these two plans by dose‐volume histogram (DVH) indices to evaluate the performance of the new MIP model with dose‐volume constraints. In addition, we developed a model to more efficiently find the best balance between tumor coverage and normal tissue protection.ResultsThe MIP model with dose‐volume constraints generates IMPT treatment plans with comparable target dose coverage, target dose homogeneity, and the maximum dose to organs at risk (OARs) compared to treatment plans from the conventional quadratic programming method without any tedious trial‐and‐error process. Some notable reduction in the mean doses of OARs is observed.ConclusionsThe treatment plans from our MIP model with dose‐volume constraints can meet all dose‐volume constraints for OARs and targets without any tedious trial‐and‐error process. This model has the potential to automatically generate IMPT plans with consistent plan quality among different treatment planners and across institutions and better protection for important parallel OARs in an effective way.