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基于剂量-线性能量传递体积约束的适形扫描质子治疗稳健优化

Robust Optimization for Spot-Scanning Proton Therapy based on Dose-Linear-Energy-Transfer Volume Constraints.

作者信息

Chen Jingyuan, Yang Yunze, Feng Hongying, Zhang Lian, Liu Zhengliang, Liu Tianming, Vargas Carlos E, Yu Nathan Y, Rwigema Jean-Claude M, Keole Sameer R, Patel Samir H, Vora Sujay A, Shen Jiajian, Liu Wei

机构信息

Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona.

Department of Radiation Oncology, the University of Miami, Florida.

出版信息

Int J Radiat Oncol Biol Phys. 2025 Apr 1;121(5):1303-1315. doi: 10.1016/j.ijrobp.2024.11.068. Epub 2024 Nov 17.

DOI:10.1016/j.ijrobp.2024.11.068
PMID:39551105
Abstract

PURPOSE

Historically, spot-scanning proton therapy (SSPT) treatment planning uses dose-volume constraints and linear-energy-transfer (LET) volume constraints separately to balance tumor control and organs-at-risk (OARs) protection. We propose a novel dose-LET-volume constraint (DLVC)-based robust optimization (DLVCRO) method for SSPT in treating prostate cancer to obtain a desirable joint dose and LET distribution to minimize adverse events.

METHODS AND MATERIALS

DLVCRO treats DLVC as soft constraints that control the shapes of the dose-LET volume histogram (DLVH) curves. It minimizes the overlap of high LET and high dose in OARs and redistributes high LET from OARs to targets in a user-defined way. Ten patients with prostate cancer were included in this retrospective study. Rectum and bladder were considered as OARs. DLVCRO was compared with the conventional robust optimization (RO) method. Plan robustness was quantified using the worst-case analysis method. Besides the dose-volume histogram indices, the analogous LET-volume histogram, extrabiological dose (the product of per voxel dose and LET) volume histogram (xBDVH) indices characterizing the joint dose/LET distributions and DLVH indices were also used. The Wilcoxon signed-rank test was performed to measure statistical significance.

RESULTS

In the nominal scenario, DLVCRO significantly improved joint distribution of dose and LET to protect OARs compared with RO. The physical dose distributions in targets and OARs are comparable. In the worst-case scenario, DLVCRO markedly enhanced OAR protection (more robust) while maintaining almost the same plan robustness in target dose coverage and homogeneity.

CONCLUSIONS

DLVCRO upgrades 2D DVH-based to 3D DLVH-based treatment planning to adjust dose/LET distributions simultaneously and robustly. DLVCRO is potentially a powerful tool to improve patient outcomes in SSPT.

摘要

目的

在历史上,点扫描质子治疗(SSPT)治疗计划分别使用剂量体积约束和线能量转移(LET)体积约束来平衡肿瘤控制和危及器官(OARs)保护。我们提出一种基于剂量-LET-体积约束(DLVC)的稳健优化(DLVCRO)方法用于前列腺癌的SSPT治疗,以获得理想的联合剂量和LET分布,从而将不良事件降至最低。

方法和材料

DLVCRO将DLVC视为控制剂量-LET体积直方图(DLVH)曲线形状的软约束。它使OARs中高LET和高剂量的重叠最小化,并以用户定义的方式将OARs中的高LET重新分配到靶区。本回顾性研究纳入了10例前列腺癌患者。将直肠和膀胱视为OARs。将DLVCRO与传统稳健优化(RO)方法进行比较。使用最坏情况分析方法对计划稳健性进行量化。除了剂量体积直方图指标外,还使用了类似的LET体积直方图、表征联合剂量/LET分布的额外生物剂量(每体素剂量与LET的乘积)体积直方图(xBDVH)指标和DLVH指标。采用Wilcoxon符号秩检验来衡量统计学显著性。

结果

在标称情况下,与RO相比,DLVCRO显著改善了剂量和LET的联合分布以保护OARs。靶区和OARs中的物理剂量分布相当。在最坏情况下,DLVCRO显著增强了OAR保护(更稳健),同时在靶区剂量覆盖和均匀性方面保持几乎相同的计划稳健性。

结论

DLVCRO将基于二维剂量体积直方图的治疗计划升级为基于三维DLVH的治疗计划,以同时稳健地调整剂量/LET分布。DLVCRO可能是改善SSPT患者治疗结果的有力工具。

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