Borderías Villarroel Elena, Geets Xavier, Sterpin Edmond
UCLouvain, Molecular Imaging-Radiotherapy and Oncology (MIRO), Brussels, Belgium.
Cliniques Universitaires Saint-Luc, Department of Radiation Oncology, Brussels, Belgium.
Phys Imaging Radiat Oncol. 2020 Jul 13;15:30-37. doi: 10.1016/j.phro.2020.06.004. eCollection 2020 Jul.
In proton therapy, inter-fractional density changes can severely compromise the effective delivery of the planned dose. Such dose distortion effects can be accounted for by treatment plan adaptation, that requires considerable automation for widespread implementation in clinics. In this study, the clinical benefit of an automatic online adaptive strategy called dose restoration (DR) was investigated. Our objective was to assess to what extent DR could replace the need for a comprehensive offline adaptive strategy.
The fully automatic and robust DR workflow was evaluated in a cohort of 14 lung IMPT patients that had a planning-CT and two repeated 4D-CTs (rCT1,rCT2). Initial plans were generated using 4D-robust optimization (including breathing-motion, setup and range errors). DR relied on isodose contours generated from the initial dose and associated patient specific weighted objectives to mimic this initial dose in repeated-CTs. These isodose contours, with their corresponding objectives, were used during re-optimization to compensate proton range distortions disregarding re-contouring. Robustness evaluations were performed for the initial, not-adapted and restored (adapted) plans.
The resulting DVH-bands showed overall improvement in DVH metrics and robustness levels for restored plans, with respect to not-adapted plans. According to CTV coverage criteria (D95%>95%Dprescription) in not-adapted plans, 35% (5/14) of the cases needed offline adaptation. After DR, Median(D95%) was increased by 1.1 [IQR,0.4] Gy and only one patient out of 14 (7%) still needed offline adaptation because of important anatomical changes.
DR has the potential to improve CTV coverage and reduce offline adaptation rate.
在质子治疗中，分次间的密度变化会严重影响计划剂量的有效递送。这种剂量畸变效应可通过治疗计划适应性调整来解决，而这需要相当程度的自动化才能在临床中广泛应用。在本研究中，我们调查了一种名为剂量恢复（DR）的自动在线自适应策略的临床益处。我们的目标是评估DR在多大程度上可以取代全面的离线自适应策略的需求。
在一组14例肺部调强质子治疗（IMPT）患者中评估了全自动且稳健的DR工作流程，这些患者有一次计划CT以及两次重复的4D-CT（rCT1、rCT2）。初始计划通过4D稳健优化生成（包括呼吸运动、摆位和射程误差）。DR依赖于从初始剂量生成的等剂量线轮廓以及相关的患者特定加权目标，以在重复CT中模拟该初始剂量。这些等剂量线轮廓及其相应目标在重新优化期间用于补偿质子射程畸变，而无需重新勾画轮廓。对初始计划、未适应性调整计划和恢复（适应性调整）计划进行了稳健性评估。
与未适应性调整计划相比，所得的剂量体积直方图（DVH）带显示恢复计划的DVH指标和稳健性水平总体上有所改善。根据未适应性调整计划中的临床靶区（CTV）覆盖标准（D95%>95%处方剂量），35%（5/14）的病例需要离线适应性调整。经过DR后，中位D95%增加了1.1 [四分位间距，0.4] Gy，14例患者中只有1例（7%）因重要的解剖结构变化仍需要离线适应性调整。
DR有潜力改善CTV覆盖并降低离线适应性调整率。
