Wheeler Philip A, Chu Michael, Holmes Rosemary, Smyth Maeve, Maggs Rhydian, Spezi Emiliano, Staffurth John, Lewis David G, Millin Anthony E
Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom.
Cardiff University, School of Engineering, Cardiff, United Kingdom.
Phys Imaging Radiat Oncol. 2019 May 16;10:41-48. doi: 10.1016/j.phro.2019.04.005. eCollection 2019 Apr.
Current automated radiotherapy planning solutions do not allow for the intuitive exploration of different treatment options during protocol calibration. This work introduces an automated planning solution, which aims to address this problem through incorporating Pareto navigation techniques into the calibration process.
For each tumour site a set of planning goals is defined. Utilising Pareto navigation techniques an operator calibrates the solution through intuitively exploring different treatment options: selecting the optimum balancing of competing planning goals for the given site. Once calibrated, fully automated plan generation is possible, with specific algorithms implemented to ensure trade-off balancing of new patients is consistent with that during calibration. Using the proposed methodology the system was calibrated for prostate and seminal vesicle treatments. The resultant solution was validated through quantitatively comparing the dose distribution of automatically generated plans (VMAT) against the previous clinical plan, for ten randomly selected patients.
VMAT yielded statistically significant improvements in: PTV conformity indices, high dose bladder metrics, mean bowel dose, and the majority of rectum dose metrics. Of particular note was the reduction in mean rectum dose (median 25.1 Gy vs. 27.5 Gy), rectum V (median 41.1% vs. 46.4%), and improvement in the conformity index for the primary PTV (median 0.86 vs. 0.79). Dosimetric improvements were not at the cost of other dose metrics.
An automated planning methodology with a Pareto navigation based calibration has been developed, which enables the complex balancing of competing trade-offs to be intuitively incorporated into automated protocols.
当前的自动放射治疗计划解决方案不允许在方案校准过程中直观地探索不同的治疗方案。本研究引入了一种自动计划解决方案，旨在通过将帕累托导航技术纳入校准过程来解决这一问题。
针对每个肿瘤部位定义一组计划目标。操作人员利用帕累托导航技术，通过直观地探索不同的治疗方案来校准解决方案：为给定部位选择相互竞争的计划目标之间的最佳平衡。一旦校准完成，就可以实现全自动计划生成，并实施特定算法以确保新患者的权衡平衡与校准期间一致。使用所提出的方法对前列腺和精囊治疗的系统进行了校准。通过对十名随机选择的患者自动生成的计划（容积调强放疗）的剂量分布与先前的临床计划进行定量比较，对所得解决方案进行了验证。
容积调强放疗在以下方面产生了统计学上显著的改善：计划靶区适形指数、膀胱高剂量指标、平均肠剂量以及大多数直肠剂量指标。特别值得注意的是平均直肠剂量的降低（中位数25.1Gy对27.5Gy）、直肠V（中位数41.1%对46.4%）以及原发计划靶区适形指数的改善（中位数0.86对0.79）。剂量学改善并非以牺牲其他剂量指标为代价。
已开发出一种基于帕累托导航校准的自动计划方法，该方法能够将相互竞争的权衡的复杂平衡直观地纳入自动方案中。
