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新型全自动治疗计划系统的临床前验证。

Pre-clinical validation of a novel system for fully-automated treatment planning.

机构信息

Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, The Netherlands; Department of Radiotherapy, Erasmus MC Cancer Institute, GD Rotterdam, The Netherlands.

出版信息

Radiother Oncol. 2021 May;158:253-261. doi: 10.1016/j.radonc.2021.03.003. Epub 2021 Mar 10.

Abstract

INTRODUCTION

Many approaches for automated treatment planning (autoplanning) have been proposed and investigated. Autoplanning can enhance plan quality compared to 'manual' trial-and-error planning, and decrease routine planning workload. A few approaches have been implemented in commercial treatment planning systems (TPSs). We performed a pre-clinical validation of a new system ('NovelATP') that is based on fully-automated multi-criterial optimization (MCO). The aim of NovelATP is to automatically generate for each patient a single high-quality, Pareto-optimal plan without manual Pareto navigation.

MATERIAL AND METHODS

Validation was performed by generating VMAT/IMRT plans for conventional treatment of prostate cancer (101 pts), prostate SBRT (20 pts), bilateral head-and-neck cancer (50 pts) and rectal cancer treated at an MR-Linac (23 pts). NovelATP autoplans were compared to plans that were generated with our in-house autoplanning system. In many previous validation studies, the latter system consistently showed enhanced plan quality when compared to manual planning.

RESULTS

Dosimetrical differences between NovelATP and benchmark plans were on average small and presumably not clinically relevant, pointing at high NovelATP dosimetric plan quality. MUs were 11-19% higher with NovelATP. NovelATP delivery times were up to 12% longer. Overall, there was a slight disadvantage for NovelATP regarding gamma analyses. Calculation times for NovelATP plans were between 29  and 151 min with no overall differences with the benchmark plans.

CONCLUSION

The new autoplanning system was able to produce high-quality plans for four highly different planning protocols/treatment sites with a total of 194 patients investigated.

摘要

简介

许多自动化治疗计划(自规划)方法已经被提出并进行了研究。与“手动”反复试验规划相比,自规划可以提高计划质量,并减少常规规划工作量。一些方法已经在商业治疗计划系统(TPS)中实现。我们对一种新的系统(“NovelATP”)进行了临床前验证,该系统基于完全自动化的多标准优化(MCO)。NovelATP 的目的是为每个患者自动生成一个高质量的、帕累托最优的单一计划,而无需手动帕累托导航。

材料和方法

通过为前列腺癌(101 例)、前列腺 SBRT(20 例)、双侧头颈部癌(50 例)和在 MR-Linac 治疗的直肠癌(23 例)的常规治疗生成 VMAT/IMRT 计划来进行验证。将 NovelATP 自规划与我们内部的自动规划系统生成的计划进行比较。在许多以前的验证研究中,当与手动规划相比时,后者系统始终显示出增强的计划质量。

结果

NovelATP 和基准计划之间的剂量学差异平均较小,推测没有临床相关性,表明 NovelATP 具有较高的剂量学计划质量。使用 NovelATP 时,MU 增加了 11-19%。NovelATP 的输送时间延长了 12%。总体而言,NovelATP 在伽马分析方面略处于劣势。NovelATP 计划的计算时间在 29 到 151 分钟之间,与基准计划没有总体差异。

结论

新的自动规划系统能够为四个高度不同的规划协议/治疗部位的 194 名患者生成高质量的计划。

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