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放射治疗中自动治疗计划方法的特征描述

Characterization of automatic treatment planning approaches in radiotherapy.

作者信息

Wortel Geert, Eekhout Dave, Lamers Emmy, van der Bel René, Kiers Karen, Wiersma Terry, Janssen Tomas, Damen Eugène

机构信息

Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.

出版信息

Phys Imaging Radiat Oncol. 2021 Jul 13;19:60-65. doi: 10.1016/j.phro.2021.07.003. eCollection 2021 Jul.

Abstract

BACKGROUND AND PURPOSE

Automatic approaches are widely implemented to automate dose optimization in radiotherapy treatment planning. This study systematically investigates how to configure automatic planning in order to create the best possible plans.

MATERIALS AND METHODS

Automatic plans were generated using protocol based automatic iterative optimization. Starting from a simple automation protocol which consisted of the constraints for targets and organs at risk (OAR), the performance of the automatic approach was evaluated in terms of target coverage, OAR sparing, conformity, beam complexity, and plan quality. More complex protocols were systematically explored to improve the quality of the automatic plans. The protocols could be improved by adding a dose goal on the outer 2 mm of the PTV, by setting goals on strategically chosen subparts of OARs, by adding goals for conformity, and by limiting the leaf motion. For prostate plans, development of an automated post-optimization procedure was required to achieve precise control over the dose distribution. Automatic and manually optimized plans were compared for 20 head and neck (H&N), 20 prostate, and 20 rectum cancer patients.

RESULTS

Based on simple automation protocols, the automatic optimizer was not always able to generate adequate treatment plans. For the improved final configurations for the three sites, the dose was lower in automatic plans compared to the manual plans in 12 out of 13 considered OARs. In blind tests, the automatic plans were preferred in 80% of cases.

CONCLUSIONS

With adequate, advanced, protocols the automatic planning approach is able to create high-quality treatment plans.

摘要

背景与目的

自动方法在放射治疗计划中的剂量优化自动化方面得到了广泛应用。本研究系统地探讨了如何配置自动计划以创建尽可能最佳的计划。

材料与方法

使用基于协议的自动迭代优化生成自动计划。从一个简单的自动化协议开始,该协议包含靶区和危及器官(OAR)的约束条件,从靶区覆盖、OAR保护、适形性、射束复杂性和计划质量等方面评估自动方法的性能。系统地探索更复杂的协议以提高自动计划的质量。可以通过在计划靶体积(PTV)外2毫米处添加剂量目标、在OAR的策略性选择子部分设置目标、添加适形性目标以及限制叶片运动来改进协议。对于前列腺计划,需要开发一种自动优化后程序以实现对剂量分布的精确控制。对20例头颈(H&N)癌、20例前列腺癌和20例直肠癌患者的自动计划和手动优化计划进行了比较。

结果

基于简单的自动化协议,自动优化器并不总是能够生成足够的治疗计划。对于三个部位改进后的最终配置,在13个考虑的OAR中,有12个OAR的自动计划剂量低于手动计划。在盲法测试中,80%的情况下自动计划更受青睐。

结论

通过适当、先进的协议,自动计划方法能够创建高质量的治疗计划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28fd/8295841/f07842a249e8/gr1.jpg

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