Multi-institutional evaluation of a Pareto navigation guided automated radiotherapy planning solution for prostate cancer

IF 3.3 2区 医学 Q2 ONCOLOGY Radiation Oncology Pub Date : 2024-04-08 DOI:10.1186/s13014-024-02404-x
Philip A Wheeler, Nicholas S West, Richard Powis, Rhydian Maggs, Michael Chu, Rachel A Pearson, Nick Willis, Bartlomiej Kurec, Katie L. Reed, David G. Lewis, John Staffurth, Emiliano Spezi, Anthony E. Millin
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Abstract

Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer. The implemented ‘Pareto Guided Automated Planning’ (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a ‘Protocol Based Automatic Iterative Optimisation’ planning framework. 30 previous patients were randomly selected by each institution (IA and IB), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions’ clinical preferences. A single automated plan (VMATAuto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMATClinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution. PGAP led to marked improvements across the majority of rectal dose metrics, with Dmean reduced by 3.7 Gy and 1.8 Gy for IA and IB respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for IB but increased for IA. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D98% was generally improved with VMATAuto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMATAuto, with 31/40 considered superior to VMATClinical upon blind review. PGAP enabled intuitive adaptation of automated protocols to an institution’s planning aims and yielded plans more congruent with the institution’s clinical preference than the locally produced manual clinical plans.
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针对前列腺癌的帕累托导航引导自动放射治疗计划解决方案的多机构评估
目前的自动规划解决方案是通过对历史数据集进行试错或机器学习来校准的。这两种方法都无法在校准过程中直观地探索不同的权衡选项,而这可能有助于确保自动解决方案符合临床偏好。帕累托导航提供了这种功能,并提供了一种潜在的校准替代方法。本研究的目的是在两家治疗前列腺癌的外部机构中验证一种自动放疗计划解决方案,该解决方案具有新颖的多维帕累托导航校准界面。实施的 "帕累托引导自动计划"(PGAP)方法是在 RayStation 中使用脚本开发的,包括一个建立在 "基于协议的自动迭代优化 "计划框架基础上的帕累托导航校准界面。每个机构(IA 和 IB)随机选取 30 名既往患者,其中 10 名用于校准,20 名用于验证。利用帕累托导航界面,根据各机构的临床偏好对自动方案进行校准。为每个验证患者生成一个单一的自动计划(VMATAuto),并使用一系列 DVH 指标将计划质量与之前治疗的临床计划(VMATClinical)进行定量比较,同时通过外部机构的盲审进行定性比较。PGAP 显著改善了大部分直肠剂量指标,IA 和 IB 的 Dmean 分别降低了 3.7 Gy 和 1.8 Gy(p < 0.001)。在膀胱方面,结果好坏参半,IB 的低剂量和中等剂量指标有所降低,而 IA 则有所提高。虽然差异在统计学上具有显著性(p < 0.05),但差异很小,不具有临床意义。直肠剂量的减少并不以 PTV 覆盖率为代价(VMATAuto 的 D98% 通常有所提高),但对 PTV 一致性有些不利。不过,直肠剂量优先于符合性的做法与校准过程中表达的偏好相一致,也是两家机构明显倾向于使用 VMATAuto 的主要驱动因素,盲审结果显示 31/40 均认为 VMATAuto 优于 VMATClinical。PGAP 能够使自动方案直观地适应医疗机构的计划目标,与本地制作的手动临床计划相比,PGAP 所产生的计划更符合医疗机构的临床偏好。
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来源期刊
Radiation Oncology
Radiation Oncology ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
6.50
自引率
2.80%
发文量
181
审稿时长
3-6 weeks
期刊介绍: Radiation Oncology encompasses all aspects of research that impacts on the treatment of cancer using radiation. It publishes findings in molecular and cellular radiation biology, radiation physics, radiation technology, and clinical oncology.
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