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计划Act:一个基于eclipse脚本API的模块,嵌入了用于本地高级非小细胞肺癌自动规划的临床优化策略

Hao Guo¹, Tenzin Kunkyab¹, Yang Lei¹

¹Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, USA.

Journal of applied clinical medical physics

|October 9, 2025

概括

"PlanAct"显著改善了对非小细胞肺癌的自动化强度调节放射治疗计划,优于现有方法,并提供更好的风险器官节约. 这种工具可以提高治疗的一致性和质量,以应对具有挑战性的病例.

科学领域:

辐射瘤学辐射瘤学
医学物理医学物理
癌症治疗方法癌症治疗方法

背景情况:

针对局部晚期非小细胞肺癌 (LA-NSCLC) 的手动强度调节放射治疗 (IMRT) 计划是资源密集的.
像RapidPlan这样的现有自动化方法通常需要对LA-NSCLC进行手动调整以达到临床目标.

研究的目的:

开发和验证PlanAct,一个基于Eclipse脚本API (ESAPI) 的模块,用于LA-NSCLC的自动IMRT规划.
将PlanAct的表现与RapidPlan和现有的临床计划进行比较.

主要方法:

计划Act是开发的模块化功能,以自动化IMRT计划生成和优化.
在56个追溯的LA-NSCLC案件中执行,使用机构质量指标对RapidPlan和临床基准进行计划评估.
统计分析评估了计划质量和满足剂量测量要求的差异.

主要成果:

与RapidPlan相比,与PlanAct优化的计划显示出更高的质量和更好的风险器官节省,特别是肺部 (p <0.001对于V20和Dmean),相比RapidPlan.
与PlanAct (1项计划) 相比,RapidPlan (18项计划) 和临床计划 (10项计划) 的未满足临床需求显著减少.
即使在复杂的解剖病例中,PlanAct也表现出卓越的剂量分布和热点控制.

结论:

计划Act是优化LA-NSCLC中自动化IMRT规划的有效工具.
实现与临床标准相美或优于临床标准的计划,即使在具有挑战性的患者病例中也是如此.
它的模块化设计显示了将其集成到未来的自主,针对患者的放射治疗规划系统中的潜力.

关键词:

基于知识的规划是基于知识的.

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