更新基于词汇优化的规划方法,以改善宫癌计划质量
Paolo Caricato1,2, Sara Trivellato3, Roberto Pellegrini4
1Medical Physics Department, Fondazione IRCCS San Gerardo Dei Tintori, Monza, Italy. paolo.caricato93@gmail.com.
Discover oncology
|September 29, 2023
概括
该mCycle自动化规划算法显著改善了宫癌放射治疗计划中的危险器官节约. 自动化计划在临床上是可以接受的,并且比手工计划更受欢迎,表现出同等或更高的质量.
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:
- 评估mCycle自动化词汇优化 (LO) 计划算法,以提高放射治疗计划的质量.
- 评估其在不损害目标覆盖范围或传递精度的情况下,在危险器官 (OAR) 节省方面的能力.
研究的目的:
- 调查mCycle LO算法的潜力,以提高治疗计划质量.
- 确定mCycle是否可以改善OAR节省,同时保持目标覆盖率和交付精度.
主要方法:
- 对24个宫癌体积调节弧度疗法 (VMAT) 计划进行了回顾性分析.
- 手动计划 (MP) 与mCycle生成的计划 (mCP01,mCP02) 的比较,使用两个版本的愿望列表 (WL).
- 高级医生进行临床评估,并使用全球质量指数进行评估.
主要成果:
- mCycle证明了改善的OAR节省,特别是在直肠,与mCP02.
- mCP01显示了优越的目标覆盖率 (PTV V95%).
- 自动化计划在临床上是可以接受的,在90%的盲目比较中是首选的,并且具有可比或更好的质量得分.
结论:
- 在mCycle中实施的词典学方法,为创建苛刻的治疗计划提供了灵活性.
- 这种方法有可能在放射治疗计划中最大限度地减少毒性.
- mCycle显示了增强OAR节省宫癌VMAT的承诺.
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