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基于人工智能的自动细分和放射治疗剂量映射用于胸部正常组织.

Jue Jiang1, Chloe Min Seo Choi1,2, Joseph O Deasy1

  • 1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.

Physics and imaging in radiation oncology
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概括

人工智能 (AI) 的可变形图像记录 (DIR) 和基于器官分割的AI剂量映射 (AIDA) 提供了对胸部器官的快速和准确的放射治疗剂量评估. 这种人工智能方法证明了临床放射治疗应用的可行性.

关键词:
人工智能的人工智能是人工智能.自动化剂量映射自动化剂量映射在CBCT中,CBCT是CBCT.肺癌是一种肺癌.注册-细分 - 注册-细分

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科学领域:

  • 放射治疗物理和技术.
  • 医学成像和图像分析.
  • 医学中的人工智能

背景情况:

  • 对对胸部器官进行的放射治疗 (RT) 的客观评估需要有效和精确的可变形剂量映射.
  • 目前的方法可能耗时,影响临床工作流程的效率.

研究的目的:

  • 实施和评估一个AI驱动的可变形图像注册 (DIR) 和基于器官细分的AI剂量映射 (AIDA) 系统.
  • 评估AIDA在肺癌患者的食道和心脏剂量映射中的准确性和速度.

主要方法:

  • 开发了一种集结刚性对齐,基于AI的器官细分在光束CT (CBCT) 上的自动化管道,以及用于剂量映射的AI-DIR.
  • AIDA剂量指标计算了72名局部晚期非小细胞肺癌患者的AIDA剂量指标,这些患者接受了并发化疗和放射治疗.
  • 将AIDA衍生剂量指标与计划剂量和手动基于轮的剂量映射 (手动DA) 进行了比较.

主要成果:

  • 每位患者的AIDA处理时间约为2分钟.
  • 人工智能细分实现了食道和心脏的高精度,平均子相似系数 (DSC) 分别为0.80和0.94.
  • 与计划剂量相比,AIDA发现心脏剂量明显较低 (p=0.04),与手册DA相比,观察到的剂量偏差更频繁 (>=1Gy).

结论:

  • 从CBCT中快速估计胸部组织放射治疗剂量,使用AIDA系统是可行的.
  • 来自AIDA的指标和细分显示了与手动剂量评估相比的性能.
  • 这些发现支持AIDA在增强放射治疗应用方面的潜在实用性.