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图像引导放射治疗中的器官轮驱动的自动匹配算法.

Yukako Kishigami1, Mitsuhiro Nakamura1, Hiroyuki Okamoto2

  • 1Department of Advanced Medical Physics, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

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图像引导放射治疗的器官轮驱动的自动匹配算法提供了临床潜力. 这种方法确保了一致的定位和旋转校正对规划目标体积覆盖的最小影响.

关键词:
观察者之间的变异性.基于器官轮的自动匹配.软组织 软组织

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科学领域:

  • 医学物理 医学物理
  • 辐射瘤学 辐射瘤学
  • 图像处理 图像处理

背景情况:

  • 图像指导放射治疗 (IGRT) 需要精确的患者定位.
  • 器官轮信息可以提高IGRT定位的准确性.
  • 宫癌治疗涉及复杂的目标体积和有风险的器官.

研究的目的:

  • 评估一种基于器官轮的IGRT自动匹配算法的临床适用性.
  • 评估算法能够产生一致和准确的患者定位的能力.
  • 为了确定轮值校正对计划目标量 (PTV) 覆盖率的影响.

主要方法:

  • 开发了一个基于体重的自动匹配算法,使用每日和参考MRI扫描的网格模型.
  • 实施了成本函数,优先考虑特定器官在三个场景中定位.
  • 优化了宫和子宫的翻译和旋转值,旋转极限为±3°.
  • 评估PTV覆盖范围,使用同otropic5mm和异otropic边缘.

主要成果:

  • 超过10毫米的翻译发生在9-18%的分数中,根据场景而异.
  • 超过80%的分数实现了小PTV的≥80%覆盖率,大PTV的≥90%实现了≥95%覆盖率.
  • 与单独的翻译定位相比,旋转校正 (±3°) 的影响很小 (中位覆盖率差异<1%).

结论:

  • 器官轮驱动的算法可以在IGRT中进行定量和优先的器官定位.
  • 算法生成了一致的位移值,证明了可靠性.
  • 有限的旋转校正 (±3°) 极少影响PTV覆盖,简化了定位过程.