概率临床目标定义与最近邻对应关系
L Rivetti1,2, G Buti2, L Amoudruz3
1Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia.
Physics in medicine and biology
|December 9, 2025
概括
这项研究引入了新的随机模型来估计微观瘤存在的概率,改善了放射治疗中的临床目标体积划分. 这些模型使用空间相关性来更好地捕捉视下疾病的传播.
科学领域:
- 辐射疗法 辐射疗法
- 医疗成像医学成像
- 计算生物学 计算生物学
背景情况:
- 放射治疗中的临床目标体积 (CTV) 划分受到医疗图像上的微观疾病不可见性的限制.
- 目前的指导方针提出了CTV的概率解释,但缺乏计算微观瘤存在 (MTP) 概率的方法.
- 这项研究解决了概率MTP估计中的差距.
研究的目的:
- 开发新的随机模型,以估计微观瘤存在 (MTP) 的概率.
- 将voxel社区内的本地空间相关性纳入,以改进MTP估计.
- 为概率性CTV定义提供统计上一致的框架.
主要方法:
- 开发了两种第一原则的随机模型:恒定边际概率 (CMP) 和可变边际概率 (VMP).
- CMP模型假设统一的MTP,适用于没有从总瘤体积 (GTV) 辐射依赖的瘤.
- VMP模型结合了辐射依赖,模拟与GTV距离的距离下降MTP.
主要成果:
- 两种CMP和VMP模型都准确地复制了MTP存在分数.
- CMP模型估计前列腺癌中MTP的0.03边际概率.
- VMP模型复制了乳腺和肺癌中的放射性瘤岛屿分布,平均绝对误差低.
结论:
- 拟议的随机模型为概率CTV划分提供了一个统计学上一致的框架.
- 这些模型通过结合局部声母相关性来增强对微观疾病传播的理解.
- 这些模型提供了一种新的方法来解决放射治疗规划中的不确定性.
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