正常的器官剂量减少通过流动性地图预测计划调整调整
Yaoying Liu1,2, Yiru Peng3, Qichao Zhou4
1National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China.
Physics in medicine and biology
|October 15, 2025
概括
本研究介绍了一种用于在线适应性辐射治疗的快速流动图预测方法. 这种方法显著降低了对健康组织的辐射剂量,同时保持瘤覆盖,提高了患者的安全.
科学领域:
- 辐射瘤学 辐射瘤学
- 医学物理 医学物理
- 人工智能在医学中的应用
背景情况:
- 放射治疗 (RT) 期间的解剖学变化需要计划适应以获得最佳结果.
- 目前的RT规划可能会导致低于最佳剂量的输送,并增加由于解剖变化的健康组织的风险.
- 在线适应性RT (OART) 旨在解决这些变化,以提高治疗疗效和安全.
研究的目的:
- 研究一种基于流动性地图预测的方法 (FM_PD),用于在OART中快速调整计划.
- 通过考虑治疗期间的结构变化来评估FM_PD在改善正常组织节约方面的潜力.
- 为了评估FM_PD对风险器官 (OAR) 的剂量影响,与非适应计划相比.
主要方法:
- 一个2D密度U-Net模型被训练使用93强度调节的RT计划用于下癌,结合PTV特异性损失.
- 计划目标体积 (PTV) 和剂量分布被转换为2D投影矩阵用于模型训练.
- 九个模拟OART的重新规划场景被用于测试;预测的流动性地图被应用于每日CTs以计算更新的剂量分布.
主要成果:
- FM_PD显著减少了对正常组织的辐射剂量,同时保持了瘤覆盖范围.
- 在关键结构中观察到剂量减少:透镜,视神经和脑干的Dmax分别下降了18.67%,19.17%和14.54%.
- 平均总体剂量下降了25.65%,对邻近的肺组织平均剂量显著下降了46.40%.
结论:
- FM_PD提供了一种快速有效的策略,用于根据解剖变化调整RT计划.
- 这种方法显著降低了对健康组织的辐射剂量,提高了患者的安全性.
- 建议在临床OART实践中使用FM_PD进行交叉分数适应,而不是保持初始计划.
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