The purpose of this work is to create a decision support methodology to predict when patients undergoing radiotherapy treatment for locally advanced lung cancer would potentially benefit from adaptive radiotherapy. The proposed methodology seeks to eliminate the manual subjective review by developing an automated statistical learning model to predict when tumor regression would trigger implementation of adaptive radiotherapy based on quantified anatomic changes observed in individual patients on-treatment cone beam computed tomographies (CTs). This proposed process seeks to improve the efficacy and efficiency of both the existing manual and automated adaptive review processes for locally advanced stage III lung cancer.

中文翻译：

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一种肺适应性放疗肿瘤消退预测建模方法

这项工作的目的是创建一种决策支持方法，以预测接受局部晚期肺癌放疗的患者何时可能从适应性放疗中受益。所提出的方法旨在通过开发自动统计学习模型来预测肿瘤消退何时​​触发自适应放疗的实施，从而消除手动主观审查，该模型基于在接受治疗的个体患者的锥形束计算机断层扫描 (CT) 中观察到的量化解剖学变化。该提议的流程旨在提高针对局部晚期 III 期肺癌的现有手动和自动自适应审查流程的功效和效率。