Lung cancer is a leading cause of death worldwide. Radiation therapy (RT) is one method to treat this disease. A common side effect of RT for lung cancer is radiation-induced lung damage (RILD) which leads to loss of lung function. RILD often compounds pre-existing smoking-related regional lung function impairment. It is difficult to predict patient outcomes due to large variability in individual response to RT. In this study, the capability of image-based modelling of regional ventilation in lung cancer patients to predict lung function post-RT was investigated. Twenty-five patient-based models were created using CT images to define the airway geometry, size and location of tumour, and distribution of emphysema. Simulated ventilation within the 20 Gy isodose volume showed a statistically significant negative correlation with the change in forced expiratory volume in 1 s 12-months post-RT (p = 0.001, R = − 0.61). Patients with higher simulated ventilation within the 20 Gy isodose volume had a greater loss in lung function post-RT and vice versa. This relationship was only evident with the combined impact of tumour and emphysema, with the location of the emphysema relative to the dose-volume being important. Our results suggest that model-based ventilation measures can be used in the prediction of patient lung function post-RT.

肺癌是世界范围内导致死亡的主要原因。放射治疗 (RT) 是治疗这种疾病的一种方法。肺癌放疗的一个常见副作用是辐射诱导的肺损伤 (RILD)，这会导致肺功能丧失。RILD 通常会加重先前存在的与吸烟相关的局部肺功能损害。由于个体对放疗的反应差异很大，因此很难预测患者的预后。在这项研究中，研究了基于图像的肺癌患者区域通气建模预测放疗后肺功能的能力。使用 CT 图像创建了 25 个基于患者的模型，以定义气道几何形状、肿瘤的大小和位置以及肺气肿的分布。p  = 0.001，R  = - 0.61）。在 20 Gy 等剂量体积内模拟通气量较高的患者在放疗后肺功能损失较大，反之亦然。这种关系仅在肿瘤和肺气肿的综合影响下才明显，肺气肿的位置相对于剂量-体积很重要。我们的结果表明，基于模型的通气措施可用于预测放疗后患者的肺功能。