Abstract
Purpose:To investigate the incorporation of pre‐therapy regional ventilation function in predicting radiation fibrosis (RF) in stage III non‐small‐cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy.Methods:37 stage III NSCLC patients were retrospectively studied. Patients received one cycle of cisplatin‐gemcitabine, followed by two to three cycles of cisplatin‐etoposide concurrently with involved‐field thoracic radiotherapy between 46 and 66 Gy (2 Gy per fraction). Pre‐therapy regional ventilation images of the lung were derived from 4DCT via a density‐change‐based image registration algorithm with mass correction. RF was evaluated at 6‐months post‐treatment using radiographic scoring based on airway dilation and volume loss. Three types of ipsilateral lung metrics were studied: (1) conventional dose‐volume metrics (V20, V30, V40, and mean‐lung‐dose (MLD)), (2) dose‐function metrics (fV20, fV30, fV40, and functional mean‐lung‐dose (fMLD) generated by combining regional ventilation and dose), and (3) dose‐subvolume metrics (sV20, sV30, sV40, and subvolume mean‐lung‐dose (sMLD) defined as the dose‐volume metrics computed on the sub‐volume of the lung with at least 60% of the quantified maximum ventilation status). Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were used to evaluate the predictability of these metrics for RF.Results:In predicting airway dilation, the area under the ROC curve (AUC) values for (V20, MLD), (fV20, fMLD), and (sV20, and sMLD) were (0.76, 0.70), (0.80, 0.74) and (0.82, 0.80), respectively. The logistic regression p‐values were (0.09, 0.18), (0.02, 0.05) and (0.004, 0.006), respectively. With regard to volume loss, the corresponding AUC values for these metrics were (0.66, 0.57), (0.67, 0.61) and (0.71, 0.69), and p‐values were (0.95, 0.90), (0.43, 0.64) and (0.08, 0.12), respectively.Conclusion:The inclusion of regional ventilation function improved predictability of radiation fibrosis. Dose‐subvolume metrics provided a promising method for incorporating functional information into the conventional dose‐volume parameters for outcome assessment.
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