期刊
RADIOTHERAPY AND ONCOLOGY
卷 187, 期 -, 页码 -出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2023.109821
关键词
Lung cancer; Functional Imaging; Dose-response Modeling; PFT
This study evaluated the factors predicting pulmonary function changes in patients receiving functional avoidance radiotherapy. The data showed that lung dose-function metrics can predict pulmonary function changes, proving the importance of reducing dose to functional lung regions and providing guidance for future clinical trials.
Purpose: Functional avoidance radiotherapy uses functional imaging to reduce pulmonary toxicity by designing radiotherapy plans that reduce doses to functional regions of the lung. A phase-II, multicenter, prospective study of 4DCT-ventilation functional avoidance was completed. Pre and posttreatment pulmonary function tests (PFTs) were acquired and assessed pulmonary function change. This study aims to evaluate which clinical, dose and dose-function factors predict PFT changes for patients treated with 4DCT-ventilation functional avoidance radiotherapy.Materials and Methods: 56 patients with locally advanced lung cancer receiving radiotherapy were accrued. PFTs were obtained at baseline and three months following radiotherapy and included forced expiratory volume in 1-second (FEV1), forced vital capacity (FVC), and FEV1/FVC. The ability of patient, clinical, dose (lung and heart), and dose-function metrics (metrics that combine dose and 4DCTventilation-based function) to predict PFT changes were evaluated using univariate and multivariate linear regression.Results: Univariate analysis showed that only dose-function metrics and the presence of chronic obstructive pulmonary disease (COPD) were significant (p<0.05) in predicting FEV1 decline. Multivariate analysis identified a combination of clinical (immunotherapy status, presence of thoracic comorbidities, smoking status, and age), along with lung dose, heart dose, and dose-function metrics in predicting FEV1 and FEV1/FVC changes.Conclusion: The current work evaluated factors predicting PFT changes for patients treated in a prospective functional avoidance radiotherapy study. The data revealed that lung dose- function metrics could predict PFT changes, validating the significance of reducing the dose to the functional lung to mitigate the decline in pulmonary function and providing guidance for future clinical trials.
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