Document Type
Conference Proceeding
Publication Date
6-2022
Publication Title
Medical Physics
Abstract
Purpose: Functional avoidance radiotherapy uses functional imaging to reduce pulmonary toxicity by designing radiotherapy plans that reduce doses to the functional lung. A novel form of lung functional imaging uses 4DCT imaging to calculate 4DCT-based lung ventilation (4DCT-ventilation) maps. A phase-II, multi-center, prospective study of 4DCT-ventilation functional avoidance was completed. Pre and post-treatment pulmonary function tests (PFTs) were acquired in order to quantitatively assess pulmonary function change. The purpose of this study is to evaluate which factors predict for PFT changes for patients treated with 4DCT-ventilation functional avoidance radiotherapy. Methods: 56 patients with locally advanced lung cancer receiving radiotherapy were accrued. Each patient had a 4DCTventilation image generated using 4DCT scans and image procession techniques. Favorable arc geometry and optimization techniques were used to generate functional avoidance plans based on the 4DCT-ventilation images. PFTs were obtained at baseline and 3 months following radiotherapy and included forced expiratory volume (FEV1) and forced vital capacity (FVC). The ability of patient, clinical, dose (lung and heart doses), and dose-function metrics to predict for PFT changes was evaluated using linear regression. Dose-function metrics were calculated as doses (mean dose, V20) to 4DCT-ventilation-based functional regions of the lung. Results: The mean pre- to post-treatment changes in FEV1 and FVC were -6.5%+18.1% (mean ± standard deviation) and -9.0%+20.1%, respectively. No patient, clinical, or standard dose metrics were predictive of PFT changes. Dose-function metrics were predictive of FEV1 decline (p=0.048) and approached significance for predicting FVC decline (p=0.061). Conclusion: The current work is the first to assess factors predicting for PFT changes for lung cancer patients treated on a prospective functional avoidance radiotherapy study. The data revealed that lung dose-function metrics were predictive of PFT changes, therefore validating the significance in reducing doses to functional portions of the lung in order to mitigate decline in pulmonary function.
Volume
49
Issue
6
First Page
E150
Last Page
E150
Recommended Citation
Ghassemi N, Castillo R, Castillo E, Jones B, Miften M, Kavanagh B, et al [Grills I, Guerrero T.] Evaluation of variables predicting pulmonary function test (PFT) changes for lung cancer patients treated on a prospective 4DCT-ventilation functional avoidance clinical trial. Med Phys. 2022 Jun; 49(6):E150.