Prediction of pulmonary function decline in fibrous interstitial lung abnormalities based on quantitative chest CT parameters

This study evaluated the predictive value of quantitative chest CT parameters for pulmonary function decline in patients with fibrotic interstitial lung abnormalities (ILA). A total of 49 patients with fibrotic ILA were followed for five years, and AI-based automated software (Aview, Coreline Soft) was used to quantify fibrotic features such as honeycombing, reticulation, and ground-glass opacity on baseline CT. The extent of fibrotic lesions was significantly correlated with annual declines in FVC and DLCO, with fibrosis extent showing the strongest association with FVC decline. These results suggest that quantitative CT analysis can serve as a useful early predictor of pulmonary function deterioration.