Computed tomography radiomics-based prognosis prediction of patients with chronic obstructive pulmonary disease

Abstract

Objectivethe objective of this study was to develop a predictive model for pulmonary ventilation function in patients with chronic obstructive pulmonary disease (COPD) utilizing computed tomography (CT) and pulmonary function parameters. Material and methoda retrospective analysis was conducted on 90 patients with COPD from our hospital, who were divided into Group I (AG, normal pulmonary function), Group II (BG, mild ventilation dysfunction), Group III (CG, moderate ventilation dysfunction), Group IV (DG, severe ventilation dysfunction), Group V (EG, very severe restrictive ventilation dysfunction), and Group VI (FG, very severe mixed ventilation dysfunction) according to pulmonary function. The imaging and pulmonary function indicators of the subjects were analyzed. Resultas lung dysfunction worsened, structural changes in the lungs on CT images also progressively worsened, manifesting as an enlargement of emphysematous areas, a decrease in lung field homogeneity, changes in lung tissue density and structure, and a reduction in lung field volume. Maximal expiratory flow (MEF) when 75%, 50% of the forced vital capacity (FVC) remained in the lung, i.e. MEF75%, MEF50%, and maximum mid-expiratory flow (MMEF75%-25%) were most highly correlated with ventilation dysfunction. Conclusionthe severity of pulmonary ventilation dysfunction in patients with COPD can be better predicted by CT imaging and pulmonary function examination indicators.