Computed tomography radiomics-based prognosis prediction of patients with chronic obstructive pulmonary disease
Year: 2024
Type: article
Study design: Observational Study
Abstract: the 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. a 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. as 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. the severity of pulmonary ventilation dysfunction in patients with COPD can be better predicted by CT imaging and pulmonary function examination indicators.
Authors: Xiaogang Zhao, Xiaojiao Qiu
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,400
OpenAlex ID: W4404144580