Quantitative CT-derived lobar inter-tapering as a candidate imaging feature associated with airway-predominant non-emphysematous COPD

Abstract

Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disorder involving varying contributions from airway abnormalities and emphysematous destruction. However, structural airway alterations in patients with airflow limitation but minimal emphysema remain incompletely characterized. Quantitative CT (QCT)-based airway morphology analysis may capture additional aspects of airway geometry associated with airway-predominant structural patterns. Objectives This study aimed to evaluate lobar airway inter-tapering abnormalities on quantitative CT in patients with non-emphysematous COPD (NE-COPD) and investigate whether incorporation of inter-tapering features improves discrimination within the studied cohort. Methods This retrospective cross-sectional study included 173 participants who underwent inspiratory thin-section chest CT and post-bronchodilator pulmonary function testing between January 2023 and March 2025. NE-COPD was defined as airflow limitation with minimal emphysema quantified by low-attenuation area percentage below −950 HU (LAA%-950 < 5%). Automated airway segmentation and centerline-based analysis were used to quantify fourth-generation lobar inter-tapering indices. A clinical model incorporating age, sex, and smoking exposure was constructed. An imaging-augmented model was subsequently developed using LASSO-selected lobar inter-tapering features together with global airway branching complexity. Model performance was evaluated using receiver operating characteristic analysis, bootstrap validation, calibration assessment, decision curve analysis, and SHAP interpretation. Results Among the 173 participants, 87 had NE-COPD and 86 were Non-COPD controls. Compared with Non-COPD controls, patients with NE-COPD demonstrated altered fourth-generation lobar inter-tapering patterns in multiple lobes. The clinical model achieved an area under the curve (AUC) of 0.717. After incorporation of quantitative airway features, the imaging-augmented model demonstrated improved discrimination, with an AUC of 0.851. Bootstrap validation demonstrated stable model performance. SHAP analysis indicated that four lobar fourth-generation inter-tapering indices accounted for a substantial proportion of feature contribution within the fitted model. Decision curve analysis suggested higher theoretical net benefit of the imaging-augmented model within the evaluated threshold probability range. Conclusion Quantitative CT-derived lobar inter-tapering was associated with pulmonary function-defined non-emphysematous COPD. These findings suggest that lobar inter-tapering represents a candidate geometric CT descriptor for characterizing airway-predominant structural patterns. Further multicenter studies with external validation and integration of complementary quantitative CT descriptors are required to determine its broader clinical utility.