BACKGROUND: Expiratory CT and lobar analysis may provide complementary information to inspiratory CT and spirometry for identifying chronic airflow limitation (CAL), but their value in population-based cohorts remains insufficiently characterised.

METHODS: We analysed 2,579 participants from the Stockholm cohort of the Swedish CArdioPulmonary bioImage Study, including 430 with CAL, defined as post-bronchodilator FEV1/FVC < 0.7. Inspiratory and expiratory chest CT scans were segmented into lung lobes using a deep-learning model. Total and lobar lung volumes, low-attenuation volume below -950 HU and below -856 HU, inspiratory - expiratory volume difference, and inspiratory fraction were calculated (inspiratory-expiratory volume/inspiratory volume). Discrimination of CAL was assessed using receiver operating characteristic analysis and regularised logistic regression.

RESULTS: Participants with CAL had higher inspiratory and expiratory lung volumes and higher low-attenuation volumes than those without CAL, while inspiratory fraction was lower. Expiratory CT measures showed stronger discrimination for CAL than inspiratory measures. A model using inspiratory CT measures alone achieved an AUC of 0.66, compared with 0.77 when inspiratory and expiratory total lung measures were combined. Adding lobar measures further improved performance to an AUC of 0.81, with 79% sensitivity, 69% specificity, 34% positive predictive value and 94% negative predictive value.

CONCLUSIONS: Quantitative expiratory CT measures showed stronger discriminatory ability for CAL than inspiratory measures in this population-based cohort. Lobar analysis provided additional regional information and modestly improved classification performance, supporting integrated inspiratory-expiratory CT assessment for identifying CAL.