Canadian respiratory journal · 2026
Computed Tomography-Based Evaluation of Airway Remodeling for Distinguishing Asthma-Chronic Obstructive Pulmonary Disease Overlap From Asthma and Chronic Obstructive Pulmonary Disease.
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Chen Mei-Cheng, Liu Yang-Li, Chen Feng-Jia, Liang Wei, Deng Wei-Wei, Ma Ling, Guo Yu-Biao, Feng Shi-Ting, Zhu Ying
Аннотация
OBJECTIVES: We aimed to explore the practicality of CT imaging for diagnosing asthma-chronic obstructive pulmonary disease (COPD) overlap syndrome (ACO).
METHOD: A total of 339 patients, including asthma, COPD, and ACO, were retrospectively collected from our hospital from February 2014 to October 2020. Airway and emphysema CT parameters were measured by image-analyzing software. Multivariate logistic regression analysis was applied to select independent variables for building the diagnostic models.
RESULT: Female gender, younger age, higher WA1st/BSA (the mean wall area of the trachea and main bronchi), and lower WT1st/BSA (the mean wall thickness of the trachea and main bronchi) were independently associated with a higher risk of developing ACO compared to COPD. Male gender, older age, lower inferior lobes mean density (MD), higher inferior lobes WA2nd% (the mean wall area of the segmental bronchus), and lower superior lobes WA2nd% were independently associated with a higher risk of developing ACO compared to asthma. The area under the receiver operating characteristic curves (AUCs) of the two differential diagnostic models for ACO was 0.736 and 0.826, respectively. The calibration curve represented good consistency between the predictions by the models and the actual observations.
CONCLUSION: The proposed models can serve as noninvasive tools to diagnose ACO from COPD and asthma. This study highlights the value of CT in evaluating airway remodeling features and holds promise for clinical application.
METHOD: A total of 339 patients, including asthma, COPD, and ACO, were retrospectively collected from our hospital from February 2014 to October 2020. Airway and emphysema CT parameters were measured by image-analyzing software. Multivariate logistic regression analysis was applied to select independent variables for building the diagnostic models.
RESULT: Female gender, younger age, higher WA1st/BSA (the mean wall area of the trachea and main bronchi), and lower WT1st/BSA (the mean wall thickness of the trachea and main bronchi) were independently associated with a higher risk of developing ACO compared to COPD. Male gender, older age, lower inferior lobes mean density (MD), higher inferior lobes WA2nd% (the mean wall area of the segmental bronchus), and lower superior lobes WA2nd% were independently associated with a higher risk of developing ACO compared to asthma. The area under the receiver operating characteristic curves (AUCs) of the two differential diagnostic models for ACO was 0.736 and 0.826, respectively. The calibration curve represented good consistency between the predictions by the models and the actual observations.
CONCLUSION: The proposed models can serve as noninvasive tools to diagnose ACO from COPD and asthma. This study highlights the value of CT in evaluating airway remodeling features and holds promise for clinical application.