Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability
- PMID: 33773402
 - DOI: 10.1016/j.ejrad.2021.109657
 
Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability
Abstract
Purpose: With the help of quantitative computed tomography (QCT), it is possible to identify smoking-associated airway remodeling. However, there is currently little information on whether QCT-based airway metrics are sensitive to early airway wall remodeling in subclinical phases of smoking-associated airway disease. This study aimed to evaluate a predictive model that normalized airway parameters and investigate structural airway alterations in smokers with normal-looking CT using the normalization scheme.
Methods: In this retrospective analysis, 222 non-smokers (male 97, female 125) and 69 smokers (male 66, female 3) from January 2014 to December 2016 were included, and airway parameters were quantitatively analyzed. To control inter-subject variability, multiple linear regressions of tracheal wall thickness (WT), diameter (D), and luminal area (LA) were performed, adjusted for age, sex, and height. Using this normalization scheme, airway parameters with matched generation were compared between smokers and non-smokers.
Results: Using the normalization scheme, it was possible to assess generation-based structural alterations of the airways in subclinical smokers. Smokers showed diffuse luminal narrowing of airways for most generations (P < 0.05, except 3rd generation), no change in wall thickness of the proximal bronchi (1st-3rd generation), and a thinning of distal airways (P <0.05, ≥4th generation).
Conclusion: QCT assessment for subclinical smokers can help identify minimal structural changes in airways induced by smoking.
Keywords: Airway remodeling; Chronic obstructive pulmonary disease; Quantitative computed tomography; Smoking.
Copyright © 2021 Elsevier B.V. All rights reserved.
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