Quantitative Computed Tomography Measurements in Chronic Obstructive Pulmonary Disease Phenotypes
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Chronic obstructive pulmonary disease (COPD) is a diverse disease with various phenotypes. while spirometry remains the primary diagnostic tool, quantitative computed tomography (QCT) may provide more thorough diagnostic and therapeutic insights. This study aimed to analyze the QCT characteristics among different COPD phenotypes and their correlation withdisease severity indicators. Methods: Prospective study of 100 stable COPD cases was conducted ,categorized them based on their clinical phenotype into: asthma-COPD overlap (ACO) (n=35), chronic bronchitis (n=35), emphysema (n=30). Patient demographics, clinical features, co-morbidities, COPD grading, CAT score, BODE index, spirometry, and inspiratory and expiratory CT scans were analyzed. QCT measurements includ low attenuation area(LAA< < -950) , the expiratory to inspiratory mean lung density (E/I-ratio MLD), the airway wall area percent (WA%) and CT based total lung volume. In all cases, correlation between QCT readings and clinical severity indices, also assesed. Results: ACO patients exhibited higher airway wall area percentage (WA%) and air trapping compared to emphysema and chronic bronchitis.Emphysema cases showed highest percentage of LAA < -950 and LAA > 15%, followed by ACO and chronic bronchitis. WA% had a significant positive correlation with CAT score and BODE index in ACO and emphysema. FEF25-75% was inversely related to LAA percentage and total lung capacity in emphysema. Conclusion: ACO patients had more CT quantifiable anomalous airway and air trapping characteristics than other phenotypes. Some QCT readings correlate with the COPD severity indices and the maximum mid expiratory flow rate in spirometry. Keywords: Chronic Obstructive Pulmonary Disease, phenotypes, quantitative CT
Authors: Azza Farag Said, Arwa Mohamed Rady, Hosny Sayed Abdelghani, Bahaa Ibrahim mohamed, Rasha A Abdelfattah
Institution: Minia University
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410179350