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Quantitative Analysis of Bronchiectasis in Alpha-1 Antitrypsin Deficiency.
Joshua De Soyza1,2, Philipp Höger3,4, Paul Ellis1,2
1Department of Applied Health Sciences, University of Birmingham, Birmingham, UK, birmingham.ac.uk.
Canadian Respiratory Journal
|June 24, 2026
Summary
Computed tomography (CT) analysis quantifies mild bronchiectasis in Alpha-1 antitrypsin deficiency (AATD). This automated method aids in assessing airway changes and may support clinical trials for new AATD therapies.
Area of Science:
- Pulmonary Medicine
- Radiology
- Genetics
Background:
- Alpha-1 antitrypsin deficiency (AATD) is linked to bronchiectasis, but visual CT assessment is subjective and time-consuming.
- Automated CT analysis offers potential for objective quantification of airway changes in AATD.
- This study evaluates CT algorithms for diagnosing mild bronchiectasis in AATD patients.
Purpose of the Study:
- To assess the utility of CT algorithms in quantifying mild bronchiectasis in Alpha-1 antitrypsin deficiency (AATD).
- To determine if automated CT analysis can provide objective and efficient assessment of airway tapering and bronchiectasis in AATD.
Main Methods:
- Utilized YACTA software to analyze CT scans from 154 patients with severe AATD.
- Extracted data on bronchiectasis index (BEI), airway wall thickness (AWPi10), and emphysema (PD15).
- Correlated algorithm-derived metrics with visual scoring and assessed associations with clinical outcomes using statistical models.
Main Results:
- BEI showed moderate correlation with visual assessments of bronchial dilatation, wall thickness, lobar involvement, and morphology.
- Identified thresholds for BEI associated with bronchial dilatation and lobar involvement, though with limited sensitivity and specificity.
- AWPi10 did not correlate with bronchial wall thickness or clinical outcomes; BEI was associated with the bronchiectasis severity index (BSI).
Conclusions:
- CT algorithm analysis demonstrates value in quantifying mild bronchiectasis in AATD.
- Automated CT analysis may serve as a valuable tool in clinical trials for emerging AATD therapies.
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