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Automated computed tomographic analysis of bronchial thickness and mucus plugs in bronchiectasis with asthma
Tjeerd van der Veer1,2, Eleni-Rosalina Andrinopoulou3,4, Punitkumar Makani5
1Department of Pulmonary Disease, Erasmus MC, Rotterdam, The Netherlands.
Background:
Bronchiectasis disease is characterised by cough, sputum and exacerbations, with chest computed tomography (CT) typically showing bronchial wall thickening and mucus plugging in addition to bronchial dilation. Asthma is a common comorbidity and associated with increased, eosinophilic, airway inflammation. Automated measurements of bronchial wall thickening and mucus plugs may serve as biomarkers for inflammation and are associated with clinical characteristics such as spirometry, blood eosinophil counts and disease severity in patients with bronchiectasis and asthma co-diagnosis.
Methods:
In a cross-sectional retrospective cohort of 64 patients with bronchiectasis disease and asthma, we applied automated image analysis to assess bronchial dimensions and mucus plug metrics on chest CT scans. These metrics were correlated with spirometry, blood eosinophil counts as well as FACED and Bronchiectasis Severity Index (BSI) scores using correlations and multiple regression analyses.
Results:
In 63 patients, bronchial wall thickness and mucus plugs were quantified. Negative correlations were observed between bronchial wall thickness markers and spirometry (bronchial wall thickness/accompanying artery diameter and forced expiratory volume in 1 s (FEV1), r= -0.37; FEV1/forced vital capacity, r= -0.30). Mucus plugs correlated negatively with spirometry and positively with FACED and BSI scores (number of mucus plugs and BSI, r=0.45). Correlations with blood eosinophil counts were very weak. In multiple regression analyses, independent associations were observed for FEV1, Pseudomonas aeruginosa and frequent exacerbations.
Conclusion:
This study identified key relationships between automated measurements of bronchial wall thickness and mucus plugs and clinical characteristics, highlighting their potential as imaging biomarkers to enhance phenotyping, improve risk assessment and facilitate tailored treatment strategies in bronchiectasis.
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