Purpose: To automatically quantify airway structural properties visualised on CT in children with cystic fibrosis (CF) and controls, including: bronchiectasis, airway wall thickening, and lumen tapering. Methods and materials: The 3D surface of the airway lumen, outer wall, and bronchial arteries were obtained using a fully automatic, in-house developed, segmentation method. Subsequently, for each detected airway branch, the Airway-Artery Ratio (AAR, ratio between airway outer wall and accompanying artery radius, a bronchiectasis measurement), Wall-Artery Ratio (WAR, ratio between airway wall thickness and accompanying artery radius), and inter-branch Lumen-Ratio (LR, ratio between a branch's lumen and its parent branch lumen radius, a tapering measurement) were computed. Because CF-related structural abnormalities only affect a portion of branches, the 75th percentile was used as summarising measurement for each subject. Results: Spirometer-guided inspiratory chest CTs of 12 CF patients (median age 10.6 years, 5 females) and 12 age and gender matched controls - lungs evaluated as normal on CT - (median age 12.4 years, 5 females) were retrospectively selected in the Sophia Children’s Hospital. 3650 airway branches were measured. We found good agreement with manually measured radii of lumen (Spearman correlation: 0.901), outer wall (0.860), and artery (0.867) on a subset of 1958 branches. CF population showed increased AAR (CF: 1.703, Controls: 1.310, p<0.011), WAR (CF: 0.850, Controls: 0.632, p<0.003), and LR (CF: 0.866, Controls: 0.771, p<0.002). All results reported are the 75th percentile. Conclusion: State-of-the-art image analysis algorithms are a sensitive method to detect and quantify CF-related structural changes of the airways.