MDCT-based longitudinal automated airway and air trapping analysis in school-age children with mild cystic fibrosis lung disease.

Objectives: Quantitative computed tomography (QCT) offers some promising markers to quantify cystic fibrosis (CF)-lung disease. Air trapping may precede irreversible bronchiectasis; therefore, the temporal interdependencies of functional and structural lung disease need to be further investigated. We aim to quantify airway dimensions and air trapping on chest CT of school-age children with mild CF-lung disease over two years.

Methods: Fully-automatic software analyzed 144 serial spirometer-controlled chest CT scans of 36 children (median 12.1 (10.2-13.8) years) with mild CF-lung disease (median ppFEV1 98.5 (90.8-103.3) %) at baseline, 3, 12 and 24 months. The airway wall percentage (WP), bronchiectasis index (BEI), as well as severe air trapping (A3) were calculated for the total lung and separately for all lobes. Mixed linear models were calculated, considering the lobar distribution of WP, BEI and A3 cross-sectionally and longitudinally.

Results: WP remained stable ( = 0.248), and BEI changed from 0.41 (0.28-0.7) to 0.54 (0.36-0.88) ( = 0.156) and A3 from 2.26% to 4.35% ( = 0.086) showing variability over two years. ppFEV1 was also stable ( = 0.276). A robust mixed linear model showed a cross-sectional, regional association between WP and A3 at each timepoint ( < 0.001). Further, BEI showed no cross-sectional, but another mixed model showed short-term longitudinal interdependencies with air trapping ( = 0.003).

Conclusions: Robust linear/beta mixed models can still reveal interdependencies in medical data with high variability that remain hidden with simpler statistical methods. We could demonstrate cross-sectional, regional interdependencies between wall thickening and air trapping. Further, we show short-term regional interdependencies between air trapping and an increase in bronchiectasis. The data indicate that regional air trapping may precede the development of bronchiectasis. Quantitative CT may capture subtle disease progression and identify regional and temporal interdependencies of distinct manifestations of CF-lung disease.