Computed Tomography Assessment of Airways Throughout Bronchial Tree Demonstrates Airway Narrowing in Severe XXXX .

@entity748 @entity1 @entity850 @entity565
RATIONALE AND OBJECTIVES: To analyze airway dimensions throughout the bronchial tree in severe @entity748 @entity1 using multidetector row computed tomography (MDCT) focusing on airway narrowing. MATERIALS AND METHODS: Thirty-two @entity1 with severe @entity565 underwent automated (BronCare software) analysis of their right lung bronchi, with counts of airways >3 mm long arising from the main bronchi (airway count) and bronchial dimension quantification at segmental and subsegmental levels (lumen area [LA], wall area [WA], and WA%). Focal @entity850 was defined as >50% narrowing of maximal LA on contiguous cross-sectional slices. Severe @entity748 were compared to 13 nonsevere @entity748 @entity1 and nonasthmatic (pooled) subjects (Wilcoxon rank tests, then stepwise logistic regression). Finally, cluster analysis of severe @entity748 @entity1 and stepwise logistic regression identified specific imaging subgroups. RESULTS: The most significant differences between severe @entity748 @entity1 and the pooled subjects were @entity850 (subsegmental and all bronchi: P  <  .002) and WA% (P  <  .0003). Stepwise logistic regression retained WA% as the only explanatory covariable (P  =  .002). Two identified clusters of severe @entity748 @entity1 differed for parameters characterizing airway narrowing (airway count: P  =  .0002; focal @entity850 : P  =  .009). Airway count was as discriminant as forced expiratory volume in 1  second/forced vital capacity (P  =  .01) to identify @entity1 in each cluster, with both variables being correlated (r  =  0.59, P  =  .005). CONCLUSIONS: Severe @entity565 -associated morphologic changes were characterized by focal bronchial stenoses and diffuse airway narrowing; the latter was associated with airflow obstruction. WA%, dependent on airway caliber, is the best parameter to identify severe @entity748 @entity1 from pooled subjects.
