Computed tomography assessment of airways throughout bronchial tree demonstrates airway narrowing in severe asthma

Pierre-Yves Brillet, Marie-Pierre Debray, Jean-Louis Golmard, Yahya Ould Hmeidi, Catalin Fetita, Camille Taillé, Michel Aubier, Philippe A Grenier
Academic Radiology 2015, 22 (6): 734-42

RATIONALE AND OBJECTIVES: To analyze airway dimensions throughout the bronchial tree in severe asthmatic patients using multidetector row computed tomography (MDCT) focusing on airway narrowing.

MATERIALS AND METHODS: Thirty-two patients with severe asthma 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 bronchial stenosis was defined as >50% narrowing of maximal LA on contiguous cross-sectional slices. Severe asthmatics were compared to 13 nonsevere asthmatic patients and nonasthmatic (pooled) subjects (Wilcoxon rank tests, then stepwise logistic regression). Finally, cluster analysis of severe asthmatic patients and stepwise logistic regression identified specific imaging subgroups.

RESULTS: The most significant differences between severe asthmatic patients and the pooled subjects were bronchial stenosis (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 asthmatic patients differed for parameters characterizing airway narrowing (airway count: P = .0002; focal bronchial stenosis: P = .009). Airway count was as discriminant as forced expiratory volume in 1 second/forced vital capacity (P = .01) to identify patients in each cluster, with both variables being correlated (r = 0.59, P = .005).

CONCLUSIONS: Severe asthma-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 asthmatic patients from pooled subjects.

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Saqib Musharaf

A good study, if include reversibilty it is best help in diagnosis beyond spirometry and chalenge testing


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