• J. Allergy Clin. Immunol. · Mar 2014

    Quantitative computed tomography-derived clusters: redefining airway remodeling in asthmatic patients.

    • Sumit Gupta, Ruth Hartley, Umair T Khan, Amisha Singapuri, Beverly Hargadon, William Monteiro, Ian D Pavord, Ana R Sousa, Richard P Marshall, Deepak Subramanian, David Parr, James J Entwisle, Salman Siddiqui, Vimal Raj, and Christopher E Brightling.
    • Department of Infection, Inflammation and Immunity, Institute for Lung Health, University of Leicester, Leicester, United Kingdom; Radiology Department, Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom. Electronic address: drsumitgupta@yahoo.com.
    • J. Allergy Clin. Immunol. 2014 Mar 1; 133 (3): 729-38.e18.

    BackgroundAsthma heterogeneity is multidimensional and requires additional tools to unravel its complexity. Computed tomography (CT)-assessed proximal airway remodeling and air trapping in asthmatic patients might provide new insights into underlying disease mechanisms.ObjectivesThe aim of this study was to explore novel, quantitative, CT-determined asthma phenotypes.MethodsSixty-five asthmatic patients and 30 healthy subjects underwent detailed clinical, physiologic characterization and quantitative CT analysis. Factor and cluster analysis techniques were used to determine 3 novel, quantitative, CT-based asthma phenotypes.ResultsPatients with severe and mild-to-moderate asthma demonstrated smaller mean right upper lobe apical segmental bronchus (RB1) lumen volume (LV) in comparison with healthy control subjects (272.3 mm(3) [SD, 112.6 mm(3)], 259.0 mm(3) [SD, 53.3 mm(3)], 366.4 mm(3) [SD, 195.3 mm(3)], respectively; P = .007) but no difference in RB1 wall volume (WV). Air trapping measured based on mean lung density expiratory/inspiratory ratio was greater in patients with severe and mild-to-moderate asthma compared with that seen in healthy control subjects (0.861 [SD, 0.05)], 0.866 [SD, 0.07], and 0.830 [SD, 0.06], respectively; P = .04). The fractal dimension of the segmented airway tree was less in asthmatic patients compared with that seen in control subjects (P = .007). Three novel, quantitative, CT-based asthma clusters were identified, all of which demonstrated air trapping. Cluster 1 demonstrates increased RB1 WV and RB1 LV but decreased RB1 percentage WV. On the contrary, cluster 3 subjects have the smallest RB1 WV and LV values but the highest RB1 percentage WV values. There is a lack of proximal airway remodeling in cluster 2 subjects.ConclusionsQuantitative CT analysis provides a new perspective in asthma phenotyping, which might prove useful in patient selection for novel therapies.Copyright © 2013 The Authors. Published by Mosby, Inc. All rights reserved.

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