posted on 2013-11-27, 15:44authored bySumit 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, Christopher E. Brightling
Background - Asthma 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.
Objectives - The aim of this study was to explore novel, quantitative, CT-determined asthma phenotypes.
Methods - Sixty-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.
Results - Patients 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 mm³ [SD, 112.6 mm³], 259.0 mm³ [SD, 53.3 mm³], 366.4 mm³ [SD, 195.3 mm³], 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.
Conclusions - Quantitative CT analysis provides a new perspective in asthma phenotyping, which might prove useful in patient selection for novel therapies.
Funding
Supported in part by GlaxoSmithKline, Wellcome Trust Senior Fellowship, and the Airway Disease Predicting Outcomes through Patient Specific Computational Modelling (AirPROM) project (funded through FP7 EU grant). This article presents independent research funded by the National Institute for Health Research (NIHR).
History
Citation
Journal of Allergy and Clinical Immunology, 2014, 133 (3), pp. 729-738.e18
Author affiliation
/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Infection, Immunity and Inflammation
Version
VoR (Version of Record)
Published in
Journal of Allergy and Clinical Immunology
Publisher
Elsevier on behalf of the American Academy of Allergy, Asthma and Immunology