Journal
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
Volume 133, Issue 3, Pages 729-+Publisher
MOSBY-ELSEVIER
DOI: 10.1016/j.jaci.2013.09.039
Keywords
Asthma; airway remodeling; distal airway; CT; quantitative imaging; phenotypes; cluster analysis; fractal analysis
Categories
Funding
- GlaxoSmithKline
- Wellcome Trust
- Airway Disease Predicting Outcomes through Patient Specific Computational Modelling (AirPROM) project
- FP7 EU grant
- National Institute for Health Research (NIHR)
- National Institute for Health Research [NF-SI-0512-10018, NF-SI-0510-10157, CL-2012-11-002, CL-2008-11-005] Funding Source: researchfish
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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 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. Conclusions: Quantitative CT analysis provides a new perspective in asthma phenotyping, which might prove useful in patient selection for novel therapies.
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