4.7 Article

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

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

Funding

  1. GlaxoSmithKline
  2. Wellcome Trust
  3. Airway Disease Predicting Outcomes through Patient Specific Computational Modelling (AirPROM) project
  4. FP7 EU grant
  5. National Institute for Health Research (NIHR)
  6. 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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