Quantitative computed tomography–derived clusters: Redefining airway remodeling in asthmatic patients Sumit Gupta, PhD, MRCP, Ruth Hartley, MBChB, MRCS,

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Quantitative computed tomography–derived clusters: Redefining airway remodeling in asthmatic patients Sumit Gupta, PhD, MRCP, Ruth Hartley, MBChB, MRCS, Umair T. Khan, MBChB, Amisha Singapuri, BSc, Beverly Hargadon, RGN, William Monteiro, MSc, Ian D. Pavord, DM, FRCP, Ana R. Sousa, PhD, Richard P. Marshall, PhD, MRCP, Deepak Subramanian, MD, MRCP, David Parr, MD, FRCP, James J. Entwisle, MBBS, FRCR, Salman Siddiqui, PhD, MRCP, Vimal Raj, MBBS, FRCR, Christopher E. Brightling, PhD, FRCP Journal of Allergy and Clinical Immunology Volume 133, Issue 3, Pages 729-738.e18 (March 2014) DOI: 10.1016/j.jaci.2013.09.039 Copyright © 2013 The Authors Terms and Conditions

Fig 1 Proximal airway remodeling in asthma phenotypes. Pictures of segmented airway tree and RB1 CT cross-section (insets) of asthmatic patients from cluster 1 (A), cluster 2 (B), and cluster 3 (C) are shown. Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E1 Densitometric indices. A cumulative voxel distribution histogram identifying derivation of various densitometric indices is shown. Perc15, 15th Percentile point. Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E2 Standardization of densitometric indices. Regression equations were calculated from measurements of the densitometric standards (extrathoracic air, blood, and 3 electron density rods) for each CT scan of every subject in relation to the standard density measures of the densitometric standards. The regression equations derived were used to adjust all the densitometric indices for each CT scan of every subject. The figure illustrates derivation of regression equation for standardization of densitometric indices for one of the subjects. Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E3 Fractal analysis of the segmented airway tree with FracLac (ImageJ) software. The JPEG image (A) of the segmented airway tree is binarized (B) by ImageJ software by assigning black pixel color for the airway tree and white pixel color for background. The box-counting algorithm places several grids of decreasing box size (C and D) over the ROI (ie, binarized image of the tracheobronchial tree to determine the fractal dimension). Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E4 Fractal dimension of low attenuation areas in lungs. Coronal CT image showing areas of low attenuation less than the threshold CT attenuation value of −950 HU on inspiratory scans (A) and −850 HU on expiratory scans (C), with each lobe coded with a different color. Respective low attenuation clusters are shown in B and D, which are used to assess the size and distribution of emphysematous lesions and air-trapping areas, respectively. Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E5 Bland-Altman plots and intraobserver repeatability with PW2 software. Differences between measures of LA (A), WA (B), and length (C) by single observers 2 months apart (y-axis) are plotted against the average of LA (Fig E5, A), WA (Fig E5, B), and length (Fig E5, C) measurements (x-axis). Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E6 Accuracy of airway morphometry assessed by using PW2 software. Comparison of PW2 and stereomicroscopic measures of LA (A and B), WA (C and D), and length (E and F) by using the paired t test and Bland-Altman plots (difference [y-axis] vs the average [x-axis] measure using the 2 methods is plotted). Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E7 Quantitative CT in healthy subjects and patients with severe asthma. Three-dimensional reconstruction of an airway tree from a healthy subject (A) and a patient with severe asthma (B) using PW2 software, illustrating that in healthy subjects subsegmental airways can be reconstructed to more generations than in asthmatic patients. This is due to increased airway narrowing and closure in asthmatic patients. The insets illustrate the cross-section of RB1 in healthy subjects and patients with severe asthma, showing that the lumen is narrowed in asthmatic patients, with a decrease in total area and an increase in percentage WA but a relatively preserved WA. Coronal section of expiratory CT from a healthy subject (C) and a patient with severe asthma (D) showing the increased low attenuation areas (color coded according to lung lobes) in patients with severe asthma compared with healthy subjects. Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions

Fig E8 Fractal dimension of the segmented airway tree on an inspiratory CT scan in asthmatic patients and healthy subjects (∗P < .05, ANOVA). Journal of Allergy and Clinical Immunology 2014 133, 729-738.e18DOI: (10.1016/j.jaci.2013.09.039) Copyright © 2013 The Authors Terms and Conditions