CT-Based Local Distribution Metric Improves Characterization of COPD

Abstract

Parametric response mapping (PRM) of paired CT lung images has been shown to improve the phenotyping of COPD by allowing for the visualization and quantification of non-emphysematous air trapping component, referred to as functional small airways disease (fSAD). Although promising, large variability in the standard method for analyzing PRM^fSAD has been observed. We postulate that representing the 3D PRM^fSAD data as a single scalar quantity (relative volume of PRM^fSAD) oversimplifies the original 3D data, limiting its potential to detect the subtle progression of COPD as well as varying subtypes. In this study, we propose a new approach to analyze PRM. Based on topological techniques, we generate 3D maps of local topological features from 3D PRM^fSAD classification maps. We found that the surface area of fSAD (S^fSAD) was the most robust and significant independent indicator of clinically meaningful measures of COPD. We also confirmed by micro-CT of human lung specimens that structural differences are associated with unique S^fSAD patterns, and demonstrated longitudinal feature alterations occurred with worsening pulmonary function independent of an increase in disease extent. These findings suggest that our technique captures additional COPD characteristics, which may provide important opportunities for improved diagnosis of COPD patients.

Figure 1

A schematic of the workflow is displayed for generating PRM topological maps. (A) CT images are acquired at expiration and inspiration. (B) PRM analysis is performed by first segmenting the lungs from the thoracic cavity. Then the CT images are filtered and spatially aligned to the expiration geometric frame. Individual voxels are then classified as normal (PRM^Norm, green), functional small airways disease (PRM^fSAD, yellow), or emphysema (PRM^Emph, red). (C) Topological feature extraction is performed on each PRM classification binary map to determine topology metrics. Presented are surface area (S) maps for PRM^fSAD (left) and PRM^Emph (right).

Figure 2

Two cases are presented with varying topological PRM features. Both cases have near-identical spirometry readouts and PRM^fSAD relative volumes yet display differing fSAD topological features: dispersed disease (I, left column) and clustered disease (II, right column). A representative slice is shown for each case for the respective (top to bottom) inspiratory CT, expiratory CT, PRM^fSAD map, and Local S^fSAD map (multiplied by Local V^fSAD in order to emphasize regions of substantial disease). PRM^fSAD relative volumes and Local S^fSAD values are displayed for comparison.

Figure 3

Observable trends between PRM and topological PRM features. Scatter plots are presented for (A) %PRM^Emph vs. %PRM^fSAD, (B) %PRM^Emph vs. Local S^Emph and (C) %PRM^fSAD vs. Local S^fSAD. Markers are color-coded for GOLD 1 through 4 (see legend). Comparison between %PRM^Emph and %PRM^fSAD showed trends with increasing disease severity that has been observed in previously published work^, . Local Sⁱ values and respective %PRMⁱ values reveals a strong correlation at low volume fractions showing greater spread with increasing volume fractions.

Figure 4

Confirmation of topological features altered by tissue microenvironment. An explanted lung from a single subject diagnosed with bronchiolitis obliterans syndrome was analyzed by microCT. Presented are the explanted lung section, expiratory CT scan, PRM^fSAD, Local V^fSAD and Local S^fSAD. All CT derived images were spatially aligned to the lung section, allowing identification of core regions (A,B) on PRM and topological maps.

Figure 5

A subject with COPD staged at baseline with GOLD-2 (first column) with 5-year follow-up (second column) revealing a progression to GOLD-3. No substantial change in %PRM^fSAD was detected (first row), however a striking drop in Local S^fSAD was found (second row). This demonstrates a potential pattern of progression, with diffuse disease coalescing into more focal distribution.