Recent Advances in Computed Tomography Imaging in Chronic Obstructive Pulmonary Disease

Abstract

Lung imaging is increasingly being used to diagnose, quantify, and phenotype chronic obstructive pulmonary disease (COPD). Although spirometry is the gold standard for the diagnosis of COPD and for severity staging, the role of computed tomography (CT) imaging has expanded in both clinical practice and research. COPD is a heterogeneous disease with considerable variability in clinical features, radiographic disease, progression, and outcomes. Recent studies have examined the utility of CT imaging in enhancing diagnostic certainty, improving phenotyping, predicting disease progression and prognostication, selecting patients for intervention, and also in furthering our understanding of the complex pathophysiology of this disease. Multiple CT metrics show promise for use as imaging biomarkers in COPD.

Keywords: computed tomography; emphysema; image registration; imaging; small airways.

Figure 1.

The technique of image registration and two fundamental approaches to extracting clinically relevant information from image registration. Inspiratory and expiratory images are matched voxel-by-voxel. Structural measures can be obtained by performing a voxel-by-voxel anatomic comparison and assessing the corresponding computed tomography (CT) density change from expiration to inspiration, with compensation for lung deformation through image registration. The top right shows a representative axial section with localization of emphysema (red), functional small airways disease (yellow), and normal (green) voxels in a patient with moderate chronic obstructive pulmonary disease (COPD). The bottom right depicts functional changes on the same slice. Here, the amount of lung deformation between inspiration and expiration is used to derive a measure of regional ventilation, termed the Jacobian determinant, a measure of local volume change from full inspiration to end expiration. The Jacobian determinant ranges from 0 to infinity; values greater than 1 indicate local expansion, and values less than 1 indicate local contraction. PRM = parametric response mapping.

Figure 2.

Differences in detection of structural lung disease using lung density measures (top panel) and after image registration with separation of emphysematous voxels and nonemphysematous gas trapping (middle panel). The bottom panel shows local volume change with respiration measured using the Jacobian determinant. Representative computed tomography (CT) scans from an individual without chronic obstructive pulmonary disease (COPD) and two individuals with moderate and severe COPD, respectively, are displayed. The figure demonstrates the differences in the three metrics for the same individuals using different tools for measuring parenchymal lung disease in COPD. PRM = parametric response mapping.

Figure 3.

Image matching and derivation of the Jacobian determinant. CT = computed tomography, D = deformation field; J = Jacobian.