Lobar Emphysema Distribution Is Associated With 5-Year Radiological Disease Progression

Abstract

Background: Emphysema has considerable variability in its regional distribution. Craniocaudal emphysema distribution is an important predictor of the response to lung volume reduction. However, there is little consensus regarding how to define upper lobe-predominant and lower lobe-predominant emphysema subtypes. Consequently, the clinical and genetic associations with these subtypes are poorly characterized.

Methods: We sought to identify subgroups characterized by upper-lobe or lower-lobe emphysema predominance and comparable amounts of total emphysema by analyzing data from 9,210 smokers without alpha-1-antitrypsin deficiency in the Genetic Epidemiology of COPD (COPDGene) cohort. CT densitometric emphysema was measured in each lung lobe. Random forest clustering was applied to lobar emphysema variables after regressing out the effects of total emphysema. Clusters were tested for association with clinical and imaging outcomes at baseline and at 5-year follow-up. Their associations with genetic variants were also compared.

Results: Three clusters were identified: minimal emphysema (n = 1,312), upper lobe-predominant emphysema (n = 905), and lower lobe-predominant emphysema (n = 796). Despite a similar amount of total emphysema, the lower-lobe group had more severe airflow obstruction at baseline and higher rates of metabolic syndrome compared with subjects with upper-lobe predominance. The group with upper-lobe predominance had greater 5-year progression of emphysema, gas trapping, and dyspnea. Differential associations with known COPD genetic risk variants were noted.

Conclusions: Subgroups of smokers defined by upper-lobe or lower-lobe emphysema predominance exhibit different functional and radiological disease progression rates, and the upper-lobe predominant subtype shows evidence of association with known COPD genetic risk variants. These subgroups may be useful in the development of personalized treatments for COPD.

Trial registration: ClinicalTrials.gov NCT00608764.

Keywords: COPD; COPD disease progression; clustering; emphysema distribution; machine learning.

Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Principal components analysis (PCA) plot of the residualized lobar emphysema variables. A, The three identified clusters: the minimal emphysema cluster is in red, the upper lobe-predominant emphysema cluster is in gray, and the lower lobe-predominant emphysema cluster is in blue. B, The unassigned group is in orange. To summarize the relationships between the five residualized lobar emphysema variables, we performed PCA on these data. The top two principal components (PC) explained almost 80% of the variance in these data (50.7% for PC1 and 26.2% for PC2). PC1 represents an “upper lobe emphysema axis,” and PC2 is a “lower-lobe emphysema” axis, based on their positive loadings for each kind of emphysema, respectively.