Role of CT-quantified Local Histogram Emphysema Patterns in Disease Clustering and COPD Outcomes

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Abstract Rationale: Emphysema, a hallmark of COPD, exhibits substantial heterogeneity in severity and anatomical distribution. The relationship between specific emphysema patterns and clinical outcomes remains incompletely characterized. Objectives: To determine if distinct emphysema patterns, identified through CT-based local histogram analysis and clustering techniques, are associated with specific COPD-related outcomes. Methods: We performed local histogram analysis of lung density from Visit 1 chest CT scans in the COPDGene cohort, quantifying low attenuation areas as paraseptal, centrilobular, or panlobular emphysema. K-medoids clustering was applied to identify distinct emphysema pattern groups. Cross-sectional and longitudinal associations with COPD-related outcomes were assessed using univariable and multivariable analyses. Clinical and imaging differences between MM and MZ smokers were also analysed. Results: In 9,167 non-Hispanic White and African American smokers, four distinct clusters emerged, characterized by varying distributions of paraseptal, panlobular, and centrilobular emphysema (P-values<0.001). These clusters demonstrated significant associations with smoking status, dyspnea scores, frequency of respiratory exacerbations, 5-year lung function decline and emphysema progression, and self-reported cardiometabolic comorbidities. MZ smokers exhibited greater emphysema per pack-year of smoking compared to MM smokers and were predominantly represented in the severe emphysema cluster. All associations remained significant after adjustment for potential confounders. Conclusion: CT-based emphysema patterns identified through local histogram analysis and clustering are associated with distinct clinical outcomes. The findings also underscore the heightened susceptibility of MZ smokers to severe emphysema patterns. Ongoing multi-omics and validation studies may reveal the molecular mechanisms of emphysema and foster personalized treatment approaches.

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