Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging

• Published in: Frontiers in Physiology
• Main Authors: Frank Li, Xuan Zhang, Alejandro P. Comellas, Eric A. Hoffman, Michael M. Graham, Ching-Long Lin
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2025-04-01
• Subjects: CT; SPECT; COPD; ventilation; small airway disease
• Online Access: https://www.frontiersin.org/articles/10.3389/fphys.2025.1555230/full
• ISSN: 1664-042X

IntroductionThe aim of this research is to elucidate chronic obstructive pulmonary disease (COPD) progression by quantifying lung ventilation heterogeneities using single-photon emission computed tomography (SPECT) images and establishing correlations with quantitative computed tomography (qCT) imaging-based metrics. This approach seeks to enhance our understanding of how structural and functional changes influence ventilation heterogeneity in COPD.MethodsEight COPD subjects completed a longitudinal study with three visits, spaced about a year apart. CT scans were performed at each visit and qCT-based variables were derived to measure the structural and functional characteristics of the lungs, while the SPECT-based variables were used to quantify lung ventilation heterogeneity. The correlations between key qCT-based variables and SPECT-based variables were examined.ResultsThe SPECT-based ventilation heterogeneity (CVTotal) showed strong correlations with the qCT-based functional small airway disease percentage (fSAD%Total) and emphysematous tissue percentage (Emph%Total) in the total lung, based on cross-sectional data. Over the 2-year period, changes in SPECT-based hot spots (TCMax) exhibited strong negative correlations with changes in fSAD%Total, Emph%Total, and the average airway diameter in the left upper lobe, as well as a strong positive correlation with alternations in airflow distribution between the upper and lower lobes.DiscussionIn conclusion, this study found strong positive cross-sectional correlations between CVTotal and both fSAD% and Emph%, suggesting that these markers primarily reflect static disease severity at a single time point. In contrast, longitudinal correlations between changes in TCMax and other variables over 2 years may capture the dynamic process of hot spot formation, independent of disease severity. These findings suggest that changes in TCMax may serve as a more sensitive biomarker than changes in CVTotal for tracking the underlying mechanisms of COPD progression.