Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging.

Front Physiol

Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States.

Published: April 2025


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Article Abstract

Introduction: The 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.

Methods: Eight 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.

Results: The SPECT-based ventilation heterogeneity (CV) showed strong correlations with the qCT-based functional small airway disease percentage (fSAD%) and emphysematous tissue percentage (Emph%) in the total lung, based on cross-sectional data. Over the 2-year period, changes in SPECT-based hot spots (TC) exhibited strong negative correlations with changes in fSAD%, Emph%, 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.

Discussion: In conclusion, this study found strong positive cross-sectional correlations between CV 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 TC 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 TC may serve as a more sensitive biomarker than changes in CV for tracking the underlying mechanisms of COPD progression.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061679PMC
http://dx.doi.org/10.3389/fphys.2025.1555230DOI Listing

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