Data Sheet 1_Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging.pdf

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.