Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging

Frank Li; Xuan Zhang; Alejandro P Comellas; Eric A Hoffman; Michael M Graham; Ching-Long Lin

doi:10.3389/fphys.2025.1555230

Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging

Front Physiol. 2025 Apr 25:16:1555230. doi: 10.3389/fphys.2025.1555230. eCollection 2025.

Authors

Frank Li^{1

2}, Xuan Zhang^{2

3}, Alejandro P Comellas⁴, Eric A Hoffman^{1

5}, Michael M Graham⁵, Ching-Long Lin^{1

2

3

5}

Affiliations

¹ Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States.
² IIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States.
³ Department of Mechanical Engineering, University of Iowa, Iowa City, IA, United States.
⁴ Department of Internal Medicine, University of Iowa, Iowa City, IA, United States.
⁵ Department of Radiology, University of Iowa, Iowa City, IA, United States.

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_Total) 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 (TC_Max) 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.

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

Keywords: COPD; CT; SPECT; small airway disease; ventilation.