Pericoronary adipose tissue feature analysis in computed tomography calcium score images in comparison to coronary computed tomography angiography.

Purpose: We investigated the feasibility and advantages of using non-contrast CT calcium score (CTCS) images to assess pericoronary adipose tissue (PCAT) and its association with major adverse cardiovascular events (MACE). PCAT features from coronary computed tomography angiography (CCTA) have been shown to be associated with cardiovascular risk but are potentially confounded by iodine. If PCAT in CTCS images can be similarly analyzed, it would avoid this issue and enable its inclusion in formal risk assessment from readily available, low-cost CTCS images.

Approach: To identify coronaries in CTCS images that have subtle visual evidence of vessels, we registered CTCS with paired CCTA images having coronary labels. We developed an "axial-disk" method giving regions for analyzing PCAT features in three main coronary arteries. We analyzed hand-crafted and radiomic features using univariate and multivariate logistic regression prediction of MACE and compared results against those from CCTA.

Results: Registration accuracy was sufficient to enable the identification of PCAT regions in CTCS images. Motion or beam hardening artifacts were often prevalent in "high-contrast" CCTA but not CTCS. Mean HU and volume were increased in both CTCS and CCTA for the MACE group. There were significant positive correlations between some CTCS and CCTA features, suggesting that similar characteristics were obtained. Using hand-crafted/radiomics from CTCS and CCTA, AUCs were 0.83/0.79 and 0.83/0.77, respectively, whereas Agatston gave AUC = 0.73.

Conclusions: Preliminarily, PCAT features can be assessed from three main coronary arteries in non-contrast CTCS images with performance characteristics that are at the very least comparable to CCTA.