Cardiac CT Perfusion Imaging of Pericoronary Adipose Tissue (PCAT) Highlighting Potential Confounds in CTA Analysis

TL;DR

This study uses cardiac CT perfusion to show that pericoronary adipose tissue (PCAT) features in CT scans can be affected by blood flow and timing, which may lead to misinterpretation of cardiovascular risk.

Contribution

The study introduces dynamic cardiac CT perfusion to investigate PCAT perfusion and its impact on PCAT assessment in coronary CT angiography.

Findings

PCAT Hounsfield units (HU) increased more than other adipose depots and showed a 7 HU swing with a two-second timing offset.

PCAT blood flow was about 23% of contiguous myocardium, and radiomic features changed by over 10% relative to initial scans.

PCAT enhancement and time-to-peak were reduced distal to significant coronary stenoses.

Abstract

Background: Features of pericoronary adipose tissue (PCAT) from coronary computed tomography angiography (CCTA) are associated with inflammation and cardiovascular risk. As PCAT is vascularly connected with coronary vasculature, the presence of iodine is a potential confounding factor on PCAT HU and textures that has not been adequately investigated. We aim to use dynamic cardiac CT perfusion (CCTP) to understand the perfusion of PCAT and determine its effects on PCAT assessment. Methods: From CCTP, we analyzed HU dynamics of territory-specific PCAT, the myocardium, and other adipose depots in patients with coronary artery disease. HU, blood flow, and radiomics were assessed over time. Changes from peak aorta time, Pa, chosen to model the acquisition time of CCTA, were obtained. Results: HU in PCAT increased more than in other adipose depots. Blood flow in PCAT was ~23% of that in the contiguous myocardium. A two-second offset [before, after] Pa resulted in [4 ± 1.1 HU, 3 ± 1.5 HU] differences in PCAT, giving a 7 HU swing. Due to changes in HU, the apparent PCAT volume reduced by ~15% from the first scan (P1) to Pa using a conventional fat window. Comparing radiomic features over time, 78% of features changed >10% relative to P1. Distal and proximal to a significant stenosis, we found less enhancement and longer time-to-peak distally in PCAT. Conclusions: CCTP elucidates blood flow in PCAT and enables the analysis of PCAT features over time. PCAT assessments (HU, apparent volume, and radiomics) are sensitive to acquisition timing and obstructive stenosis, which may confound the interpretation of PCAT in CCTA images. Data normalization may be in order.

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