Key result
Dynamic cardiac CT perfusion showed that PCAT assessments are sensitive to acquisition timing, with a 2-second offset causing a 7 HU swing and apparent volume reducing by ~15%.
Why the study?
The confounding effect of iodine on pericoronary adipose tissue HU and textures during CCTA had not been adequately investigated.
Does dynamic cardiac CT perfusion reveal confounding effects of iodine on pericoronary adipose tissue assessment in patients with coronary artery disease?
Observational
Does dynamic cardiac CT perfusion reveal confounding effects of iodine on pericoronary adipose tissue assessment in patients with coronary artery disease?
PCAT assessments derived from CCTA are sensitive to acquisition timing and obstructive stenosis due to iodine perfusion, highlighting the need for data normalization.
PCAT metrics on CCTA may vary with iodine timing; leaves open need for standardized protocols in future studies.
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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Wu et al. (2025) conducted an observational in Coronary artery disease. Dynamic cardiac CT perfusion (CCTP) was evaluated on HU dynamics, blood flow, and radiomics of territory-specific PCAT. Dynamic cardiac CT perfusion showed that PCAT assessments are sensitive to acquisition timing, with a 2-second offset causing a 7 HU swing and apparent volume reducing by ~15%.
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