Pericoronary adipose tissue feature analysis in CT calcium score images with comparison to coronary CTA
Yingnan Song, Hao Wu, Juhwan Lee, Justin Kim, Ammar Hoori, Tao Hu,, Vladislav Zimin, Mohamed Makhlouf, Sadeer Al-Kindi, Sanjay Rajagopalan,, Chun-Ho Yun, Chung-Lieh Hung, David L. Wilson

TL;DR
This study demonstrates that pericoronary adipose tissue features can be effectively extracted from non-contrast CT calcium score images, providing comparable risk prediction to coronary CTA without iodine-related confounding.
Contribution
The paper introduces a novel registration and analysis method enabling PCAT feature extraction from CTCS images, expanding risk assessment options.
Findings
PCAT features from CTCS correlate with those from CCTA.
CTCS-based PCAT analysis achieves similar predictive performance as CCTA.
Artifacts in CCTA do not affect CTCS-based PCAT feature extraction.
Abstract
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 CTA (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. 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 a novel axial-disk method giving regions for analyzing PCAT features in three main coronary arteries. We analyzed novel hand-crafted and radiomic features using univariate and multivariate logistic regression…
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Taxonomy
TopicsCardiovascular Disease and Adiposity · Cardiac Imaging and Diagnostics
MethodsLogistic Regression
