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
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 prediction of MACE and
compared results against those from CCTA. Registration accuracy was sufficient
to enable the identification of PCAT regions in CTCS images. Motion or beam
hardening artifacts were often present in high-contrast CCTA but not CTCS. Mean
HU and volume were increased in both CTCS and CCTA for 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 0.82/0.79 and 0.83/0.77
respectively, while Agatston gave AUC=0.73. 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.