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.

通过分析非对比度 CTMS 图像，可以评估周冠状动脉脂肪组织（PCAT）并确定其与重大不良心血管事件（MACE）之间的关联。PCAT 特征可以在 CTCS 图像中定量分析，可用于低成本的心血管风险评估，而无需考虑碘造成的影响。

CT 钙化评分图像中周围冠状动脉脂肪组织特征分析与冠状动脉 CTA 的比较

Pericoronary adipose tissue feature analysis in CT calcium score images  with comparison to coronary CTA

Pericoronary adipose tissue (PCAT) is the deposition of fat in the vicinity
of the coronary arteries. It is an indicator of coronary inflammation and
associated with coronary artery disease. Non-invasive coronary CT angiography
(CCTA) is presently used to obtain measures of the thickness, volume, and
attenuation of fat deposition. However, prior works solely focus on measuring
PCAT using semi-automated approaches at the right coronary artery (RCA) over
the left coronary artery (LCA). In this pilot work, we developed a fully
automated approach for the measurement of PCAT mean attenuation and volume in
the region around both coronary arteries. First, we used a large subset of
patients from the public ImageCAS dataset (n = 735) to train a 3D full
resolution nnUNet to segment LCA and RCA. Then, we automatically measured PCAT
in the surrounding arterial regions. We evaluated our method on a held-out test
set of patients (n = 183) from the same dataset. A mean Dice score of 83% and
PCAT attenuation of -73.81 $\pm$ 12.69 HU was calculated for the RCA, while a
mean Dice score of 81% and PCAT attenuation of -77.51 $\pm$ 7.94 HU was
computed for the LCA. To the best of our knowledge, we are the first to develop
a fully automated method to measure PCAT attenuation and volume at both the RCA
and LCA. Our work underscores how automated PCAT measurement holds promise as a
biomarker for identification of inflammation and cardiac disease.

我们开发了一种全自动的方法，对冠状动脉周围的区域进行心周脂肪均值和体积的测量。我们在公共 ImageCAS 数据集的一个大子集上训练了一个三维全分辨率的 nnUNet 来分割左冠状动脉和右冠状动脉。然后，我们自动测量了冠状动脉周围的心周脂肪。我们在同一数据集的一个独立测试集上评估了我们的方法，得到了 RCA 的平均 Dice 分数为 83％，心周脂肪均值衰减为 - 73.81 ± 12.69 HU，而 LCA 的平均 Dice 分数为 81％，心周脂肪均值衰减为 - 77.51 ± 7.94 HU。我们是第一个开发出全自动测量冠状动脉周围心周脂肪衰减和体积的方法。我们的工作突显了自动化心周脂肪测量在炎症和心脏疾病识别中的潜力。

CT 血管造影中冠周脂肪组织衰减和体积的自动测量

Automated Measurement of Pericoronary Adipose Tissue Attenuation and  Volume in CT Angiography

Features of pericoronary adipose tissue (PCAT) assessed 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. Use dynamic cardiac CT
perfusion (CCTP) to inform contrast determinants of PCAT assessment. From CCTP,
we analyzed HU dynamics of territory-specific PCAT, 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 time of CCTA, were obtained. HU in PCAT increased more than in other
adipose depots. The estimated blood flow in PCAT was ~23% of that in the
contiguous myocardium. Comparing PCAT distal and proximal to a significant
stenosis, we found less enhancement and longer time-to-peak distally.
Two-second offsets [before, after] Pa resulted in [ 4-HU, 3-HU] differences in
PCAT. Due to changes in HU, the apparent PCAT volume reduced ~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. CCTP
elucidates blood flow in PCAT and enables analysis of PCAT features over time.
PCAT assessments (HU, apparent volume, and radiomics) are sensitive to
acquisition timing and the presence of obstructive stenosis, which may confound
the interpretation of PCAT in CCTA images. Data normalization may be in order.

使用心动脉 CT 肿瘤灌注（CCTP）技术研究了心脏病患者中冠心病相关脂肪组织 (PCAT) 的影像特征和血流动力学性质，发现 PCAT 的血流量约为相应心肌的 23％，PCAT 在影像特征、表观体积和放射图像学方面的评估受取像时间和梗阻性狭窄存在的干扰因素的影响敏感。