Zou Lei, Xiao Xigang, Jia Yulin, Yin Feng, Zhu Jing, Gao Qi, Xue Ming, Dong Shushan
Radiology Department, the First Affiliated Hospital of Harbin Medical University, Harbin, China.
Clinical Science, Philips Healthcare, Beijing, China.
Quant Imaging Med Surg. 2023 May 1;13(5):2975-2988. doi: 10.21037/qims-22-1019. Epub 2023 Apr 3.
Coronary atherosclerosis is a chronic inflammatory condition. Pericoronary adipose tissue (PCAT) attenuation is closely related to coronary inflammation. This study aimed to investigate the relationship between PCAT attenuation parameters and coronary atherosclerotic heart disease (CAD) using dual-layer spectral detector computed tomography (SDCT).
This cross-sectional study included eligible patients who underwent coronary computed tomography angiography using SDCT at the First Affiliated Hospital of Harbin Medical University between April 2021 and September 2021. Patients were classified as CAD (with coronary artery atherosclerotic plaque) or non-CAD (without coronary artery atherosclerotic plaque). Propensity score matching was used to match the two groups. The fat attenuation index (FAI) was used to quantify PCAT attenuation. The FAI was measured on conventional images (120 kVp) and virtual monoenergetic images (VMI) by semiautomatic software. The slope of the spectral attenuation curve (λ) was calculated. Regression models were established to evaluate the predictive value of PCAT attenuation parameters for CAD.
A total of 45 patients with CAD and 45 patients without CAD were enrolled. The PCAT attenuation parameters in the CAD group were significantly higher than those in the non-CAD group (all P values <0.05). The PCAT attenuation parameters of vessels with or without plaques in the CAD group were higher than those of vessels without plaques in the non-CAD group (all P values <0.05). In the CAD group, the PCAT attenuation parameters of vessels with plaques were slightly higher than those of vessels without plaques (all P values >0.05). In receiver operating characteristic curve analysis, the FAIVMI model achieved an area under the curve (AUC) of 0.8123 for discriminating between patients with and without CAD, which was higher than those of the FAI model (AUC =0.7444) and the λ model (AUC =0.7230). However, the combined model of FAIVMI, FAI, and λ obtained the best performance (AUC =0.8296) of all the models.
PCAT attenuation parameters obtained using dual-layer SDCT can aid in distinguishing patients with and without CAD. By detecting increases in PCAT attenuation parameters, it might be possible to predict the formation of atherosclerotic plaques before they appear.
冠状动脉粥样硬化是一种慢性炎症性疾病。冠状动脉周围脂肪组织（PCAT）衰减与冠状动脉炎症密切相关。本研究旨在使用双层光谱探测器计算机断层扫描（SDCT）研究PCAT衰减参数与冠状动脉粥样硬化性心脏病（CAD）之间的关系。
这项横断面研究纳入了2021年4月至2021年9月期间在哈尔滨医科大学附属第一医院接受SDCT冠状动脉计算机断层扫描血管造影的符合条件的患者。患者被分为CAD组（有冠状动脉粥样硬化斑块）或非CAD组（无冠状动脉粥样硬化斑块）。采用倾向评分匹配法对两组进行匹配。脂肪衰减指数（FAI）用于量化PCAT衰减。通过半自动软件在常规图像（120 kVp）和虚拟单能量图像（VMI）上测量FAI。计算光谱衰减曲线的斜率（λ）。建立回归模型以评估PCAT衰减参数对CAD的预测价值。
共纳入45例CAD患者和45例非CAD患者。CAD组的PCAT衰减参数显著高于非CAD组（所有P值<0.05）。CAD组有或无斑块血管的PCAT衰减参数高于非CAD组无斑块血管的PCAT衰减参数（所有P值<0.05）。在CAD组中，有斑块血管的PCAT衰减参数略高于无斑块血管的PCAT衰减参数（所有P值>0.05）。在受试者工作特征曲线分析中，FAIVMI模型区分CAD患者和非CAD患者的曲线下面积（AUC）为0.8123，高于FAI模型（AUC =0.7444）和λ模型（AUC =0.7230）。然而，FAIVMI、FAI和λ的联合模型在所有模型中表现最佳（AUC =0.8296）。
使用双层SDCT获得的PCAT衰减参数有助于区分CAD患者和非CAD患者。通过检测PCAT衰减参数的增加，有可能在动脉粥样硬化斑块出现之前预测其形成。
