Correlation between pericoronary adipose tissue and coronary artery disease assessed by 512- slice ct spectral at E Hospital

Objective: To investigate the association between pericoronary adipose tissue (PCAT) attenuation and coronary artery disease (CAD) using a 512-slice Spectral CT scanner at E Hospital. Methods: This cross-sectional descriptive study included 117 patients divided into three groups: the non-stenotic group, the non-significant stenosis group, and the severe stenosis group, with 39 patients in each group. Fat attenuation index (FAI) measurements at 40 keV and 70 keV, λHU, and effective atomic number (Eff-Z) were obtained using dedicated workstation software. In the non-stenotic group, the volume of interest (ROI) was measured 10–50 mm from the origin of the right coronary artery (RCA) and within a 40-mm segment of the left anterior descending artery (LAD) and left circumflex artery (LCx). In patients with stenosis, measurements were performed around the site of the most severe stenosis. The attenuation threshold for adipose tissue was set at −190 to −30 HU. Patients with significant stenosis detected on coronary CT angiography underwent digital subtraction angiography (DSA) for comparison. Results: Significant differences in PCAT attenuation parameters measured using 512-slice CT were observed across the three study groups in the individual coronary artery branches (p < 0.05). In the RCA, FAI at 40 keV (FAI40keV) was an independent predictor of significant stenosis, with a cutoff value of −163.25 HU and a sensitivity of 94.4%. In the LAD and LCx, FAI at 70 keV (FAI70keV) and [λHU value to be specified] were significant parameters for assessing the risk of coronary artery stenosis. Conclusion: PCAT attenuation parameters in the three major coronary arteries vary according to the severity of stenosis. FAI40keV is an independent predictor of significant coronary artery stenosis. The 512-slice Spectral CT technology enables sensitive FAI quantification at low energy levels, providing an important imaging biomarker of underlying vascular inflammation and offering particular value for early cardiovascular risk stratification.