Evaluating the role of pericoronary adipose tissue on coronary artery disease: insights from CCTA on risk assessment, vascular stenosis, and plaque characteristics

Introduction Pericoronary adipose tissue (PCAT) plays a significant role in the occurrence and progression of coronary artery disease (CAD). This study investigates the relationship between PCAT and CAD, focusing on the occurrence of the disease, the severity of vascular narrowing, and the characteristics of arterial plaques. Methods We analyzed a cohort of 152 individuals with CAD and 55 individuals with non-coronary artery disease (N-CAD). Participants underwent both coronary computed tomography angiography (CCTA) and digital subtraction angiography (DSA). Utilizing United Imaging software for artificial intelligence delineation, we measured the fat attenuation index (FAI) and volume of PCAT in the left anterior descending (LAD), left circumflex (LCX), and right coronary arteries (RCA). Results Our findings demonstrate that while CCTA is effective in diagnosing CAD compared to DSA, its diagnostic power for individual coronary arteries remains limited. Further analysis revealed that the FAI of the RCA and the overall PCAT volume independently influenced CAD (OR: 1.057, 95% CI: 1.002 to 1.116; OR: 0.967, 95% CI: 0.936 to 0.999). FAI showed a significant independent effect on RCA stenosis (OR: 1.041, 95% CI: 1.003 to 1.081), while the fat volume of the LAD had a significant independent effect on LAD stenosis (OR: 0.884, 95% CI: 0.809 to 0.965). A higher FAI and a lower fat volume were significantly correlated with more severe vascular stenosis percentages in all three arteries ( p < 0.05), except for the fat volume and stenosis of the LCX. Moreover, we found the significant differences in the fat volume of the LCX between different plaque types ( H = 8.869, p = 0.012), with calcified plaques consistently exhibiting the lowest fat volume across all three arteries. Finally, the likelihood ratio test confirmed that incorporating the PCAT fat volume parameter of LAD significantly improved the diagnostic ability of CCTA for both CAD ( p = 0.01543) and LAD stenosis ( p = 0.001585). Conclusion The quantification of PCAT has potential application value in the comprehensive assessment of CAD. It is recommended that cardiology and radiology departments consider incorporating PCAT into the assessment criteria for patients suspected of having CAD.