Objective To conduct an analysis of the diagnostic efficacy of coronary computed tomography angiography (CCTA) combined with coronary plaque parameters in the diagnosis of acute coronary syndrome (ACS).

Methods Patients who experienced a documented ACS event (acute myocardial infarction or unstable angina with objective evidence of plaque rupture) from January 2019 to March 2020 and had undergone CCTA from 1 month to 2 years before the ACS event were retrospectively collected.Plaque parameters and pericoronal fat characteristics pericoronal fat attenuation index (FAI) were collected by CCTA examination.Information gain was used to assess the relative importance of each feature, and receiver operating characteristic curves were used to assess the risk value of individual or combined features for predicting ACS.

Results This study comprised 59 patients.The median interval between CCTA and ACS events was 341 days (IQR 166-544 and range 55-702), with acute myocardial infarction occurring in 94.9% of patients.The prevalence and FAI of low-attenuation plaques in culprit lesions were significantly higher than those in non-culprit lesions (P < 0.05 and P < 0.01).FAI showed the highest information gain (0.051, 95%CI: 0.050-0.052), followed by low attenuation plaques (0.028, 95%CI : 0.027-0.029) and plaque volume (0.023, 95%CI: 0.022-0.024).Lesions with higher FAI and the presence of low-attenuation plaque were associated with a higher risk of subsequent ACS culprit lesions (hazard ratio for FAI and low-attenuation plaque, respectively, HR=3.251, 95%CI: 1.310-8.040, P < 0.01 and HR=2.601, 95%CI: 1.356-4.945, P < 0.05).The model with FAI, low-attenuation plaque and plaque volume showed the best performance in predicting ACS risk (AUC=0.737, 95%CI: 0.714-0.767).

Conclusions The combination of plaque parameters and pericoronal fat characteristics can improve noninvasive prediction of ACS risk in patients with non-obstructive coronary artery disease.