Pericoronary fat attenuation index and major adverse cardiovascular events: a systematic review and meta-analysis

Background: Perivascular adipose tissue (PVAT) plays a significant role in the pathophysiology of atherosclerosis. Changes in its computed tomography (CT) attenuation reflect the inflammatory status of the vascular wall. The pericoronary fat attenuation index (FAI), derived from coronary computed tomography angiography (CCTA), is a non-invasive imaging biomarker that quantifies the CT attenuation of pericoronary fat to indirectly assess local inflammatory activity. This study aimed to evaluate the predictive value of CCTA-derived FAI for major adverse cardiovascular events (MACEs) through a meta-analysis. Methods: Two investigators systematically searched the PubMed and Web of Science databases from inception until 21 October 2025 for cohort studies assessing the association between FAI and MACE. Study quality was assessed using the Newcastle-Ottawa Scale (NOS), and the quality of evidence was evaluated using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. Adjusted hazard ratios (aHRs) and their 95% confidence intervals (CIs) were pooled using a random-effects model. Meta-analysis and sensitivity analyses were performed to explore sources of heterogeneity and the robustness of the results. Results: low FAI): high FAI was significantly associated with an increased risk of MACE (pooled aHR =5.00; 95% CI: 3.30-7.58; P<0.001), with moderate GRADE evidence quality. (II) Continuous variable [per 1 Hounsfield unit (HU) increase]: each 1 HU increase in FAI was associated with a 24% increase in MACE risk (pooled aHR =1.24; 95% CI: 1.08-1.43; P=0.002), with low GRADE evidence quality. Sensitivity analyses and funnel plots indicated robust pooled results and a low likelihood of publication bias. Conclusions: CCTA-derived FAI is a strong independent predictor of MACE. Incorporating FAI into routine CCTA assessment may improve cardiovascular risk stratification, demonstrating significant potential for clinical translation.