OP3 Improved cardiac risk stratification in individuals with high risk plaque features using the perivascular fat attenuation index on CCTA

Introduction High-risk plaque (HRP) features on coronary computed tomography angiography (CCTA) are indicators of increased cardiac risk. Coronary inflammation induces spatial changes in perivascular adipose tissue (PVAT) composition, which can be quantified with the perivascular Fat Attenuation Index (FAI). We hypothesized that perivascular FAI mapping can further stratify the cardiac risk associated with HRP on CCTA. Methods Individuals from the CRISP-CT (Cardiovascular RISk Prediction using Computed Tomography) study were included (n=3,912, mean age 55.7±13.7 years, 41.1% females). Perivascular FAI mapping was performed around the proximal right coronary artery and was calculated based on the weighted average attenuation of PVAT using the CaRi-HEART algorithm, as previously described. HRP features were defined as the presence of either positive remodelling, low-attenuation plaque, spotty calcification or napkin-ring sign. The association with future incidence of major adverse cardiac events (cardiac mortality or non-fatal myocardial infarction) was assessed using Cox regression models (adjusted for age, sex, epicardial fat volume and coronary artery disease [≥50% stenosis]). Results The prevalence of HRP and high FAI (≥-70.1 Hounsfield Units, as previously validated) was 23.6% (n=923) and 24.3% (n=952), respectively. Over a median follow-up of 5.6 years (25th-75th percentile: 4.0–7.0 years) 91 MACE were recorded. Patients with both HRP features and high FAI (FAI+/HRP+) had a 6.3-fold higher adjusted risk of MACE compared to those with neither of these risk features (HRP-/FAI-). Furthermore, patients without HRP features but with high FAI (HRP-/FAI+) had a 4.9-fold higher adjusted risk of MACE compared to the reference (HRP-/FAI-) group. Conclusion FAI is a stronger predictor of cardiac mortality than high-risk plaques, and there is additive predictive value between plaque morphology and coronary inflammatory burden. There is need for tools to provide comprehensive risk assessment based on CCTA, by extracting, weighting and interpreting all available information from these scans.