According to the results of the CRISP-CT study presented at the 2018 ESC Congress, the perivascular fat attenuation index (FAI) — a new CT-based metric monitoring coronary perivascular adipose tissue (PVAT) changes — is a predictor of cardiac mortality.

Although widely used to screen for coronary disease, noninvasive CT angiography does not detect small vulnerable plaques that can cause acute coronary syndromes. The identification of inflamed arteries could facilitate the early detection of atherosclerosis, but a measurement technique is not readily available in the clinic.

Previously, Charalambos Antoniades and colleagues showed that vascular inflammation induces phenotypic changes in PVAT that are detectable using CT and quantifiable with the FAI. The objective of their new study was to evaluate the predictive value of the FAI for adverse outcomes by performing coronary PVAT mapping on CT scans from two independent cohorts of 1,872 patients and 2,040 patients (median follow-up of 72 and 54 months, respectively).

FAI values around the proximal right coronary artery and left anterior descending artery were predictive of all-cause and cardiac mortality. A cut-off FAI ≥–70.1 Hounsfield units was associated with a fivefold to ninefold increase in the risk of cardiac death. Inclusion of the FAI also significantly improved the discriminatory value of traditional risk factors for death.

“We have validated a novel tool to flag high-risk individuals that are currently missed through traditional interpretation of CT scans,” says Antoniades, adding that the FAI will contribute to more personalized strategies for the prevention of cardiovascular disease. Future directions include the integration of artificial intelligence and machine learning into the FAI. “The FAI is not a static biomarker with a fixed definition; it will continue to evolve, allowing further improvements in risk prediction,” concludes Antoniades.