Beyond plaque and stenosis: Coronary inflammation imaging with the fat attenuation index.
Authors
Affiliations (3)
Affiliations (3)
- Department of Cardiovascular Medicine, Institute of Science Tokyo, Tokyo, Japan. Electronic address: [email protected].
- Department of Cardiovascular Medicine, Institute of Science Tokyo, Tokyo, Japan.
- Department of Cardiovascular Medicine, Tsuchiura Kyodo General Hospital, Ibaraki, Japan.
Abstract
Pericoronary adipose tissue (PCAT) imaging has emerged as a promising noninvasive marker of coronary inflammation and an adjunctive risk-stratification tool beyond conventional coronary computed tomography angiography (CCTA) findings such as luminal stenosis and plaque morphology. The fat attenuation index (FAI), derived from CCTA, quantifies phenotypic changes in pericoronary fat driven by vascular inflammation. The CRISP-CT study demonstrated that elevated FAI around the right coronary artery independently predicted cardiac mortality. The ORFAN study further established that the FAI-Score-an artificial intelligence-adjusted derivative of raw PCAT attenuation-predicts cardiac events even in the absence of obstructive coronary artery disease. Multiple meta-analyses have consistently demonstrated that elevated PCAT attenuation is associated with an increased risk of major adverse cardiovascular events. It should be emphasized, however, that current evidence supports FAI/FAI-Score primarily as a prognostic marker; trial-level evidence that FAI-guided management decisions improve patient outcomes is not yet available. Beyond established prognostic applications, investigational uses include the identification of functionally significant lesions, acute coronary syndrome mechanism characterization, vasospastic angina prediction, myocardial infarction with non-obstructive coronary arteries assessment, treatment-response monitoring, and risk stratification in diabetic populations; these emerging applications require prospective validation. The fat radiomic profile, a machine-learning-derived extension, captures structural remodeling in pericoronary fat that persists beyond the acute inflammatory changes detected by FAI alone. However, substantial technical challenges remain. Reconstruction algorithms and tube voltage introduce measurement variability that can exceed the biological signal, and no major cardiovascular society has issued formal recommendations for routine clinical use. This review provides an overview of the biological rationale, measurement methodology, prognostic evidence, emerging and investigational applications, and current limitations of PCAT-based coronary inflammation imaging.