ESC Congress 2026 Abstract · Oct 26, 2026
The role of pericoronary adipose tissue inflammation in atherosclerotic plaque progression and vulnerability: insights from three different CCT-based studies
By Matyas B, Benedek T, Rat N et al.
Background: Inflammation of pericoronary adipose tissue (PCAT) is a critical driver of atherosclerotic plaque progression and destabilization. Although cardiac computed tomography (CCT) provides detailed anatomical evaluation of coronary artery disease, traditional CCT-derived markers, including stenosis severity and coronary artery calcium score (CACs), fail to fully capture plaque biological activity. Purpose: The aim of these studies was to investigate the clinical significance of PCAT inflammation using CCT-based artificial intelligence (AI)–supported radiomic analysis and quantitative assessment of the fat attenuation index (FAI) across different pathological and therapeutic settings. Methods: A total of 668 patients presenting with chest pain were enrolled. All underwent CCT for evaluation of CACs, plaque morphology, and PCAT-derived FAI, with quantitative analysis performed on more than 2,000 coronary segments. Three substudies were conducted: post–COVID-19 inflammation (n=255), CACs-based vulnerability analysis (n=336), and longitudinal assessment of intensive statin therapy (n=77). Results: Elevated FAI values were consistently associated with high-risk plaque (HRP) morphology and adverse coronary phenotypes, supporting FAI as a marker of biologically active atherosclerosis. Post–COVID-19 patients showed significantly higher FAI-Score centiles across all major coronary territories compared with controls (overall p<0.05), indicating persistent inflammation despite non-obstructive disease. The RCA exhibited greater inflammatory burden than the LCA (p<0.01). In the CACs substudy, HRP features were present even in patients with CACs=0 (10.87%), and nearly 9% were classified as high risk by AI-based profiling. Although CACs moderately correlated with disease burden and stenosis severity (p<0.0001), its association with inflammation was weak (r²=0.08), highlighting partial dissociation between calcification and inflammatory activity. Lipid-rich vulnerable plaques with elevated FAI were identified in symptomatic CACs=0 patients, including cases requiring revascularization. In the longitudinal statin cohort, intensive therapy significantly reduced FAI across all vessels (p<0.005) and was accompanied by favorable plaque remodeling, with increased calcified/fibrotic components and reduced lipid-rich volume (p<0.05). FAI correlated positively with non-calcified and lipid-rich plaque volumes (p<0.001). Conclusions: AI-enhanced quantification of PCAT inflammation using FAI independently identifies biologically active, high-risk coronary plaques across diverse clinical settings. The detection of vulnerable plaques in CACs=0 patients, persistent post–COVID-19 inflammation, and the measurable anti-inflammatory effects of statin therapy collectively underscore the limitations of purely anatomical assessment and support a transition toward inflammation-guided cardiovascular risk stratification and personalized preventive cardiology.Study design and patient workflow