Coronary Inflammation and Cardiovascular Events in Patients Without Obstructive Coronary Artery Disease

This review evaluates the role of vascular inflammation in patients who develop myocardial infarction with non-obstructive coronary arteries (MINOCA). It also introduces pericoronary adipose tissue (PCAT) and epicardial adipose tissue (EAT) as possible biomarkers for risk prediction in patients with non-obstructive coronary artery disease (CAD). PCAT and EAT contribute to the development and progression of coronary artery inflammation and plaque vulnerability. Coronary computed tomography angiography (CCTA) can detect localized areas of inflammation through changes in the attenuation values of PCAT and EAT. Attenuation values can be further integrated with traditional risk factors using artificial intelligence to generate risk scores that significantly enhance prognostic accuracy in patients with and without obstructive coronary artery disease. Assessing PCAT and EAT inflammation via CCTA and AI-driven risk algorithms enable precise risk prediction of MINOCA and major adverse coronary events (MACE) in patients with non-obstructive CAD.