State-of-the-Art Imaging Biomarkers in Screening of Atherosclerotic Cardiovascular Disease.

Abstract

Atherosclerotic cardiovascular disease (ASCVD) is the leading global cause of death and evolves over decades through a prolonged subclinical phase, providing a critical opportunity for early detection and prevention. Traditional risk prediction models estimate future cardiovascular risk but may under- or overestimate individual risk, particularly in borderline- and intermediate-risk patients, making them insufficient to guide preventive therapy decisions. Imaging biomarkers complement clinical risk assessment by directly detecting and quantifying subclinical atherosclerosis, enabling more personalized preventive strategies. Coronary artery calcium (CAC) scoring with noncontrast electrocardiographic (ECG)-gated CT remains the most established and guideline-endorsed imaging biomarker for risk reclassification. Coronary CT angiography provides incremental prognostic information through assessment of plaque burden, plaque composition, and high-risk plaque features, while emerging techniques, including quantitative plaque analysis and pericoronary adipose assessment, further characterize plaque biology and inflammatory activity. Beyond coronary imaging, extracoronary biomarkers, including carotid and aortic imaging, epicardial adipose tissue, and arterial stiffness assessments provide complementary information about systemic vascular and cardiometabolic health. In addition, opportunistic biomarkers identified at routine CT and MRI examinations, such as incidental coronary and extracoronary calcifications, breast arterial calcification, hepatic steatosis, visceral adiposity, sarcopenia, osteoporosis, and cerebral imaging markers, expand opportunities for cardiovascular risk assessment without additional imaging or radiation. Although many emerging biomarkers require further standardization and outcome-based validation, integration of imaging biomarkers with clinical risk factors, standardized reporting, and artificial intelligence has the potential to improve ASCVD risk stratification and enable more precise and personalized cardiovascular prevention.