Cardiac CT for personalized phenotyping in stable coronary artery disease: toward precision medicine.
Authors
Affiliations (6)
Affiliations (6)
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.
- 1st Department of Cardiology, Medical University of Warsaw, Warsaw 02-091, Poland.
- Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw 04-628, Poland.
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, United States.
- British Heart Foundation, Centre for Cardiovascular Science, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom.
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 10117, Germany.
Abstract
Following technological developments and new landmark trials, the diagnostic work-up of symptomatic chronic coronary artery disease (CAD) has evolved. Clinical guidelines now favor noninvasive anatomical assessments by coronary CT angiography (CCTA) as the first-line modality to evaluate CAD in the majority of patients with chest pain. This shift from ischemia testing to stenosis and plaque characterization has resulted in the development of new imaging biomarkers reflecting a variety of coronary plaque features, many of which have proven to be important clinical risk markers. Consequently, there has been a transition from qualitative to semi-quantitative and fully quantitative plaque acquisitions over the entire coronary tree. With the integration of artificial intelligence, novel software enables rapid quantitative acquisitions of plaque components, making them feasible for use in clinical practice. CCTA has also enabled identification of precursor features associated with plaque development such as peri-coronary artery adipose tissue attenuation and epicardial adipose tissue volume. This review provides an overview of CCTA derived plaque features in CAD and associated imaging biomarkers of risk to highlight their potential applications in precision phenotyping and individualized management decisions. It further outlines anticipated future developments that may enable widespread clinical adoption of these novel imaging biomarkers.