Dr. John Jeffrey Carr is the Cornelius Vanderbilt Professor of Radiology and Radiological Sciences and Professor of Biomedical Informatics and Cardiovascular Medicine. Clinically, he specializes in non-invasive cardiovascular imaging computed tomography (CT) and magnetic resonance imaging (MRI). He is a physician-scientist using non-invasive imaging to not only identify disease but to predict disease before it becomes clinical evident.
Dr. Carr’s research is focused on developing quantitative imaging phenotypes and biomarkers applicable to population-based and personalized medicine. His current research is using advanced computed tomography (CT) techniques to measure coronary blood vessels, coronary plaque and the surrounding pericardial adipose tissue (fat cells) as a means to better understand who is at highest risk for myocardial infarction (heart attacks) and heart failure later in life (NIH-NHLBI 7R01HL098445-05). This project is part of the NHLBI Coronary Artery Risk Development in Young Adults Study (CARDIA). He is also part of NHLBI’s Cardiovascular Research Grid (CVRG) and leads the imaging informatics project. He has expertise in phenotyping for genetic studies, epidemiologic and clinical trials with non-invasive imaging and has extensive research experience with humans, non-human primates and small animals. Important contributions include: establishing coronary artery calcified plaque as a strong predictor of CVD events independent of risk factors: demonstrating that estrogen replacement therapy results in significant reduction of subclinical coronary artery disease in women and that pericardial adipose tissue independently adds to the prediction of CVD events.
He is a founding member and past president of the Society of Cardiovascular Computed Tomography (SCCT). He is a fellow of the American College of Radiology (FACR), American College of Cardiology (FACC), American Heart Association (FAHA) and Society of Cardiovascular Computed Tomography (FSCCT).
At our center, Dr. Carr collaborates in the analysis and interpretation of collected cardiac MRI data for the Memory & Aging Project.