Non-invasive detection of coronary inflammation using computed tomography in the multi-ethnic study of atherosclerosis - in the current healthcare environment, improving yield from performed tests…

The National Heart Lung and Blood Institute awarded the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center $852,991 on August 15, 2026, under the Cardiovascular Diseases Research program (CFDA 93.837) to conduct a longitudinal study of coronary inflammation detection using computed tomography.

The recipient will measure epicardial fat density and peri-coronary fat attenuation in 17,138 non-contrast cardiac CT scans drawn from the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, comprising 6,814 participants in the baseline study and scans from four subsequent exams (approximately 2-year intervals). The study examines whether fat beds around the heart and coronaries serve as biomarkers for atherosclerotic cardiovascular disease risk independent of coronary artery calcium scores, and whether non-contrast CT scans can function as a dual source for both coronary calcification and inflammation or visceral fat measurement. The work leverages over 20 years of validated follow-up data and repeat imaging across a multi-ethnic, comprehensively phenotyped population. The goal is to develop risk-stratification strategies targeting inflammation to reduce cardiovascular disease development and better personalize preventive treatment.

Performance takes place in Torrance, California. The award runs through May 31, 2030.

Non-invasive detection of coronary inflammation using computed tomography in the multi-ethnic study of atherosclerosis - in the current healthcare environment, improving yield from performed tests to obtain incremental information will result in reducing costs by better risk stratifying patients for atherosclerotic cardiovascular disease (ASCVD) risk is a laudable goal. The interplay between epicardial FAT density and pericoronary FAT attenuation and ASCVD events has not been previously studied longitudinally in a primary prevention or population-based cohort. Understanding relationships between these FAT beds and early CVD may permit development of strategies targeting inflammation to reduce cardiometabolic and CVD development. This study poses to leverage the multi-ethnic study of atherosclerosis (MESA) as a rigorously compiled and highly validated dataset using a comprehensively phenotyped, multi-ethnic cohort. We will utilize the considerable resources already invested in the collection of almost 20,000 well performed CT scans to determine prevalence, risk factor associations, and prognostic value using over 20 years of careful adjudicated ASCVD follow up and repeat imaging. Specifically, we will measure epicardial FAT density and peri-coronary FAT attenuation in 17,138 non-contrast cardiac CT scans: 6,814 participants in the baseline study, along with CAC scans from exam 2 (N=2908), exam 3 (N=2764), exam 4 (N=1388) and exam 5 (N=3264). Each exam was approximately 2 years after the prior exam. The scientific premise is that these FAT beds (both around the heart - epicardial, and around the coronaries - peri-coronary) may portend risk for CVD independent of CAC, and that these non-contrast CT scans can serve as a viable source of both CAC and measures of inflammation/visceral FAT measurement. The hope is that this may serve as a way to further personalize medicine to deliver appropriate preventative treatment, emphasizing therapeutic intervention for those who are at higher predicted risk. These aspects are highly innovative, as is the emphasis on evaluating FAT volume and density as a risk enhancing, effect modifier for asymptomatic individuals is unique to our knowledge. With achievement of the proposed study aims, a valuable epidemiological database will be developed, and the opportunity to utilize existing CAC scans for routine visceral FAT volume and density and pericoronary FAT CVD risk stratification will move closer to reality. There are already moves to automate this process, so if this study is successful, can lead to more scalable and automated detection on the millions of heart scans obtained each year, as well as the tens of millions of annual thoracic CT scans. We feel the proposal is highly significant with considerable potential to exert a direct, positive impact on CVD prevention and provide mechanistic insights and targets to the role of inflammation and CVD events.