Matthias Jung, MD | Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital; Vineet K. Raghu, PhD; Jakob Weiss, MD
Competition Sponsor: National Academy of Medicine
Awardee Year: 2024
Cardiovascular disease (CVD) is the leading cause of death in the United States. Current cardiovascular guidelines and treatments rely on chronologic age (years lived since birth) to assess risk and guide interventions. However, chronologic age may not fully capture an individual’s health status or risk of disease, as individuals age at different rates. Measures of biological age, which reflect an individual’s overall health status, could provide a more nuanced understanding of aging, and potentially improve CVD risk assessment and personalized decision-making. Existing biological age measures, such as telomere length or epigenetic clocks, predominantly focus on molecular changes in blood and have shown variable concordance as each may capture distinct hallmarks of aging. To date, little is known about how anatomical data derived from radiological imaging can indicate aging. Our team is developing a novel approach called MRI-Age, a biological age clock based on deep learning applied to magnetic resonance imaging (MRI) scans. This method leverages anatomical information derived from MRI to estimate an individual’s biological age. By using MRI-Age, we aim to provide a more comprehensive measure of aging that could enhance CVD risk prediction and tailor treatment strategies more effectively.