Preliminary study of myocardial substance metabolism in amateur athletes - Based on 1H-MRS

Motivation: Exploring metabolic markers for detecting cardiac remodeling (CR) in athletes to differentiate adaptive from harmful changes. Goal(s): To use 1H-MRS for identifying metabolites predictive of CR in athletes. Approach: Recruitment of male athletes and controls for CMR examination, analysis of myocardial metabolites using 1H-MRS, and application of machine learning algorithms to construct predictive models for CR. Results: Discovery of a correlation between increased myocardial creatine levels and lipid ratios in athletes with CR, with 1H-MRS proving effective in predicting CR, highlighting MYCL-CH3/W as a particularly predictive metabolite, and positioning the KNN algorithm as a robust predictive tool. Impact: The study advanced sports cardiology by identifying myocardial metabolites as noninvasive markers for differentiating between healthy and adverse cardiac remodeling in athletes, enhancing training strategies and early detection of cardiac risk.