Cardiac arrhythmia and heart failure are major cardiovascular diseases that affect millions of people worldwide. Several metabolic risk factors such as blood pressure and glucose have been implicated in the development and progression of these conditions. Novel imaging phenotypes help achieve accurate risk prediction and effectively identify high-risk patients and risk factors. The study will investigate the relationship between metabolic traits, develop more accurate and personalized approaches for the prevention and treatment of cardiac arrhythmia and heart failure, and identify novel biomarkers and potential drug targets.
Project duration: the project is expected to complete within 3 years. Depending on the progress of the research project, we may extend the scope and/or duration of the project.
Public health impact: Our study will help to understand the relationship between metabolism traits and primary and secondary prevention of cardiac arrythmia and heart failure. Our work will also develop machine learning algorithms based on imaging phenotypes to enable earlier detection and more precise risk stratification.