DESCRIPTION (provided by applicant): One in every four deaths in the US is caused by heart disease. Heart disease is the leading cause of death for both men and women and for people of most ethnicities including African Americans, Hispanics and Whites. Besides common preventive measures, detecting early signs of cardiac abnormalities is the key for preventing death caused by heart disease. While we have a range of non-invasive MRI techniques to detect brain abnormalities, techniques for imaging the heart are still underdeveloped and often inadequate. In particular, it has been extremely challenging, if not entirely impossible, to image and track myocardial fibers in vivo. Myocardial fiber forms a unique helical spiral from base to apex of the heart. This structure is a key determinant of the mechanical and electric properties of the myocardium. While diffusion tensor imaging (DTI) has been the only technique that allows the mapping of myocardial fibers non-invasively, it has been applied primarily ex vivo. In vivo DTI of live human hearts has been only performed in a limited few studies. There are currently no clinically accepted techniques for imaging and tracking the myocardial fibers. The objective of this application is to develop and validate a radically new way to image myocardial fibers in vivo based on the technique of susceptibility tensor imaging (STI) and tractography. STI measures the interaction between magnetic fields and myocardium. It utilizes this interaction to quantify tissue property and reconstruct fiber structures. The proposed technique is fast, high resolution, non-invasive and quantitative. If successful, STI will allow the routine examination of the microstructure and connectivity of myocardium with high spatial details. It will fill in a majo gap in our capability to evaluate the myocardial conditions of both healthy and diseased hearts.

PUBLIC HEALTH RELEVANCE: This research will develop an in vivo MRI-based technique for assessing myocardial fibers. This novel technique will address an important technological gap in diagnosing cardiac disease. If our hypotheses are correct, this may save lives by providing earlier diagnosis of abnormal heart conditions.