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Myocardial Tissue Characterization with MR Relaxometry in Heart Failure


Biography

Overview
Project Summary Heart failure (HF) has emerged as the greatest current challenge in cardiovascular medicine. Detection of subclinical cardiac dysfunction could give us a unique opportunity to treat patients at an earlier stage of disease and to modify the risk factors to prevent or slow HF development and progression. In HF with dilated non-ischemic cardiomyopathy (NICM), early changes in extracellular matrix volume (ECV) and formation of myocardial fibrosis and inflammation result in impairment of ventricle function and precipitation of arrhythmias. Therefore, early detection of these changes could have significant clinical impact. Cardiovascular magnetic resonance (CMR) is a non-invasive, multifaceted, powerful imaging modality that employs no ionization radiation, has high spatial resolution and provides excellent soft tissue contrast. Myocardial T1 and T2 relaxation times change in the presence of interstitial diffuse fibrosis and inflammation. A major limitation of current CMR technique is use of semi-quantitative and subjective assessment of disease status. Novel advances in CMR allow voxel-wise quantification of relaxation times to characterize myocardial tissue composition, analogous to myocardial regional biopsy, as a unique and powerful tool which is unparalleled by any other imaging modality. We have recently developed novel approaches to accurately measure in-vivo myocardial T1 and T2 times. In this study, we propose to continue development, refinement and multi-center/multi-vendor evaluation of our multi-slice T1 and T2 mapping sequences. Concurrently, in a pilot clinical study, we will assess the predictive value of T1, T2 and ECV in patients with newly recognized dilated NICM for HF progression and adverse cardiac events over a 2-year clinical follow up. We will also assess incremental value of CMR vs. non-CMR markers of HF progression and adverse cardiac events.
R01HL129157
NEZAFAT, REZA

Time
2017-05-15
2021-04-30
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.