Cardiac MRI has become an indispensable imaging modality in the investigation of patients with suspected heart disease. It has emerged as the gold standard test for cardiac function, volumes, and mass and allows noninvasive tissue characterization and the assessment of myocardial perfusion. Quantitative MRI already has a key role in the development and incorporation of machine learning in clinical imaging, potentially offering major improvements in both workflow efficiency and diagnostic accuracy. As the clinical applications of a wide range of quantitative cardiac MRI techniques are being explored and validated, we are expanding our capabilities for earlier detection, monitoring, and risk stratification of disease, potentially guiding personalized management decisions in various cardiac disease models. In this article we review established and emerging quantitative techniques, their clinical applications, highlight novel advances, and appraise their clinical diagnostic potential. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:693-711.
Keywords: machine learning; mapping; perfusion; quantitative; tissue characterization.
© 2019 International Society for Magnetic Resonance in Medicine.