TY - JOUR AV - public IS - 3 A1 - Seraphim, A A1 - Knott, KD A1 - Augusto, J A1 - Bhuva, AN A1 - Manisty, C A1 - Moon, JC SN - 1522-2586 N2 - 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. KW - machine learning KW - mapping KW - perfusion KW - quantitative KW - tissue characterization JF - Journal of Magnetic Resonance Imaging VL - 51 TI - Quantitative cardiac MRI N1 - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions. ID - discovery10076525 UR - https://discovery.ucl.ac.uk/id/eprint/10076525/ Y1 - 2020/03// ER -