Author + information
- Received April 2, 2018
- Revision received August 29, 2018
- Accepted August 30, 2018
- Published online December 3, 2018.
- aDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
- bDepartment of Cardiovascular Medicine, University Hospitals, Harrington Heart and Vascular Institute, Cleveland Medical Center and Case Western Reserve School of Medicine, Cleveland, Ohio
- cDepartment of Radiology, Case Western Reserve University, Cleveland, Ohio
- ↵∗Address for correspondence:
Dr. Nicole Seiberlich, Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106.
Cardiovascular magnetic resonance is a versatile tool that enables noninvasive characterization of cardiac tissue structure and function. Parametric mapping techniques have allowed unparalleled differentiation of pathophysiological differences in the myocardium such as the delineation of myocardial fibrosis, hemorrhage, and edema. These methods are increasingly used as part of a tool kit to characterize disease states such as cardiomyopathies and coronary artery disease more accurately. Currently conventional mapping techniques require separate acquisitions for T1 and T2 mapping, the values of which may depend on specifics of the magnetic resonance imaging system hardware, pulse sequence implementation, and physiological variables including blood pressure and heart rate. The cardiac magnetic resonance fingerprinting (cMRF) technique has recently been introduced for simultaneous and reproducible measurement of T1 and T2 maps in a single scan. The potential for this technique to provide consistent tissue property values independent of variables including scanner, pulse sequence, and physiology could allow an unbiased framework for the assessment of intrinsic properties of cardiac tissue including structure, perfusion, and parameters such as extracellular volume without the administration of exogenous contrast agents. This review seeks to introduce the basics of the cMRF technique, including pulse sequence design, dictionary generation, and pattern matching. The potential applications of cMRF in assessing diseases such as nonischemic cardiomyopathy are also briefly discussed, and ongoing areas of research are described.
This work was funded by the National Institutes of Health (NIH), National Science Foundation (NSF), and National Center for Research Resources (NCRR) (grants R01HL094557, R01DK098503, CBET 1553441, and C06 RR12463-01). The authors have received financial support from Siemens Healthineers. Dr. Seiberlich has a research agreement with Siemens.
- Received April 2, 2018.
- Revision received August 29, 2018.
- Accepted August 30, 2018.
- 2018 American College of Cardiology Foundation
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