MRI has become a key component of clinical medicine because it offers exquisite images of soft tissues that can be made sensitive to almost any disease process. However, it is increasingly clear that the current paradigm of MRI has run up against significant limitations that are, in many cases, unavoidable. Current clinical MRI is effective but practically restricted to a qualitative depiction of a limited set of tissue propertis which are visualized through a series of different acquisitions. Further, the reliance on human interpretation limits the total amount of information that can be assessed in any given exam. Here we propose a radically different paradigm that could dramatically increase the efficiency and specificity of MRI by taking a completely different approach to image acquisition, post-processing and visualization. This new class of methods, Magnetic Resonance Fingerprinting (MRF), overcomes traditional limitations by fully embracing the concept of signal incoherence at the core of compressed sensing. Because of the richness of the parameters that can be analyzed, MR- Fingerprinting methods could augment current interpretation to improve diagnosis and monitoring of disease. Indeed, we are proposing an altogether new approach to medical imaging that directly collects anatomically informed quantitative information about disease state and physiology.

Public Health Relevance

Despite exquisite soft tissue visualization and a significant impact on health care in the 40 years since its conceptualization, MRI as it is used today still has significant limitations due to complexity of scanning, inefficient image acquisition, qualitatie rather than quantitative imaging, and complicated image interpretation. We present a new paradigm which we call MR fingerprinting (MRF) in which we overcome these limitations by changing the acquisition, post-processing, and by extension interpretation of MR images. MRF represents an altogether new approach to medical imaging that directly collects anatomically informed quantitative information about disease state and physiology.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project (R01)
Project #
Application #
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Case Western Reserve University
Schools of Medicine
United States
Zip Code
Jiang, Yun; Ma, Dan; Keenan, Kathryn E et al. (2016) Repeatability of magnetic resonance fingerprinting T1 and T2 estimates assessed using the ISMRM/NIST MRI system phantom. Magn Reson Med :
Chen, Yong; Jiang, Yun; Pahwa, Shivani et al. (2016) MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology 279:278-86
Pierre, Eric Y; Ma, Dan; Chen, Yong et al. (2016) Multiscale reconstruction for MR fingerprinting. Magn Reson Med 75:2481-92
Jiang, Yun; Ma, Dan; Jerecic, Renate et al. (2016) MR fingerprinting using the quick echo splitting NMR imaging technique. Magn Reson Med :
Ma, Dan; Pierre, Eric Y; Jiang, Yun et al. (2016) Music-based magnetic resonance fingerprinting to improve patient comfort during MRI examinations. Magn Reson Med 75:2303-14
Cauley, Stephen F; Setsompop, Kawin; Ma, Dan et al. (2015) Fast group matching for MR fingerprinting reconstruction. Magn Reson Med 74:523-8
Badve, Chaitra; Yu, Alice; Rogers, Matthew et al. (2015) Simultaneous T1 and T2 Brain Relaxometry in Asymptomatic Volunteers using Magnetic Resonance Fingerprinting. Tomography 1:136-144
Jiang, Yun; Ma, Dan; Seiberlich, Nicole et al. (2015) MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout. Magn Reson Med 74:1621-31