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Magnetic resonance fingerprinting

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Ma, Dan, Gulani, Vikas, Seiberlich, Nicole, Liu, Kecheng, Sunshine, Jeffrey L., Duerk, Jeffrey L., Griswold, Mark A.·2013·Nature

DOI 10.1038/nature11971PMC PMC3602925

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Abstract

Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization--which we term 'magnetic resonance fingerprinting' (MRF)--that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.

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Authors: Ma, D., Gulani, V., Seiberlich, N., Liu, K., Sunshine, J. L., Duerk, J. L., & Griswold, M. A.
Affiliations: Case Western Reserve University (US)
University Hospitals of Cleveland (US)
Siemens Healthcare (United States) (US)
Corresponding author: Griswold, Mark A.
ORCID: Ma, Dan
Gulani, Vikas
Seiberlich, Nicole
Liu, Kecheng
Sunshine, Jeffrey L.
Duerk, Jeffrey L.
Griswold, Mark A.
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2013-03
Volume: 495
Issue: 7440
Pages: 187-192
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature11971
PMC: PMC3602925
OpenAlex: W2144288697
Cited by: 1,577
References: 53
Citations by year: 2026: 115 · 2025: 147 · 2024: 148 · 2023: 160 · 2022: 149 · 2021: 175 · 2020: 168 · 2019: 157 · 2018: 108 · 2017: 101 · 2016: 65 · 2015: 42 · 2014: 26 · 2013: 10
FWCI: 36.92
Type: journal article
Language: en
Open access: green
europepmc.org
Licence: www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
OhioLink ETD Center (Ohio Library and Information Network) (submittedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Funders: Agence Nationale de la Recherche (ANR-20-CE19-0030, ANR-11-INBS-0006, ANR-21-CE17-0028)
National Institutes of Health (KL2TR000440)
National Heart, Lung, and Blood Institute (R01HL094557)
National Center for Advancing Translational Sciences
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Physical Sciences › Chemistry › Spectroscopy › Advanced NMR Techniques and Applications
Physical Sciences › Chemistry › Spectroscopy › NMR spectroscopy and applications
Keywords: magnetic resonance fingerprinting, quantitative MRI, pattern recognition, tissue characterization, disease detection, non-invasive measurement, nuclear magnetic resonance
MeSH terms: Algorithms, Diagnostic Tests, Routine, Humans, Motion, Magnetic Resonance Spectroscopy, Pattern Recognition, Automated, Research Design, Sensitivity and Specificity, Reproducibility of Results, Phantoms, Imaging

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