Magnetic resonance fingerprinting

• Published in: Nature (London) Vol. 495; no. 7440; pp. 187 - 192
• Main Authors: Ma, Dan, Gulani, Vikas, Seiberlich, Nicole, Liu, Kecheng, Sunshine, Jeffrey L., Duerk, Jeffrey L., Griswold, Mark A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.03.2013; Nature Publishing Group
• Subjects: 631/1647/245/1628; 639/301/930/2735; 639/766/930/2735; Algorithms; Data acquisition; Diagnostic Tests, Routine - methods; Dictionaries; Evolution; Humanities and Social Sciences; Humans; Magnetic resonance; Magnetic Resonance Spectroscopy - methods; Magnetic studies; Motion; multidisciplinary; NMR; Nuclear magnetic resonance; Pattern Recognition, Automated; Phantoms, Imaging; Radio frequency; Reproducibility of Results; Research Design; Science; Sensitivity and Specificity; Spectrum analysis; Studies; United States
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature11971

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. A new approach to magnetic resonance, ‘magnetic resonance fingerprinting', is reported, which combines a data acquisition scheme with a pattern-recognition algorithm that looks for the ‘fingerprints’ of interest within the data. Raising the profile of NMR Although nuclear magnetic resonance is a powerful analytical tool for many scientific and medical disciplines, usually only a fraction of its potential power is harnessed. Most implementations are qualitative, and restricted in the range of properties that are probed. Dan Ma and colleagues introduce a new approach — termed magnetic resonance fingerprinting — aimed at greatly enhancing the amount of quantitative information that can be obtained in one measurement. Their approach combines a data-acquisition scheme that is indiscriminate in the material properties that it probes with pattern-recognition algorithms that look for the 'fingerprints' of interest within the data. Magnetic resonance fingerprinting has the potential to detect and analyse early indicators of disease or complex changes in materials, as well as increasing the sensitivity, specificity and speed of magnetic resonance studies.