Magnetic resonance fingerprinting

Dan Ma, Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L. Sunshine, Jeffrey L. Duerk and Mark A. Griswold ()
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Dan Ma: Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
Vikas Gulani: Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
Nicole Seiberlich: Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
Kecheng Liu: Siemens Healthcare USA, 51 Valley Stream Parkway, Malvern, Pennsylvania 19355, USA
Jeffrey L. Sunshine: Case Western Reserve University and University Hospitals of Cleveland, 11100 Euclid Avenue, Cleveland, Ohio 44106, USA
Jeffrey L. Duerk: Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA
Mark A. Griswold: Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106, USA

Nature, 2013, vol. 495, issue 7440, 187-192

Abstract: 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.

Date: 2013
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Citations: View citations in EconPapers (6)

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DOI: 10.1038/nature11971

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