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  Partial volume mapping using magnetic resonance fingerprinting

Deshmane, A., McGivney, D., Ma, D., Jiang, Y., Badve, C., Gulani, V., et al. (2019). Partial volume mapping using magnetic resonance fingerprinting. NMR in Biomedicine, 32(5), 1-17. doi:10.1002/nbm.4082.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-1782-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7A13-F
Genre: Journal Article

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Deshmane, A1, 2, Author              
McGivney, DA, Author
Ma, D, Author
Jiang, Y, Author
Badve, C, Author
Gulani, V, Author
Seiberlich, N, Author
Griswold, MA, Author
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that maps multiple tissue properties through pseudorandom signal excitation and dictionary-based reconstruction. The aim of this study is to estimate and validate partial volumes from MRF signal evolutions (PV-MRF), and to characterize possible sources of error. Partial volume model inversion (pseudoinverse) and dictionary-matching approaches to calculate brain tissue fractions (cerebrospinal fluid, gray matter, white matter) were compared in a numerical phantom and seven healthy subjects scanned at 3 T. Results were validated by comparison with ground truth in simulations and ROI analysis in vivo. Simulations investigated tissue fraction errors arising from noise, undersampling artifacts, and model errors. An expanded partial volume model was investigated in a brain tumor patient. PV-MRF with dictionary matching is robust to noise, and estimated tissue fractions are sensitive to model errors. A 6% error in pure tissue T1 resulted in average absolute tissue fraction error of 4% or less. A partial volume model within these accuracy limits could be semi-automatically constructed in vivo using k-means clustering of MRF-mapped relaxation times. Dictionary-based PV-MRF robustly identifies pure white matter, gray matter and cerebrospinal fluid, and partial volumes in subcortical structures. PV-MRF could also estimate partial volumes of solid tumor and peritumoral edema. We conclude that PV-MRF can attribute subtle changes in relaxation times to altered tissue composition, allowing for quantification of specific tissues which occupy a fraction of a voxel.

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 Dates: 2019-032019-05
 Publication Status: Published in print
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 Identifiers: eDoc: e4082
DOI: 10.1002/nbm.4082
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Title: NMR in Biomedicine
Source Genre: Journal
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Publ. Info: London : Heyden & Son
Pages: - Volume / Issue: 32 (5) Sequence Number: - Start / End Page: 1 - 17 Identifier: ISSN: 0952-3480
CoNE: https://pure.mpg.de/cone/journals/resource/954925574973