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  3D 31P MRSI of the human brain at 9.4 Tesla: Optimization and quantitative analysis of metabolic images

Ruhm, L., Dorst, J., Avdievitch, N., Wright, A., & Henning, A. (2021). 3D 31P MRSI of the human brain at 9.4 Tesla: Optimization and quantitative analysis of metabolic images. Magnetic Resonance in Medicine, 86(5), 2368-2383. doi:10.1002/mrm.28891.

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Ruhm, L1, 2, Author           
Dorst, J1, 2, Author           
Avdievitch, N2, 3, Author           
Wright, AM1, 2, Author           
Henning, A1, 2, Author           
Affiliations:
1Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528692              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              

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 Abstract: Purpose: To present 31 P whole brain MRSI with a high spatial resolution to probe quantitative tissue analysis of 31 P MRSI at an ultrahigh field strength of 9.4 Tesla.

Methods: The study protocol included a 31 P MRSI measurement with an effective resolution of 2.47 mL. For SNR optimization, the nuclear Overhauser enhancement at 9.4 Tesla was investigated. A sensitivity correction was achieved by applying a low rank approximation of the γ-adenosine triphosphate signal. Group analysis and regression on individual volunteers were performed to investigate quantitative concentration differences between different tissue types.

Results: Differences in gray and white matter tissue 31 P concentrations could be investigated for 12 different 31 P resonances. In addition, the first highly resolved quantitative MRSI images measured at B0 = 9.4 Tesla of 31 P detectable metabolites with high SNR could be presented.

Conclusion: With an ultrahigh field strength B0 = 9.4 Tesla, 31 P MRSI moves further toward quantitative metabolic imaging, and subtle differences in concentrations between different tissue types can be detected.

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 Dates: 2021-072021-11
 Publication Status: Published in print
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 Identifiers: DOI: 10.1002/mrm.28891
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Title: Magnetic Resonance in Medicine
Source Genre: Journal
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Publ. Info: New York : Wiley-Liss
Pages: - Volume / Issue: 86 (5) Sequence Number: - Start / End Page: 2368 - 2383 Identifier: ISSN: 0740-3194
CoNE: https://pure.mpg.de/cone/journals/resource/954925538149