Literature DB >> 34219281

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

Loreen Ruhm1,2, Johanna Dorst1,2, Nikolai Avdievitch1, Andrew Martin Wright1,2, Anke Henning1,3.   

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.
© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  9.4 T; MRSI; Phosphorus; chemical shift imaging; quantitative metabolic images; ultrahigh field

Year:  2021        PMID: 34219281     DOI: 10.1002/mrm.28891

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  1 in total

1.  Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T.

Authors:  Andreas Korzowski; Nina Weckesser; Vanessa L Franke; Johannes Breitling; Steffen Goerke; Heinz-Peter Schlemmer; Mark E Ladd; Peter Bachert; Daniel Paech
Journal:  Front Neurol       Date:  2021-12-23       Impact factor: 4.003

  1 in total

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