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Nonparametric 5D D-R2 distribution imaging with single-shot EPI at 21.1 T: Initial results for in vivo rat brain.
Rosenberg, Jens T; Grant, Samuel C; Topgaard, Daniel.
Affiliation
  • Rosenberg JT; National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States. Electronic address: rosenb@ufl.edu.
  • Grant SC; National High Magnetic Field Laboratory, Florida State University, Tallahassee FL, United States; Chemical and Biomedical Engineering, FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL, United States. Electronic address: grant@magnet.fsu.edu.
  • Topgaard D; Physical Chemistry, Lund University, Lund, Sweden.. Electronic address: daniel.topgaard@fkem1.lu.se.
J Magn Reson ; 341: 107256, 2022 08.
Article in En | MEDLINE | ID: mdl-35753184
ABSTRACT
In vivo human diffusion MRI is by default performed using single-shot EPI with greater than 50-ms echo times and associated signal loss from transverse relaxation. The individual benefits of the current trends of increasing B0 to boost SNR and employing more advanced signal preparation schemes to improve the specificity for selected microstructural properties eventually may be cancelled by increased relaxation rates at high B0 and echo times with advanced encoding. Here, initial attempts to translate state-of-the-art diffusion-relaxation correlation methods from 3 T to 21.1 T are made to identify hurdles that need to be overcome to fulfill the promises of both high SNR and readily interpretable microstructural information.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Echo-Planar Imaging / Diffusion Magnetic Resonance Imaging Limits: Animals / Humans Language: En Journal: J Magn Reson Journal subject: DIAGNOSTICO POR IMAGEM Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Echo-Planar Imaging / Diffusion Magnetic Resonance Imaging Limits: Animals / Humans Language: En Journal: J Magn Reson Journal subject: DIAGNOSTICO POR IMAGEM Year: 2022 Document type: Article
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