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Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain

Authors :
Mark D. Grier
Essa Yacoub
Gregor Adriany
Russell L. Lagore
Noam Harel
Ru-Yuan Zhang
Christophe Lenglet
Kâmil Uğurbil
Jan Zimmermann
Sarah R. Heilbronner
Source :
NeuroImage, Vol 255, Iss , Pp 119200- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.

Details

Language :
English
ISSN :
10959572
Volume :
255
Issue :
119200-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.4e5d8d4a81ba4bc9ab08e7c02769541e
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2022.119200