Literature DB >> 29753105

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.

Omer F Gulban1, Federico De Martino1, An T Vu2, Essa Yacoub3, Kamil Uğurbil3, Christophe Lenglet4.   

Abstract

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  7 T; Cortex; Depth dependent analysis; Diffusion MRI; Gyral bias; High resolution

Mesh:

Year:  2018        PMID: 29753105      PMCID: PMC6118131          DOI: 10.1016/j.neuroimage.2018.05.010

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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