The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density.
Magn Reson Med
; 79(5): 2738-2744, 2018 05.
Article
em En
| MEDLINE
| ID: mdl-28921634
ABSTRACT
PURPOSE:
To investigate whether diffusion MRI can be used to study cortical segregation based on a contrast related to neurite density, thus providing a complementary tool to myelin-based MRI techniques used for myeloarchitecture.METHODS:
Several myelin-sensitive MRI methods (e.g., based on T1 , T2 , and T2*) have been proposed to parcellate cortical areas based on their myeloarchitecture. Recent improvements in hardware, acquisition, and analysis methods have opened the possibility of achieving a more robust characterization of cortical microstructure using diffusion MRI. High-quality diffusion MRI data from the Human Connectome Project was combined with recent advances in fiber orientation modeling. The orientational average of the fiber orientation distribution was used as a summary parameter, which was displayed as inflated brain surface views.RESULTS:
Diffusion MRI identifies cortical patterns consistent with those previously seen by MRI methods used for studying myeloarchitecture, which have shown patterns of high myelination in the sensorimotor strip, visual cortex, and auditory areas and low myelination in frontal and anterior temporal areas.CONCLUSION:
In vivo human diffusion MRI provides a useful complementary noninvasive approach to myelin-based methods used to study whole-brain cortical parcellation, by exploiting a contrast based on tissue microstructure related to neurite density, rather than myelin itself. Magn Reson Med 792738-2744, 2018. © 2017 International Society for Magnetic Resonance in Medicine.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Processamento de Sinais Assistido por Computador
/
Encéfalo
/
Neuritos
/
Imagem de Difusão por Ressonância Magnética
Limite:
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article