Imaging laminar structures in the gray matter with diffusion MRI.
Neuroimage
; 197: 677-688, 2019 08 15.
Article
em En
| MEDLINE
| ID: mdl-29309898
The cortical layers define the architecture of the gray matter and its neuroanatomical regions and are essential for brain function. Abnormalities in cortical layer development, growth patterns, organization, or size can affect brain physiology and cognition. Unfortunately, while large population studies are underway that will greatly increase our knowledge about these processes, current non-invasive techniques for characterizing the cortical layers remain inadequate. For decades, high-resolution T1 and T2 Weighted Magnetic Resonance Imaging (MRI) have been the method-of-choice for gray matter and layer characterization. In the past few years, however, diffusion MRI has shown increasing promise for its unique insights into the fine structure of the cortex. Several different methods, including surface analysis, connectivity exploration, and sub-voxel component modeling, are now capable of exploring the diffusion characteristics of the cortex. In this review, we will discuss current advances in the application of diffusion imaging for cortical characterization and its unique features, with a particular emphasis on its spatial resolution, arguably its greatest limitation. In addition, we will explore the relationship between the diffusion MRI signal and the cellular components of the cortex, as visualized by histology. While the obstacles facing the widespread application of cortical diffusion imaging remain daunting, the information it can reveal may prove invaluable. Within the next few years, we predict a surge in the application of this technique and a concomitant expansion of our knowledge of cortical layers.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Córtex Cerebral
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Imagem de Difusão por Ressonância Magnética
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Neuroimagem
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Substância Cinzenta
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article