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Revisiting double diffusion encoding MRS in the mouse brain at 11.7T: Which microstructural features are we sensitive to?
Vincent, Mélissa; Palombo, Marco; Valette, Julien.
Afiliação
  • Vincent M; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), MIRCen, F-92260, Fontenay-aux-Roses, France; Neurodegenerative Diseases Laboratory, UMR9199, CEA, CNRS, Université Paris Sud, Université Paris-Saclay, F-92260, Fontenay-aux-Roses, France.
  • Palombo M; Department of Computer Science and Centre for Medical Image Computing, University College of London, London, WC1E 6BT, United Kingdom.
  • Valette J; Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), MIRCen, F-92260, Fontenay-aux-Roses, France; Neurodegenerative Diseases Laboratory, UMR9199, CEA, CNRS, Université Paris Sud, Université Paris-Saclay, F-92260, Fontenay-aux-Roses, France. Electronic address: julien.valette@cea.fr.
Neuroimage ; 207: 116399, 2020 02 15.
Article em En | MEDLINE | ID: mdl-31778817
ABSTRACT
Brain metabolites, such as N-acetylaspartate or myo-inositol, are constantly probing their local cellular environment under the effect of diffusion. Diffusion-weighted NMR spectroscopy therefore presents unparalleled potential to yield cell-type specific microstructural information. Double diffusion encoding (DDE) consists in applying two diffusion blocks, where gradient's direction in the second block is varied during the course of the experiment. Unlike single diffusion encoding, DDE measurements at long mixing time display some angular modulation of the signal amplitude which reflects microscopic anisotropy (µA), while requiring relatively low gradient strength. This angular dependence has been formerly used to quantify cell fiber diameter using a model of isotropically oriented infinite cylinders. However, how additional features of the cell microstructure (such as cell body diameter, fiber length and branching) may also influence the DDE signal has been little explored. Here, we used a cryoprobe as well as state-of-the-art post-processing to perform DDE acquisitions with high accuracy and precision in the mouse brain at 11.7 â€‹T. We then compared our results to simulated DDE datasets obtained in various 3D cell models in order to pinpoint which features of cell morphology may influence the most the angular dependence of the DDE signal. While the infinite cylinder model poorly fits our experimental data, we show that incorporating branched fiber structure in our model allows more realistic interpretation of the DDE signal. Lastly, data acquired in the short mixing time regime suggest that some sensitivity to cell body diameter might be retrieved, although additional experiments would be required to further support this statement.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Encéfalo / Imagem de Difusão por Ressonância Magnética / Neurônios Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Encéfalo / Imagem de Difusão por Ressonância Magnética / Neurônios Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Ano de publicação: 2020 Tipo de documento: Article