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Quantifying myelin in crossing fibers using diffusion-prepared phase imaging: Theory and simulations.
Cottaar, Michiel; Wu, Wenchuan; Tendler, Benjamin C; Nagy, Zoltan; Miller, Karla; Jbabdi, Saad.
Afiliação
  • Cottaar M; Wellcome Centre for Integrative Neuroimaging-Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
  • Wu W; Wellcome Centre for Integrative Neuroimaging-Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
  • Tendler BC; Wellcome Centre for Integrative Neuroimaging-Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
  • Nagy Z; Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland.
  • Miller K; Wellcome Centre for Integrative Neuroimaging-Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
  • Jbabdi S; Wellcome Centre for Integrative Neuroimaging-Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
Magn Reson Med ; 86(5): 2618-2634, 2021 11.
Article em En | MEDLINE | ID: mdl-34254349
ABSTRACT

PURPOSE:

Myelin has long been the target of neuroimaging research. However, most available techniques can only provide a voxel-averaged estimate of myelin content. In the human brain, white matter fiber pathways connecting different brain areas and carrying different functions often cross each other in the same voxel. A measure that can differentiate the degree of myelination of crossing fibers would provide a more specific marker of myelination. THEORY AND

METHODS:

One MRI signal property that is sensitive to myelin is the phase accumulation. This sensitivity is used by measuring the phase accumulation of the signal remaining after diffusion-weighting, which is called diffusion-prepared phase imaging (DIPPI). Including diffusion-weighting before estimating the phase accumulation has two distinct advantages for estimating the degree of myelination (1) It increases the relative contribution of intra-axonal water, whose phase is related linearly to the thickness of the surrounding myelin (in particular the log g-ratio); and (2) it gives directional information, which can be used to distinguish between crossing fibers. Here the DIPPI sequence is described, an approach is proposed to estimate the log g-ratio, and simulations are used and DIPPI data acquired in an isotropic phantom to quantify other sources of phase accumulation.

RESULTS:

The expected bias is estimated in the log g-ratio for reasonable in vivo acquisition parameters caused by eddy currents (~4%-10%), remaining extra-axonal signal (~15%), and gradients in the bulk off-resonance field (<10% for most of the brain).

CONCLUSION:

This new sequence may provide a g-ratio estimate per fiber population crossing within a voxel.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Substância Branca / Bainha de Mielina Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Substância Branca / Bainha de Mielina Idioma: En Ano de publicação: 2021 Tipo de documento: Article