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Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations

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...

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Autores principales: Cottaar, Michiel, Wu, Wenchuan, Tendler, Benjamin C., Nagy, Zoltan, Miller, Karla, Jbabdi, Saad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8581995/
https://www.ncbi.nlm.nih.gov/pubmed/34254349
http://dx.doi.org/10.1002/mrm.28907
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author Cottaar, Michiel
Wu, Wenchuan
Tendler, Benjamin C.
Nagy, Zoltan
Miller, Karla
Jbabdi, Saad
author_facet Cottaar, Michiel
Wu, Wenchuan
Tendler, Benjamin C.
Nagy, Zoltan
Miller, Karla
Jbabdi, Saad
author_sort Cottaar, Michiel
collection PubMed
description 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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spelling pubmed-85819952021-11-18 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 Magn Reson Med Research Articles—Imaging Methodology 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. John Wiley and Sons Inc. 2021-07-13 2021-11 /pmc/articles/PMC8581995/ /pubmed/34254349 http://dx.doi.org/10.1002/mrm.28907 Text en © 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles—Imaging Methodology
Cottaar, Michiel
Wu, Wenchuan
Tendler, Benjamin C.
Nagy, Zoltan
Miller, Karla
Jbabdi, Saad
Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title_full Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title_fullStr Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title_full_unstemmed Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title_short Quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: Theory and simulations
title_sort quantifying myelin in crossing fibers using diffusion‐prepared phase imaging: theory and simulations
topic Research Articles—Imaging Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8581995/
https://www.ncbi.nlm.nih.gov/pubmed/34254349
http://dx.doi.org/10.1002/mrm.28907
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