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Surface-based tracking for short association fibre tractography

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in th...

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Autores principales: Shastin, Dmitri, Genc, Sila, Parker, Greg D., Koller, Kristin, Tax, Chantal M.W., Evans, John, Hamandi, Khalid, Gray, William P., Jones, Derek K., Chamberland, Maxime
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009610/
https://www.ncbi.nlm.nih.gov/pubmed/35809886
http://dx.doi.org/10.1016/j.neuroimage.2022.119423
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author Shastin, Dmitri
Genc, Sila
Parker, Greg D.
Koller, Kristin
Tax, Chantal M.W.
Evans, John
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
Chamberland, Maxime
author_facet Shastin, Dmitri
Genc, Sila
Parker, Greg D.
Koller, Kristin
Tax, Chantal M.W.
Evans, John
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
Chamberland, Maxime
author_sort Shastin, Dmitri
collection PubMed
description It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30–40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.
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spelling pubmed-100096102023-03-14 Surface-based tracking for short association fibre tractography Shastin, Dmitri Genc, Sila Parker, Greg D. Koller, Kristin Tax, Chantal M.W. Evans, John Hamandi, Khalid Gray, William P. Jones, Derek K. Chamberland, Maxime Neuroimage Article It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30–40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed. Academic Press 2022-10-15 /pmc/articles/PMC10009610/ /pubmed/35809886 http://dx.doi.org/10.1016/j.neuroimage.2022.119423 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shastin, Dmitri
Genc, Sila
Parker, Greg D.
Koller, Kristin
Tax, Chantal M.W.
Evans, John
Hamandi, Khalid
Gray, William P.
Jones, Derek K.
Chamberland, Maxime
Surface-based tracking for short association fibre tractography
title Surface-based tracking for short association fibre tractography
title_full Surface-based tracking for short association fibre tractography
title_fullStr Surface-based tracking for short association fibre tractography
title_full_unstemmed Surface-based tracking for short association fibre tractography
title_short Surface-based tracking for short association fibre tractography
title_sort surface-based tracking for short association fibre tractography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10009610/
https://www.ncbi.nlm.nih.gov/pubmed/35809886
http://dx.doi.org/10.1016/j.neuroimage.2022.119423
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