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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-10-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922005407 |
| _version_ | 1811216377110855680 |
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| author | Dmitri Shastin Sila Genc Greg D. Parker Kristin Koller Chantal M.W. Tax John Evans Khalid Hamandi William P. Gray Derek K. Jones Maxime Chamberland |
| author_facet | Dmitri Shastin Sila Genc Greg D. Parker Kristin Koller Chantal M.W. Tax John Evans Khalid Hamandi William P. Gray Derek K. Jones Maxime Chamberland |
| author_sort | Dmitri Shastin |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-12T06:38:02Z |
| format | Article |
| id | doaj.art-671cc8bec68a472797b01733af150a9c |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-04-12T06:38:02Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-671cc8bec68a472797b01733af150a9c2022-12-22T03:43:48ZengElsevierNeuroImage1095-95722022-10-01260119423Surface-based tracking for short association fibre tractographyDmitri Shastin0Sila Genc1Greg D. Parker2Kristin Koller3Chantal M.W. Tax4John Evans5Khalid Hamandi6William P. Gray7Derek K. Jones8Maxime Chamberland9Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom; Corresponding author at: Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff, CF24 4HQ, United Kingdom.Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Image Sciences Institute, University Medical Center Utrecht, Utrecht, NetherlandsCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom; Department of Neurology, University Hospital of Wales, Cardiff, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United KingdomCardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the NetherlandsIt 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.http://www.sciencedirect.com/science/article/pii/S1053811922005407Short association fiberslU-fibersSuperficial white matterTractographySurface |
| spellingShingle | Dmitri Shastin Sila Genc Greg D. Parker Kristin Koller Chantal M.W. Tax John Evans Khalid Hamandi William P. Gray Derek K. Jones Maxime Chamberland Surface-based tracking for short association fibre tractography NeuroImage Short association fibersl U-fibers Superficial white matter Tractography Surface |
| 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 | Short association fibersl U-fibers Superficial white matter Tractography Surface |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922005407 |
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