Surface-based tracking for short association fibre tractography

Shastin, Dmitri, Genc, Sila, Parker, Greg D., Koller, Kristin ORCID: https://orcid.org/0000-0001-6676-7106, Tax, Chantal M.W. ORCID: https://orcid.org/0000-0002-7480-8817, Evans, John ORCID: https://orcid.org/0000-0002-6619-4245, Hamandi, Khalid, Gray, William P. ORCID: https://orcid.org/0000-0001-7595-8887, Jones, Derek K. ORCID: https://orcid.org/0000-0003-4409-8049 and Chamberland, Maxime ORCID: https://orcid.org/0000-0001-7064-0984 2022. Surface-based tracking for short association fibre tractography. NeuroImage 260 , 119423. 10.1016/j.neuroimage.2022.119423

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Abstract

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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine Cardiff University Brain Research Imaging Centre (CUBRIC)
Additional Information:	This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher:	Elsevier
ISSN:	1053-8119
Funders:	Wellcome Trust
Date of First Compliant Deposit:	11 July 2022
Date of Acceptance:	29 June 2022
Last Modified:	11 Oct 2023 19:54
URI:	https://orca.cardiff.ac.uk/id/eprint/151239

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