OA Dhollander 2021 Fixel based Analysis of Diffusion MRI
Journal article
Dhollander, Thijs, Clemente, Adam, Singh, Mervyn, Boonstra, Frederique, Civier, Oren, Duque, Juan Dominguez, Egorova, Natalia, Enticott, Peter, Fuelscher, Ian, Gajamange, Sanuji, Genc, Sila, Gottlieb, Elie, Hyde, Christian, Imms, Phoebe, Kelly, Claire, Kirkovski, Melissa, Kolbe, Scott, Liang, Xiaoyun, Malhotra, Atul, ... Caeyenberghs, Karen. (2021). OA Dhollander 2021 Fixel based Analysis of Diffusion MRI. NeuroImage. 241, p. Article: 118417. https://doi.org/10.1016/j.neuroimage.2021.118417
Authors | Dhollander, Thijs, Clemente, Adam, Singh, Mervyn, Boonstra, Frederique, Civier, Oren, Duque, Juan Dominguez, Egorova, Natalia, Enticott, Peter, Fuelscher, Ian, Gajamange, Sanuji, Genc, Sila, Gottlieb, Elie, Hyde, Christian, Imms, Phoebe, Kelly, Claire, Kirkovski, Melissa, Kolbe, Scott, Liang, Xiaoyun, Malhotra, Atul, Mito, Remika, Poudel, Govinda, Silk, Tim J., Vaughan, David N., Zanin, Julien, Raffelt, David and Caeyenberghs, Karen |
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Abstract | Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple “crossing” fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the “Fixel-Based Analysis” (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities. |
Keywords | Fixel-based analysis; diffusion MRI; Fixel; white matter; microstructure; fibre density; fibre-bundle cross-section; statistical analysis |
Year | 2021 |
Journal | NeuroImage |
Journal citation | 241, p. Article: 118417 |
Publisher | Elsevier B.V. |
ISSN | 1053-8119 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.neuroimage.2021.118417 |
Scopus EID | 2-s2.0-85111751114 |
Open access | Published as ‘gold’ (paid) open access |
Research or scholarly | Research |
Page range | 1-17 |
Funder | Australian Research Council (ARC) |
National Health and Medical Research Council (NHMRC) | |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 21 Jul 2021 |
Publication process dates | |
Accepted | 20 Jul 2021 |
Deposited | 19 Oct 2021 |
ARC Funded Research | This output has been funded, wholly or partially, under the Australian Research Council Act 2001 |
Grant ID | ARC/FT160100077 |
NHMRC/1143816 |
https://acuresearchbank.acu.edu.au/item/8wx1y/oa-dhollander-2021-fixel-based-analysis-of-diffusion-mri
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Publisher's version
OA_Dhollander_2021_Fixel_based_Analysis_of_Diffusion_MRI.pdf | |
License: CC BY 4.0 | |
File access level: Open |
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