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dc.contributor.authorRaffelt, David A-
dc.contributor.authorTournier, Jacques-Donald-
dc.contributor.authorSmith, Robert E-
dc.contributor.authorVaughan, David N-
dc.contributor.authorJackson, Graeme D-
dc.contributor.authorRidgway, Gerard R-
dc.contributor.authorConnelly, Alan-
dc.identifier.citationNeuroImage 2017; 144(Pt A): 58-73en_US
dc.description.abstractVoxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel ('fixels'), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.en_US
dc.subjectMagnetic Resonance Imagingen_US
dc.titleInvestigating white matter fibre density and morphology using fixel-based analysisen_US
dc.typeJournal Articleen_US
dc.identifier.affiliationFlorey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationDepartment of Biomedical Engineering, Division of Imaging Sciences & Biomedical Engineering, King's College London, London, UKen_US
dc.identifier.affiliationCentre for the Developing Brain, King's College London, London, UKen_US
dc.identifier.affiliationFlorey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationDepartment of Neurology, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationDepartment of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationFMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, UKen_US
dc.identifier.affiliationWellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UKen_US
dc.type.austinJournal Articleen_US
item.openairetypeJournal Article-
item.fulltextNo Fulltext- Florey Institute of Neuroscience and Mental Health-
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