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Abstract #2857

Optimising Connectivity-based Fixel Enhancement: A method for whole-brain statistical analysis of diffusion MRI

David Raffelt 1 , Robert E Smith 1 , J-Donald Tournier 2,3 , Gerard R Ridgway 4,5 , David Vaughan 1,6 , and Alan Connelly 1,7

1 Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia, 2 Centre for the Developing Brain, King's College London, London, United Kingdom, 3 Department of Biomedical Engineering, King's College London, London, United Kingdom, 4 FMRIB Centre, University of Oxford, Oxford, United Kingdom, 5 UCL Institute of Neurology, University College London, London, United Kingdom, 6 Department of Medicine, University of Melbourne, Melbourne, Australia, 7 The Department of Florey Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia

Voxel-based analysis is being increasingly used to study white matter development, aging and pathology. Connectivity-based Fixel Enhancement (CFE) is a recently developed statistical method that enables whole-brain analysis of fibre-specific diffusion MRI measures within regions containing crossing fibres. While this method does not require an arbitrary test-statistic threshold, it is dependent on other parameters for the enhancement step. We assessed CFE performance by introducing simulated pathology into in vivo data, and explored combinations of enhancement parameters while varying the pathology region, effect size and pre-smoothing spatial extent. Results suggest CFE parameters are relatively insensitive to pathology region and effect size.

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