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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