Abstract #0841

Tractographic Threshold-Free Cluster Enhancement: Whole-Brain Statistical Analysis of Diffusion MRI Measures in the Presence of Crossing Fibres

David A. Raffelt¹, Robert E. Smith¹, Jacques-Donald Tournier¹,², Gerard R. Ridgway³, Victor L. Villemagne⁴, Christopher C. Rowe⁴, Olivier Salvado⁵, Alan Connelly¹,²

¹Advanced MRI Development, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia; ²Department of Medicine, University of Melbourne, Melbourne, VIC, Australia; ³Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, England, United Kingdom; ⁴Department of Nuclear Medicine, Austin Health, Melbourne, VIC, Australia; ⁵The Australian E-Health Research Centre, CSIRO, Brisbane, QLD, Australia

Recent work has focused on the development of more interpretable quantitative diffusion MRI measures that can be associated with a specific fibre bundle within a voxel containing crossing fibres. Unfortunately, traditional methods for voxel-based analysis of 3D images cannot be applied to analyse these measures, since the definition of the local neighbourhood for smoothing and cluster construction is ambiguous when adjacent voxels may contain different fibre populations. We propose a novel statistical framework for whole-brain voxel-based analysis of bundle-specific diffusion MRI measures, which uses group-average fibre tractography to define the local neighbourhood for clustering and smoothing purposes.