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Abstract #0665

Tract-Based Cluster Analysis

Pedro Angel Luque Laguna1,2, Francisco de Santiago Requejo1,2, Steven Williams2, Laura H. Goldstein3, Marco Catani1, and Flavio Dell'Acqua1,2,4

1Natbrainlab, Forensic and Neurodevelopmental Science, King's College London, London, United Kingdom, 2Department of Neuroimaging, King's College London, London, United Kingdom, 3Department of Psychology, King's College London, London, United Kingdom, 4The Sackler Institute for Translational Neurodevelopment, King's College London, London, United Kingdom

The use of a-priori anatomical information can effectively improve statistical analysis of neuroimaging data. In this work, we introduce a new method called Tract-Based Cluster Analysis (TBCA) that exploits the rich anatomical information present in a whole-brain tractogram to inform the cluster-level inference analysis of voxel-based images. The method is based on the novel concept of hyper-voxel which incorporates local and global anatomical information derived from tractography data. When applied to real clinical data TBCA demonstrates clear benefits compared to previous cluster-level inference approaches.

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