Abstract #0665

Tract-Based Cluster Analysis

Pedro Angel Luque Laguna^1,2, Francisco de Santiago Requejo^1,2, Steven Williams², Laura H. Goldstein³, Marco Catani¹, and Flavio Dell'Acqua^1,2,4

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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