Abstract #3391

Characterizing neurodegeneration in progressive supranuclear palsy using VBM and SVM classification

Karsten Mueller¹, Robert Jech^2,3, Cecilia Bonnet^2,3, Jaroslav Tintěra⁴, Harald E Möller¹, Klaus Fassbender⁵, Jan Kassubek⁶, Markus Otto⁶, Evžen Růžička^2,3, and Matthias L Schroeter^1,7

¹Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ²Department of Neurology and Center of Clinical Neuroscience, Charles University in Prague, Prague, Czech Republic, ³1st Faculty of Medicine and General University Hospital in Prague, Prague, Czech Republic, ⁴Institute for Clinical and Experimental Medicine, Prague, Czech Republic, ⁵Clinic and Polyclinic for Neurology, Saarland University Homburg, Homburg, Germany, ⁶Clinic and Polyclinic for Neurology, University of Ulm, Ulm, Germany, ⁷Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany

Structural brain differences were investigated between patients with progressive supranuclear palsy (PSP) and healthy controls with T1-weighted images (MP-RAGE) acquired at four centers with different 3T scanners (Siemens). Using voxel-based morphometry, we found a major decline in gray matter density in brainstem, insula, striatum, and frontomedian regions that is in line with the current literature. Support-vector-machine classification provided a high sensitivity of disease detection when using relevant brain regions in feature selection.

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