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Abstract #3391

Characterizing neurodegeneration in progressive supranuclear palsy using VBM and SVM classification

Karsten Mueller1, Robert Jech2,3, Cecilia Bonnet2,3, Jaroslav Tintěra4, Harald E Möller1, Klaus Fassbender5, Jan Kassubek6, Markus Otto6, Evžen Růžička2,3, and Matthias L Schroeter1,7

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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