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Abstract #4297

Characterizing neurodegeneration in progressive supranuclear palsy using VBM and SVM classification

Karsten Mueller 1 , Sandrine Bisenius 1 , Adrian Danek 2 , Janine Diehl-Schmid 3 , Klaus Fassbender 4 , Hans Foerstl 3 , Armin Giese 2 , Holger Jahn 5 , Frank Jessen 6 , Jan Kassubek 7 , Johannes Kornhuber 8 , Bernhard Landwehrmeyer 7 , Martin Lauer 9 , Albert Ludolph 7 , Markus Otto 7 , Johannes Prudlo 10 , Anja Schneider 11 , Katharina Stuke 1 , and Matthias L Schroeter 1

1 Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2 Clinic of Neurology and Center for Neuropathology and Prion Research, Ludwig Maximilian University of Munich, Germany, 3 Clinic and Polyclinic for Psychiatry and Psychotherapy, Technical University of Munich, Germany, 4 Clinic and Polyclinic for Neurology, Saarland University Homburg, Germany, 5 Clinic for Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Germany, 6 Clinic and Polyclinic for Psychiatry and Psychotherapy, University of Bonn, Germany, 7 Clinic and Polyclinic for Neurology, University of Ulm, Germany, 8 Clinic for Psychiatry and Psychotherapy, University of Erlangen, Germany, 9 Clinic and Polyclinic for Psychiatry, Psychosomatic Medicine, and Psychotherapy, University of Wuerzburg, Germany, 10 Clinic and Polyclinic for Neurology, University of Rostock, Germany, 11 Clinic for Psychiatry and Psychotherapy, University of Goettingen, Germany

We investigated structural brain differences between patients with progressive supranuclear palsy (PSP) and healthy controls with T1-weighted images acquired in five different centers of the German consortium for fronto-lobar degeneration (FTLD). Using voxel-based morphometry, we found a major decline in gray matter density in brainstem and thalamus, but also in striatum (putamen and caudate) that is in-line with the current literature. SVM classification provides a high sensitivity of disease detection when using relevant brain regions in feature selection.

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