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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