%0 Journal Article
%A Huppertz, Hans-Jürgen
%A Möller, Leona
%A Südmeyer, Martin
%A Hilker, Rüdiger
%A Hattingen, Elke
%A Egger, Karl
%A Amtage, Florian
%A Respondek, Gesine
%A Stamelou, Maria
%A Schnitzler, Alfons
%A Pinkhardt, Elmar H
%A Oertel, Wolfgang H
%A Knake, Susanne
%A Kassubek, Jan
%A Höglinger, Günter U
%T Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification.
%J Movement disorders
%V 31
%N 10
%@ 0885-3185
%C New York, NY
%I Wiley
%M DZNE-2020-05167
%P 1506-1517
%D 2016
%X Clinical differentiation of parkinsonian syndromes is still challenging.A fully automated method for quantitative MRI analysis using atlas-based volumetry combined with support vector machine classification was evaluated for differentiation of parkinsonian syndromes in a multicenter study.Atlas-based volumetry was performed on MRI data of healthy controls (n = 73) and patients with PD (204), PSP with Richardson's syndrome phenotype (106), MSA of the cerebellar type (21), and MSA of the Parkinsonian type (60), acquired on different scanners. Volumetric results were used as input for support vector machine classification of single subjects with leave-one-out cross-validation.The largest atrophy compared to controls was found for PSP with Richardson's syndrome phenotype patients in midbrain (-15
%K Brain: diagnostic imaging
%K Cerebellar Diseases: diagnostic imaging
%K Humans
%K Magnetic Resonance Imaging: methods
%K Multiple System Atrophy: diagnostic imaging
%K Parkinsonian Disorders: classification
%K Parkinsonian Disorders: diagnostic imaging
%K Support Vector Machine
%K Supranuclear Palsy, Progressive: diagnostic imaging
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:27452874
%R 10.1002/mds.26715
%U https://pub.dzne.de/record/138845