Disease-Specific Regions Outperform Whole-Brain Approaches in Identifying Progressive Supranuclear Palsy: A Multicentric MRI Study.
To identify progressive supranuclear palsy (PSP), we combined voxel-based morphometry (VBM) and support vector machine (SVM) classification using disease-specific features in multicentric magnetic resonance imaging (MRI) data. Structural brain differences were investigated at four centers between 20 patients with PSP and 20 age-matched healthy controls with T1-weighted MRI at 3T. To pave the way for future application in personalized medicine, we applied SVM classification to identify PSP on an individual level besides group analyses based on VBM. We found a major decline in gray matter density in the brainstem, insula, and striatum, and also in frontomedian regions, which is in line with current literature. Moreover, SVM classification yielded high accuracy rates above 80% for disease identification in imaging data. Focusing analyses on disease-specific regions-of-interest (ROI) led to higher accuracy rates compared to a whole-brain approach. Using a polynomial kernel (instead of a linear kernel) led to an increased sensitivity and a higher specificity of disease detection. Our study supports the application of MRI for individual diagnosis of PSP, if combined with SVM approaches. We demonstrate that SVM classification provides high accuracy rates in multicentric data-a prerequisite for potential application in diagnostic routine.
Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.
Karsten
K
Mueller
Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague Prague, Czechia.
Robert
R
Jech
Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague Prague, Czechia.
Cecilia
C
Bonnet
Institute for Clinical and Experimental Medicine Prague, Czechia.
Jaroslav
J
Tintěra
Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague Prague, Czechia.
Jaromir
J
Hanuška
Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.
Harald E
HE
Möller
Department of Neurology, Saarland University Homburg Homburg, Germany.
Klaus
K
Fassbender
Department of Neurology, University of Ulm Ulm, Germany.
Albert
A
Ludolph
Department of Neurology, University of Ulm Ulm, Germany.
Jan
J
Kassubek
Department of Neurology, University of Ulm Ulm, Germany.
Markus
M
Otto
Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague Prague, Czechia.
Evžen
E
Růžička
Department of Neurology, University of UlmUlm, Germany; Department of Neurology, University of UlmUlm, Germany.
Matthias L
ML
Schroeter
atypical parkinsonism; magnetic resonance imaging; progressive supranuclear palsy; support vector machine classification; voxel-based morphometry