Structural parameters are superior to eigenvector centrality in detecting progressive supranuclear palsy with machine learning & multimodal MRI

Structural parameters are superior to eigenvector centrality in detecting progressive supranuclear palsy with machine learning & multimodal MRI

Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized initially by falls and eye movement impairment. This multimodal imaging study aimed at eliciting structural and functional disease-specific brain alterations. T1-weighted and resting-state functional MRI were app...

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Bibliographic Details
Main Authors: Franziska Albrecht, Karsten Mueller, Tommaso Ballarini, Klaus Fassbender, Jens Wiltfang, Markus Otto, Robert Jech, Mattias L. Schroeter, Adrian Danek, Janine Diehl-Schmid, Holger Jahn, Jan Kassubek, Johannes Kornhuber, Bernhard Landwehrmeyer, Martin Lauer, Johannes Prudlo, Anja Schneider, Albert C. Ludolph, Klaus Fliesbach, Sarah Anderl-Straub, Katharina Brüggen, Marie Fischer, Hans Förstl, Anke Hammer, György Homola, Walter Just, Johannes Levin, Nicolai Marroquin, Anke Marschhauser, Danielé Pino, Magdalena Nagl, Timo Oberstein, Lea Hüper, Maryna Polyakova, Hannah Pellkofer, Tanja Richter-Schmidinger, Carola Rossmeier, Marianna Kulko, Elisa Semler, Annika Spottke, Petra Steinacker, Angelika Thöne-Otto, Ingo Uttner, Heike Zech
Format: Article
Language:English
Published: Elsevier 2024-08-01
Series:Heliyon
Subjects:
Progressive supranuclear palsy
Magnetic resonance imaging
Resting-state functional connectivity
Voxel-based morphometry
Eigenvector centrality
Support vector machine
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024109413

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http://www.sciencedirect.com/science/article/pii/S2405844024109413

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