%0 Journal Article
%A Volkmann, Heiko
%A Höglinger, Günter U
%A Grön, Georg
%A Barlescu, Lavinia
%A Müller, Hans-Peter
%A Kassubek, Jan
%T MRI classification of progressive supranuclear palsy, Parkinson disease and controls using deep learning and machine learning algorithms for the identification of regions and tracts of interest as potential biomarkers.
%J Computers in biology and medicine
%V 185
%@ 0010-4825
%C Amsterdam [u.a.]
%I Elsevier Science
%M DZNE-2024-01428
%P 109518
%D 2025
%X Quantitative magnetic resonance imaging (MRI) analysis has shown promise in differentiating neurodegenerative Parkinsonian syndromes and has significantly advanced our understanding of diseases like progressive supranuclear palsy (PSP) in recent years.The aim of this study was to develop, implement and compare MRI analysis algorithms based on artificial intelligence (AI) that can differentiate PSP not only from healthy controls but also from Parkinson disease (PD), by analyzing changes in brain structure and microstructure. Specifically, this study focused on identifying regions of interest (ROIs) and tracts of interest (TOIs) that are crucial for the algorithms to provide clinically relevant performance indices for the distinction between disease variants.MR data comprised diffusion tensor imaging (DTI - tractwise fractional anisotropy statistics (TFAS)) and T1-weighted (T1-w) data (texture analysis of the corpus callosum (CC)). One subject sample with 74 PSP patients and 63 controls was recorded at 3.0T at multiple sites. The other sample came from a single site, consisting of 66 PSP patients, 66 PD patients, and 44 controls, recorded at 1.5T. Four different machine learning algorithms (ML) and a deep learning (DL) neural network approach using Tensor Flow were implemented for the study. The training of the algorithms was performed on 80 
%K Deep learning (Other)
%K Diffusion tensor imaging (DTI) (Other)
%K Machine learning (Other)
%K Magnetic resonance imaging (MRI) (Other)
%K Neuropathology (Other)
%K Progressive supranuclear palsy (Other)
%K tau protein (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:39662313
%R 10.1016/j.compbiomed.2024.109518
%U https://pub.dzne.de/record/273979