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arXiv 2020年

作者： Dyrba, Martin Hanzig, Moritz Altenstein, Slawek Bader, Sebastian Ballarini, Tommaso Brosseron, Frederic Buerger, Katharina Cantré, Daniel Dechent, Peter Dobisch, Laura Düzel, Emrah Ewers, Michael Fliessbach, Klaus Glanz, Wenzel Haynes, John-Dylan Heneka, Michael T. Janowitz, Daniel Keles, Deniz B. Kilimann, Ingo Laske, Christoph Maier, Franziska Metzger, Coraline D. Munk, Matthias H. Perneczky, Robert Peters, Oliver Preis, Lukas Priller, Josef Rauchmann, Boris Roy, Nina Scheffler, Klaus Schneider, Anja Schott, Björn H. Spottke, Annika Spruth, Eike J. Weber, Marc-André Ertl-Wagner, Birgit Wagner, Michael Wiltfang, Jens Jessen, Frank Teipel, Stefan J. Rostock Germany Institute of Visual and Analytic Computing University of Rostock Rostock Germany Berlin Germany Department of Psychiatry and Psychotherapy Charité - Universitätsmedizin Berlin Campus Charité Mitte Berlin Germany Bonn Germany Department for Neurodegenerative Diseases and Geriatric Psychiatry University Hospital Bonn Bonn Germany Munich Germany University Hospital Ludwig Maximilian University Munich Germany Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology Rostock University Medical Center Rostock Germany MR-Research in Neurosciences Department of Cognitive Neurology Georg-August-University Goettingen Germany Magdeburg Germany Otto-von-Guericke University Magdeburg Germany Bernstein Center for Computational Neuroscience Berlin Germany Department of Psychiatry and Psychotherapy Charité - Universitätsmedizin Berlin Campus Benjamin Franklin Berlin Germany Department of Psychosomatic Medicine Rostock University Medical Center Rostock Germany Tuebingen Germany Section for Dementia Research Hertie Institute for Clinical Brain Research Tuebingen Germany Department of Psychiatry and Psychotherapy University of Tuebingen Tuebingen Germany Department of Psychiatry Medical Faculty University of Cologne Cologne Germany Department of Psychiatry and Psychotherapy Otto-von-Guericke University Magdeburg Germany Systems Neurophysiology Department of Biology Darmstadt University of Technology Darmstadt Germany Department of Psychiatry and Psychotherapy University Hospital Ludwig Maximilian University Munich Germany Ludwig Maximilian University Munich Germany School of Public Health Imperial College London London United Kingdom Department of Psychiatry and Psychotherapy Klinikum rechts der Isar Technical University Munich Munich Germany Department for Biomedical Magnetic Resonance University of Tuebingen Tuebingen Germany Goettingen Germany Department of Psychiatry and Psychotherapy

Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. Methods: We trained a CNN for the detection of AD in N=663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N=1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection. Results: Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC≥0.91) and moderate accuracy for amnestic MCI versus controls (AUC≈0.74). Relevance maps indicated that hippocampal atrophy was considered as the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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