1. Artificial intelligence–based rapid brain volumetry substantially improves differential diagnosis in dementia
- Author
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Jan Rudolph, Johannes Rueckel, Jörg Döpfert, Wen Xin Ling, Jens Opalka, Christian Brem, Nina Hesse, Maria Ingenerf, Vanessa Koliogiannis, Olga Solyanik, Boj F. Hoppe, Hanna Zimmermann, Wilhelm Flatz, Robert Forbrig, Maximilian Patzig, Boris‐Stephan Rauchmann, Robert Perneczky, Oliver Peters, Josef Priller, Anja Schneider, Klaus Fliessbach, Andreas Hermann, Jens Wiltfang, Frank Jessen, Emrah Düzel, Katharina Buerger, Stefan Teipel, Christoph Laske, Matthis Synofzik, Annika Spottke, Michael Ewers, Peter Dechent, John‐Dylan Haynes, Johannes Levin, Thomas Liebig, Jens Ricke, Michael Ingrisch, and Sophia Stoecklein
- Subjects
Alzheimer's disease ,artificial intelligence ,brain volumetry ,clinical cohorts ,frontotemporal dementia ,Neurology. Diseases of the nervous system ,RC346-429 ,Geriatrics ,RC952-954.6 - Abstract
Abstract Introduction This study evaluates the clinical value of a deep learning–based artificial intelligence (AI) system that performs rapid brain volumetry with automatic lobe segmentation and age‐ and sex‐adjusted percentile comparisons. Methods Fifty‐five patients—17 with Alzheimer's disease (AD), 18 with frontotemporal dementia (FTD), and 20 healthy controls—underwent cranial magnetic resonance imaging scans. Two board‐certified neuroradiologists (BCNR), two board‐certified radiologists (BCR), and three radiology residents (RR) assessed the scans twice: first without AI support and then with AI assistance. Results AI significantly improved diagnostic accuracy for AD (area under the curve −AI: 0.800, +AI: 0.926, p
- Published
- 2024
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