Abstract #4125

Diagnostic Decision Support in Alzheimer’s Disease: Predicting Typical and Mixed Forms from Combined Routine Brain Volumetry and Cognitive Assessment

Alexis Roche^1,2,3, Daniel Damian⁴, Frédéric Pedron¹, Bénédicte Maréchal^1,2,3, Patric Hagmann¹, Philippe Maeder¹, Reto Meuli¹, Tobias Kober^1,2,3, and Jean-François Démonet⁴

¹Department of Radiology, CHUV, Lausanne, Switzerland, ²Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ³LTS5, EPFL, Lausanne, Switzerland, ⁴Leenaards Memory Centre, CHUV, Lausanne, Switzerland

We implemented an automated classifier using T1-weighted magnetic resonance imaging-based brain volumetry and the Montreal Cognitive Assessment test to predict whether patients of a University Memory Clinic with suspected neurocognitive disorders have subjective complaints, or suffer from either typical or mixed forms of Alzheimer's disease. The classifier achieved an accuracy of 80.8% and was found to require both psychometric and brain morphometric data to perform best.

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