Abstract #1973
Subject classification based on functional connectivity and white matter microstructure in a rat model of Alzheimer’s using machine learning
Yujian Diao1,2,3, Catarina Tristão Pereira2,4, Ting Yin2, and Ileana Ozana Jelescu2,5
1Laboratory of Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 2CIBM Center for Biomedical Imaging, Lausanne, Switzerland, 3Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 4Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal, 5Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
Synopsis
Impaired brain glucose consumption is a possible trigger of Alzheimer’s disease (AD). Previous work revealed affected brain structure and function by insulin resistance in terms of functional connectivity and white matter microstructure in a rat model of AD. Here, functional and structural metrics were further used to classify Alzheimer’s from control rats using logistic regression. Our study highlights the MRI-derived biomarkers that best discriminate Alzheimer’s vs control rats early in the course of the disease, with potential translation to human AD.
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