Abstract #1973

Subject classification based on functional connectivity and white matter microstructure in a rat model of Alzheimer’s using machine learning

Yujian Diao^1,2,3, Catarina Tristão Pereira^2,4, Ting Yin², and Ileana Ozana Jelescu^2,5

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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