A Deep Learning MRI Investigation of Choroid Plexus Hypertrophy and Alzheimer’s Disease Proteinopathy

Motivation: To apply a deep learning MRI architecture investigating the role of ChP hypertrophy on cerebral proteinopathy and clinical progression in Alzheimer's Disease. Goal(s): To compare ChP volumes with cerebral protein retention and relevance to clinical progression. Approach: A fully convolutional neural network was applied to non-contrasted 3D T1-weighted MRI to assess relationships with PET and cerebrospinal fluid assays of amyloid and tau. Results: Application of a deep learning architecture to non-contrasted head MRIs revealed that ChP volume increased in participants with stable versus progressive cognitive impairment, after controlling for age and sex, and is correlated directly with amyloid and tau retention in AD. Impact: Understanding the role of the ChP in neurotoxin clearance from the brains of healthy and AD individuals will provide pathways for future research to target dysfunction with disease progression, motivating clinical intervention for efficient CSF flow and egress.