Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder.

ABSTRACT: Predicting future brain topography can give insight into neural correlates of aging and neurodegeneration. Due to variability in the aging process, it has been challenging to precisely estimate brain topographical change according to aging. Here, we predict age-related brain metabolic change by generating future brain ¹⁸F-Fluorodeoxyglucose PET. A cross-sectional PET dataset of cognitively normal subjects with different age was used to develop a generative model. The model generated PET images using age information and characteristic individual features. Predicted regional metabolic changes were correlated with the real changes obtained by follow-up data. This model was applied to produce a brain metabolism aging movie by generating PET at different ages. Normal population distr

SUBMITTER: Choi H 

PROVIDER: S-EPMC6052253 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature