Keywords: Neurofluids, Neurofluids, Glymphatic system, CSF
Motivation: Methods to assess the activity of the glymphatic system are required to illustrate an association between glymphatic dysfunction and neurodegenerative diseases.
Goal(s): Our aim is to develop a deep neural network-based method to assess glymphatic activity in the human brain.
Approach: We trained a deep neural network to generate T2map and CSF fraction map, which is a quantitative CSF measurement. We then compared the predicted CSFF across 60 OASIS-3 subjects, which include both healthy controls and patients with Alzheimer's disease (AD).
Results: Significant differences in CSFF were observed in the frontal, temporal, and posterior cingulate cortex and precuneus.
Impact: Our method reduces the requirements to acquire additional multi-echo spin-echo T2w images for CSFF analysis. This may enhance the utility of CSFF analysis for assessing the dysfunction in the glymphatic system.
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