Meeting Banner
Abstract #0468

Synthesis of CSF fraction map using deep neural networks and exploration of its potential application in assessing glymphatic dysfunction

Gawon Lee1 and Se-Hong Oh1,2
1Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Korea, Republic of, 2Diagnostic Radiology, Diagnostic Institute, The Cleveland Clinic, Cleveland, OH, United States

Synopsis

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.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords