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Abstract #1357

Multi-Metabolite AI Boosted CEST-MRF in an MPTP Mouse Parkinson’s Model

Hagar Shmuely1, Michal Rivlin1, and Or Perlman1,2
1Department of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel, 2Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel

Synopsis

Keywords: CEST / APT / NOE, CEST & MT, MRF, Glutamate, Parkinson's Disease

Motivation: Previous glutamate CEST-weighted studies were unable to separate the confounding effects stemming from different proton pools.

Goal(s): To develop a rapid and quantitative CEST MR Fingerprinting (MRF) pipeline for glutamate, amide, and semisolid MT imaging and validate it using a Parkinson’s disease (PD) mouse model.

Approach: An AI-based CEST-MRF framework was designed and used for imaging glutamate phantoms and MPTP PD mice (n=8).

Results: In-vitro maps were in excellent agreement with ground truth (r=0.95, p<0.0001). The in-vivo maps exhibited significant increases in the glutamate and MT concentrations following MPTP treatment, in agreement with MRS.

Impact: A multi-metabolite CEST-MRF quantitative approach was developed and validated using a mouse PD model. The extensive semisolid MT, amide and glutamate proton-exchange maps are expected to aid in the diagnosis and characterization of Parkinson’s disease.

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Keywords