We introduce ChEST, a novel model that can estimate both chemical exchange and magnetic susceptibility tensor effects from resonance frequency shift. For reconstruction, an iterative algorithm is designed to solve the inverse problem of the new model. When tested using numerical simulation datasets, our method successfully generated mean magnetic susceptibility, magnetic susceptibility anisotropy, principal eigenvector, and chemical exchange maps in high accuracy as compared to conventional methods. Application to in-vivo human brain was conducted, revealing promising outcomes.
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