Abstract #0875

High-Resolution Dynamic 31P-MRSI Using High-Order Partially Separable Functions

Chao Ma¹, Fan Lam¹, Qiang Ning^1,2, Bryan A. Clifford^1,2, Qiegen Liu¹, Curtis L. Johnson¹, and Zhi-Pei Liang^1,2

¹Beckman Institute, University of Illinois Urbana-Champaign, Urbana, IL, United States, ²Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, United States

Dynamic MRSI measures the temporal changes of metabolite concentrations by acquiring a time series of MRSI data. These data can be used in a range of applications, including the study of the response of a metabolic system to a perturbation. However, high-resolution dynamic MRSI is challenging due to poor SNR resulting from the low concentrations of metabolites. This work presents a new method for high-resolution dynamic 31P-MRSI using high-order partially separable functions. The method has been validated using in vivo dynamic 31P-MRSI experiments, producing encouraging results.

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