Fan Lam1, Qiang Ning1,2, Chao Ma1, Bryan Clifford1,2, and Zhi-Pei Liang1,2
1Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, United States, 2Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States
We present an integrative subspace-based sampling and reconstruction method for 3D high-resolution mapping of brain metabolites and neurotransmitters using MRSI. An echo-planar spectroscopic imaging sequence with J-resolved encoding capability has been developed to implement the proposed sparse sampling strategy for fast spatiospectral encoding. An explicit subspace model-based reconstruction scheme that incorporates J-resolved spectral prior to enable joint reconstruction of the metabolite and neurotransmitter signal components from the sparse data is described. Results from experimental data are used to demonstrate the capability of the proposed method in producing high-resolution and high-SNR spatiospectral distributions of both metabolites and neurotransmitters.