Chao Ma1, Fan Lam1, Qiegen Liu1, and Zhi-Pei Liang1,2
1Beckman Institute, University of Illinois Urbana-Champaign, Urbana, IL, United States, 2Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, United States
Multidimensional spectroscopy increases spectral dispersion and enables accurate detection of more metabolites (e.g., Glu and GABA in 1H-MRSI of the brain) whose spectra largely overlap with other metabolites. However, the additional dimension of spectral information is obtained at the cost of increased data acquisition time, limiting the practical utility of in vivo multidimensional MRSI. This work presents a novel tensor-based approach to accelerated high-resolution multidimensional 1H-MRSI. The proposed method has been validated using phantom and in vivo J-resolved 2D 1H-MRSI experimental studies on a 3T scanner, producing encouraging results. The method should enhance the practical utility of multidimensional MRSI.
