Accelerated J‐resolved 1H‐MRSI with limited and sparse sampling of (k, t1, t2‐space. Issue 1 (29th July 2020) - Tang, Lihong; Zhao, Yibo; Li, Yudu; Guo, Rong; Clifford, Bryan; El Fakhri, Georges; Ma, Chao; Liang, Zhi‐Pei; Luo, Jie
Abstract : Purpose: To accelerate the acquisition of J‐resolved proton magnetic resonance spectroscopic imaging ( 1 H‐MRSI) data for high‐resolution mapping of brain metabolites and neurotransmitters. Methods: The proposed method used a subspace model to represent multidimensional spatiospectral functions, which significantly reduced the number of parameters to be determined from J‐resolved 1 H‐MRSI data. A semi‐LASER–based (Localization by Adiabatic SElective Refocusing) echo‐planar spectroscopic imaging (EPSI) sequence was used for data acquisition. The proposed data acquisition scheme sampled k, t 1, t 2 ‐space in variable density, where t 1 and t 2 specify the J‐coupling and chemical‐shift encoding times, respectively. Selection of the J‐coupling encoding times (or, echo time values) was based on a Cramer‐Rao lower bound analysis, which were optimized for gamma‐aminobutyric acid (GABA) detection. In image reconstruction, parameters of the subspace‐based spatiospectral model were determined by solving a constrained optimization problem. Results: Feasibility of the proposed method was evaluated using both simulated and experimental data from a spectroscopic phantom. The phantom experimental results showed that the proposed method, with a factor of 12 acceleration in data acquisition, could determine the distribution of J‐coupled molecules with expected accuracy. In vivo study with healthy human subjects also showed that 3D maps of brain metabolites and neurotransmitters can be obtained with a nominal spatial resolution of 3.0 × 3.0 × 4.8 mm 3 from J‐resolved 1 H‐MRSI data acquired in 19.4 min. Conclusions: This work demonstrated the feasibility of highly accelerated J‐resolved 1 H‐MRSI using limited and sparse sampling of k, t 1, t 2 ‐space and subspace modeling. With further development, the proposed method may enable high‐resolution mapping of brain metabolites and neurotransmitters in clinical applications.