Abstract
PURPOSE: To develop a practical method to enable 3D T(1) mapping of brain metabolites. THEORY AND METHODS: Due to the high dimensionality of the imaging problem underlying metabolite T(1) mapping, measurement of metabolite T(1) values has been currently limited to a single voxel or slice. This work achieved 3D metabolite T(1) mapping by leveraging a recent ultrafast MRSI technique called SPICE (spectroscopic imaging by exploiting spatiospectral correlation). The Ernst-angle FID MRSI data acquisition used in SPICE was extended to variable flip angles, with variable-density sparse sampling for efficient encoding of metabolite T(1) information. In data processing, a novel generalized series model was used to remove water and subcutaneous lipid signals; a low-rank tensor model with prelearned subspaces was used to reconstruct the variable-flip-angle metabolite signals jointly from the noisy data. RESULTS: The proposed method was evaluated using both phantom and healthy subject data. Phantom experimental results demonstrated that high-quality 3D metabolite T(1) maps could be obtained and used for correction of T(1) saturation effects. In vivo experimental results showed metabolite T(1) maps with a large spatial coverage of 240 × 240 × 72 mm(3) and good reproducibility coefficients (< 11%) in a 14.5-min scan. The metabolite T(1) times obtained ranged from 0.99 to 1.44 s in gray matter and from 1.00 to 1.35 s in white matter. CONCLUSION: We successfully demonstrated the feasibility of 3D metabolite T(1) mapping within a clinically acceptable scan time. The proposed method may prove useful for both T(1) mapping of brain metabolites and correcting the T(1)-weighting effects in quantitative metabolic imaging.