High-resolution, volumetric diffusion-weighted MR spectroscopic imaging of the brain

To achieve high-resolution, three-dimensional (3D) quantitative diffusion-weighted MR spectroscopic imaging (DW-MRSI) for molecule-specific microstructural imaging of the brain.

We introduced and integrated several innovative acquisition and processing strategies for DW-MRSI: (a) a new double-spin-echo sequence combining selective excitation, bipolar diffusion encoding, rapid spatiospectral sampling, interleaved water spectroscopic imaging data, and a special sparsely sampled echo-volume-imaging (EVI)-based navigator, (b) a rank-constrained time-resolved reconstruction from the EVI data to capture spatially varying phases, (c) a model-based phase correction for DW-MRSI data, and (d) a multi-b-value subspace-based method for water/lipids removal and spatiospectral reconstruction using learned metabolite subspaces, and e) a hybrid subspace and parametric model-based parameter estimation strategy. Phantom and in vivo experiments were performed to validate the proposed method and demonstrate its ability to map metabolite-specific diffusion parameters in 3D.

The proposed method generated reproducible metabolite diffusion coefficient estimates, consistent with those from a standard single-voxel DW spectroscopy (SV-DWS) method. High-SNR multi-molecular mean diffusivity (MD) maps can be obtained at a 6.9  $\times$ 6.9 $\times$ 7.0 mm ${\hspace{0.17em}}^3$ nominal resolution with large 3D brain coverage. High-resolution (4.4 $\times$ 4.4 $\times$ 5.6 mm ${\hspace{0.17em}}^3$ ) metabolite and diffusion coefficient maps can be obtained within 20 mins for the first time. Tissue-dependent metabolite MDs were observed, i.e., larger MDs for NAA, creatine, and choline in white matter than gray matter, with region-specific differences.

We demonstrated an unprecedented capability of simultaneous, high-resolution metabolite and diffusion parameter mapping. This imaging capability has strong potential to offer richer molecular and tissue-compartment-specific microstructural information for various clinical and neuroscience applications.