Simultaneous Mapping of Water Diffusion Coefficients and Metabolite Distributions of the Brain Using MR Spectroscopic Imaging Without Water Suppression

Abstract

To simultaneously map water diffusion coefficients and metabolite distributions of the brain in magnetic resonance spectroscopic imaging (MRSI) experiments within a clinically feasible time. Methods: A diffusion-preparation module was introduced in water-unsuppressed MRSI acquisition sequence to generate diffusion weighting of the water signals. Fast spatiospectral encodings were achieved using echo-planar spectroscopic imaging readouts with blipped phase encodings for sparse sampling. Navigator signals were embedded in the data acquisition sequence, which were used for detection of data corrupted by physiological motion in the diffusion preparation period. In data processing, a novel model-based method was developed to effectively use sparse (k, t)-space spectroscopic signals for reconstruction of the spatial distributions of water diffusion coefficients and metabolite concentrations. Results: Both phantom experiments and in vivo experiments were carried out to evaluate the feasibility and performance of the proposed method.In an 8-minute scan, diffusion weighted images and apparent diffusion coefficients map at 2.0×1.0×1.0 mm 3 were obtained simultaneously with metabolite maps at 2.0×3.0×3.0 mm 3 nominal resolution. Conclusion: We demonstrated the feasibility of using the unsuppressed water signals from MRSI experiments to map the water diffusion coefficients of brain tissues and proposed a novel method to achieve simultaneous mapping of water diffusion coefficients and metabolite distributions. Significance: The proposed method provides a unique imaging tool for simultaneous diffusion and metabolic imaging. This method is expected to be useful for various brain imaging applications.

Multi-Parametric Molecular Imaging of the Brain Using Optimized Multi-TE Subspace MRSI

“…More advanced spatial/spectral constraints such as learned nonlinear lowdimensional manifolds [28], [45] and generative-image-modelbased spatial constraints [46] will be developed to enhance the reconstruction performance. The current water imaging data acquisition can also be further enhanced with higher-resolution encoding (e.g., blips along both k y and k z ) and additional preparation modules (T 1 /T 2 preparation or diffusion encoding modules [47]) to generate more imaging contrasts as well as richer quantitative imaging capability. Moreover, multi-slab or simultaneous multi-slice excitation strategies [48]- [50] will be incorporated in subsequent publications to demonstrate further accelerated acquisition and larger brain coverage.…”