No abstract

Purpose:To develop a subspace learning method for the recently proposed subspace-based MRSI approach known as SPICE, and achieve ultrafast 1 H-MRSI of the brain. Theory and Methods: A novel strategy is formulated to learn a low-dimensional subspace representation of MR spectra from specially acquired training data and use the learned subspace for general MRSI experiments. Specifically, the subspace learning problem is formulated as learning "empirical" distributions of molecule-specific spectral parameters (e.g., concentrations, lineshapes, and frequency shifts) by integrating physics-based model and the training data. The learned spectral parameters and quantum mechanical simulation basis can then be combined to construct acquisition-specific subspace for spatiospectral encoding and processing. High-resolution MRSI acquisitions combining ultrashort-TE/short-TR excitation, sparse sampling, and the elimination of water suppression have been performed to evaluate the feasibility of the proposed method. Results: The accuracy of the learned subspace and the capability of the proposed method in producing high-resolution 3D 1 H metabolite maps and high-quality spatially resolved spectra (with a nominal resolution of ∼2.4 × 2.4 × 3 mm 3 in 5 minutes) were demonstrated using phantom and in vivo studies. By eliminating water suppression, we are also able to extract valuable information from the water signals for data processing (B 0 map, frequency drift, and coil sensitivity) as well as for mapping tissue susceptibility and relaxation parameters. Conclusions: The proposed method enables ultrafast 1 H-MRSI of the brain using a learned subspace, eliminating the need of acquiring subject-dependent navigator data (known as  1 ) in the original SPICE technique. It represents a new way to perform MRSI experiments and an important step toward practical applications of highresolution MRSI. K E Y W O R D SMR spectroscopic imaging, no water suppression, rapid spatiospectral encoding, subspace learning, union-of-subspaces model 378 |

No abstract

Purpose To enable simultaneous high‐resolution mapping of brain function and metabolism. Methods An encoding scheme was designed for interleaved acquisition of functional MRI (fMRI) data in echo volume imaging trajectories and MR spectroscopic imaging (MRSI) data in echo‐planar spectroscopic imaging trajectories. The scheme eliminates water and lipid suppression and utilizes free induction decay signals to encode both functional and metabolic information with ultrashort TE, short TR, and sparse sampling of )(normalk,0.166667emt‐space. A subspace‐based image reconstruction method was introduced for processing both the fMRI and MRSI data. The complementary information in the fMRI and MRSI data sets was also utilized to improve image reconstruction in the presence of intrascan head motion, field drift, and tissue susceptibility changes. Results In‐vivo experimental results were obtained from healthy human subjects in resting‐state fMRI/MRSI experiments. In these experiments, the proposed method was able to simultaneously acquire metabolic and functional information from the brain in high resolution. For scans of 6.5 minutes, we achieved 3.0 × 3.0 × 1.8 mm3 spatial resolution for fMRI, 1.9 × 2.5 × 3.0 mm3 nominal spatial resolution for MRSI, and 1.9 × 1.9 × 1.8 mm3 nominal spatial resolution for quantitative susceptibility maps. Conclusion This work demonstrates the feasibility of simultaneous high‐resolution mapping of brain function and metabolism with improved spatial resolution and synergistic image reconstruction.

Impaired oxygen and cellular metabolism is a hallmark of ischaemic injury in acute stroke. Magnetic resonance spectroscopic imaging (MRSI) has long been recognized as a potentially powerful tool for non-invasive metabolic imaging. Nonetheless, long acquisition time, poor spatial resolution, and narrow coverage have limited its clinical application. Here we investigated the feasibility and potential clinical utility of rapid, high spatial resolution, near whole-brain 3D metabolic imaging based on a novel MRSI technology. In an 8-min scan, we simultaneously obtained 3D maps of N-acetylaspartate and lactate at a nominal spatial resolution of 2.0 × 3.0 × 3.0 mm3 with near whole-brain coverage from a cohort of 18 patients with acute ischaemic stroke. Serial structural and perfusion MRI was used to define detailed spatial maps of tissue-level outcomes against which high-resolution metabolic changes were evaluated. Within hypoperfused tissue, the lactate signal was higher in areas that ultimately infarcted compared with those that recovered (P < 0.0001). Both lactate (P < 0.0001) and N-acetylaspartate (P < 0.001) differed between infarcted and other regions. Within the areas of diffusion-weighted abnormality, lactate was lower where recovery was observed compared with elsewhere (P < 0.001). This feasibility study supports further investigation of fast high-resolution MRSI in acute stroke.