MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B/B-homogeneity, specific absorption rate restrictions, long measurement times, and low spatial resolution. To overcome these limitations, we propose an ultra-high resolution (UHR) MRSI sequence that provides a 128×128 matrix with a nominal voxel volume of 1.7×1.7×8mm in a comparatively short measurement time. A clinically feasible scan time of 10-20min is reached via a short TR of 200 ms due to an optimised free induction decay-based acquisition with shortened water suppression as well as parallel imaging (PI) using Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA). This approach is not limited to a rectangular region of interest in the centre of the brain, but also covers cortical brain regions. Transversal pulse-cascaded Hadamard encoding was able to further extend the coverage to 3D-UHR-MRSI of four slices (100×100×4 matrix size), with a measurement time of 17min. Lipid contamination was removed during post-processing using L2-regularisation. Simulations, phantom and volunteer measurements were performed. The obtained single-slice and 3D-metabolite maps show the brain in unprecedented detail (e.g., hemispheres, ventricles, gyri, and the contrast between grey and white matter). This facilitates the use of UHR-MRSI for clinical applications, such as measurements of the small structures and metabolic pathologic deviations found in small Multiple Sclerosis lesions.

PurposeShort‐echo‐time proton MR spectra at 7T feature nine to 10 distinct macromolecule (MM) resonances that overlap with the signals of metabolites. Typically, a metabolite‐nulled in vivo MM spectrum is included in the quantification`s prior knowledge to provide unbiased metabolite quantification. However, this MM model may fail if MMs are pathologically altered. In addition, information about the individual MM peaks is lost. In this study, we aimed to create an improved MM model by parameterization of the in vivo MM spectrum into individual components, and to use this new model to quantify free induction decay MR spectroscopic imaging (FID‐MRSI) data.MethodsThe measured in vivo MM spectrum was parameterized using advanced method for accurate, robust, and efficient spectral fitting (AMARES) and Hankel‐Lanczos singular value decomposition algorithms from which six different MM models were derived. Soft constraints were applied to avoid over‐parameterization. All MM models were combined with simulated metabolite spectra to form complete basis sets. FID‐MRSI data from 14 healthy volunteers were quantified via LCModel, and the results were compared between all basis sets.ResultsThe MM model using nine individual AMARES‐parameterized MM components with additional soft constraints achieved the most reliable results. Nine MMs and seven metabolites were mapped simultaneously over the whole slice.ConclusionThe proposed MM model may facilitate studies that involve patients with pathologically altered MMs. Magn Reson Med 79:1231–1240, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Objectives Available clinical magnetic resonance spectroscopic imaging (MRSI) sequences are hampered by long scan times, low spatial resolution, strong field inhomogeneities, limited volume coverage, and low signal-to-noise ratio. High-resolution, whole-brain mapping of more metabolites than just N-acetylaspartate, choline, and creatine within clinically attractive scan times is urgently needed for clinical applications. The aim is therefore to develop a free induction decay (FID) MRSI sequence with rapid concentric ring trajectory (CRT) encoding for 7 T and demonstrate its clinical feasibility for mapping the whole cerebrum of healthy volunteers and patients. Materials and Methods Institutional review board approval and written informed consent were obtained. Time-efficient, 3-dimensional encoding of an ellipsoidal k-space by in-plane CRT and through-plane phase encoding was integrated into an FID-MRSI sequence. To reduce scan times further, repetition times were shortened, and variable temporal interleaves were applied. Measurements with different matrix sizes were performed to validate the CRT encoding in a resolution phantom. One multiple sclerosis patient, 1 glioma patient, and 6 healthy volunteers were prospectively measured. For the healthy volunteers, brain segmentation was performed to quantify median metabolic ratios, Cramér-Rao lower bounds (CRLBs), signal-to-noise ratios, linewidths, and brain coverage among all measured matrix sizes ranging from a 32 × 32 × 31 matrix with 6.9 × 6.9 × 4.2 mm3 nominal voxel size acquired in ~3 minutes to an 80 × 80 × 47 matrix with 2.7 × 2.7 × 2.7 mm3 nominal voxel size in ~15 minutes for different brain regions. Results Phantom structures with diameters down to 3 to 4 mm were visible. In vivo MRSI provided high spectral quality (median signal-to-noise ratios, >6.3 and linewidths, <0.082 ppm) and fitting quality. Cramér-Rao lower bounds were ranging from less than 22% for glutamine (highest CRLB in subcortical gray matter) to less than 9.5% for N-acetylaspartate for the 80 × 80 × 47 matrix (highest CRLB in the temporal lobe). This enabled reliable mapping of up to 8 metabolites (N-acetylaspartate, N-acetylaspartyl glutamate, total creatine, glutamine, glutamate, total choline, myo-inositol, glycine) and macromolecules for all resolutions. Coverage of the whole cerebrum allowed visualization of the full extent of diffuse and local multiple sclerosis-related neurochemical changes (eg, up to 100% increased myo-inositol). Three-dimensional brain tumor metabolic maps provided valuable information beyond that of single-slice MRSI, with up to 200% higher choline, up to 100% increased glutamine, and increased glycine in tumor tissue. Conclusions Seven Tesla FID-MRSI with time-efficient CRT readouts offers clinically attractive acquisition protocols tailored either for speed or for the investigation of small pathologic details and low-abundant metabolites. This can complement clinical MR studies of various brain disorders. Significant metabolic anomalies were demonstrated in a multiple sclerosis and a glioma patient for myo-inositol, glutamine, total choline, glycine, and N-acetylaspartate concentrations.

PurposeFull‐slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k‐space filtering, but this prolongs scan times and reduces the signal‐to‐noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR‐efficiency further. In this study, we propose an SNR‐efficient spatial‐spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming‐weighted k‐space, thus termed density‐weighted‐CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR.Theory and MethodsTrajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single‐slice, field‐of‐view 220 × 220 mm2, matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density‐weighted‐CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e‐CONCEPT), (b) elliptical phase‐encoding, and (c) 5‐fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding.ResultsBy intrinsically sampling a Hamming‐weighted k‐space, density‐weighted‐CONCEPT removed Gibbs‐ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e‐CONCEPT, elliptical phase‐encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding (all P < 0.05), respectively, which lead to improved metabolic maps.ConclusionDensity‐weighted‐CONCEPT provides clinically attractive full‐slice high‐resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874–2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Purpose Proton MR spectroscopic imaging (MRSI) benefits from B0 ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already‐fast sampling via concentric rings, we implemented additional, non‐Cartesian, hybrid through‐time/through‐k‐space (tt/tk)‐generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities. Methods Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single‐slice free induction decay (FID)‐MRSI. Through‐time/through‐k‐space‐GRAPPA with constant/variable‐density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole‐brain FID‐MRSI. Results Using iMUSICAL for coil combination yielded the highest signal‐to‐noise ratio (SNR) (+9%) and lowest Cramer‐Rao lower bounds (CRLBs) (‐6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g‐factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two‐fold, variable‐density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data. Conclusion Through‐time/through‐k‐space‐GRAPPA can accelerate already time‐efficient non‐Cartesian spatial‐spectral 2D/3D‐MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.