Extensive Brain Pathologic Alterations Detected with 7.0-T MR Spectroscopic Imaging Associated with Disability in Multiple Sclerosis.

Background MR spectroscopic imaging (MRSI) allows in vivo assessment of brain metabolism and is of special interest in multiple sclerosis (MS), where morphologic MRI cannot depict major parts of disease activity. Purpose To evaluate the ability of 7.0-T MRSI to depict and visualize pathologic alterations in the normal-appearing white matter (NAWM) and cortical gray matter (CGM) in participants with MS and to investigate their relation to disability. Materials and Methods Free-induction decay MRSI was performed at 7.0 T. Participants with MS and age- and sex-matched healthy controls were recruited prospectively between January 2016 and December 2017. Metabolic ratios were obtained in white matter lesions, NAWM, and CGM regions. Subgroup analysis for MS-related disability based on Expanded Disability Status Scale (EDSS) scores was performed using analysis of covariance. Partial correlations were applied to explore associations between metabolic ratios and disability. Results Sixty-five participants with MS (mean age ± standard deviation, 34 years ± 9; 34 women) and 20 age- and sex-matched healthy controls (mean age, 32 years ± 7; 11 women) were evaluated. Higher signal intensity of myo-inositol (mI) with and without reduced signal intensity of N-acetylaspartate (NAA) was visible on metabolic images in the NAWM of participants with MS. A higher ratio of mI to total creatine (tCr) was observed in the NAWM of the centrum semiovale of all MS subgroups, including participants without disability (marginal mean ± standard error, healthy controls: 0.78 ± 0.04; EDSS 0-1: 0.86 ± 0.03 [P = .02]; EDSS 1.5-3: 0.95 ± 0.04 [P < .001]; EDSS ≥3.5: 0.94 ± 0.04 [P = .001]). A lower ratio of NAA to tCr was found in MS subgroups with disabilities, both in their NAWM (marginal mean ± standard error, healthy controls: 1.46 ± 0.04; EDSS 1.5-3: 1.33 ± 0.03 [P = .03]; EDSS ≥3.5: 1.30 ± 0.04 [P = .01]) and CGM (marginal mean ± standard error, healthy controls: 1.42 ± 0.05; EDSS ≥3.5: 1.23 ± 0.05 [P = .006]). mI/NAA correlated with EDSS (NAWM of centrum semiovale: r = 0.47, P < .001; parietal NAWM: r = 0.43, P = .002; frontal NAWM: r = 0.34, P = .01; frontal CGM: r = 0.37, P = .004). Conclusion MR spectroscopic imaging at 7.0 T allowed in vivo visualization of multiple sclerosis pathologic findings not visible at T1- or T2-weighted MRI. Metabolic abnormalities in the normal-appearing white matter and cortical gray matter were associated with disability. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Barker in this issue.

Effects of Short- and Long-Term Aerobic-Strength Training and Determinants of Walking Speed in the Elderly.

BACKGROUND/AIMS: Walking speed (WS) is an objective measure of physical capacity and a modifiable risk factor of morbidity and mortality in the elderly. In this study, we (i) determined effects of 3-month supervised aerobic-strength training on WS, muscle strength, and habitual physical activity; (ii) evaluated capacity of long-term (21 months) training to sustain higher WS; and (iii) identified determinants of WS in the elderly. METHODS: Volunteers (F 48/M 14, 68.4 ± 7.1 years) completed either 3-month aerobic-strength (3 × 1 h/week, n = 48) or stretching (active control, n = 14) intervention (study A). Thirty-one individuals (F 24/M 7) from study A continued in supervised aerobic-strength training (2 × 1 h/week, 21 months) and 6 (F 5/M 1) became nonexercising controls. RESULTS: Three-month aerobic-strength training increased preferred and maximal WS (10-m walk test, p < 0.01), muscle strength (p < 0.01) and torque (p < 0.01) at knee extension, and 24-h habitual physical activity (p < 0.001), while stretching increased only preferred WS (p < 0.03). Effect of training on maximal WS was most prominent in individuals with baseline WS between 1.85 and 2.30 m·s-1. Maximal WS measured before intervention correlated negatively with age (r = -0.339, p = 0.007), but this correlation was weakened by the intervention (r = -0.238, p = 0.06). WS progressively increased within the first 9 months of aerobic-strength training (p < 0.001) and remained elevated during 21-month intervention (p < 0.01). Cerebellar gray matter volume (MRI) was positively associated with maximal (r = 0.54; p < 0.0001) but not preferred WS and explained >26% of its variability, while age had only minor effect. CONCLUSIONS: Supervised aerobic-strength training increased WS, strength, and dynamics of voluntary knee extension as well as habitual physical activity in older individuals. Favorable changes in WS were sustainable over the 21-month period by a lower dose of aerobic-strength training. Training effects on WS were not limited by age, and cerebellar cortex volume was the key determinant of WS.

Neurocognitive performance in relapsing-remitting multiple sclerosis patients is associated with metabolic abnormalities of the thalamus but not the hippocampus- GABA-edited 1H MRS study.

OBJECTIVES: Multiple sclerosis (MS) is an inflammatory demyelinating disease that may cause physical disabling as well as cognitive dysfunction. The presented study investigated how the neuropsychological status depends on the thalamus and hippocampus's metabolic processes, using γ-aminobutyric acid-edited magnetic resonance spectroscopy (GABA-edited 1H MRS) in patients with early MS, and how the results differ from healthy volunteers. METHODS: We recruited 36 relapsing-remitting (RRMS) MS patients and 22 controls (CON). In addition to common 1H MRS metabolites, such as N-acetyl-aspartate (tNAA), myoinositol (mIns), total choline and creatine (tCr, tCho), we also evaluated GABA and glutamate/glutamine (Glx). Metabolite ratios were correlated with the results of Single-Digit Modality Test (SDMT) and Expanded Disability Status Score (EDSS). RESULTS: In the thalamus, GABA ratios (GABA/tCr, GABA/tNAA) were significantly lower in RRMS patients than in CON. Both tCho- and mIns-ratios correlated with lower scores of SDMT but not with EDSS. Metabolic ratios in the hippocampus did not differ between RRMS and CON and did not correlate with any of performed tests. DISCUSSION: This study is the first to provide GABA-edited 1H MRS evidence for MS-related metabolic changes of the thalamus and hippocampus. The findings underline the importance of evaluating subcortical grey matter in MS patients to improve understanding of the clinical manifestations of MS and as a potential future target for treatment.

Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T.

PURPOSE: Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. METHODS: We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs. RESULTS: Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate. DISCUSSION: We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.

Frequency drift in MR spectroscopy at 3T.

PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. DISCUSSION: This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

k-Space-based coil combination via geometric deep learning for reconstruction of non-Cartesian MRSI data.

PURPOSE: State-of-the-art whole-brain MRSI with spatial-spectral encoding and multichannel acquisition generates huge amounts of data, which must be efficiently processed to stay within reasonable reconstruction times. Although coil combination significantly reduces the amount of data, currently it is performed in image space at the end of the reconstruction. This prolongs reconstruction times and increases RAM requirements. We propose an alternative k-space-based coil combination that uses geometric deep learning to combine MRSI data already in native non-Cartesian k-space. METHODS: Twelve volunteers were scanned at a 3T MR scanner with a 20-channel head coil at 10 different positions with water-unsuppressed MRSI. At the eleventh position, water-suppressed MRSI data were acquired. Data of 7 volunteers were used to estimate sensitivity maps and form a base for simulating training data. A neural network was designed and trained to remove the effect of sensitivity profiles of the coil elements from the MRSI data. The water-suppressed MRSI data of the remaining volunteers were used to evaluate the performance of the new k-space-based coil combination relative to that of a conventional image-based alternative. RESULTS: For both approaches, the resulting metabolic ratio maps were similar. The SNR of the k-space-based approach was comparable to the conventional approach in low SNR regions, but underperformed for high SNR. The Cramér-Rao lower bounds show the same trend. The analysis of the FWHM showed no difference between the two methods. CONCLUSION: k-Space-based coil combination of MRSI data is feasible and reduces the amount of raw data immediately after their sampling.

Positivity of oligoclonal bands in the cerebrospinal fluid predisposed to metabolic changes and rearrangement of inhibitory/excitatory neurotransmitters in subcortical brain structures in multiple sclerosis.

BACKGROUND: The latest diagnostic criteria for multiple sclerosis (MS) have revitalized the role of oligoclonal bands synthesis in the cerebrospinal fluid (CSF-OCB). This study identifies predictors of CSF-OCB-positivity among in vivo metabolic markers in the subcortical gray/white matter in MS patients after their first episode (CIS) and in patients with relapsing-remitting course (RRMS). METHODS: The study enrolled 13 CIS and 23 RRMS patients. Metabolism was evaluated using Mescher-Garwood-edited proton-magnetic resonance spectroscopy on a 3T MR scanner. In addition to N-acetyl-aspartate (tNAA), myoinositol (mIns), and choline- and creatine compounds (tCho, tCr) were also evaluated γ-aminobutyric acid (GABA) and glutamate-glutamine (Glx) ratios. RESULTS: CSF-OCB-positivity was found in 76.9% of CIS and 78.2% of RRMS patients. GABA and Glx ratios in putamen and corpus callosum strongly determined CSF-OCB-positive CIS patients. Other essential predictors of CSF-OCB-positive CIS were mIns and Glx ratios in the putamen, and tCho/tNAA in the corpus callosum. In RRMS, GABA ratios in the right thalamus and Glx ratios in the left hippocampus strongly predicted CSF-OCB-positive patients. tCho/tNAA and tNAA/tCr in the left hippocampus were also identified as essential predictors of CSF-OCB-positive RRMS patients. CONCLUSION: This is the first in vivo evidence of GABA-Glx rearrangement in CSF-OCB-positive patients since its early stages of MS.

Cardiac autonomic function in patients with early multiple sclerosis.

PURPOSE: Cardiac autonomic dysfunction has been reported in patients with long-standing multiple sclerosis (MS); however, data in early disease are limited. The present study was aimed at evaluating cardiac autonomic function in patients with early MS in the context of white matter metabolic status, which could potentially affect functions of the autonomic brain centers. METHODS: Cardiac sympathetic and baroreflex cardiovagal responses to the Valsalva maneuver, orthostatic test, and the Stroop test were evaluated in 16 early, treatment-naïve patients with relapsing-remitting MS, and in 14 healthy participants. Proton magnetic resonance spectroscopic imaging (MRSI) of the brain was performed in eight of these MS patients and in eight controls. RESULTS: Valsalva maneuver outcomes were comparable between patients and controls. At baseline, norepinephrine levels were lower (p = 0.027) in MS patients compared to controls. The patients had higher heart rate (p = 0.034) and lower stroke volume (p = 0.008), but similar blood pressure, cardiac output and norepinephrine increments from baseline to 2 min of the orthostatic test compared to controls. MS patients and controls did not differ in responses to the Stroop test. MRSI showed lower total N-acetylaspartate/total creatine (p = 0.038) and higher myo-inositol/total creatine (p = 0.013) in MS lesions compared to non-lesional white matter. CONCLUSION: Our results show normal cardiac sympathetic and baroreflex cardiovagal function in MS patients with relapsing-remitting MS with lesions at the post-acute/early resolving stage. TRIAL REGISTRATION: The study was registered at ClinicalTrials.gov under the Identifier: NCT03052595 and complies with the STROBE checklist for cohort, case-control, and cross-sectional studies.

High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI.

OBJECTIVES: Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in a patient cohort of 23 high-grade gliomas (HGG). MATERIALS AND METHODS: We preoperatively measured 23 patients with histologically verified HGGs (17 male, 8 female, age 53 ± 15) with an MRSI sequence based on concentric ring trajectories with a 64 × 64 × 39 measurement matrix, and a 3.4 × 3.4 × 3.4 mm3 nominal voxel volume in 15 min. Quantification used a basis-set of 17 components including N-acetyl-aspartate (NAA), total choline (tCho), total creatine (tCr), glutamate (Glu), glutamine (Gln), glycine (Gly) and 2-hydroxyglutarate (2HG). The resultant metabolic images were evaluated for their reliability as well as their quality and compared to spatially segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast enhanced + edema, peritumoral) based on clinical data and also compared to histopathology (e.g., grade, IDH-status). RESULTS: Eighteen of the patient measurements were considered usable. In these patients, ten metabolites were quantified with acceptable quality. Gln, Gly, and tCho were increased and NAA and tCr decreased in nearly all tumor regions, with other metabolites such as serine, showing mixed trends. Overall, there was a reliable characterization of metabolic tumor areas. We also found heterogeneity in the metabolic images often continued into the peritumoral region. While 2HG could not be satisfyingly quantified, we found an increase of Glu in the contrast-enhancing region of IDH-wildtype HGGs and a decrease of Glu in IDH1-mutant HGGs. CONCLUSIONS: We successfully demonstrated high-resolution 7T 3D-MRSI in HGG patients, showing metabolic differences between tumor regions and peritumoral tissue for multiple metabolites. Increases of tCho, Gln (related to tumor metabolism), Gly (related to tumor proliferation), as well as decreases in NAA, tCr, and others, corresponded very well to clinical tumor segmentation, but were more heterogeneous and often extended into the peritumoral region.

Effects of different macromolecular models on reproducibility of FID-MRSI at 7T.

PURPOSE: A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID-MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility. METHODS: Clinically feasible, high-resolution FID-MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test-retest reproducibility of MRSI scans was assessed voxel-wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model. RESULTS: The full MM model provided the most reproducible quantification of total NAA, total Cho, myo-inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to -0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites. CONCLUSION: Clinically feasible FID-MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered.

Clinical High-Resolution 3D-MR Spectroscopic Imaging of the Human Brain at 7 T.

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 mm nominal voxel size acquired in ~3 minutes to an 80 × 80 × 47 matrix with 2.7 × 2.7 × 2.7 mm 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.

Hippocampal GABA levels correlate with retrieval performance in an associative learning paradigm.

Neural plasticity is a complex process dependent on neurochemical underpinnings. Next to the glutamatergic system which contributes to memory formation via long-term potentiation (LTP) and long-term depression (LTD), the main inhibitory neurotransmitter, GABA is crucially involved in neuroplastic processes. Hence, we investigated changes in glutamate and GABA levels in the brain in healthy participants performing an associative learning paradigm. Twenty healthy participants (10 female, 25 ±â€¯5 years) underwent paired multi-voxel magnetic resonance spectroscopy imaging before and after completing 21 days of a facial associative learning paradigm in a longitudinal study design. Changes of GABA and glutamate were compared to retrieval success in the hippocampus, insula and thalamus. No changes in GABA and glutamate concentration were found after 21 days of associative learning. However, baseline hippocampal GABA levels were significantly correlated with initial retrieval success (pcor = 0.013, r = 0.690). In contrast to the thalamus and insula (pcor>0.1), higher baseline GABA levels in the hippocampus were associated with better retrieval performance in an associative learning paradigm. Therefore, our findings support the importance of hippocampal GABA levels in memory formation in the human brain in vivo.

Non-Cartesian GRAPPA and coil combination using interleaved calibration data - application to concentric-ring MRSI of the human brain at 7T.

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.

The influence of spatial resolution on the spectral quality and quantification accuracy of whole-brain MRSI at 1.5T, 3T, 7T, and 9.4T.

PURPOSE: Inhomogeneities in the static magnetic field (B0 ) deteriorate MRSI data quality by lowering the spectral resolution and SNR. MRSI with low spatial resolution is also prone to lipid bleeding. These problems are increasingly problematic at ultra-high fields. An approach to tackling these challenges independent of B0 -shim hardware is to increase the spatial resolution. Therefore, we investigated the effect of improved spatial resolution on spectral quality and quantification at 4 field strengths. METHODS: Whole-brain MRSI data was simulated for 3 spatial resolutions and 4 B0 s based on experimentally acquired MRI data and simulated free induction decay signals of metabolites and lipids. To compare the spectral quality and quantification, we derived SNR normalized to the voxel size (nSNR), linewidth and metabolite concentration ratios, their Cramer-Rao-lower-bounds (CRLBs), and the absolute percentage error (APE) of estimated concentrations compared to the gold standard for the whole-brain and 8 brain regions. RESULTS: At 7T, we found up to a 3.4-fold improved nSNR (in the frontal lobe) and a 2.8-fold reduced linewidth (in the temporal lobe) for 1 cm3 versus 0.25 cm3 resolution. This effect was much more pronounced at higher and less homogenous B0 (1.6-fold improved nSNR and 1.8-fold improved linewidth in the parietal lobe at 3T). This had direct implications for quantification: the volume of reliably quantified spectra increased with resolution by 1.2-fold and 1.5-fold (when thresholded by CRLBs or APE, respectively). CONCLUSION: MRSI data quality benefits from increased spatial resolution particularly at higher B0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field.

Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer.

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data. Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T1-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions. Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes. Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.

High-resolution metabolic mapping of gliomas via patch-based super-resolution magnetic resonance spectroscopic imaging at 7T.

OBJECTIVES: To demonstrate the feasibility of 7 T magnetic resonance spectroscopic imaging (MRSI), combined with patch-based super-resolution (PBSR) reconstruction, for high-resolution multi-metabolite mapping of gliomas. MATERIALS AND METHODS: Ten patients with WHO grade II, III and IV gliomas (6/4, male/female; 45 ±â€¯9 years old) were prospectively measured between 2014 and 2018 on a 7 T whole-body MR imager after routine 3 T magnetic resonance imaging (MRI) and positron emission tomography (PET). Free induction decay MRSI with a 64 × 64-matrix and a nominal voxel size of 3.4 × 3.4 × 8 mm³ was acquired in six minutes, along with standard T1/T2-weighted MRI. Metabolic maps were obtained via spectral LCmodel processing and reconstructed to 0.9 × 0.9 × 8 mm³ resolutions via PBSR. RESULTS: Metabolite maps obtained from combined 7 T MRSI and PBSR resolved the density of metabolic activity in the gliomas in unprecedented detail. Particularly in the more heterogeneous cases (e.g. post resection), metabolite maps enabled the identification of complex metabolic activities, which were in topographic agreement with PET enhancement. CONCLUSIONS: PBSR-MRSI combines the benefits of ultra-high-field MR systems, cutting-edge MRSI, and advanced postprocessing to allow millimetric resolution molecular imaging of glioma tissue beyond standard methods. An ideal example is the accurate imaging of glutamine, which is a prime target of modern therapeutic approaches, made possible due to the higher spectral resolution of 7 T systems.

7 T Magnetic Resonance Spectroscopic Imaging in Multiple Sclerosis: How Does Spatial Resolution Affect the Detectability of Metabolic Changes in Brain Lesions?

OBJECTIVES: The aim of this study was to assess the utility of increased spatial resolution of magnetic resonance spectroscopic imaging (MRSI) at 7 T for the detection of neurochemical changes in multiple sclerosis (MS)-related brain lesions. MATERIALS AND METHODS: This prospective, institutional review board-approved study was performed in 20 relapsing-remitting MS patients (9 women/11 men; mean age ± standard deviation, 30.8 ± 7.7 years) after receiving written informed consent. Metabolic patterns in MS lesions were compared at 3 different spatial resolutions of free induction decay MRSI with implemented parallel imaging acceleration: 2.2 × 2.2 × 8 mm; 3.4 × 3.4 × 8 mm; and 6.8 × 6.8 × 8 mm voxel volumes, that is, matrix sizes of 100 × 100, 64 × 64, and 32 × 32, respectively. The quality of data was assessed by signal-to-noise ratio and Cramér-Rao lower bounds. Statistical analysis was performed using Wilcoxon signed-rank tests with correction for multiple testing. RESULTS: Seventy-seven T2-hyperintense MS lesions were investigated (median volume, 155.7 mm; range, 10.8-747.0 mm). The mean metabolic ratios in lesions differed significantly between the 3 MRSI resolutions (ie, 100 × 100 vs 64 × 64, 100 × 100 vs 32 × 32, and 64 × 64 vs 32 × 32; P < 0.001). With the ultra-high resolution (100 × 100), we obtained 40% to 80% higher mean metabolic ratios and 100% to 150% increase in maximum metabolic ratios in the MS lesions compared with the lowest resolution (32 × 32), while maintaining good spectral quality (signal-to-noise ratio >12, Cramér-Rao lower bounds <20%) and measurement time of 6 minutes. There were 83% of MS lesions that showed increased myo-inositol/N-acetylaspartate with the 100 × 100 resolution, but only 66% were distinguishable with the 64 × 64 resolution and 35% with the 32 × 32 resolution. CONCLUSIONS: Ultra-high-resolution MRSI (~2 × 2 × 8 mm voxel volume) can detect metabolic alterations in MS, which cannot be recognized by conventional MRSI resolutions, within clinically acceptable time.

Real-time Correction of Motion and Imager Instability Artifacts during 3D γ-Aminobutyric Acid-edited MR Spectroscopic Imaging.

Purpose To compare the involuntary head motion, frequency and B0 shim changes, and effects on data quality during real-time-corrected three-dimensional γ-aminobutyric acid-edited magnetic resonance (MR) spectroscopic imaging in subjects with mild cognitive impairment (MCI), patients with Parkinson disease (PD), and young and older healthy volunteers. Materials and Methods In this prospective study, MR spectroscopic imaging datasets were acquired at 3 T after written informed consent was obtained. Translational and rotational head movement, frequency, and B0 shim were determined with an integrated volumetric navigator. Head motion patterns and imager instability were investigated in 33 young healthy control subjects (mean age ± standard deviation, 31 years ± 5), 34 older healthy control subjects (mean age, 67 years ± 8), 34 subjects with MCI (mean age, 72 years ± 5), and 44 patients with PD (mean age, 64 years ± 8). Spectral quality was assessed by means of region-of-interest analysis. Group differences were evaluated with Bonferroni-corrected Mann-Whitney tests. Results Three patients with PD and four subjects with MCI were excluded because of excessive head motion (ie, > 0.8 mm translation per repetition time of 1.6 seconds throughout >10 minutes). Older control subjects, patients with PD, and subjects with MCI demonstrated 1.5, 2, and 2.5 times stronger head movement, respectively, than did young control subjects (1.79 mm ± 0.77) (P < .001). Of young control subjects, older control subjects, patients with PD, and subjects with MCI, 6%, 35%, 38%, and 51%, respectively, moved more than 3 mm during the MR spectroscopic imaging acquisition of approximately 20 minutes. The predominant movements were head nodding and "sliding out" of the imager. Frequency changes were 1.1- and 1.4-fold higher in patients with PD (P = .007) and subjects with MCI (P < .001), respectively, and B0 shim changes were 1.3-, 1.5-, and 1.9-fold higher in older control subjects (P = .005), patients with PD (P < .001), and patients with MCI (P < .001), respectively, compared with those of young control subjects (12.59 Hz ± 2.49, 3.61 Hz · cm-1 ± 1.25). Real-time correction provided high spectral quality in all four groups (signal-to-noise ratio >15, Cramér-Rao lower bounds < 20%). Conclusion Real-time motion and B0 monitoring provides valuable information about motion patterns and B0 field variations in subjects with different predispositions for head movement. Immediate correction improves data quality, particularly in patients who have difficulty avoiding movement. © RSNA, 2017 Online supplemental material is available for this article.

Ultra-high resolution brain metabolite mapping at 7 T by short-TR Hadamard-encoded FID-MRSI.

MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B0/B1+-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 1.7×1.7×8mm3 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.

Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T.

PURPOSE: Full-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 METHODS: Trajectories 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. RESULTS: By 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. CONCLUSION: Density-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.