Predicting dynamic, motion-related changes in B0 field in the brain at a 7T MRI using a subject-specific fine-trained U-net.

PURPOSE: Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B0 ), which is a prerequisite for high quality data. Thus, characterization of changes to B0 , for example induced by patient movement, is important for MR applications that are prone to B0 inhomogeneities. METHODS: We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction. A 3D U-net was trained on in vivo gradient-echo brain 7T MRI data. The input consisted of B0 maps and anatomical images at an initial position, and anatomical images at a different head position (obtained by applying a rigid-body transformation on the initial anatomical image). The output consisted of B0 maps at the new head positions. We further fine-trained the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data. RESULTS: Our approach was compared to established dynamic B0 field mapping via interleaved navigators, which suffer from limited spatial resolution and the need for undesirable sequence modifications. Qualitative and quantitative comparison showed similar performance between an interleaved navigator-equivalent method and proposed method. CONCLUSION: It is feasible to predict B0 maps from rigid subject movement and, when combined with external tracking hardware, this information could be used to improve the quality of MR acquisitions without the use of navigators.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T.

INTRODUCTION: Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. METHODS: Five volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6'-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. RESULTS: One hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). CONCLUSION: This study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 2.

Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1.

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

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.

QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping.

PURPOSE: Quantitative susceptibility mapping (QSM) estimates the spatial distribution of tissue magnetic susceptibilities from the phase of a gradient-echo signal. QSM algorithms require a signal mask to delineate regions with reliable phase for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artifacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing. Moreover, this method is integrated within an open-source software framework: QSMxT. METHODS: A robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information and suppressing streaking artifacts. RESULTS: Compared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artifacts caused by unreliable phase and high dynamic ranges of susceptibility sources. It is also robust across a range of acquisitions at 3 T in volunteers and phantoms, at 7 T in tumor patients, and in an in silico head phantom, with significant artifact and error reductions, greater anatomical detail, and minimal parameter tuning. CONCLUSION: The two-pass masking and reconstruction procedure separates reliable from less reliable phase regions, enabling a more accurate QSM reconstruction that mitigates artifacts, operates without anatomical priors, and requires minimal parameter tuning. The technique and its integration within QSMxT makes QSM processing more accessible and robust to streaking artifacts.

Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain.

Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.

Improved susceptibility weighted imaging at ultra-high field using bipolar multi-echo acquisition and optimized image processing: CLEAR-SWI.

PURPOSE: Susceptibility Weighted Imaging (SWI) has become established in the clinical investigation of stroke, microbleeds, tumor vascularization, calcification and iron deposition, but suffers from a number of shortcomings and artefacts. The goal of this study was to reduce the sensitivity of SWI to strong B1 and B0 inhomogeneities at ultra-high field to generate homogeneous images with increased contrast and free of common artefacts. All steps in SWI processing have been addressed - coil combination, phase unwrapping, image combination over echoes, phase filtering and homogeneity correction - and applied to an efficient bipolar multi-echo acquisition to substantially improve the quality of SWI. PRINCIPAL RESULTS: Our findings regarding the optimal individual processing steps lead us to propose a Contrast-weighted, Laplace-unwrapped, bipolar multi-Echo, ASPIRE-combined, homogeneous, improved Resolution SWI, or CLEAR-SWI. CLEAR-SWI was compared to two other multi-echo SWI methods and standard, single-echo SWI with the same acquisition time at 7 T in 10 healthy volunteers and with single-echo SWI in 13 patients with brain tumors. CLEAR-SWI had improved contrast-to-noise and homogeneity, reduced signal dropout and was not compromised by the artefacts which affected standard SWI in 10 out of 13 cases close to tumors (as assessed by expert raters), as well as generating T2* maps and phase images which can be used for Quantitative Susceptibility Mapping. In a comparison with other multi-echo SWI methods, CLEAR-SWI had the fewest artefacts, highest SNR and generally higher contrast-to-noise. MAJOR CONCLUSIONS: CLEAR-SWI eliminates the artefacts common in standard, single-echo SWI, reduces signal dropouts and improves image homogeneity and contrast-to-noise. Applied clinically, in a study of brain tumor patients, CLEAR-SWI was free of the artefacts which affected standard, single-echo SWI.

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.

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.

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.

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.

Whole-slice mapping of GABA and GABA+ at 7T via adiabatic MEGA-editing, real-time instability correction, and concentric circle readout.

An adiabatic MEscher-GArwood (MEGA)-editing scheme, using asymmetric hyperbolic secant editing pulses, was developed and implemented in a B1+-insensitive, 1D-semiLASER (Localization by Adiabatic SElective Refocusing) MR spectroscopic imaging (MRSI) sequence for the non-invasive mapping of γ-aminobutyric acid (GABA) over a whole brain slice. Our approach exploits the advantages of edited-MRSI at 7T while tackling challenges that arise with ultra-high-field-scans. Spatial-spectral encoding, using density-weighted, concentric circle echo planar trajectory readout, enabled substantial MRSI acceleration and an improved point-spread-function, thereby reducing extracranial lipid signals. Subject motion and scanner instabilities were corrected in real-time using volumetric navigators optimized for 7T, in combination with selective reacquisition of corrupted data to ensure robust subtraction-based MEGA-editing. Simulations and phantom measurements of the adiabatic MEGA-editing scheme demonstrated stable editing efficiency even in the presence of ±0.15 ppm editing frequency offsets and B1+ variations of up to ±30% (as typically encountered in vivo at 7T), in contrast to conventional Gaussian editing pulses. Volunteer measurements were performed with and without global inversion recovery (IR) to study regional GABA levels and their underlying, co-edited, macromolecular (MM) signals at 2.99 ppm. High-quality in vivo spectra allowed mapping of pure GABA and MM-contaminated GABA+ (GABA + MM) along with Glx (Glu + Gln), with high-resolution (eff. voxel size: 1.4 cm3) and whole-slice coverage in 24 min scan time. Metabolic ratio maps of GABA/tNAA, GABA+/tNAA, and Glx/tNAA were correlated linearly with the gray matter fraction of each voxel. A 2.15-fold increase in gray matter to white matter contrast was observed for GABA when enabling IR, which we attribute to the higher abundance of macromolecules at 2.99 ppm in the white matter than in the gray matter. In conclusion, adiabatic MEGA-editing with 1D-semiLASER selection is as a promising approach for edited-MRSI at 7T. Our sequence capitalizes on the benefits of ultra-high-field MRSI while successfully mitigating the challenges related to B0/B1+ inhomogeneities, prolonged scan times, and motion/scanner instability artifacts. Robust and accurate 2D mapping has been shown for the neurotransmitters GABA and Glx.

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.

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.

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.

Key clinical benefits of neuroimaging at 7T.

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

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.

Simultaneous mapping of metabolites and individual macromolecular components via ultra-short acquisition delay 1 H MRSI in the brain at 7T.

PURPOSE: Short-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. METHODS: The 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. RESULTS: The 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. CONCLUSION: The 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.