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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'- 2 H 2 ]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2 H MRSI (DMI) and 1 H 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'- 2 H 2 ]-glucose administration using time-resolved 3D 2 H FID-MRSI with elliptical phase encoding at 7T and 3D 1 H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T., Results: One hour after oral tracer administration regionally averaged deuterium labeled Glx 4 concentrations and the dynamics were not significantly different over all participants between 7T 2 H DMI and 3T 1 H 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 Glc 6 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 2 H and 1 H data points a weak to moderate negative correlation was observed for Glx 4 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 Glc 6 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 1 H 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 2 H 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., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rupert Lanzenberger reports financial support was provided by Siemens Healthcare AG. Rupert Lanzenberger reports a relationship with BM Health GmbH that includes: equity or stocks. R. Lanzenberger received investigator-initiated research funding from Siemens Healthcare regarding clinical research using PET/MR. He is a shareholder of the start-up company BM Health GmbH since 2019., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

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 B 0 /B 1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage., (© 2021 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

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., (© 2019 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Proton MRS ( 1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B 0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: Inhomogeneities in the static magnetic field (B 0 ) 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 B 0 -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 B 0 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 cm 3 versus 0.25 cm 3 resolution. This effect was much more pronounced at higher and less homogenous B 0 (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 B 0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B 0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field., (© 2019 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

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.

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 mm 2 , 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., (© 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

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., (© 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.)

MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B 0 /B 1 + 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.3 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., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Long echo time (TE) MR spectroscopy (MRS) sequences are sensitive only to metabolites of low molecular weight. At shorter TE, significantly more metabolite signals are detectable, including broad signals of high-molecular-weight macromolecules (MMs). Although the presence of MM resonances can bias metabolite quantification at short TE, proper quantification of MMs is important since MMs themselves may serve as potentially valuable biomarkers for many pathologies. We have therefore developed an FID-based 2D-MR Spectroscopic Imaging (2D-MRSI) sequence to map MMs in healthy brain tissue at 7 T within a scan time of ~17 min and a repetition time of 879 ms. This 2D-MRSI technique provides MM maps over a whole slice (i.e., including cortical gray matter) at an ultra-short acquisition delay of 1.3 ms, using double inversion for efficient nulling of low-molecular-weight metabolites. The optimal sequence parameters were estimated using Bloch simulations, phantom testing, and in vivo validation. The acquired in vivo MM spectra (n=6) included nine distinct MM peaks in the range of ~0.9-3.7 ppm. The measured average MM spectrum was incorporated into the LCModel basis set and utilized for further quantification of MRSI data sets without metabolite nulling, which were acquired in five additional volunteers. The quantification results for two basis sets, one including the MMs and one without MM spectrum, were compared. Due to the high spectral resolution and full signal detection provided by the FID-MRSI sequence, we could successfully map five important brain metabolites. Most quantified metabolite signal amplitudes were significantly lower since the inclusion of MMs into the basis set corrected the overestimation of metabolite signals. The precision of fit (i.e., Cramér Rao lower bounds) remained unchanged. Our MM maps show that the overall MM contribution was higher in gray matter than in white matter. In conclusion, the acquired MM spectrum improved the accuracy of metabolite quantification and allowed the acquisition of high spatial resolution maps of five major brain metabolites and also MMs., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

This work presents a new approach for high-resolution MRSI of the brain at 7 T in clinically feasible measurement times. Two major problems of MRSI are the long scan times for large matrix sizes and the possible spectral contamination by the transcranial lipid signal. We propose a combination of free induction decay (FID)-MRSI with a short acquisition delay and acceleration via in-plane two-dimensional generalised autocalibrating partially parallel acquisition (2D-GRAPPA) with adiabatic double inversion recovery (IR)-based lipid suppression to allow robust high-resolution MRSI. We performed Bloch simulations to evaluate the magnetisation pathways of lipids and metabolites, and compared the results with phantom measurements. Acceleration factors in the range 2-25 were tested in a phantom. Five volunteers were scanned to verify the value of our MRSI method in vivo. GRAPPA artefacts that cause fold-in of transcranial lipids were suppressed via double IR, with a non-selective symmetric frequency sweep. The use of long, low-power inversion pulses (100 ms) reduced specific absorption rate requirements. The symmetric frequency sweep over both pulses provided good lipid suppression (>90%), in addition to a reduced loss in metabolite signal-to-noise ratio (SNR), compared with conventional IR suppression (52-70%). The metabolic mapping over the whole brain slice was not limited to a rectangular region of interest. 2D-GRAPPA provided acceleration up to a factor of nine for in vivo FID-MRSI without a substantial increase in g-factors (<1.1). A 64 × 64 matrix can be acquired with a common repetition time of ~1.3 s in only 8 min without lipid artefacts caused by acceleration. Overall, we present a fast and robust MRSI method, using combined double IR fat suppression and 2D-GRAPPA acceleration, which may be used in (pre)clinical studies of the brain at 7 T., (© 2015 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Gaucher disease type 1 (GD1) is an autosomal recessive lysosomal storage disorder, characterised by accumulation of glycosphingolipids in visceral organs. Although considered non-neuronopathic neurological involvement has been reported in single cases. The aim of our study was to investigate central and peripheral nervous system involvement in patients with GD1. We investigated nine unrelated patients with GD1 by three-dimensional cerebral 1H-magnetic resonance spectroscopic imaging and clinical and neurophysiological tests. We found an increased choline level on MRS in four patients. One of these patients had mixed axonal neuropathy and subclinical involvement of the central somatosensory tract as well as monoclonal gammopathy. One patient with normal cerebral choline levels had evidence of bilateral carpal tunnel syndrome upon neurophysiological exam. The N370S mutation was found in 11 out of 18 alleles. Three patients were compound heterozygous for the L444P mutation. There was no correlation between increased cerebral choline levels and type of mutations. MRS findings suggest that in patients with classical non-neuronopathic GD1, the brain is involved at a subclinical level in some patients.

In a systematic study on the interdependence of linewidth, signal-to-noise ratio (SNR), and spatial resolution in 3D proton spectroscopic imaging ((1)H-SI) at 3 T, we demonstrate reduced linewidths with increased spatial resolution due to reduced magnetic inhomogeneity within the brain. High-precision quantitative data (0.75-0.094 cm(3)) were obtained for all resolutions, enabling the creation of metabolic maps that display details such as the ventricles, sulci, and gyri. High-resolution (1)H-SI allows differences in metabolic ratios to be estimated for anatomically defined regions in gray (GM) and white matter (WM). Seven distinct regions in a healthy brain were anatomically segmented and their metabolic ratios were compared quantitatively. Data from a tumor patient are also presented to demonstrate potential clinical applications. Because of the high resolution, the metabolite ratios could be determined for distinct pathologic regions within the tumor and its surroundings. The method was additionally applied to a patient with patchy Pelizaeus Merzbacher disease (PMD), and compared to single-voxel spectroscopy performed in the same session. High-resolution SI data were demonstrated in our study to allow the direct matching of anatomic and metabolic images. This may enhance the clinical value of (1)H-SI., (Copyright 2003 Wiley-Liss, Inc.)