The natural variation in estrogen secretion throughout the female menstrual cycle impacts various organs, including estrogen receptor (ER)-expressed skeletal muscle. Many women commonly experience increased fatigue or reduced energy levels in the days leading up to and during menstruation, when blood estrogen levels decline. Yet, it remains unclear whether endogenous 17β-estradiol, a major estrogen component, directly affects the energy metabolism in skeletal muscle due to the intricate and fluctuating nature of female hormones. In this study, we employed 2D 31P FID-MRSI at 7T to investigate phosphoryl metabolites in the soleus muscle of a cohort of young females (average age: 28 ± 6 years, n = 7) during the early follicular (EF) and peri-ovulation (PO) phases, when their blood 17β-estradiol levels differ significantly (EF: 28 ± 18 pg/mL vs. PO: 71 ± 30 pg/mL, p < 0.05), while the levels of other potentially interfering hormones remain relatively invariant. Our findings reveal a reduction in ATP-referenced phosphocreatine (PCr) levels in the EF phase compared to the PO phase for all participants (5.4 ± 4.3%). Furthermore, we observe a linear correlation between muscle PCr levels and blood 17β-estradiol concentrations (r = 0.64, p = 0.014). Conversely, inorganic phosphate Pi and phospholipid metabolite GPC levels remain independent of 17β-estradiol but display a high correlation between the EF and PO phases (p = 0.015 for Pi and p = 0.0008 for GPC). The robust association we have identified between ATP-referenced PCr and 17β-estradiol suggests that 17β-estradiol plays a modulatory role in the energy metabolism of skeletal muscle.

Lafora disease is a fatal teenage-onset progressive myoclonus epilepsy and neurodegenerative disease associated with polyglucosan bodies. Polyglucosans are long-branched and as a result precipitation- and aggregation-prone glycogen. In mouse models, downregulation of glycogen synthase, the enzyme that elongates glycogen branches, prevents polyglucosan formation and rescues Lafora disease. Mouse work, however, has not yet revealed the mechanisms of polyglucosan generation, and few in vivo human studies have been performed. Here, non-invasive in vivo magnetic resonance spectroscopy (1H and 31P) was applied to test scan feasibility and assess neurotransmitter balance and energy metabolism in Lafora disease towards a better understanding of pathogenesis. Macromolecule-suppressed gamma-aminobutyric acid (GABA)-edited 1H magnetic resonance spectroscopy and 31P magnetic resonance spectroscopy at 3 and 7 tesla, respectively, were performed in 4 Lafora disease patients and a total of 21 healthy controls (12 for the 1H magnetic resonance spectroscopy and 9 for the 31PMRS). Spectra were processed using in-house software and fit to extract metabolite concentrations. From the 1H spectra, we found 33% lower GABA concentrations (P = 0.013), 34% higher glutamate + glutamine concentrations (P = 0.011) and 24% lower N-acetylaspartate concentrations (P = 0.0043) in Lafora disease patients compared with controls. From the 31P spectra, we found 34% higher phosphoethanolamine concentrations (P = 0.016), 23% lower nicotinamide adenine dinucleotide concentrations (P = 0.003), 50% higher uridine diphosphate glucose concentrations (P = 0.004) and 225% higher glucose 6-phosphate concentrations in Lafora disease patients versus controls (P = 0.004). Uridine diphosphate glucose is the substrate of glycogen synthase, and glucose 6-phosphate is its extremely potent allosteric activator. The observed elevated uridine diphosphate glucose and glucose 6-phosphate levels are expected to hyperactivate glycogen synthase and may underlie the generation of polyglucosans in Lafora disease. The increased glutamate + glutamine and reduced GABA indicate altered neurotransmission and energy metabolism, which may contribute to the disease's intractable epilepsy. These results suggest a possible basis of polyglucosan formation and potential contributions to the epilepsy of Lafora disease. If confirmed in larger human and animal model studies, measurements of the dysregulated metabolites by magnetic resonance spectroscopy could be developed into non-invasive biomarkers for clinical trials.

PURPOSE:Our aim was to design and build a 3T 31P/1H calf coil that is capable of providing both good 31P and 1H transmit and receive performance, as well as being capable of accommodating a near-infrared spectroscopy (NIRS) device for simultaneous NIRS data and MRI/MRS acquisition. METHOD:In this work, we propose a new 3T 31P/1H birdcage combination design consisting of two co-centrically positioned birdcages on the same surface to maximize transmit efficiency and sensitivity for both nuclei. The 31P birdcage is a high-pass birdcage, whereas the 1H birdcage is a low-pass one to minimize coupling. The diameter of the 31P/1H birdcage combination was designed to be large enough to accommodate a NIRS device for simultaneous NIRS data and MRI/MRS acquisition. RESULTS:The one-layer coil structure of the birdcage combination significantly streamlines the mechanical design and coil assembly process. Full-wave simulation results show that the 31P and 1H are very well decoupled with each other, and the 1H and 31P SNR surpasses that of their standalone counterparts in the central area. Experiment results show that the inclusion of a NIRS device does not significantly affect the performance of the coil, thus enabling simultaneous NIRS and MRI readouts during exercise. CONCLUSION:Our findings demonstrate the feasibility and effectiveness of this dual-tuned coil design for combined NIRS and MRS measurements, offering potential benefits for studying metabolic and functional changes in the skeletal muscle in vivo.

Reproducible and accurate fitting of the magnetic resonance spectrum is critical for estimating metabolite concentrations. We have previously developed a fitting software called ProFit-1D which was shown to fit 9.4T semi-LASER data from the human brain with high accuracy and precision. In this study, we adapted ProFit-1D to fit J-difference edited spectra acquired at a clinical field strength of 3T and to assessed its performance in simulated and in vivo data. ProFit-1D was adapted to fit J-difference edited data with alterations to the fitting range to exclude the 1.3 ppm lipid resonance, starting T2 relaxation constants, initial fit parameters, and adaptive spectral baseline determination. The accuracy of ProFit-1D was systematically evaluated on simulated GABA-edited and 2-hydroxyglutarate-edited (2HG-edited) data with different types of in vivo parameter variations and compared to that of LCModel and Gannet, two software commonly used to fit J-difference edited data. The precision of ProFit-1D was also evaluated in GABA-edited spectra acquired in vivo in the occipital cortex (OCC) and medial prefrontal cortex (mPFC) of healthy participants at 3T using subsets of averages and compared to that of LCModel and Gannet. The 2HG fit error was also evaluated for ProFit-1D in 2HG-edited spectra acquired in glioma patients and compared to that of LCModel. Overall, it was found that ProFit-1D generally produced fits with low parameter fit errors across a variety of parameter variations. GABA, glutamate plus glutamine (Glx), and 2HG levels were also more accurately estimated with ProFit-1D than with LCModel and Gannet across different spectral disturbances and simulated concentrations. ProFit-1D was found to be as precise as LCModel and more precise than Gannet in estimating GABA and Glx. 2HG fit errors were 45% lower with ProFit-1D than with LCModel. Thus, ProFit-1D was found to produce high-quality fits to J-difference edited data with high accuracy and precision. ### Competing Interest Statement The authors have declared no competing interest.

PURPOSE:The novel bilateral orthogonality generative acquisitions method has been developed for homogeneous T 2 * $$ {\mathrm{T}}_2^{\ast } $$ images without the effects of transmit field inhomogeneity using a parallel-transmission (pTx) system at 7 T. THEORY AND METHODS:A new method has been introduced using four low-angle gradient-echo (GRE) acquisitions to obtain homogeneous T 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast by removing the effects of transmit field inhomogeneity in the pTx system. First, two input images are obtained in circularly polarized mode and another mode in which the first transmit channel or channel group have an additional transmit phase of π. The last two acquisitions are single-channel acquisitions for a dual-channel system or single-channel group acquisitions for more than two channels. The introduced method is demonstrated in dual-channel and eight-channel pTx systems using phantom and whole-brain in vivo experiments. Noise performance of the proposed method is also tested against the ratio of two GRE acquisitions and the TIAMO (time-interleaved acquisitions of modes) method. RESULTS:Th new method results in more homogeneous T 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast in the final images than the compared methods, particularly in the low-intensity regions of circularly polarized-mode images for the images obtained via ratio of the two GRE acquisitions. CONCLUSION:The introduced method is easy to implement, robust, and provides homogeneous T 2 * $$ {\mathrm{T}}_2^{\ast } $$ images of the whole brain using pTx systems with any number of channels, compared with the ratio of the two GRE images and the TIAMO method.

AbstractGamma‐hydroxy‐butyric acid (GABA) and glutamate are neurotransmitters with essential importance for cognitive processing. Here, we investigate relationships between GABA, glutamate, and brain ß‐amyloid (Aß) burden before clinical manifestation of Alzheimer's disease (AD). Thirty cognitively healthy adults (age 69.9 ± 6 years) received high‐resolution atlas‐based 1H‐magnetic resonance spectroscopic imaging (MRSI) at ultra‐high magnetic field strength of 7 Tesla for gray matter‐specific assessment of GABA and glutamate. We assessed Aß burden with positron emission tomography and risk factors for AD. Higher gray matter GABA and glutamate related to higher Aß‐burden (ß = 0.60, p < 0.05; ß = 0.64, p < 0.02), with positive effect modification by apolipoprotein‐E‐epsilon‐4‐allele (APOE4) (p = 0.01‐0.03). GABA and glutamate negatively related to longitudinal change in verbal episodic memory performance (ß = ‐0.48; p = 0.02; ß = ‐0.50; p = 0.01). In vivo measures of GABA and glutamate reflect early AD pathology at old age, in an APOE4‐dependent manner. GABA and glutamate may represent promising biomarkers and potential targets for early therapeutic intervention and prevention.Highlights Gray matter‐specific metabolic imaging with high‐resolution atlas‐based MRSI at 7 Tesla. Higher GABA and glutamate relate to ß‐amyloid burden, in an APOE4‐dependent manner. Gray matter GABA and glutamate identify older adults with high risk of future AD. GABA and glutamate might reflect altered synaptic and neuronal activity at early AD.

Despite opposing insulin sensitivity and cardiometabolic risk, both athletes and patients with type 2 diabetes have increased skeletal myocyte fat storage: the so-called "athlete's paradox". In a parallel non-randomised, non-blinded trial (NCT03065140), we characterised and compared the skeletal myocyte lipid signature of 29 male endurance athletes and 30 patients with diabetes after undergoing deconditioning or endurance training respectively. The primary outcomes were to assess intramyocellular lipid storage of the vastus lateralis in both cohorts and the secondary outcomes were to examine saturated and unsaturated intramyocellular lipid pool turnover. We show that athletes have higher intramyocellular fat saturation with very high palmitate kinetics, which is attenuated by deconditioning. In contrast, type 2 diabetes patients have higher unsaturated intramyocellular fat and blunted palmitate and linoleate kinetics but after endurance training, all were realigned with those of deconditioned athletes. Improved basal insulin sensitivity was further associated with better serum cholesterol/triglycerides, glycaemic control, physical performance, enhanced post insulin receptor pathway signalling and metabolic sensing. We conclude that insulin-resistant, maladapted intramyocellular lipid storage and turnover in patients with type 2 diabetes show reversibility after endurance training through increased contributions of the saturated intramyocellular fatty acid pools. Clinical Trial Registration: NCT03065140: Muscle Fat Compartments and Turnover as Determinant of Insulin Sensitivity (MISTY).

Tobacco smoking is one of the main causes of premature death worldwide and quitting success remains low, highlighting the need to understand the neurobiological mechanisms underlying relapse. Preclinical models have shown that the amygdala and glutamate play an important role in nicotine addiction. The aims of this study were to compare glutamate and other metabolites in the amygdala between smokers and controls, and between different smoking states. Furthermore, associations between amygdalar metabolite levels and smoking characteristics were explored. A novel non -water -suppressed proton magnetic resonance spectroscopy protocol was applied to quantify neurometabolites in 28 male smokers (>= 15 cigarettes/day) and 21 non-smoking controls, matched in age, education, verbal IQ, and weekly alcohol consumption. Controls were measured once (baseline) and smokers were measured in a baseline state (1-3 h abstinence), during withdrawal (24 h abstinence) and in a satiation state (directly after smoking). Baseline spectroscopy data were compared between groups by independent t -tests or Mann -Whitney -U tests. Smoking state differences were investigated by repeated -measures analyses of variance (ANOVAs). Associations between spectroscopy data and smoking characteristics were explored using Spearman correlations. Good spectral quality, high anatomical specificity (98% mean gray matter) and reliable quantification of most metabolites of interest were achieved in the amygdala. Metabolite levels did not differ between groups, but smokers showed significantly higher glutamine levels at baseline than satiation. Glx levels were negatively associated with pack -years and smoking duration. In summary, this study provides first insights into the neurometabolic profile of the amygdala in smokers with high anatomical specificity. By applying proton magnetic resonance spectroscopy, neurometabolites in smokers during different smoking states and non-smoking controls were quantified reliably. A significant shift in glutamine levels between smoking states was detected, with lower concentrations in satiation than baseline. The negative association between Glx levels and smoking quantity and duration may imply altered glutamate homeostasis with more severe nicotine addiction.

Purpose: While two-dimensional (2D) in vivo spectroscopy yields rich information and has been successfully used in clinical trials, it requires a localization scheme that minimizes the impact of chemical shift displacement on J-coupling evolution, a robust frequency drift correction and dedicated processing and quantification methods. Considering these needs this study demonstrates a novel data acquisition and an analysis pipeline to quantify 16 metabolites in mmol/kg in the human brain using a 2D J-resolved metabolite-cycled (MC) semiLASER localization sequence at 9.4 T in the human brain. Methods: Metabolite spectra were acquired in vivo using the newly developed J-resolved MC semiLASER localization sequence with maximum echo sampling (MES) at 9.4 T. In order to account for the underlying macromolecular (MM) spectra in the acquired metabolite spectra, J-resolved MM spectra were acquired using a double inversion recovery (DIR) J-resolved MC semiLASER. Spectral fitting was performed with ProFit 2.0 using a simulated basis set from VesPA tailored to 2D J-resolved semiLASER with MES. Finally, metabolite concentrations were calculated using internal water referencing. Results: Tissue concentrations for 16 metabolites in mmol/kg are reported after correcting for number of protons, tissue content, and relaxation effects of both water and metabolites at 9.4T. Quantification results of spectra considering 8 and 2 averages per TE did not show any significant differences. Conclusion: 2D spectra of metabolites acquired at 9.4T and 2D MMs acquired at any field strength are presented for the first time. Basis set simulation and quantification of metabolites for metabolite spectra acquired using maximum-echo-sampled 2D J-resolved semiLASER was performed for the first time. The sensitivity in the detection of J-coupled metabolites such as glutamine, glucose or lactate. At ultra-high field, the acquisition duration of 2D MRS can be also substantially reduced since only a very low number of averages per TE are needed. ### Competing Interest Statement The authors have declared no competing interest.

Drawing inspiration from previous works using 1H FID MRSI, this study quantifies metabolite concentrations at 9.4 T in the human cerebrum of a volunteer cohort and performs a respective group analysis to derive region specific metabolite concentrations. Voxel-specific corrections were performed for both water and individual metabolites, as well as used tissue specific T1-relaxation times. Anatomical and magnetic resonance spectroscopic imaging data were collected using MP2RAGE and FID MRSI sequences, and subsequent data underwent a series of preprocessing techniques. Results showed consistent metabolite maps for key metabolites (NAA, tCr, Glu, tCho and mI), while instability in data quality was noted for lower slices. This study not only showcases the potential of metabolite quantification and mapping at 9.4 T but also underscores the necessity for meticulous data processing to ensure accurate metabolite representations. Comparisons with earlier works and single voxel results validate the methodologies adopted.Highlights ### Competing Interest StatementThe authors have declared no competing interest.

Background: Fat infiltration in skeletal muscle is related to declining muscle strength, whereas excess subcutaneous fat is implicated in the development of metabolic diseases. Methods: Using multi-slice axial T2-weighted (T2w) MR images, this retrospective study characterized muscle fat infiltration (MFI) and fat distribution in the lower extremity of 107 subjects (64M/43F, age 11–79 years) with diverse ethnicities (including White, Black, Latino, and Asian subjects). Results: MRI data analysis shows that MFI, evaluated by the relative intensities of the pixel histogram profile in the calf muscle, tends to increase with both age and BMI. However, statistical significance was found only for the age correlation in women (p < 0.002), and the BMI correlation in men (p = 0.04). Sex disparities were also seen in the fat distribution, which was assessed according to subcutaneous fat thickness (SFT) and the fibula bone marrow cross-sectional area (BMA). SFT tends to decrease with age in men (p < 0.01), whereas SFT tends to increase with BMI only in women (p < 0.01). In contrast, BMA tends to increase with age in women (p < 0.01) and with BMI in men (p = 0.04). Additionally, MFI is positively correlated with BMA but not with SFT, suggesting that compromised bone structure may contribute to fat infiltration in the surrounding skeletal muscle. Conclusions: The findings of this study highlight a sex factor affecting MFI and fat distribution, which may offer valuable insights into effective strategies to prevent and treat MFI in women versus men.

PURPOSE:To develop and evaluate a novel method for computationally efficient reconstruction from noisy MR spectroscopic imaging (MRSI) data. METHODS:The proposed method features (a) a novel strategy that jointly learns a nonlinear low-dimensional representation of high-dimensional spectroscopic signals and a neural-network-based projector to recover the low-dimensional embeddings from noisy/limited data; (b) a formulation that integrates the forward encoding model, a regularizer exploiting the learned representation, and a complementary spatial constraint; and (c) a highly efficient algorithm enabled by the learned projector within an alternating direction method of multipliers (ADMM) framework, circumventing the computationally expensive network inversion subproblem. RESULTS:The proposed method has been evaluated using simulations as well as in vivo   1 $$ {}^1 $$ H and   31 $$ {}^{31} $$ P MRSI data, demonstrating improved performance over state-of-the-art methods, with about 6 × $$ \times $$ fewer averages needed than standard Fourier reconstruction for similar metabolite estimation variances and up to 100 × $$ \times $$ reduction in processing time compared to a prior neural network constrained reconstruction method. Computational and theoretical analyses were performed to offer further insights into the effectiveness of the proposed method. CONCLUSION:A novel method was developed for fast, high-SNR spatiospectral reconstruction from noisy MRSI data. We expect our method to be useful for enhancing the quality of MRSI or other high-dimensional spatiospectral imaging data.

Four basis transmit k-space trajectories (a single variable density spiral-in, a two stack of variable density spiral-in, a three stack of variable density spiral-in and a SPINS trajectory) were optimized for pTx radiofrequency pulse design in order to match the excitation target pattern. The parameter to be optimized where the parameter of the analytical equations of the basis trajectories. The procedure was tested on local excitation and whole brain-like excitation target patterns. Optimized trajectories enabled considerably improved radiofrequency pulse performance, compared to radiofrequency pulses based on unsuited trajectories. The optimization code is available online as open source (https://github.com/ole1965/workflow_OTUP.git).

• Purpose This study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4 T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and its reproducibility of metabolite ratio (/tCr) maps for 10 brain metabolites. • Methods Measurements were performed twice on five volunteers using a non-accelerated FID MRSI 2D sequence at 9.4 T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, CRLB and the concentration ratio maps were investigated. Intra-subject, inter-session coefficient of variation of the mean metabolite ratios (/tCr) of each slice was calculated. • Results L2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected. Transversal, sagittal and coronal of many metabolite ratio maps correspond to anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Additionally, results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement. • Conclusion Concentration ratio maps (/tCr) for 4 metabolites (tCho, NAA, Glu, mI) spanning the majority and six metabolites (NAAG, GABA, GSH, Tau, Gln, Asp) covering 32 mm in the upper part of the brain were acquired at 9.4 T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline.

Glutamate is the major excitatory transmitter in the brain and malfunction of the related metabolism is associated with various neurological diseases and disorders. The observation of labeling changes in the spectra after the administration of a 13C labelled tracer is a common tool to gain better insights into the function of the metabolic system. But so far, only a very few studies presenting the labeling effects in more than two voxels to show the spatial dependence of metabolism.In the present work, the labeling effects were measured in a transversal plane in the human brain using ultra-short TE and TR 1H FID-MRSI. The measurement set-up was most simple: The [1-13C]Glc was administered orally instead of intravenous and the spectra were measured with a pure 1H technique without the need of a 13C channel (as Boumezbeur et al. demonstrated in 2004). Thus, metabolic maps and enrichment curves could be obtained for more metabolites and in more voxels than ever before in human brain. Labeling changes could be observed in [4–13C]glutamate, [3–13C]glutamate+glutamine, [2–13C]glutamate+glutamine, [4–13C]glutamine, and [3–13C]aspartate with a high temporal (3.6 min) and spatial resolution (32 × 32 grid with nominal voxel size of 0.33 µL) in five volunteers.

Simultaneous assessment of the brain and the cervical spinal cord is of great importance in clinical decision making in areas such as head & neck cancer, traumatic injury, multiple sclerosis or stroke. The small diameter of the cervical spinal cord necessitates high spatial resolution, so there is a growing need to provide 7T simultaneous head and cervical spinal cord imaging, to greatly benefit from increased signal-to-noise ratio and contrast at ultrahigh field. In this work, we developed a 7T 16ch transceiver array that is capable for simultaneous and high-resolution brain and cervical spinal cord imaging.

Brain energy metabolism, for which glucose is the main fuel, is essential not only for normal brain function but also for its active role in the mechanisms that underly brain diseases. Deuterium Metabolic Imaging (DMI) is a promising MR modality for investigating whole brain energy metabolism in humans at ultra-high field. In this study, we explore the potential of DMI in the human brain in vivo at 7T. We present whole brain 3D DMI maps of well-resolved deuterated ( 2 H) metabolite resonances of water, glucose and glutamate/glutamine (Glx) following oral administration of [6,6’- 2 H 2 ]-labelled glucose.

In in vivo 1H-MRSI of the prostate, small matrix sizes can cause voxel bleeding extending to regions far from a voxel, dispersing a signal of interest outside that voxel and mixing extra-prostatic residual lipid signals into the prostate. To resolve this problem, we developed a three-dimensional overdiscretized reconstruction method. Without increasing the acquisition time from current 3D MRSI acquisition methods, this method is aimed to improve the localization of metabolite signals in the prostate without compromising on SNR. The proposed method consists of a 3D spatial overdiscretization of the MRSI grid, followed by noise decorrelation with small random spectral shifts and weighted spatial averaging to reach a final target spatial resolution. We successfully applied the three-dimensional overdiscretized reconstruction method to 3D prostate 1H-MRSI data at 3T. Both in phantom and in vivo, the method proved to be superior to conventional weighted sampling with Hamming filtering of k-space. Compared with the latter, the overdiscretized reconstructed data with smaller voxel size showed up to 10% less voxel bleed while maintaining higher SNR by a factor of 1.87 and 1.45 in phantom measurements. For in vivo measurements, within the same acquisition time and without loss of SNR compared with weighted k-space sampling and Hamming filtering, we achieved increased spatial resolution and improved localization in metabolite maps.

MR spectroscopy (MRS) is capable of probing information on metabolites within the body but suffers from an inherently low sensitivity. In the case of proton (1H) MRS, significant spectral overlap also hampers accurate quantification. Therefore, the significant advantages provided by ultra-high magnetic field strengths such as the increased signal-to-noise ratio and spectral dispersion are especially beneficial for MRS. Despite these benefits, technical challenges remain that need to be addressed to allow for ultra-high field MRS to reach its full potential. This chapter is divided into three parts. The first part will discuss the benefits, challenges, and ways to address these issues. The second part will focus on (1H) MRS methods and clinical applications, while the last part will focus on carbon (13C), phosphorous (31P), and deuterium (2H) MRS methods and applications. The chapter is limited to MRS in the human brain at field strengths of 7 and 9.4 T.