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

•The reproducibility assessment of magnetic resonance spectroscopy was explored.•CV and ICC showed good reliability of within- and between- scanning sessions.•Bland-Altman plots indicated strong agreement in the repeated measurements.•Pearson correlation coefficients showed great reproducibility across three machines.•It revealed higher reproducibility for the intra-vendor than the inter-vendor. Proton magnetic resonance spectroscopy (1H-MRS) has potential in clinical diagnosis and understanding the mechanism of illnesses. However, its application is limited by the lack of standardization in data acquisition and processing across time points and between different magnetic resonance imaging (MRI) system vendors. This study examines whether metabolite concentrations obtained from different sessions, scanner models, and vendors can be reliably reproduced and combined for diagnostic analysis-an important consideration for rare disease research. Participants underwent magnetic resonance scanning once on two separate days within one week (one session per day, each including two 1H-MRS scans without subject movement) on each machine. Absolute metabolite concentrations were analyzed for reliability of within- and between- session using the coefficient of variation (CV), intraclass correlation coefficient (ICC) and Bland-Altman (BA) plot, and for reproducibility across the machines using the Pearson correlation coefficient. As for within- and between- session, most of the CV values for a group of all the first or second scans of a session, and from each session were below 20 %, and most of ICCs ranged from moderate (0.4≤ICC<0.59) to excellent (ICC≥0.75), which indicated high reliability. Most of the BA plots had the line of equality between 95 % confidence interval of bias (mean difference), therefore the differences over scanning time could be negligible. Majority of the Pearson correlation coefficients approached 1 with statistical significance (P < 0.001), showing high reproducibility across the three scanners. Additionally, the intra-vendor reproducibility was greater than the inter-vendor ones. [Display omitted]

Alterations in glutamatergic neurotransmission are implicated in the pathophysiology of depression, and the glutamatergic system represents a treatment target for depression. To summarize the nature of glutamatergic alterations in patients with depression, we conducted a meta-analysis of proton magnetic resonance (1H-MRS) spectroscopy studies examining levels of glutamate. We used the search terms: depress* AND (MRS OR “magnetic resonance spectroscopy”). The search was performed with MEDLINE, Embase, and PsycINFO. The inclusion criteria were 1H-MRS studies comparing levels of glutamate + glutamine (Glx), glutamate, or glutamine between patients with depression and healthy controls. Standardized mean differences (SMD) were calculated to assess group differences in the levels of glutamatergic neurometabolites. Forty-nine studies met the eligibility criteria, which included 1180 patients and 1066 healthy controls. There were significant decreases in Glx within the medial frontal cortex (SMD = −0.38; 95% CI, −0.69 to −0.07) in patients with depression compared with controls. Subanalyses revealed that there was a significant decrease in Glx in the medial frontal cortex in medicated patients with depression (SMD = −0.50; 95% CI, −0.80 to −0.20), but not in unmedicated patients (SMD = −0.27; 95% CI, −0.76 to 0.21) compared with controls. Overall, decreased levels of glutamatergic metabolites in the medial frontal cortex are linked with the pathophysiology of depression. These findings are in line with the hypothesis that depression may be associated with abnormal glutamatergic neurotransmission.

The structural role of pectins in plant primary cell walls is not yet well understood because of the complex and disordered nature of the cell wall polymers. We recently introduced multidimensional solid-state nuclear magnetic resonance spectroscopy to characterize the spatial proximities of wall polysaccharides. The data showed extensive cross peaks between pectins and cellulose in the primary wall of Arabidopsis (Arabidopsis thaliana), indicating subnanometer contacts between the two polysaccharides. This result was unexpected because stable pectin-cellulose interactions are not predicted by in vitro binding assays and prevailing cell wall models. To investigate whether the spatial contacts that give rise to the cross peaks are artifacts of sample preparation, we now compare never-dried Arabidopsis primary walls with dehydrated and rehydrated samples. Onedimensional ¹³C spectra, two-dimensional ¹³C-¹³C correlation spectra, water-polysaccharide correlation spectra, and dynamics data all indicate that the structure, mobility, and intermolecular contacts of the polysaccharides are indistinguishable between never-dried and rehydrated walls. Moreover, a partially depectinated cell wall in which 40% of homogalacturonan is extracted retains cellulose-pectin cross peaks, indicating that the cellulose-pectin contacts are not due to molecular crowding. The cross peaks are observed both at −20°C and at ambient temperature, thus ruling out freezing as a cause of spatial contacts. These results indicate that rhamnogalacturonan I and a portion of homogalacturonan have significant interactions with cellulose microfibrils in the native primary wall. This pectin-cellulose association may be formed during wall biosynthesis and may involve pectin entrapment in or between cellulose microfibrils, which cannot be mimicked by in vitro binding assays.

In schizophrenia, abnormal neural metabolite concentrations may arise from cortical damage following neuroinflammatory processes implicated in acute episodes. Inflammation is associated with increased glutamate, whereas the antioxidant glutathione may protect against inflammation-induced oxidative stress. We hypothesized that patients with stable schizophrenia would exhibit a reduction in glutathione, glutamate, and/or glutamine in the cerebral cortex, consistent with a post-inflammatory response, and that this reduction would be most marked in patients with “residual schizophrenia”, in whom an early stage with positive psychotic symptoms has progressed to a late stage characterized by long-term negative symptoms and impairments. We recruited 28 patients with stable schizophrenia and 45 healthy participants matched for age, gender, and parental socio-economic status. We measured glutathione, glutamate and glutamine concentrations in the anterior cingulate cortex (ACC), left insula, and visual cortex using 7T proton magnetic resonance spectroscopy (MRS). Glutathione and glutamate were significantly correlated in all three voxels. Glutamine concentrations across the three voxels were significantly correlated with each other. Principal components analysis (PCA) produced three clear components: an ACC glutathione–glutamate component; an insula-visual glutathione–glutamate component; and a glutamine component. Patients with stable schizophrenia had significantly lower scores on the ACC glutathione–glutamate component, an effect almost entirely leveraged by the sub-group of patients with residual schizophrenia. All three metabolite concentration values in the ACC were significantly reduced in this group. These findings are consistent with the hypothesis that excitotoxicity during the acute phase of illness leads to reduced glutathione and glutamate in the residual phase of the illness.

Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes but is hindered by a lack of automated annotation and standardized methods for structure elucidation of candidate disease biomarkers. Here we describe a system for identifying molecular species derived from nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and data modeling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as Statistical Total Correlation Spectroscopy (STOCSY), Subset Optimization by Reference Matching (STORM) and Resolution-Enhanced (RED)-STORM to identify other signals in the NMR spectra relating to the same molecule. It also uses two-dimensional NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multi-dimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take 2 or 3 days. This approach to biomarker discovery is efficient and cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. It requires a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to perform solid phase extraction (SPE), liquid chromatography (LC) fraction collection, LC-NMR-mass spectroscopy and one-dimensional and two-dimensional NMR experiments. Nicholson et al. describe a system for identifying molecular species derived from nuclear magnetic resonance spectroscopy-based metabolic phenotyping studies, with detailed information on sample preparation, data acquisition and modeling. They recommend eight modular workflows to be followed in sequential order.

Background Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis. Methods Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality. Results Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (Δ H24-H0 ) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients. Conclusions Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes. Trial registration All human serum samples were collected and stored, provided by the “center of biologic resources for liver disease”, in Jean Verdier Hospital, Bondy, France (BB-0033-00027).

Spectral editing allows direct measurement of low-concentration metabolites, such as GABA, glutathione (GSH) and lactate (Lac), relevant for understanding brain (patho)physiology. The most widely used spectral editing technique is MEGA-PRESS, which has been diversely implemented across research sites and vendors, resulting in variations in the final resolved edited signal. In this paper, we describe an effort to develop a new universal MEGA-PRESS sequence with HERMES functionality for the major MR vendor platforms with standardized RF pulse shapes, durations, amplitudes and timings. New RF pulses were generated for the universal sequence. Phantom experiments were conducted on Philips, Siemens, GE and Canon 3 T MRI scanners using 32-channel head coils. In vivo experiments were performed on the same six subjects on Philips and Siemens scanners, and on two additional subjects, one on GE and one on Canon scanners. On each platform, edited MRS experiments were conducted with the vendor-native and universal MEGA-PRESS sequences for GABA (TE = 68 ms) and Lac editing (TE = 140 ms). Additionally, HERMES for GABA and GSH was performed using the universal sequence at TE = 80 ms. The universal sequence improves inter-vendor similarity of GABA-edited and Lac-edited MEGA-PRESS spectra. The universal HERMES sequence yields both GABA- and GSH-edited spectra with negligible levels of crosstalk on all four platforms, and with strong agreement among vendors for both edited spectra. In vivo GABA+/Cr, Lac/Cr and GSH/Cr ratios showed relatively low variation between scanners using the universal sequence. In conclusion, phantom and in vivo experiments demonstrate successful implementation of the universal sequence across all four major vendors, allowing editing of several metabolites across a range of TEs.

•Recent advances in MRS now allow for event-related functional MRS, with temporal resolution in the order of seconds.•We provide a user guide for experimental design, data acquisition and analysis considerations for event-related fMRS.•We use simulations to determine optimal settings to detect event-related changes in GABA.•We provide a critical perspective on the appropriate interpretation of event-related fMRS. Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. “Single-voxel” MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

Many developmental processes, such as plasticity and aging, or pathological processes such as neurological diseases are characterized by modulations of specific cellular types and their microstructures. Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) is a powerful technique for probing microstructure, yet its information arises from the ubiquitous, non-specific water signal. By contrast, diffusion-weighted Magnetic Resonance Spectroscopy (DW-MRS) allows specific characterizations of tissues such as brain and muscle in vivo by quantifying the diffusion properties of MR-observable metabolites. Many brain metabolites are predominantly intracellular, and some of them are preferentially localized in specific brain cell populations, e.g., neurons and glia. Given the microstructural sensitivity of diffusion-encoding filters, investigation of metabolite diffusion properties using DW-MRS can thus provide exclusive cell and compartment-specific information. Furthermore, since many models and assumptions are used for quantification of water diffusion, metabolite diffusion may serve to generate a-priori information for model selection in DW-MRI. However, DW-MRS measurements are extremely challenging, from the acquisition to the accurate and correct analysis and quantification stages. In this review, we survey the state-of-the-art methods that have been developed for the robust acquisition, quantification and analysis of DW-MRS data and discuss the potential relevance of DW-MRS for elucidating brain microstructure in vivo. The review highlights that when accurate data on the diffusion of multiple metabolites is combined with accurate computational and geometrical modeling, DW-MRS can provide unique cell-specific information on the intracellular structure of brain tissue, in health and disease, which could serve as incentives for further application in vivo in human research and clinical MRI. •Diffusion-weighted MRS (DW-MRS) allows to investigate brain metabolite diffusion.•Most brain metabolites are predominantly intracellular and cell specific.•Diffusion properties of brain metabolites provide exclusive cell-specific information.•The most recent methods for DW-MRS data acquisition and analysis are reviewed.•The potential relevance of DW-MRS for elucidating brain microstructure is discussed.