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Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.

With a 40‐year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past., This work defines terms and explains concepts used to describe all aspects of MR spectroscopy, starting from the definition of the MR signal and its theoretical basis to acquisition methods, processing and quantification procedures, as well as terms involved in describing results, including quality aspects, reproducibility or indications of error. Also featured are specific suggestions for future use of terms where multiple conventions have emerged or previously coexisted.

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article. ispartof: RADIOLOGY vol:295 issue:1 pages:171-180 ispartof: location:United States status: published

Purpose: To investigate neuronal dysfunction in the thalami of juvenile myoclonic epilepsy (JME) by using proton magnetic resonance spectroscopy (MRS). Methods: We performed single-voxel proton MRS over the right and the left thalami of 15 consecutive patients (10 women, 5 men) with JME (mean age 20.3 years) and 16 healthy volunteers (10 women, 6 men) (mean age 24.5 years). All patients had seizure onset in late childhood-teenage, normal neurologic examination, typical electroencephalogram (EEG) of JME and normal magnetic resonance imaging (MRI). We determined N-acetylaspartate (NAA) values and NAA over creatine-phosphocreatine (Cr) values. Mann-Whitney U-test was used to evaluate group differences. Results: Group analysis showed that echo time (TE) 270 integral value of NAA over left thalamus were significantly decreased in JME patients as compared with controls (34.6033 +/- 15.8386; 48.0362 +/- 22.2407, respectively, P = 0.019). Also group analysis showed that thalami NAA/Cr ratios were significantly decreased in JME patients (right side, 2.21 +/- 1.07; left side 2.00 +/- 0.72) as compared with controls (right side, 3.45 +/- 1.50; left side, 3.08. +/- 1.60; P = 0.011 and P = 0.030, respectively). Conclusion: In the previous studies, NAA values inpatients with JME found that they were not statistically lower in thalami than control group. But, in our study, NAA value was found tow as well. It has been known that NAA is a neuronal marker and hence it is a valuable metabolite in the neuron physiopathology. As a result, in the patients with JME we tried to support the theory that the underlying mechanism of the generalized seizures was the abnormal thalamocortical circuity, determining the thalamic neuronal dysfunction in MRS statistically.

The purpose of this work was to harmonize data acquisition and post-processing of single voxel proton MRS (H-1-MRS) at 7T, and to determine metabolite concentrations and the accuracy and reproducibility of metabolite levels in the adult human brain. This study was performed in compliance with local institutional human ethics committees. The same seven subjects were each examined twice using four different 7T MR systems from two different vendors using an identical semi-localization by adiabatic selective refocusing spectroscopy sequence. Neurochemical profiles were obtained from the posterior cingulate cortex (gray matter, GM) and the corona radiata (white matter, WM). Spectra were analyzed with LCModel, and sources of variation in concentrations (subject', institute' and random') were identified with a variance component analysis. Concentrations of 10-11 metabolites, which were corrected for T-1, T-2, magnetization transfer effects and partial volume effects, were obtained with mean Cramer-Rao lower bounds below 20%. Data variances and mean concentrations in GM and WM were comparable for all institutions. The primary source of variance for glutamate, myo-inositol, scyllo-inositol, total creatine and total choline was between subjects. Variance sources for all other metabolites were associated with within-subject and system noise, except for total N-acetylaspartate, glutamine and glutathione, which were related to differences in signal-to-noise ratio and in shimming performance between vendors. After multi-center harmonization of acquisition and post-processing protocols, metabolite concentrations and the sizes and sources of their variations were established for neurochemical profiles in the healthy brain at 7T, which can be used as guidance in future studies quantifying metabolite and neurotransmitter concentrations with H-1-MRS at ultra-high magnetic field. Copyright (c) 2015 John Wiley & Sons, Ltd.