1D-spectral editing and 2D multispectral in vivo1H-MRS and 1H-MRSI - Methods and applications

SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform

Multimodal neuroimaging data of various brain disorders provides valuable information to understand brain function in health and disease. Various neuroimaging-based databases have been developed that mainly consist of volumetric magnetic resonance imaging (MRI) data. We present the comprehensive web-based neuroimaging platform "SWADESH" for hosting multi-disease, multimodal neuroimaging, and neuropsychological data along with analytical pipelines. This novel initiative includes neurochemical and magnetic susceptibility data for healthy and diseased conditions, acquired using MR spectroscopy (MRS) and quantitative susceptibility mapping (QSM) respectively. The SWADESH architecture also provides a neuroimaging database which includes MRI, MRS, functional MRI (fMRI), diffusion weighted imaging (DWI), QSM, neuropsychological data and associated data analysis pipelines. Our final objective is to provide a master database of major brain disease states (neurodegenerative, neuropsychiatric, neurodevelopmental, and others) and to identify characteristic features and biomarkers associated with such disorders.

How can I measure brain acetylcholine levels in vivo? Advantages and caveats of commonly used approaches

The neurotransmitter acetylcholine (ACh) plays a central role in the regulation of multiple cognitive and behavioral processes, including attention, learning, memory, motivation, anxiety, mood, appetite, and reward. As a result, understanding ACh dynamics in the brain is essential for elucidating the neural mechanisms underlying these processes. In vivo measurements of ACh in the brain have been challenging because of the low concentrations and rapid turnover of this neurotransmitter. Here, we review a number of techniques that have been developed to measure ACh levels in the brain in vivo. We follow this with a deeper focus on use of genetically encoded fluorescent sensors coupled with fiber photometry, an accessible technique that can be used to monitor neurotransmitter release with high temporal resolution and specificity. We conclude with a discussion of methods for analyzing fiber photometry data and their respective advantages and disadvantages. The development of genetically encoded fluorescent ACh sensors is revolutionizing the field of cholinergic signaling, allowing temporally precise measurement of ACh release in awake, behaving animals. Use of these sensors has already begun to contribute to a mechanistic understanding of cholinergic modulation of complex behaviors.

Selective filtration of NMR signals arising from weakly- and strongly-coupled spin systems

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for analyzing chemical and biological systems. However, in complex solutions with similar molecular components, NMR signals can overlap, making it challenging to distinguish and quantify individual species. In this paper, we introduce new spectral editing sequences that exploit the differences in nuclear spin interactions (J-couplings) between weakly- and strongly-coupled two-spin systems. These sequences selectively attenuate or nullify undesired spin magnetization while they preserve the desired signals, resulting in simplified NMR spectra and potentially facilitating single-species imaging applications. We demonstrate the effectiveness of our approach using a 31P spectral filtration method on a model system of nicotinamide dinucleotide (NAD), which exists in oxidized (NAD+) and reduced (NADH) forms. The presented sequences are robust to field inhomogeneity, do not require additional sub-spectra, and retain a significant portion of the original signal.

Neurochemical correlations in short echo time proton magnetic resonance spectroscopy

Neurochemical concentrations determined by magnetic resonance spectroscopy (MRS) have been treated as statistically independent measurements in various clinical MRS studies. However, spectral overlap, independent of any biological effects, could lead to significant correlations between neurochemical concentrations extracted from spectral fitting of MRS data, confounding determination of correlations of biological origin. Short echo time (TE) proton MRS spectra are very crowded because of the comparatively narrow chemical shift dispersion of proton nuclear spins. In this study, the complex neurochemical correlations of spectral origin in short-TE MRS spectra were quantified. The effects of macromolecules and the background spectral baseline on metabolite-metabolite correlations were also analyzed. Our results demonstrate the importance of factoring in spectral correlations when correlating overlapping metabolite signals in short-TE spectra with clinical parameters.

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non-destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR-based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high-quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR-based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

High-field ex vivo and in vivo two-dimensional nuclear magnetic resonance spectroscopy in murine brain: Resolving and exploring the molecular environment

The structural and chemical complexities within the brain pose a challenge that few noninvasive techniques can tackle with the dexterity of nuclear magnetic resonance (NMR) spectroscopy. Still, even with the advent of ultrahigh fields and of cryogenically cooled coils for in vivo research, the superposition of metabolic resonances arising from the brain remains a challenge. The present study explores the potential to tackle this milieu using a combination of two-dimensional (2D) NMR techniques, implemented on murine brains in vivo at 15.2 T and ex vivo at 14.1 T. While both experiments were affected by substantial inhomogeneous broadenings conveying distinct elongated lineshapes to the cross-peaks, the ability of increased fields to resolve off-diagonal resonances was clear. A comparison between the corresponding conventional and double quantum-filtered correlated spectroscopy traces enabled an improved assignment of in vivo resonances on the basis of more sensitive ex vivo 2D acquisitions, foremost on the basis of homonuclear cross-relaxation-driven correlations for peaks resonating downfield from water, and of heteronuclear correlations at natural abundance for the upfield protons. With the aid of such 2D correlations approximately 29 metabolites could be resolved and identified. This enhanced resolution was used to explore features related to the metabolites' diffusivities, their exposure to water, and their facility to undergo magnetization transfers to amide/amine/hydroxyl resonances. Cross-peaks from main murine brain biomolecules, including choline, creatine, γ-aminobutyric acid, N-acetyl aspartate, glutamine, and glutamate, showed enhancements in several of these various features, opening interesting vistas about metabolite compartmentalization as viewed by these 2D NMR experiments.

Real-Time Monitoring of Neurotransmitters in the Brain of Living Animals

Neurotransmitters, as important chemical small molecules, perform the function of neural signal transmission from cell to cell. Excess concentrations of neurotransmitters are often closely associated with brain diseases, such as Alzheimer's disease, depression, schizophrenia, and Parkinson's disease. On the other hand, the release of neurotransmitters under the induced stimulation indicates the occurrence of reward-related behaviors, including food and drug addiction. Therefore, to understand the physiological and pathological functions of neurotransmitters, especially in complex environments of the living brain, it is urgent to develop effective tools to monitor their dynamics with high sensitivity and specificity. Over the past 30 years, significant advances in electrochemical sensors and optical probes have brought new possibilities for studying neurons and neural circuits by monitoring the changes in neurotransmitters. This Review focuses on the progress in the construction of sensors for in vivo analysis of neurotransmitters in the brain and summarizes current attempts to address key issues in the development of sensors with high selectivity, sensitivity, and stability. Combined with the latest advances in technologies and methods, several strategies for sensor construction are provided for recording chemical signal changes in the complex environment of the brain.

Ketamine and Zinc: Treatment of Anorexia Nervosa Via Dual NMDA Receptor Modulation

Anorexia nervosa is a disorder associated with serious adverse health outcomes, for which there is currently considerable treatment ineffectiveness. Characterised by restrictive eating behaviours, distorted body image perceptions and excessive physical activity, there is growing recognition anorexia nervosa is associated with underlying dysfunction in excitatory and inhibitory neurometabolite metabolism and signalling. This narrative review critically explores the role of N-methyl-D-aspartate receptor-mediated excitatory and inhibitory neurometabolite dysfunction in anorexia nervosa and its associated biomarkers. The existing magnetic resonance spectroscopy literature in anorexia nervosa is reviewed and we outline the brain region-specific neurometabolite changes that have been reported and their connection to anorexia nervosa psychopathology. Considering the proposed role of dysfunctional neurotransmission in anorexia nervosa, the potential utility of zinc supplementation and sub-anaesthetic doses of ketamine in normalising this is discussed with reference to previous research in anorexia nervosa and other neuropsychiatric conditions. The rationale for future research to investigate the combined use of low-dose ketamine and zinc supplementation to potentially extend the therapeutic benefits in anorexia nervosa is subsequently explored and promising biological markers for assessing and potentially predicting treatment response are outlined.

In-phase simultaneous spectral editing of lactate and alanine with suppression of J-coupled lipids by the modified selective multiple quantum coherence sequences

¹H magnetic resonance spectroscopy (MRS) with the multiple quantum coherence (MQC) technique allows for the detection of lactate, an end product of glycolysis, in the environment of lipids. The method can also be used to detect alanine, a byproduct of glutaminolysis. An issue is that when both lactate and alanine are detected together by the MQC technique, a phase mismatch arises between lactate and alanine signals due to off-resonance rotations and the difference in double quantum coherence frequencies between the two molecules. Such phase mismatch can cause errors in spectral fitting and metabolite quantification. In this study, we designed two pulse sequences that eliminate such phase differences of lactate and alanine while suppressing lipid signals by modifications of the Selective Multiple Quantum Coherence (Sel-MQC) sequence, a well-known MQC technique. Using the product operator formalism and the off-resonance rotation matrices, the phase evolutions of lactate and alanine during the spectrally selective pulses and the free precession times of the sequence at the single quantum, double quantum and zero quantum coherence states of these molecules were calculated. The multiple quantum (MQ) evolution time t₁ that can remove the phase difference of lactate and alanine at the echo was calculated and fine-tuned with experiments. The lactate and alanine signal intensities and the editing efficiencies from the two modified Sel-MQC sequences were theoretically predicted by using the product operator evolutions and compared with the experimental data. The J-coupled lipid signals were successfully suppressed by both sequences. One of the two developed sequences was applied to a human body with a phantom of lactate and alanine, which resulted in successful in-phase editing of lactate and alanine and suppression of the lipid signals from the body. The study sets an important foundation for the noninvasive detection of lactate and alanine from tumors of cancer patients.

Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics

While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) ¹H-MRS techniques. While short TE ¹H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) ¹H-MRS with longer TE to filter overlapping resonances. The ¹H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE ¹H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors

Simple Summary

Magnetic resonance spectroscopic imaging is an imaging method that can map the distribution of multiple biochemicals in the human brain in one scan. Using stronger magnetic fields, such as 7 Tesla, allows for higher resolution images and more biochemical maps. To test these results, we compared it to positron emission tomography, the established clinical standard for metabolic imaging. This comparison mainly looked at the overlap between regions with increased signal between both methods. We found that the molecules glutamine and glycine, only mappable at 7 Tesla, corresponded better to positron emission tomography than the commonly used choline.

Abstract

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints

We present a novel method to enhance the SNR for multi-TE MR spectroscopic imaging (MRSI) data by integrating learned nonlinear low-dimensional model and spatial constraints. A deep complex convolutional autoen-coder (DCCAE) was developed to learn a nonlinear low-dimensional representation of the high-dimensional multi-TE 1 H spectroscopy signals. The learned model significantly reduces the data dimension thus serving as an effective constraint for noise reduction. A reconstruction formulation was proposed to integrate the spatiospectral encoding model, the learned model, and a spatial constraint for an SNR-enhancing reconstruction from multi-TE data. The proposed method has been evaluated using both numerical simulations and in vivo brain MRSI experiments. The superior denoising performance of the proposed over alternative methods was demonstrated, both qualitatively and quantitatively. In vivo multi-TE data was used to assess the improved metabolite quantification reproducibility and accuracy achieved by the proposed method. We expect the proposed SNR-enhancing reconstruction to enable faster and/or higher-resolution multi-TE 1 H-MRSI of the brain, potentially useful for various clinical applications.

High-resolution, 3D multi-TE 1 H MRSI using fast spatiospectral encoding and subspace imaging

PURPOSE

To develop a novel method to achieve fast, high-resolution, 3D multi-TE ¹ H-MRSI of the brain.

METHODS

A new multi-TE MRSI acquisition strategy was developed that integrates slab selective excitation with adiabatic refocusing for better volume coverage, rapid spatiospectral encoding, sparse multi-TE sampling, and interleaved water navigators for field mapping and calibration. Special data processing strategies were developed to interpolate the sparsely sampled data, remove nuisance signals, and reconstruct multi-TE spatiospectral distributions with high SNR. Phantom and in vivo experiments have been carried out to demonstrate the capability of the proposed method.

RESULTS

The proposed acquisition can produce multi-TE ¹ H-MRSI data with three TEs at a nominal spatial resolution of 3.4 × 3.4 × 5.3 mm³ in around 20 min. High-SNR brain metabolite spatiospectral reconstructions can be obtained from both a metabolite phantom and in vivo experiments by the proposed method.

CONCLUSION

High-resolution, 3D multi-TE ¹ H-MRSI of the brain can be achieved within clinically feasible time. This capability, with further optimizations, could be translated to clinical applications and neuroscience studies where simultaneously mapping metabolites and neurotransmitters and TE-dependent molecular spectral changes are of interest.

Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances

Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.

Neurocognitive performance in relapsing-remitting multiple sclerosis patients is associated with metabolic abnormalities of the thalamus but not the hippocampus- GABA-edited 1H MRS study

OBJECTIVES

Multiple sclerosis (MS) is an inflammatory demyelinating disease that may cause physical disabling as well as cognitive dysfunction. The presented study investigated how the neuropsychological status depends on the thalamus and hippocampus's metabolic processes, using γ-aminobutyric acid-edited magnetic resonance spectroscopy (GABA-edited ¹H MRS) in patients with early MS, and how the results differ from healthy volunteers.

METHODS

We recruited 36 relapsing-remitting (RRMS) MS patients and 22 controls (CON). In addition to common ¹H MRS metabolites, such as N-acetyl-aspartate (tNAA), myoinositol (mIns), total choline and creatine (tCr, tCho), we also evaluated GABA and glutamate/glutamine (Glx). Metabolite ratios were correlated with the results of Single-Digit Modality Test (SDMT) and Expanded Disability Status Score (EDSS).

RESULTS

In the thalamus, GABA ratios (GABA/tCr, GABA/tNAA) were significantly lower in RRMS patients than in CON. Both tCho- and mIns-ratios correlated with lower scores of SDMT but not with EDSS. Metabolic ratios in the hippocampus did not differ between RRMS and CON and did not correlate with any of performed tests.

DISCUSSION

This study is the first to provide GABA-edited ¹H MRS evidence for MS-related metabolic changes of the thalamus and hippocampus. The findings underline the importance of evaluating subcortical grey matter in MS patients to improve understanding of the clinical manifestations of MS and as a potential future target for treatment.

The chemical tools for imaging dopamine release

Dopamine is a modulatory neurotransmitter involved in learning, motor functions, and reward. Many neuropsychiatric disorders, including Parkinson's disease, autism, and schizophrenia, are associated with imbalances or dysfunction in the dopaminergic system. Yet, our understanding of these pervasive public health issues is limited by our ability to effectively image dopamine in humans, which has long been a goal for chemists and neuroscientists. The last two decades have witnessed the development of many molecules used to trace dopamine. We review the small molecules, nanoparticles, and protein sensors used with fluorescent microscopy/photometry, MRI, and PET that shape dopamine research today. None of these tools observe dopamine itself, but instead harness the biology of the dopamine system-its synthetic and metabolic pathways, synaptic vesicle cycle, and receptors-in elegant ways. Their advantages and weaknesses are covered here, along with recent examples and the chemistry and biology that allow them to function.

MEGA-PRESS of GABA+: Influences of acquisition parameters

γ-aminobutyric acid (GABA) was the first molecule that was edited with MEGA-PRESS. GABA edited spectroscopy is challenged by limited selectivity of editing pulses. Coediting of resonances from macromolecules (MM) is the greatest single limitation of GABA edited spectroscopy. In this contribution, relative signal contributions from GABA, MM and homocarnosine to the total MEGA-PRESS edited signal at ~3 ppm, i.e., GABA+, are simulated at 3 tesla using several acquisition schemes. The base scheme is modeled after those currently supplied by vendors: it uses typical pulse shapes and lengths, it minimizes the first echo time (TE), and the delay between the editing pulses is kept at TE/2. Edited spectra are simulated for imperfect acquisition parameters such as incorrect frequency, larger chemical shift displacement, incorrect transmit B₁ -field calibration for localization and editing pulses, and longer TE. An alternative timing scheme and longer editing pulses are also considered. Additional simulations are performed for symmetric editing around the MM frequency to suppress the MM signal. The relative influences of these acquisition parameters on the constituents of GABA+ are examined from the perspective of modern experimental designs for investigating brain GABA concentration differences in healthy and diseased humans. Other factors that influence signal contributions, such as T₁ and T₂ relaxation times are also considered.

Spectral editing in 1 H magnetic resonance spectroscopy: Experts' consensus recommendations

Spectral editing in in vivo ¹ H-MRS provides an effective means to measure low-concentration metabolite signals that cannot be reliably measured by conventional MRS techniques due to signal overlap, for example, γ-aminobutyric acid, glutathione and D-2-hydroxyglutarate. Spectral editing strategies utilize known J-coupling relationships within the metabolite of interest to discriminate their resonances from overlying signals. This consensus recommendation paper provides a brief overview of commonly used homonuclear editing techniques and considerations for data acquisition, processing and quantification. Also, we have listed the experts' recommendations for minimum requirements to achieve adequate spectral editing and reliable quantification. These include selecting the right editing sequence, dealing with frequency drift, handling unwanted coedited resonances, spectral fitting of edited spectra, setting up multicenter clinical trials and recommending sequence parameters to be reported in publications.

Effects of SSRI treatment on GABA and glutamate levels in an associative relearning paradigm

Impaired cognitive flexibility represents a widespread symptom in psychiatric disorders, including major depressive disorder (MDD), a disease, characterized by an imbalance of neuro-transmitter concentrations. While memory formation is mostly associated with glutamate, also gamma-Aminobutyric acid (GABA) and serotonin show attributions in a complex interplay between neurotransmitter systems. Treatment with selective serotonin reuptake inhibitors (SSRIs) does not solely affect the serotonergic system but shows downstream effects on GABA- and glutamatergic neurotransmission, potentially helping to restore cognitive function via neuroplastic effects. Hence, this study aims to elaborate the effects of associative relearning and SSRI treatment on GABAergic and glutamatergic function within and between five brain regions using magnetic resonance spectroscopy imaging (MRSI).

In this study, healthy subjects were randomized into four groups which underwent three weeks of an associative relearning paradigm, with or without emotional connotation, under SSRI (10mg escitalopram) or placebo administration. MRSI measurements, using a spiral-encoded, 3D-GABA-edited MEGA-LASER sequence at 3T, were performed on the first and last day of relearning. Mean GABA+/tCr (GABA+ = GABA + macromolecules; tCr = total creatine) and Glx/tCr (Glx = glutamate + glutamine) ratios were quantified in a ROI-based approach for the hippocampus, insula, putamen, pallidum and thalamus, using LCModel. A total of 66 subjects ((37 female, mean age ± SD = 25.4±4.7) for Glx/tCr and 58 subjects (32 female, mean age ± SD = 25.1±4.7) for GABA+/tCr were included in the final analysis.

A significant measurement by region and treatment (SSRI vs placebo) interaction on Glx/tCr ratios was found (p_cor=0.017), with post hoc tests confirming differential effects on hippocampus and thalamus (p_cor=0.046). Moreover, treatment by time comparison, for each ROI independently, showed a reduction of hippocampal Glx/tCr ratios after SSRI treatment (p_uncor=0.033). No significant treatment effects on GABA+/tCr ratios or effects of relearning condition on any neurotransmitter ratio could be found.

Here, we showed a significant SSRI- and relearning-driven interaction effect of hippocampal and thalamic Glx/tCr levels, suggesting differential behavior based on different serotonin transporter and receptor densities. Moreover, an indication for Glx/tCr adaptions in the hippocampus after three weeks of SSRI treatment could be revealed. Our findings are in line with animal studies reporting glutamate adaptions in the hippocampus following chronic SSRI intake. Due to the complex interplay of serotonin and hippocampal function, involving multiple serotonin receptor subtypes on glutamatergic cells and GABAergic interneurons, the interpretation of underlying neurobiological actions remains challenging.

INSPECTOR: free software for magnetic resonance spectroscopy data inspection, processing, simulation and analysis

In vivo magnetic resonance spectroscopy (MRS) is a powerful tool for biomedical research and clinical diagnostics, allowing for non-invasive measurement and analysis of small molecules from living tissues. However, currently available MRS processing and analytical software tools are limited in their potential for in-depth quality management, access to details of the processing stream, and user friendliness. Moreover, available MRS software focuses on selected aspects of MRS such as simulation, signal processing or analysis, necessitating the use of multiple packages and interfacing among them for biomedical applications. The freeware INSPECTOR comprises enhanced MRS data processing, simulation and analytical capabilities in a one-stop-shop solution for a wide range of biomedical research and diagnostic applications. Extensive data handling, quality management and visualization options are built in, enabling the assessment of every step of the processing chain with maximum transparency. The parameters of the processing can be flexibly chosen and tailored for the specific research problem, and extended confidence information is provided with the analysis. The INSPECTOR software stands out in its user-friendly workflow and potential for automation. In addition to convenience, the functionalities of INSPECTOR ensure rigorous and consistent data processing throughout multi-experiment and multi-center studies.

In vivo γ-aminobutyric acid increase as a biomarker of the epileptogenic zone: An unbiased metabolomics approach

OBJECTIVE

Following surgery, focal seizures relapse in 20% to 50% of cases due to the difficulty of delimiting the epileptogenic zone (EZ) by current imaging or electrophysiological techniques. Here, we evaluate an unbiased metabolomics approach based on ex vivo and in vivo nuclear magnetic resonance spectroscopy (MRS) methods to discriminate the EZ in a mouse model of mesiotemporal lobe epilepsy (MTLE).

METHODS

Four weeks after unilateral injection of kainic acid (KA) into the dorsal hippocampus of mice (KA-MTLE model), we analyzed hippocampal and cortical samples with high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS). Using advanced multivariate statistics, we identified the metabolites that best discriminate the injected dorsal hippocampus (EZ) and developed an in vivo MEGAPRESS MRS method to focus on the detection of these metabolites in the same mouse model.

RESULTS

Multivariate analysis of HRMAS data provided evidence that γ-aminobutyric acid (GABA) is largely increased in the EZ of KA-MTLE mice and is the metabolite that best discriminates the EZ when compared to sham and, more importantly, when compared to adjacent brain regions. These results were confirmed by capillary electrophoresis analysis and were not reversed by a chronic exposition to an antiepileptic drug (carbamazepine). Then, using in vivo noninvasive GABA-edited MRS, we confirmed that a high GABA increase is specific to the injected hippocampus of KA-MTLE mice.

SIGNIFICANCE

Our strategy using ex vivo MRS-based untargeted metabolomics to select the most discriminant metabolite(s), followed by in vivo MRS-based targeted metabolomics, is an unbiased approach to accurately define the EZ in a mouse model of focal epilepsy. Results suggest that GABA is a specific biomarker of the EZ in MTLE.

Characterization of dysregulated glutamine metabolism in human glioma tissue with 1H NMR

Gliomas are one of the most common types of brain tumors. Given low survival and high treatment resistance rates, particularly for high grade gliomas, there is a need for specific biomarkers that can be used to stratify patients for therapy and monitor treatment response. Recent work has demonstrated that metabolic reprogramming, often mediated by inflammation, can lead to an upregulation of glutamine as an energy source for cancer cells. As a result, glutamine pathways are an emerging pharmacologic target. The goal of this pilot study was to characterize changes in glutamine metabolism and inflammation in human glioma samples and explore the use of glutamine as a potential biomarker. ¹H high-resolution magic angle spinning nuclear magnetic resonance spectra were acquired from ex vivo glioma tissue (n = 16, grades II–IV) to quantify metabolite concentrations. Tumor inflammatory markers were quantified using electrochemiluminescence assays. Glutamate, glutathione, lactate, and alanine, as well as interleukin (IL)-1β and IL-8, increased significantly in samples from grade IV gliomas compared to grades II and III (p ≤ .05). Following dimension reduction of the inflammatory markers using probabilistic principal component analysis, we observed that glutamine, alanine, glutathione, and lactate were positively associated with the first inflammatory marker principal component. Our findings support the hypothesis that glutamine may be a key marker for glioma progression and indicate that inflammation is associated with changes in glutamine metabolism. These results motivate further in vivo investigation of glutamine as a biomarker for tumor progression and treatment response.

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications.

Proton nuclear magnetic resonance J-spectroscopy of phantoms containing brain metabolites on a portable 0.05 T MRI scanner

We examined approaches for obtaining ¹H NMR spectra of brain metabolites on a low-field (B₀ = 0.05 T) portable MRI scanner, which was developed in our laboratory with the aim of bringing cost-effective radiological services to populations in underserved, remote regions. The low static magnetic field B₀ dictates low signal to noise ratio for metabolites in the mM concentration range, and results in an overall spectral region for the ¹H resonances of these metabolites narrower than the linewidth obtainable in our scanner. The narrow spectral range also precludes the possibility of suppressing the large contribution of the water resonance at the acquisition stage. We used a spectroscopic Carr-Purcell-Meiboom-Gill (CPMG) sequence to acquire multiecho data from solutions of J-coupled brain metabolites, focusing on lactic acid, a metabolite whose concentration is negligible in the healthy brain and increases significantly in several disease conditions. The J spectra we obtained for lactate from the Fourier transformation of the multiecho data are spectrally well-resolved for a range of echo spacing values. We show that the J spectra at different echo spacings fit well with simulations of the evolution of echo train signal of the lactate under the same conditions. Applying a J-refocused variant of the CPMG sequence, the J modulation of the echo decay is removed, providing a way for subtracting the large contribution of the non-modulated component in the J spectrum in conditions where notching it using post-processing methods is impossible. We also demonstrate by means of experimental data and simulations that in our experimental conditions, J-spectra of other prominent brain metabolites, such as the neurotransmitter glutamate, do not yield discernible peaks and only contribute to a broad peak at zero frequency.

Motion correction in magnetic resonance spectroscopy

In vivo proton magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) are valuable tools to study normal and abnormal human brain physiology. However, they are sensitive to motion, due to strong crusher gradients, long acquisition times, reliance on high magnetic field homogeneity, and particular acquisition methods such as spectral editing. The effects of motion include incorrect spatial localization, phase fluctuations, incoherent averaging, line broadening, and ultimately quantitation errors. Several retrospective methods have been proposed to correct motion-related artifacts. Recent advances in hardware also allow prospective (real-time) correction of the effects of motion, including adjusting voxel location, center frequency, and magnetic field homogeneity. This article reviews prospective and retrospective methods available in the literature and their implications for clinical MRS/MRSI. In combination, these methods can attenuate or eliminate most motion-related artifacts and facilitate the acquisition of high-quality data in the clinical research setting.

Transcranial magnetic stimulation and magnetic resonance spectroscopy: Opportunities for a bimodal approach in human neuroscience

Over the last decade, there has been an increasing number of studies combining transcranial magnetic stimulation (TMS) and magnetic resonance spectroscopy (MRS). MRS provides a manner to non-invasively investigate molecular concentrations in the living brain and thus identify metabolites involved in physiological and pathological processes. Particularly the MRS-detectable metabolites glutamate, the major excitatory neurotransmitter, and gamma-aminobutyric acid (GABA), the major inhibitory neurotransmitter, are of interest when combining TMS and MRS. TMS is a non-invasive brain stimulation technique that can be applied either as a neuromodulation or neurostimulation tool, specifically targeting glutamatergic and GABAergic mechanisms. The combination of TMS and MRS can be used to evaluate alterations in brain metabolite levels following an interventional TMS protocol such as repetitive TMS (rTMS) or paired associative stimulation (PAS). MRS can also be combined with a variety of non-interventional TMS protocols to identify the interplay between brain metabolite levels and measures of excitability or receptor-mediated inhibition and facilitation. In this review, we provide an overview of studies performed in healthy and patient populations combining MRS and TMS, both as a measurement tool and as an intervention. TMS and MRS may reveal complementary and comprehensive information on glutamatergic and GABAergic neurotransmission. Potentially, connectivity changes and dedicated network interactions can be probed using the combined TMS-MRS approach. Considering the ongoing technical developments in both fields, combined studies hold future promise for investigations of brain network interactions and neurotransmission.

Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations

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.

Accelerated J-resolved 1 H-MRSI with limited and sparse sampling of ( k , t 1 , t 2 -space

PURPOSE

To accelerate the acquisition of J-resolved proton magnetic resonance spectroscopic imaging (¹ H-MRSI) data for high-resolution mapping of brain metabolites and neurotransmitters.

METHODS

The proposed method used a subspace model to represent multidimensional spatiospectral functions, which significantly reduced the number of parameters to be determined from J-resolved ¹ H-MRSI data. A semi-LASER-based (Localization by Adiabatic SElective Refocusing) echo-planar spectroscopic imaging (EPSI) sequence was used for data acquisition. The proposed data acquisition scheme sampled k , t 1 , t 2 -space in variable density, where t₁ and t₂ specify the J-coupling and chemical-shift encoding times, respectively. Selection of the J-coupling encoding times (or, echo time values) was based on a Cramer-Rao lower bound analysis, which were optimized for gamma-aminobutyric acid (GABA) detection. In image reconstruction, parameters of the subspace-based spatiospectral model were determined by solving a constrained optimization problem.

RESULTS

Feasibility of the proposed method was evaluated using both simulated and experimental data from a spectroscopic phantom. The phantom experimental results showed that the proposed method, with a factor of 12 acceleration in data acquisition, could determine the distribution of J-coupled molecules with expected accuracy. In vivo study with healthy human subjects also showed that 3D maps of brain metabolites and neurotransmitters can be obtained with a nominal spatial resolution of 3.0 × 3.0 × 4.8 mm³ from J-resolved ¹ H-MRSI data acquired in 19.4 min.

CONCLUSIONS

This work demonstrated the feasibility of highly accelerated J-resolved ¹ H-MRSI using limited and sparse sampling of k , t 1 , t 2 -space and subspace modeling. With further development, the proposed method may enable high-resolution mapping of brain metabolites and neurotransmitters in clinical applications.

Effect of Age on GABA+ and Glutathione in a Pediatric Sample

BACKGROUND AND PURPOSE

Gamma-aminobutyric acid (GABA) is the primary inhibitory neurotransmitter in the human brain and is implicated in several neuropathologies. Glutathione is a major antioxidant in the brain and is considered a marker of oxidative stress. Several studies have reported age-related declines in GABA levels in adulthood, but the trajectory of both GABA and glutathione during childhood has not been well explored. The aim of this study is to establish how GABA and glutathione vary with age during early development.

MATERIALS AND METHODS

Twenty-three healthy children (5.6-13.9 years of age) were recruited for this study. MR imaging/MR spectroscopy experiments were conducted on a 3T MR scanner. A 27-mL MR spectroscopy voxel was positioned in the frontal lobe. J-difference edited MR spectroscopy was used to spectrally edit GABA and glutathione. Data were analyzed using the Gannet software, and GABA+ (GABA + macromolecules/homocarnosine) and glutathione were quantified using water (GABA+_H2O and Glutathione_H2O) and Cr (GABA+/Cr and glutathione/Cr) as concentration references. Also, the relative gray matter contribution to the voxel volume (GM_ratio) was estimated from structural images. Pearson correlation coefficients were used to examine the association between age and GABA+_H2O (and glutathione_H2O), between age and GABA+/Cr (and glutathione/Cr), and between age and GM_ratio.

RESULTS

Both GABA+_H2O (r = 0.63, P = .002) and GABA+/Cr (r = 0.48, P = .026) significantly correlated with age, whereas glutathione measurements and GM_ratio did not.

CONCLUSIONS

We demonstrate increases in GABA and no differences in glutathione with age in a healthy pediatric sample. This study provides insight into neuronal maturation in children and may facilitate better understanding of normative behavioral development and the pathophysiology of developmental disorders.

Lactate measurement by neurochemical profiling in the dorsolateral prefrontal cortex at 7T: accuracy, precision, and relaxation times

PURPOSE

This assesses the potential of measuring lactate in the human brain using three non-editing MRS methods at 7T and compares the accuracy and precision of the methods.

METHODS

¹ H MRS data were measured in the right dorsolateral prefrontal cortex using a semi-adiabatic spin-echo full-intensity acquired localized sequence with three different protocols: (I) TE = 16 ms, (II) TE = 110 ms, and (III) TE = 16 ms, TI = 300 ms. T₁ and T₂ relaxation times of lactate were also measured. Simulated spectra were generated for three protocols with known concentrations, using a range of spectral linewidths and SNRs to assess the effect of data quality on the measurement precision and accuracy.

RESULTS

Lactate was quantified in all three protocols with mean Cramér-Rao lower bound of 8% (I), 13% (II), and 7% (III). The T₁ and T₂ relaxation times of lactate were 1.9 ± 0.2 s and 94 ± 13 ms, respectively. Simulations predicted a spectral linewidth-associated underestimation of lactate measurement. Simulations, phantom and in vivo results showed that protocol II was most affected by this underestimation. In addition, the estimation error was insensitive to a broad range of spectral linewidth with protocol I. Within-session coefficient of variances of lactate were 6.1 ± 7.9% (I), 22.3 ± 12.3% (II), and 5.1 ± 5.4% (III), respectively.

CONCLUSION

We conclude that protocols I and III have the potential to measure lactate at 7T with good reproducibility, whereas the measurement accuracy and precision depend on spectral linewidth and SNR, respectively. Moreover, simulation is valuable for the optimization of measurement protocols in future study design and the correction for measurement bias.

Cancer metabolism in a snapshot: MRS(I)

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by ¹³ C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-¹³ C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr ¹³ C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the ¹³ C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. ³¹ P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole ¹ H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.

Simultaneous editing of GABA and GSH with Hadamard-encoded MR spectroscopic imaging

PURPOSE

To evaluate the feasibility of simultaneous MR spectroscopic imaging (MRSI) of gamma-aminobutyric acid (GABA) and glutathione (GSH) in the human brain using Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES).

METHODS

Point RESolved Spectroscopy (PRESS)-localized MRSI was performed in GABA and GSH phantoms and in the human brain (n = 3) using HERMES editing and compared to conventional MEGA editing of each metabolite. Multiplet patterns, signal intensities, and metabolite crosstalk were compared between methods. GABA+ and GSH levels were compared between methods for bias and variability. Linear regression of HERMES-MRSI GABA+/H₂ O and GSH/H₂ O versus gray matter (GM) fraction were performed to assess differences between GM and white matter (WM).

RESULTS

Phantom HERMES-MRSI scans gave comparable GABA+ and GSH signals to MEGA-MRSI across the PRESS-localized volume. In vivo, HERMES-reconstructed GABA+ and GSH values had minimal measurement bias and variability relative to MEGA-MRSI. Intersubject coefficients of variation (CV) from two regions within the PRESS-localized volume for HERMES and MEGA were 6-12% for GABA+ and 6-19% for GSH. Interregion CVs were 5-15% for GABA+ and 3-17% for GSH. The GABA+/H₂ O and GSH/H₂ O ratios were ~1.8 times higher and ~1.9 times higher, respectively, in GM than in WM.

CONCLUSION

HERMES-MRSI of GABA+ and GSH was found to be practical in the human brain with minimal measurement bias and comparable variability to separate MEGA-edited acquisitions of each metabolite performed in double the scan time. The HERMES-MRSI is a promising method for simultaneously mapping the distribution of multiple low-concentration metabolites.

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.

Optimized in vivo brain glutamate measurement using long-echo-time semi-LASER at 7 T

A short echo time (T_E ) is commonly used for brain glutamate measurement by ¹ H MRS to minimize drawbacks of long T_E such as signal modulation due to J evolution and T₂ relaxation. However, J coupling causes the spectral patterns of glutamate to change with T_E , and the shortest achievable T_E may not produce the optimal glutamate measurement. The purpose of this study was to determine the optimal T_E for glutamate measurement at 7 T using semi-LASER (localization by adiabatic selective refocusing). Time-domain simulations were performed to model the T_E dependence of glutamate signal energy, a measure of glutamate signal strength, and were verified against measurements made in the human sensorimotor cortex (five subjects, 2 × 2 × 2 cm³ voxel, 16 averages) on a 7 T MRI scanner. Simulations showed a local maximum of glutamate signal energy at T_E  = 107 ms. In vivo, T_E  = 105 ms produced a low Cramér-Rao lower bound of 6.5 ± 2.0% across subjects, indicating high-quality fits of the prior knowledge model to in vivo data. T_E  = 105 ms also produced the greatest glutamate signal energy with the smallest inter-subject glutamate-to-creatine ratio (Glu/Cr) coefficient of variation (CV), 4.6%. Using these CVs, we performed sample size calculations to estimate the number of participants per group required to detect a 10% change in Glu/Cr between two groups with 95% confidence. 13 were required at T_E  = 45 ms, the shortest achievable echo time on our 7 T MRI scanner, while only 5 were required at T_E  = 105 ms, indicating greater statistical power. These results indicate that T_E  = 105 ms is optimum for in vivo glutamate measurement at 7 T with semi-LASER. Using long T_E decreases power deposition by allowing lower maximum RF pulse amplitudes in conjunction with longer RF pulses. Importantly, long T_E minimizes macromolecule contributions, eliminating the requirement for acquisition of separate macromolecule spectra or macromolecule fitting techniques, which add additional scan time or bias the estimated glutamate fit.

Two-Dimensional Proton Magnetic Resonance Spectroscopy versus J-Editing for GABA Quantification in Human Brain: Insights from a GABA-Aminotransferase Inhibitor Study

Metabolite-specific, scalar spin-spin coupling constant (J)-editing ¹H MRS methods have become gold-standard for measuring brain γ-amino butyric acid (GABA) levels in human brain. Localized, two-dimensional (2D) ¹H MRS technology offers an attractive alternative as it significantly alleviates the problem of severe metabolite signal overlap associated with standard 1D MRS and retains spectroscopic information for all MRS-detectable species. However, for metabolites found at low concentration, a direct, in vivo, comprehensive methods comparison is challenging and has not been reported to date. Here, we document an assessment of comparability between 2D ¹H MRS and J-editing methods for measuring GABA in human brain. This clinical study is unique in that it involved chronic administration a GABA-amino transferase (AT) inhibitor (CPP-115), which induces substantial increases in brain GABA concentration, with normalization after washout. We report a qualitative and quantitative comparison between these two measurement techniques. In general, GABA concentration changes detected using J-editing were closely mirrored by the 2D ¹H MRS time courses. The data presented are particularly encouraging considering recent 2D ¹H MRS methodological advances are continuing to improve temporal resolution and spatial coverage for achieving whole-brain, multi-metabolite mapping.

Frequency and phase correction for multiplexed edited MRS of GABA and glutathione

PURPOSE

Detection of endogenous metabolites using multiplexed editing substantially improves the efficiency of edited magnetic resonance spectroscopy. Multiplexed editing (i.e., performing more than one edited experiment in a single acquisition) requires a tailored, robust approach for correction of frequency and phase offsets. Here, a novel method for frequency and phase correction (FPC) based on spectral registration is presented and compared against previously presented approaches.

METHODS

One simulated dataset and 40 γ-aminobutyric acid-/glutathione-edited HERMES datasets acquired in vivo at three imaging centers were used to test four FPC approaches: no correction; spectral registration; spectral registration with post hoc choline-creatine alignment; and multistep FPC. The performance of each routine for the simulated dataset was assessed by comparing the estimated frequency/phase offsets against the known values, whereas the performance for the in vivo data was assessed quantitatively by calculation of an alignment quality metric based on choline subtraction artifacts.

RESULTS

The multistep FPC approach returned corrections that were closest to the true values for the simulated dataset. Alignment quality scores were on average worst for no correction, and best for multistep FPC in both the γ-aminobutyric acid- and glutathione-edited spectra in the in vivo data.

CONCLUSIONS

Multistep FPC results in improved correction of frequency/phase errors in multiplexed γ-aminobutyric acid-/glutathione-edited magnetic resonance spectroscopy experiments. The optimal FPC strategy is experiment-specific, and may even be dataset-specific. Magn Reson Med 80:21-28, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Big GABA: Edited MR spectroscopy at 24 research sites

Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.