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

GABA-edited MEGA-PRESS at 3 T: Does a measured macromolecule background improve linear combination modeling?

PURPOSE

The J-difference edited γ-aminobutyric acid (GABA) signal is contaminated by other co-edited signals-the largest of which originates from co-edited macromolecules (MMs)-and is consequently often reported as "GABA+." MM signals are broader and less well-characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS.

METHODS

To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants.

RESULTS

Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%).

CONCLUSIONS

Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra.

Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling

PURPOSE

Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a 2D linear-combination model (2D-LCM) of individual transients ("model-based FPC"). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates.

METHODS

We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the SD of those ground-truth errors, and amplitude Cramér Rao lower bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data.

RESULTS

2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of FPC and amplitudes performed substantially better at low-to-very-low SNR.

CONCLUSION

Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, for example, long TEs or strong diffusion weighting.

GABA and glutamate response to social processing: a functional MRS feasibility study

Several studies have suggested that atypical social processing in neurodevelopmental conditions (e.g. autism) is associated with differences in excitation and inhibition, through changes in the levels of glutamate and gamma-aminobutyric acid (GABA). While associations between baseline metabolite levels and behaviours can be insightful, assessing the neurometabolic response of GABA and glutamate during social processing may explain altered neurochemical function in more depth. Thus far, there have been no attempts to determine whether changes in metabolite levels are detectable using functional MRS (fMRS) during social processing in a control population. We performed Mescher-Garwood point resolved spectroscopy edited fMRS to measure the dynamic response of GABA and glutamate in the superior temporal sulcus (STS) and visual cortex (V1) while viewing social stimuli, using a design that allows for analysis in both block and event-related approaches. Sliding window analyses were used to investigate GABA and glutamate dynamics at higher temporal resolution. The changes of GABA and glutamate levels with social stimulus were largely non-significant. A small decrease in GABA levels was observed during social stimulus presentation in V1, but no change was observed in STS. Conversely, non-social stimulus elicited changes in both GABA and glutamate levels in both regions. Our findings suggest that the current experimental design primarily captures effects of visual stimulation, not social processing. Here, we discuss the feasibility of using fMRS analysis approaches to assess changes in metabolite response.

Metabolite T2 relaxation times decrease across the adult lifespan in a large multi-site cohort

Purpose

Relaxation correction is crucial for accurately estimating metabolite concentrations measured using in vivo magnetic resonance spectroscopy (MRS). However, the majority of MRS quantification routines assume that relaxation values remain constant across the lifespan, despite prior evidence of T2 changes with aging for multiple of the major metabolites. Here, we comprehensively investigate correlations between T2 and age in a large, multi-site cohort.

Methods

We recruited approximately 10 male and 10 female participants from each decade of life: 18-29, 30-39, 40-49, 50-59, and 60+ years old (n=101 total). We collected PRESS data at 8 TEs (30, 50, 74, 101, 135, 179, 241, and 350 ms) from voxels placed in white-matter-rich centrum semiovale (CSO) and gray-matter-rich posterior cingulate cortex (PCC). We quantified metabolite amplitudes using Osprey and fit exponential decay curves to estimate T2.

Results

Older age was correlated with shorter T2 for tNAA, tCr3.0, tCr3.9, tCho, Glx, and tissue water in CSO and PCC; rs = -0.21 to -0.65, all p<0.05, FDR-corrected for multiple comparisons. These associations remained statistically significant when controlling for cortical atrophy. T2 values did not differ across the adult lifespan for mI. By region, T2 values were longer in the CSO for tNAA, tCr3.0, tCr3.9, Glx, and tissue water and longer in the PCC for tCho and mI.

Conclusion

These findings underscore the importance of considering metabolite T2 changes with aging in MRS quantification. We suggest that future 3T work utilize the equations presented here to estimate age-specific T2 values instead of relying on uniform default values.

Universal dynamic fitting of magnetic resonance spectroscopy

PURPOSE

Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type.

METHODS

A simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting.

RESULTS

Analysis of synthetic functional 1H-MRS data shows a marked decrease in parameter uncertainty as predicted by prior work. Analysis with our tool replicates the results of two previously published studies using the original in vivo functional and diffusion-weighted data. Finally, joint spectral fitting with diffusion orientation models is demonstrated in synthetic data.

CONCLUSION

A toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time

PURPOSE

Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete scan.

METHODS

There were three tracks: Track 1: simulated data, Track 2: identical acquisition parameters with in vivo data, and Track 3: different acquisition parameters with in vivo data. The mean squared error, signal-to-noise ratio, linewidth, and a proposed shape score metric were used to quantify model performance. Challenge organizers provided open access to a baseline model, simulated noise-free data, guides for adding synthetic noise, and in vivo data.

RESULTS

Three submissions were compared. A covariance matrix convolutional neural network model was most successful for Track 1. A vision transformer model operating on a spectrogram data representation was most successful for Tracks 2 and 3. Deep learning (DL) reconstructions with 80 transients achieved equivalent or better SNR, linewidth and fit error compared to conventional 320 transient reconstructions. However, some DL models optimized linewidth and SNR without actually improving overall spectral quality, indicating a need for more robust metrics.

CONCLUSION

DL-based reconstruction pipelines have the promise to reduce the number of transients required for GABA-edited MRS.

Repeatability of Lac+ measurements in healthy human brain at 3 T

PURPOSE

In vivo quantification of lactate has numerous applications in studying the pathology of both cerebral and musculoskeletal systems. Due to its low concentration (~0.5-1 mM), and overlap with lipid signals, traditional 1H MR spectra acquired in vivo using a small voxel and short echo time often result in an inadequate signal to detect and resolve the lactate peak, especially in healthy human volunteers.

METHODS

In this study, using a semi-LASER acquisition with long echo time (TE = 288 ms) and large voxel size (80 × 70 × 20 mm3), we clearly visualize the combined signal of lactate and threonine. Therefore, we call the signal at 1.33 ppm Lac+ and quantify Lac+ concentration from water suppressed spectra in healthy human brains in vivo. Four participants (22-37 years old; mean age = 28 ± 5.4; three male, one female) were scanned on four separate days, and on each day four measurements were taken. Intra-day values are calculated for each participant by comparing the four measurements on a single day. Inter-day values were calculated using the mean intra-day measurements.

RESULTS

The mean intra-participant Lac+ concentration, standard deviation (SD), and coefficient of variation (CV) ranged from 0.49 to 0.61 mM, 0.02 to 0.07 mM, and 4% to 13%, respectively, across four volunteers. The inter-participant Lac+ concentration, SD, and CV was 0.53 mM, ±0.06 mM, and 11%.

CONCLUSION

Repeatability is shown in Lac+ measurement in healthy human brain using a long echo time semi-LASER sequence with a large voxel in about 3.5 min at 3 T.

Impact of acquisition and modeling parameters on the test-retest reproducibility of edited GABA

Literature values vary widely for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA) measured with edited magnetic resonance spectroscopy (MRS). Reasons for this variation remain unclear. Here, we tested whether three acquisition parameters-(1) sequence complexity (two-experiment MEscher-GArwood Point RESolved Spectroscopy [MEGA-PRESS] vs. four-experiment Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy [HERMES]); (2) editing pulse duration (14 vs. 20 ms); and (3) scanner frequency drift (interleaved water referencing [IWR] turned ON vs. OFF)-and two linear combination modeling variations-(1) three different coedited macromolecule models (called "1to1GABA", "1to1GABAsoft", and "3to2MM" in the Osprey software package); and (2) 0.55- versus 0.4-ppm spline baseline knot spacing-affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (mean age: 30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 min. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). We identified the best test-retest reproducibility following postprocessing with a composite model of the 0.9- and 3-ppm macromolecules ("3to2MM"); this model performed particularly well for the HERMES data. Furthermore, sparser (0.55- compared with 0.4-ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. However, reproducibility did not consistently differ for MEGA-PRESS compared with HERMES, for 14- compared with 20-ms editing pulses, or for IWR-ON versus IWR-OFF. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies that focus on individual patient differences in GABA+ or changes following an intervention.

A preliminary study of dynamic neurochemical changes in the dorsolateral prefrontal cortex during working memory

Working memory (WM) is one of the fundamental cognitive functions associated with the dorsolateral prefrontal cortex (DLPFC). However, the neurochemical mechanisms of WM, including the dynamic changes in neurometabolites such as glutamate and GABA in the DLPFC, remain unclear. Here, we investigated WM-related glutamate and GABA changes, alongside hemodynamic responses in the DLPFC, using a combination of functional magnetic resonance spectroscopy (fMRS) and functional magnetic resonance imaging (fMRI). During a WM task, we measured Glx (glutamate + glutamine) and GABA levels using GABA editing MEscher-GArwood Point REsolved Spectroscopy (MEGA-PRESS) sequence and blood-oxygen-level-dependent (BOLD) signal changes. In the DLPFC, we observed elevated Glx levels and increased BOLD signal changes during a 2-back task. Specifically, the Glx levels in the DLPFC were significantly higher during the 2-back task compared with fixation, although this difference was not significant when compared with a 0-back task. However, Glx levels during the 0-back task were higher than during fixation. Furthermore, there was a positive correlation between Glx levels in the DLPFC during the 2-back task and the corresponding BOLD signal changes. Notably, higher Glx increases were associated with increased DLPFC activation and lower WM task performance in individuals. No notable changes in DLPFC GABA levels were observed during WM processing. These findings suggest that the modulation of glutamatergic activity in the DLPFC may play a crucial role in both working memory processing and its associated performance outcomes.

Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling

Purpose

Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a two-dimensional linear-combination model (2D-LCM) of individual transients ('model-based FPC'). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates.

Methods

We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the standard deviation of those ground-truth errors, and amplitude Cramér Rao Lower Bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data.

Results

2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of frequency and phase correction and amplitudes performed substantially better at low-to-very-low SNR.

Conclusion

Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, e.g., long TEs or strong diffusion weighting.

Brain glutathione and GABA+ levels in autistic children

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies

Single-voxel proton magnetic resonance spectroscopy (SV 1 H-MRS) is an in vivo noninvasive imaging technique used to detect neurotransmitters and metabolites. It enables repeated measurements in living participants to build explanatory neurochemical models of psychiatric symptoms and testing of therapeutic approaches. Given the tight link among glutamate, gamma-amino butyric acid (GABA), glutathione and glutamine within the cellular machinery, MRS investigations of neurocognitive and psychiatric disorders must quantify a network of metabolites simultaneously to capture the pathophysiological states of interest. Metabolite-selective sequences typically provide improved metabolite isolation and spectral modelling simplification for a single metabolite at a time. Non-metabolite-selective sequences provide information on all detectable human brain metabolites, but feature many signal overlaps and require complicated spectral modelling. Although there are short-echo time (TE) MRS sequences that do not use spectral editing and are optimised to target either glutamate, GABA or glutathione, these approaches usually imply a precision tradeoff for the remaining two metabolites. Given the interest in assessing psychiatric and neurocognitive diseases that involve excitation-inhibition imbalances along with oxidative stress, there is a need to survey the literature on the quantification precision of current metabolite-selective MRS techniques. In this review, we locate and describe 17 studies that report on the quality of simultaneously acquired MRS metabolite data in the human brain. We note several factors that influence the data quality for single-shot acquisition of multiple metabolites of interest using metabolite-selective MRS: (1) internal in vivo references; (2) brain regions of interests; (3) field strength of scanner; and/or (4) optimised acquisition parameters. We also highlight the strengths and weaknesses of various SV spectroscopy techniques that were able to quantify in vivo glutamate, GABA and glutathione simultaneously. The insights from this review will assist in the development of new MRS pulse sequences for simultaneous, selective measurements of these metabolites and simplified spectral modelling.

Design and methodology for a proof of mechanism study of individualized neuronavigated continuous Theta burst stimulation for auditory processing in adolescents with autism spectrum disorder

It has been suggested that aberrant excitation/inhibition (E/I) balance and dysfunctional structure and function of relevant brain networks may underlie the symptoms of autism spectrum disorder (ASD). However, the nomological network linking these constructs to quantifiable measures and mechanistically relating these constructs to behavioral symptoms of ASD is lacking. Herein we describe a within-subject, controlled, proof-of-mechanism study investigating the pathophysiology of auditory/language processing in adolescents with ASD. We utilize neurophysiological and neuroimaging techniques including magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG) metrics of language network structure and function. Additionally, we apply a single, individually targeted session of continuous theta burst stimulation (cTBS) as an experimental probe of the impact of perturbation of the system on these neurophysiological and neuroimaging outcomes. MRS, fMRI, and MEG measures are evaluated at baseline and immediately prior to and following cTBS over the posterior superior temporal cortex (pSTC), a region involved in auditory and language processing deficits in ASD. Also, behavioral measures of ASD and language processing and DWI measures of auditory/language network structures are obtained at baseline to characterize the relationship between the neuroimaging and neurophysiological measures and baseline symptom presentation. We hypothesize that local gamma-aminobutyric acid (GABA) and glutamate concentrations (measured with MRS), and structural and functional activity and network connectivity (measured with DWI and fMRI), will significantly predict MEG indices of auditory/language processing and behavioral deficits in ASD. Furthermore, a single session of cTBS over left pSTC is hypothesized to lead to significant, acute changes in local glutamate and GABA concentration, functional activity and network connectivity, and MEG indices of auditory/language processing. We have completed the pilot phase of the study (n=20 Healthy Volunteer adults) and have begun enrollment for the main phase with adolescents with ASD (n=86; age 14-17). If successful, this study will establish a nomological network linking local E/I balance measures to functional and structural connectivity within relevant brain networks, ultimately connecting them to ASD symptoms. Furthermore, this study will inform future therapeutic trials using cTBS to treat the symptoms of ASD.

Dynamics of γ-aminobutyric acid concentration in the human brain in response to short visual stimulation

OBJECTIVE

To find a possible quantitative relation between activation-induced fast (< 10 s) changes in the γ-aminobutyric acid (GABA) level and the amplitude of a blood oxygen level-dependent contrast (BOLD) response (according to magnetic resonance spectroscopy [MRS] and functional magnetic resonance imaging [fMRI]).

MATERIALS AND METHODS

fMRI data and MEGA-PRESS magnetic resonance spectra [echo time (TE)/repetition time (TR) = 68 ms/1500 ms] of an activated area in the visual cortex of 33 subjects were acquired using a 3 T MR scanner. Stimulation was performed by presenting an image of a flickering checkerboard for 3 s, repeated with an interval of 13.5 s. The time course of GABA and creatine (Cr) concentrations and the width and height of resonance lines were obtained with a nominal time resolution of 1.5 s. Changes in the linewidth and height of n-acetylaspartate (NAA) and Cr signals were used to determine the BOLD effect.

RESULTS

In response to the activation, the BOLD-corrected GABA + /Cr ratio increased by 5.0% (q = 0.027) and 3.8% (q = 0.048) at 1.6 and 3.1 s, respectively, after the start of the stimulus. Time courses of Cr and NAA signal width and height reached a maximum change at the 6th second (~ 1.2-1.5%, q < 0.05).

CONCLUSION

The quick response of the observed GABA concentration to the short stimulus is most likely due to a release of GABA from vesicles followed by its packaging back into vesicles.

Brain Glutathione and GABA+ levels in autistic children

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a large cohort of children aged 8-12 years with ASD (n=52) and typically developing children (TDC, n=49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Protocol to conduct functional magnetic resonance spectroscopy in different age groups of human participants

We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022).1.

Cortical Mechanisms Underlying Immersive Interactive Virtual Walking Treatment for Amelioration of Neuropathic Pain after Spinal Cord Injury: Findings from a Preliminary Investigation of Thalamic Inhibitory Function

BACKGROUND

Neuropathic pain following spinal cord injury (SCI) affects approximately 60% of individuals with SCI. Effective pharmacological and non-pharmacological treatments remain elusive. We recently demonstrated that our immersive virtual reality walking intervention (VRWalk) may be effective for SCI NP. Additionally, we found that SCI NP may result from a decrease in thalamic γ-aminobutyric-acid (GABA), which disturbs central sensorimotor processing.

OBJECTIVE

While we identified GABAergic changes associated with SCI NP, a critical outstanding question is whether a decrease in SCI NP generated by our VRWalk intervention causes GABA content to rise.

METHOD

A subset of participants (n = 7) of our VRWalk trial underwent magnetic resonance spectroscopy pre- and post-VRWalk intervention to determine if the decrease in SCI NP is associated with an increase in thalamic GABA.

RESULTS

The findings revealed a significant increase in thalamic GABA content from pre- to post-VRWalk treatment.

CONCLUSION

While the current findings are preliminary and should be interpreted with caution, pre- to post-VRWalk reductions in SCI NP may be mediated by pre- to post-treatment increases in thalamic GABA by targeting and normalizing maladaptive sensorimotor cortex reorganization. Understanding the underlying mechanisms of pain recovery can serve to validate the efficacy of home-based VR walking treatment as a means of managing pain following SCI. Neuromodulatory interventions aimed at increasing thalamic inhibitory function may provide more effective pain relief than currently available treatments.

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.

Event-related functional magnetic resonance spectroscopy

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.

Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology

There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.

Advances in molecular and imaging biomarkers in lower-grade gliomas

INTRODUCTION

Lower-grade (grade 2-3) gliomas (LGGs) constitutes a group of primary brain tumors with variable clinical behaviors and treatment responses. Recent advancements in molecular biology have redefined their classification, and novel imaging modalities emerged for the noninvasive diagnosis and follow-up.

AREAS COVERED

This review comprehensively analyses the current knowledge on molecular and imaging biomarkers in LGGs. Key molecular alterations, such as IDH mutations and 1p/19q codeletion, are discussed for their prognostic and predictive implications in guiding treatment decisions. Moreover, the authors explore theranostic biomarkers for the potential of tailored therapies. Additionally, they also describe the utility of advanced imaging modalities, including widely available techniques, as dynamic susceptibility contrast perfusion-weighted imaging and less validated, emerging approaches, for the noninvasive LGGs characterization and follow-up.

EXPERT OPINION

The integration of molecular markers enhanced the stratification of LGGs, leading to the new concept of integrated histomolecular classification. While the IDH mutation is an established key prognostic and predictive marker, recent results from IDH inhibitors trials showed its potential value as a theranostic marker. In this setting, advanced MRI techniques such as 2-D-hydroxyglutarate spectroscopy are very promising for the noninvasive diagnosis and monitoring of LGGs. This progress offers exciting prospects for personalized medicine and improved treatment outcomes in LGGs.

N-acetylcysteine does not alter neurometabolite levels in non-treatment seeking adolescents who use alcohol heavily: A preliminary randomized clinical trial

Current treatments for adolescent alcohol use disorder (AUD) are mainly psychosocial and limited in their efficacy. As such, pharmacotherapies are being investigated as potential adjunctive treatments to bolster treatment outcomes. N-acetylcysteine is a promising candidate pharmacotherapy for adolescent AUD because of its tolerability and demonstrated ability to modulate glutamatergic, GABAergic, and glutathione systems. The primary objective of this double-blind, placebo-controlled, within-subjects crossover preliminary investigation was to measure potential changes within glutamate + glutamine (Glx), GABA, and glutathione levels in the dorsal anterior cingulate cortex (dACC) using proton magnetic resonance spectroscopy during 10-days of N-acetylcysteine (1200 mg twice daily) compared to 10-days of placebo in non-treatment seeking adolescents who use alcohol heavily (N = 31; 55% female). Medication adherence was confirmed via video. Effects on alcohol use were measured using Timeline Follow-Back as an exploratory aim. Linear mixed effects models controlling for baseline metabolite levels, brain tissue composition, alcohol use, cannabis use, and medication adherence found no significant differences in Glx, GABA, or glutathione levels in the dACC after N-acetylcysteine compared to placebo. There were also no measurable effects on alcohol use; however, this finding was underpowered. Findings were consistent in the subsample of participants who met criteria for AUD (n = 19). The preliminary null findings in brain metabolite levels may be due to the young age of participants, relatively low severity of alcohol use, and non-treatment seeking status of the population investigated. Future studies can use these findings to conduct larger, well-powered studies within adolescents with AUD.

Severity of prematurity and age impact early postnatal development of GABA and glutamate systems

Gamma-aminobutyric acid (GABA) and glutamatergic system perturbations following premature birth may explain neurodevelopmental deficits in the absence of structural brain injury. Using GABA-edited spectroscopy (MEscher-GArwood Point Resolved Spectroscopy [MEGA-PRESS] on 3 T MRI), we have described in-vivo brain GABA+ (+macromolecules) and Glx (glutamate + glutamine) concentrations in term-born infants. We report previously unavailable comparative data on in-vivo GABA+ and Glx concentrations in the cerebellum, the right basal ganglia, and the right frontal lobe of preterm-born infants without structural brain injury. Seventy-five preterm-born (gestational age 27.8 ± 2.9 weeks) and 48 term-born (39.6 ± 0.9 weeks) infants yielded reliable MEGA-PRESS spectra acquired at post-menstrual age (PMA) of 40.2 ± 2.3 and 43.0 ± 2 weeks, respectively. GABA+ (median 2.44 institutional units [i.u.]) concentrations were highest in the cerebellum and Glx higher in the cerebellum (5.73 i.u.) and basal ganglia (5.16 i.u.), with lowest concentrations in the frontal lobe. Metabolite concentrations correlated positively with advancing PMA and postnatal age at MRI (Spearman's rho 0.2-0.6). Basal ganglia Glx and NAA, and frontal GABA+ and NAA concentrations were lower in preterm compared with term infants. Moderate preterm infants had lower metabolite concentrations than term and extreme preterm infants. Our findings emphasize the impact of premature extra-uterine stimuli on GABA-glutamate system development and may serve as early biomarkers of neurodevelopmental deficits.

A comprehensive guide to MEGA-PRESS for GABA measurement

The aim of this guideline is to provide a series of evidence-based recommendations that allow those new to using MEGA-PRESS to produce high-quality data for the measurement of GABA levels using edited magnetic resonance spectroscopy with the MEGA-PRESS sequence at 3T. GABA is the main inhibitory neurotransmitter of the central nervous system and has been increasingly studied due to its relevance in many clinical disorders of the central nervous system. MEGA-PRESS is the most widely used method for quantification of GABA at 3T, but is technically challenging and operates at a low signal-to-noise ratio. Therefore, the acquisition of high-quality MRS data relies on avoiding numerous pitfalls and observing important caveats. The guideline was developed by a working party that consisted of experts in MRS and experts in guideline development and implementation, together with key stakeholders. Strictly following a translational framework, we first identified evidence using a systematically conducted scoping literature review, then synthesized and graded the quality of evidence that formed recommendations. These recommendations were then sent to a panel of 21 world leaders in MRS for feedback and approval using a modified-Delphi process across two rounds. The final guideline consists of 23 recommendations across six domains essential for GABA MRS acquisition (Parameters, Practicalities, Data acquisition, Confounders, Quality/reporting, Post-processing). Overall, 78% of recommendations were formed from high-quality evidence, and 91% received agreement from over 80% of the expert panel. These 23 expert-reviewed recommendations and accompanying extended documentation form a readily useable guideline to allow those new to using MEGA-PRESS to design appropriate MEGA-PRESS study protocols and generate high-quality data.

Multinuclear Magnetic Resonance Spectroscopy at Ultra-High-Field: Assessing Human Cerebral Metabolism in Healthy and Diseased States

The brain is a highly energetic organ. Although the brain can consume metabolic substrates, such as lactate, glycogen, and ketone bodies, the energy metabolism in a healthy adult brain mainly relies on glucose provided via blood. The cerebral metabolism of glucose produces energy and a wide variety of intermediate metabolites. Since cerebral metabolic alterations have been repeatedly implicated in several brain disorders, understanding changes in metabolite levels and corresponding cell-specific neurotransmitter fluxes through different substrate utilization may highlight the underlying mechanisms that can be exploited to diagnose or treat various brain disorders. Magnetic resonance spectroscopy (MRS) is a noninvasive tool to measure tissue metabolism in vivo. ¹H-MRS is widely applied in research at clinical field strengths (≤3T) to measure mostly high abundant metabolites. In addition, X-nuclei MRS including, ¹³C, ²H, ¹⁷O, and ³¹P, are also very promising. Exploiting the higher sensitivity at ultra-high-field (>4T; UHF) strengths enables obtaining unique insights into different aspects of the substrate metabolism towards measuring cell-specific metabolic fluxes in vivo. This review provides an overview about the potential role of multinuclear MRS (¹H, ¹³C, ²H, ¹⁷O, and ³¹P) at UHF to assess the cerebral metabolism and the metabolic insights obtained by applying these techniques in both healthy and diseased states.

J-difference GABA-edited MRS reveals altered cerebello-thalamo-cortical metabolism in patients with hepatic encephalopathy

Hepatic encephalopathy (HE) is a common neurological manifestation of liver cirrhosis and is characterized by an increase of ammonia in the brain accompanied by a disrupted neurotransmitter balance, including the GABAergic and glutamatergic systems. The aim of this study is to investigate metabolic abnormalities in the cerebello-thalamo-cortical system of HE patients using GABA-edited MRS and links between metabolite levels, disease severity, critical flicker frequency (CFF), motor performance scores, and blood ammonia levels. GABA-edited MRS was performed in 35 participants (16 controls, 19 HE patients) on a clinical 3 T MRI system. MRS voxels were placed in the right cerebellum, left thalamus, and left motor cortex. Levels of GABA+ and of other metabolites of interest (glutamine, glutamate, myo-inositol, glutathione, total choline, total NAA, and total creatine) were assessed. Group differences in metabolite levels and associations with clinical metrics were tested. GABA+ levels were significantly increased in the cerebellum of patients with HE. GABA+ levels in the motor cortex were significantly decreased in HE patients, and correlated with the CFF (r = 0.73; p < .05) and motor performance scores (r = -0.65; p < .05). Well-established HE-typical metabolite patterns (increased glutamine, decreased myo-inositol and total choline) were confirmed in all three regions and were closely linked to clinical metrics. In summary, our findings provide further evidence for alterations in the GABAergic system in the cerebellum and motor cortex in HE. These changes were accompanied by characteristic patterns of osmolytes and oxidative stress markers in the cerebello-thalamo-cortical system. These metabolic disturbances are a likely contributor to HE motor symptoms in HE. In patients with hepatic encephalopathy, GABA+ levels in the cerebello-thalamo-cortical loop are significantly increased in the cerebellum and significantly decreased in the motor cortex. GABA+ levels in the motor cortex strongly correlate with critical flicker frequency (CFF) and motor performance score (pegboard test tPEG), but not blood ammonia levels (NH3).

Quantification of GABA concentration measured noninvasively in the human posterior cingulate cortex with 7 T ultra-short-TE MR spectroscopy

PURPOSE

The increased spectral dispersion achieved at ultra-high field permits quantification of γ-aminobutyric acid (GABA) concentrations at ultra-short-TE without editing. This work investigated the influence of spectral quality and different LCModel fitting approaches on quantification of GABA. Additionally, the sensitivity with which cross-sectional and longitudinal variations in GABA concentrations can be observed was characterized.

METHODS

In - vivo spectra were acquired in the posterior cingulate cortex of 10 volunteers at 7 T using a STEAM sequence. Synthetically altered spectra with different levels of GABA signals were used to investigate the reliability of GABA quantification with different LCModel fitting approaches and different realizations of SNR. The synthetically altered spectra were also used to characterize the sensitivity of GABA quantification.

RESULTS

The best LCModel fitting approach used stiff spline baseline, no soft constraints, and measured macromolecules in the basis set. With lower SNR, coefficients of variation increased dramatically. Longitudinal and cross-sectional variations in GABA of 10% could be detected with 79 and 48 participants per group, respectively. However, the small cohort may bias the calculation of the coefficients of variation and of the sample size that would be needed to detect variations in GABA.

CONCLUSION

Reliable quantification of normal and abnormal GABA concentrations was achieved for high quality 7 T spectra using LCModel fitting.

Feasibility and implications of using subject-specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data

Expert consensus recommends linear-combination modeling (LCM) of 1 H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions are usually derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied widely. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the MM baseline. Fully tissue- and relaxation-corrected metabolite levels were compared between MM strategies. Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values were found for the cohort-mean measured MM. Metabolite-age associations were consistently found for two major singlet signals (total creatine (tCr])and total choline (tCho)) for all MM strategies; however, findings for metabolites that are less distinguishable from the background signals associations depended on the MM strategy. A variance partition analysis indicated that up to 44% of the total variance was related to the choice of MM strategy. Additionally, the variance partition analysis reproduced the metabolite-age association for tCr and tCho found in the simpler correlation analysis. In summary, the inclusion of a single high signal-to-noise ratio MM basis function (cohort-mean) in the short-TE LCM leads to more lower model residuals and AIC values compared with MM strategies with more degrees of freedom (Gaussian parametrization) or subject-specific MM information. Integration of multiple LCM analyses into a single statistical model potentially allows to identify the robustness in the detection of underlying effects (e.g., metabolite vs. age), reduces algorithm-based bias, and estimates algorithm-related variance.

Impact of gradient scheme and non-linear shimming on out-of-voxel echo artifacts in edited MRS

Out-of-voxel (OOV) signals are common spurious echo artifacts in MRS. These signals often manifest in the spectrum as very strong "ripples," which interfere with spectral quantification by overlapping with targeted metabolite resonances. Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient schemes are algorithmically optimized to suppress all potential alternative coherence transfer pathways (CTPs), and should suppress unwanted OOV echoes. In addition, second-order shimming uses non-linear gradient fields to maximize field homogeneity inside the voxel, which unfortunately increases the diversity of local gradient fields outside of the voxel. Given that strong local spatial B0 gradients can refocus unintended CTPs, it is possible that OOVs are less prevalent when only linear first-order shimming is applied. Here we compare the size of unwanted OOV signals in Hadamard-edited (HERMES) data acquired with either a local gradient scheme (which we refer to here as "Shared") or DOTCOPS, and with first- or second-order shimming. We collected data from 15 healthy volunteers in two brain regions (voxel size 30 × 26 × 26 mm3 ) from which it is challenging to acquire MRS data: medial prefrontal cortex and left temporal cortex. Characteristic OOV echoes were seen in both GABA- and GSH-edited spectra for both brain regions, gradient schemes, and shimming approaches. A linear mixed-effect model revealed a statistically significant difference in the average residual based on the gradient scheme in both GABA- (p < 0.001) and GSH-edited (p < 0.001) spectra: that is, the DOTCOPS gradient scheme resulted in smaller OOV artifacts compared with the Shared scheme. There were no significant differences in OOV artifacts associated with shimming method. Thus, these results suggest that the DOTCOPS gradient scheme for J-difference-edited PRESS acquisitions yields spectra with smaller OOV echo artifacts than the Shared gradient scheme implemented in a widely disseminated editing sequence.

Brain total creatine differs between primary progressive aphasia (PPA) subtypes and correlates with disease severity

Primary progressive aphasia (PPA) is comprised of three subtypes: logopenic (lvPPA), non-fluent (nfvPPA), and semantic (svPPA). We used magnetic resonance spectroscopy (MRS) to measure tissue-corrected metabolite levels in the left inferior frontal gyrus (IFG) and right sensorimotor cortex (SMC) from 61 PPA patients. We aimed to: (1) characterize subtype differences in metabolites; and (2) test for metabolite associations with symptom severity. tCr differed by subtype across the left IFG and right SMC. tCr levels were lowest in lvPPA and highest in svPPA. tCr levels predicted lvPPA versus svPPA diagnosis. Higher IFG tCr and lower Glx correlated with greater disease severity. As tCr is involved in brain energy metabolism, svPPA pathology might involve changes in specific cellular energy processes. Perturbations to cellular energy homeostasis in language areas may contribute to symptoms. Reduced cortical excitatory capacity (i.e. lower Glx) in language regions may also contribute to symptoms. Thus, tCr may be useful for differentiating between PPA subtypes, and both tCr and Glx might have utility in understanding PPA mechanisms and tracking progression.

Impact of acquisition and modeling parameters on test-retest reproducibility of edited GABA

Literature values for within-subject test-retest reproducibility of gamma-aminobutyric acid (GABA), measured with edited magnetic resonance spectroscopy (MRS), vary widely. Reasons for this variation remain unclear. Here we tested whether sequence complexity (two-experiment MEGA-PRESS versus four-experiment HERMES), editing pulse duration (14 versus 20 ms), scanner frequency drift (interleaved water referencing (IWR) turned ON versus OFF), and linear combination modeling variations (three different co-edited macromolecule models and 0.55 versus 0.4 ppm spline baseline knot spacing) affected the within-subject coefficient of variation of GABA + macromolecules (GABA+). We collected edited MRS data from the dorsal anterior cingulate cortex from 20 participants (30.8 ± 9.5 years; 10 males). Test and retest scans were separated by removing the participant from the scanner for 5-10 minutes. Each acquisition consisted of two MEGA-PRESS and two HERMES sequences with editing pulse durations of 14 and 20 ms (referred to here as: MEGA-14, MEGA-20, HERMES-14, and HERMES-20; all TE = 80 ms, 224 averages). Reproducibility did not consistently differ for MEGA-PRESS compared with HERMES or for 14 compared with 20 ms editing pulses. A composite model of the 0.9 and 3 ppm macromolecules (particularly for HERMES) and sparser (0.55 compared with 0.4 ppm) spline baseline knot spacing yielded generally better test-retest reproducibility for GABA+. Replicating our prior results, linear combination modeling in Osprey compared with simple peak fitting in Gannet resulted in substantially better test-retest reproducibility. These results highlight the importance of model selection for edited MRS studies of GABA+, particularly for clinical studies which focus on individual patient differences in GABA+ or changes following an intervention.

Imaging oxidative stress in brains of chronic methamphetamine users: A combined 1H-magnetic resonance spectroscopy and peripheral blood biomarker study

Introduction

Preclinical data suggest methamphetamine (MA), a widely used stimulant drug, can harm the brain by causing oxidative stress and inflammation, but only limited information is available in humans. We tested the hypothesis that levels of glutathione (GSH), a major antioxidant, would be lower in the brains of chronic human MA preferring polysubstance users. We also explored if concentrations of peripheral immunoinflammatory blood biomarkers were related with brain GSH concentrations.

Methods

20 healthy controls (HC) (33 years; 11 M) and 14 MA users (40 years; 9 M) completed a magnetic resonance spectroscopy (MRS) scan, with GSH spectra obtained by the interleaved J-difference editing MEGA-PRESS method in anterior cingulate cortex (ACC) and left dorsolateral prefrontal cortex (DLPFC). Peripheral blood samples were drawn for measurements of immunoinflammatory biomarkers. Independent samples t-tests evaluated MA vs. HC differences in GSH.

Results

GSH levels did not differ between HC and MA users (ACC p = 0.30; DLPFC p = 0.85). A total of 17 of 25 immunoinflammatory biomarkers were significantly elevated in MA users and matrix metalloproteinase (MMP)-2 (r = 0.577, p = 0.039), myeloperoxidase (MPO) (r = -0.556, p = 0.049), and MMP-9 (r = 0.660, p = 0.038) were correlated with brain levels of GSH.

Conclusion

Normal brain GSH in living brain of chronic MA users is consistent with our previous postmortem brain finding and suggests that any oxidative stress caused by MA, at the doses used by our participants, might not be sufficient to cause either a compensatory increase in, or substantial overutilization of, this antioxidant. Additionally, more research is required to understand how oxidative stress and inflammatory processes are related and potentially dysregulated in MA use.

Accurate prediction of isocitrate dehydrogenase -mutation status of gliomas using SLOW-editing magnetic resonance spectroscopic imaging at 7 T MR

Background

2-hydroxy-glutarate (2HG) is a metabolite that accumulates in isocitrate dehydrogenase (IDH)-mutated gliomas and can be detected noninvasively using MR spectroscopy. However, due to the low concentration of 2HG, established magnetic resonance spectroscopic imaging (MRSI) techniques at the low field have limitations with respect to signal-to-noise and to the spatial resolution that can be obtained within clinically acceptable measurement times. Recently a tailored editing method for 2HG detection at 7 Tesla (7 T) named SLOW-EPSI was developed. The underlying prospective study aimed to compare SLOW-EPSI to established techniques at 7 T and 3 T for IDH-mutation status determination.

Methods

The applied sequences were MEGA-SVS and MEGA-CSI at both field strengths and SLOW-EPSI at 7 T only. Measurements were performed on a MAGNETOM-Terra 7 T MR-scanner in clinical mode using a Nova 1Tx32Rx head coil and on a 3 T MAGNETOM-Prisma scanner with a standard 32-channel head coil.

Results

Fourteen patients with suspected glioma were enrolled. Histopathological confirmation was available in 12 patients. IDH mutation was confirmed in 9 out of 12 cases and 3 cases were characterized as IDH wildtype. SLOW-EPSI at 7 T showed the highest accuracy for IDH-status prediction (91.7% accuracy, 11 of the 12 predictions correct with 1 false negative case). At 7 T, MEGA-CSI had an accuracy of 58.3% and MEGA-SVS had an accuracy of 75%. At 3 T, MEGA-CSI showed an accuracy of 63.6% and MEGA-SVS of 33.3%. The co-edited cystathionine was detected in 2 out of 3 oligodendroglioma cases with 1p/19q codeletion.

Conclusions

Depending on the pulse sequence, spectral editing can be a powerful tool for the noninvasive determination of the IDH status. SLOW-editing EPSI sequence is the preferable pulse sequence when used at 7 T for IDH-status characterization.

Iron- and Neuromelanin-Weighted Neuroimaging to Study Mitochondrial Dysfunction in Patients with Parkinson's Disease

The underlying causes of Parkinson's disease are complex, and besides recent advances in elucidating relevant disease mechanisms, no disease-modifying treatments are currently available. One proposed pathophysiological hallmark is mitochondrial dysfunction, and a plethora of evidence points toward the interconnected nature of mitochondria in neuronal homeostasis. This also extends to iron and neuromelanin metabolism, two biochemical processes highly relevant to individual disease manifestation and progression. Modern neuroimaging methods help to gain in vivo insights into these intertwined pathways and may pave the road to individualized medicine in this debilitating disorder. In this narrative review, we will highlight the biological rationale for studying these pathways, how distinct neuroimaging methods can be applied in patients, their respective limitations, and which challenges need to be overcome for successful implementation in clinical studies.

MRSCloud: A cloud-based MRS tool for basis set simulation

PURPOSE

The purpose of this study is to present a cloud-based spectral simulation tool "MRSCloud," which allows MRS users to simulate a vendor-specific and sequence-specific basis set online in a convenient and time-efficient manner. This tool can simulate basis sets for GE, Philips, and Siemens MR scanners, including conventional acquisitions and spectral editing schemes with PRESS and semi-LASER localization at 3 T.

METHODS

The MRSCloud tool was built on the spectral simulation functionality in the FID-A software package. We added three extensions to accelerate computation (ie, one-dimensional projection method, coherence pathways filters, and precalculation of propagators). The RF waveforms were generated based on vendors' generic pulse shapes and timings. Simulations were compared within MRSCloud using different numbers of spatial resolution (21 × 21, 41 × 41, and 101 × 101). Simulated metabolite basis functions from MRSCloud were compared with those generated by the generic FID-A and MARSS, and a phantom-acquired basis set from LCModel. Intraclass correlation coefficients were calculated to measure the agreement between individual metabolite basis functions. Statistical analysis was performed using R in RStudio.

RESULTS

Simulation time for a full PRESS basis set is approximately 11 min on the server. The interclass correlation coefficients ICCs were at least 0.98 between MRSCloud and FID-A and were at least 0.96 between MRSCloud and MARSS. The interclass correlation coefficients between simulated MRSCloud basis spectra and acquired LCModel basis spectra were lowest for glutamine at 0.68 and highest for N-acetylaspartate at 0.96.

CONCLUSIONS

Substantial reductions in runtime have been achieved. High ICC values indicated that the accelerating features are running correctly and produce comparable and accurate basis sets.

Cellular Lactate Spectroscopy Using 1.5 Tesla Clinical Apparatus

Cellular lactate is a key cellular metabolite and marker of anaerobic glycolysis. Cellular lactate uptake, release, production from glucose and glycogen, and interconversion with pyruvate are important determinants of cellular energy. It is known that lactate is present in the spectrum of neoplasms and low malignancy (without necrotic lesions). Also, the appearance of lactate signals is associated with anaerobic glucose, mitochondrial dysfunction, and other inflammatory responses. The aim of this study was the detection of lactate in cell cultures with the use of proton magnetic resonance (¹H MRS) and a 1.5 Tesla clinical apparatus (MR OPTIMA 360), characterized as a medium-field system. In this study, selected metabolites, together with cellular lactate, were identified with the use of an appropriate protocol and management algorithm. This paper describes the results obtained for cancer cell cultures. This medium-field system has proven the possibility of detecting small molecules, such as lactate, with clinical instruments. ¹H MRS performed using clinical MR apparatus is a useful tool for clinical analysis.

Brain metabolite alterations related to alcohol use: a meta-analysis of proton magnetic resonance spectroscopy studies

Alcohol misuse and alcohol use disorder (AlUD) have neurobiological consequences. This meta-analysis of proton magnetic resonance spectroscopy (MRS) studies aimed to assess the differences in brain metabolite levels in alcohol misuse and AUD relative to controls (PROSPERO registration: CRD42020209890). Hedge's g with random-effects modeling was used. Sub-group and meta-regression techniques explored potential sources of demographic and MRS parameter heterogeneity. A comprehensive literature review identified 43 studies, resulting in 69 models across gray and white matter (GM, WM). Lower N-acetylaspartate levels were found in frontal, anterior cingulate cortex (ACC), hippocampal, and cerebellar GM, and frontal and parietal WM, suggesting decreased neuronal and axonal viability. Lower choline-containing metabolite levels (all metabolites contributing to choline peak) were found in frontal, temporal, thalamic, and cerebellar GM, and frontal and parietal WM, suggesting membrane alterations related to alcohol misuse. Lower creatine-containing metabolite levels (Cr; all metabolites contributing to Cr peak) were found in temporal and occipital cortical GM, while higher levels were noted in midbrain/brainstem GM; this finding may have implications for using Cr as an internal reference. The lack of significant group differences in glutamate-related levels is possibly related to biological and methodological complexities. The few studies reporting on GABA found lower levels restricted to the ACC. Confounding variables were age, abstinence duration, treatment status, and MRS parameters (echo time, quantification type, data quality). This first meta-analysis of proton MRS studies consolidates the numerous individual studies to identify neurometabolite alterations within alcohol misuse and AUD. Future studies can leverage this new formalized information to investigate treatments that might effectively target the observed disturbances.

Quantifying GABA in Addiction: A Review of Proton Magnetic Resonance Spectroscopy Studies

Gamma-aminobutyric acid (GABA) signaling plays a crucial role in drug reward and the development of addiction. Historically, GABA neurochemistry in humans has been difficult to study due to methodological limitations. In recent years, proton magnetic resonance spectroscopy (¹H-MRS, MRS) has emerged as a non-invasive imaging technique that can detect and quantify human brain metabolites in vivo. Novel sequencing and spectral editing methods have since been developed to allow for quantification of GABA. This review outlines the clinical research utilization of ¹H-MRS in understanding GABA neurochemistry in addiction and summarizes current literature that reports GABA measurements by MRS in addiction. Research on alcohol, nicotine, cocaine, and cannabis addiction all suggest medications that modulate GABA signaling may be effective in reducing withdrawal, craving, and other addictive behaviors. Thus, we discuss how improvements in current MRS techniques and design can optimize GABA quantification in future studies and explore how monitoring changes to brain GABA could help identify risk factors, improve treatment efficacy, further characterize the nature of addiction, and provide crucial insights for future pharmacological development.

Single-Voxel Proton Magnetic Resonance Spectroscopy of the Thalamus in Idiopathic Epileptic Dogs and in Healthy Control Dogs

The role of magnetic resonance spectroscopy (MRS) in the investigation of brain metabolites in epileptic syndromes in dogs has not been explored systematically to date. The aim of this study was to investigate metabolites in the thalamus in dogs affected by idiopathic epilepsy (IE) with and without antiepileptic drug treatment (AEDT) and to compare them to unaffected controls. Our hypothesis is that similar to humans with generalized epilepsy and loss of consciousness, N-acetyl aspartate (NAA) would be reduced, and glutamate–glutamine (Glx) would be increased in treated and untreated IE in comparison with the control group. In this prospective case–control study, Border Collie (BC) and Greater Swiss Mountain dog (GSMD) were divided into three groups: (1) healthy controls, IE with generalized tonic–clonic seizures with (2) and without (3) AEDT. A total of 41 BC and GSMD were included using 3 Tesla single-voxel proton MRS of the thalamus (PRESS localization, shortest TE, TR = 2000 ms, NSA = 240). After exclusion of 11 dogs, 30 dogs (18 IE and 12 healthy controls) remained available for analysis. Metabolite concentrations were estimated with LCModel using creatine as reference and compared using Kruskal–Wallis and Wilcoxon rank-sum tests. The Kruskal–Wallis test revealed significant differences in the NAA-to-creatine (p = 0.04) and Glx-to-creatine (p = 0.03) ratios between the three groups. The Wilcoxon rank-sum test further showed significant reduction in the NAA/creatine ratio in idiopathic epileptic dogs under AEDT compared to epileptic dogs without AEDT (p = 0.03) and compared to healthy controls (p = 0.03). In opposite to humans, Glx/creatine ratio was significantly reduced in dogs with IE under AEDT compared to epileptic dogs without AEDT (p = 0.03) and controls (p = 0.02). IE without AEDT and healthy controls did not show significant difference, neither in NAA/creatine (p = 0.60), nor in Glx-to-creatine (p = 0.55) ratio. In conclusion, MRS showed changes in dogs with IE and generalized seizures under AEDT, but not in those without AEDT. Based upon these results, MRS can be considered a useful advanced imaging technique for the evaluation of dogs with IE in the clinical and research settings.

Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

Neuroimaging Methods to Map In Vivo Changes of OXPHOS and Oxidative Stress in Neurodegenerative Disorders

Mitochondrial dysfunction is a pathophysiological hallmark of most neurodegenerative diseases. Several clinical trials targeting mitochondrial dysfunction have been performed with conflicting results. Reliable biomarkers of mitochondrial dysfunction in vivo are thus needed to optimize future clinical trial designs. This narrative review highlights various neuroimaging methods to probe mitochondrial dysfunction. We provide a general overview of the current biological understanding of mitochondrial dysfunction in degenerative brain disorders and how distinct neuroimaging methods can be employed to map disease-related changes. The reviewed methodological spectrum includes positron emission tomography, magnetic resonance, magnetic resonance spectroscopy, and near-infrared spectroscopy imaging, and how these methods can be applied to study alterations in oxidative phosphorylation and oxidative stress. We highlight the advantages and shortcomings of the different neuroimaging methods and discuss the necessary steps to use these for future research. This review stresses the importance of neuroimaging methods to gain deepened insights into mitochondrial dysfunction in vivo, its role as a critical disease mechanism in neurodegenerative diseases, the applicability for patient stratification in interventional trials, and the quantification of individual treatment responses. The in vivo assessment of mitochondrial dysfunction is a crucial prerequisite for providing individualized treatments for neurodegenerative disorders.

SLOW: A novel spectral editing method for whole-brain MRSI at ultra high magnetic field

PURPOSE

At ultra-high field (UHF), B₁ ⁺ -inhomogeneities and high specific absorption rate (SAR) of adiabatic slice-selective RF-pulses make spatial resolved spectral-editing extremely challenging with the conventional MEGA-approach. The purpose of the study was to develop a whole-brain resolved spectral-editing MRSI at UHF (UHF, B₀  ≥ 7T) within clinical acceptable measurement-time and minimal chemical-shift-displacement-artifacts (CSDA) allowing for simultaneous GABA/Glx-, 2HG-, and PE-editing on a clinical approved 7T-scanner.

METHODS

Slice-selective adiabatic refocusing RF-pulses (2π-SSAP) dominate the SAR to the patient in (semi)LASER based MEGA-editing sequences, causing large CSDA and long measurement times to fulfill SAR requirements, even using SAR-minimized GOIA-pulses. Therefore, a novel type of spectral-editing, called SLOW-editing, using two different pairs of phase-compensated chemical-shift selective adiabatic refocusing-pulses (2π-CSAP) with different refocusing bandwidths were investigated to overcome these problems.

RESULTS

Compared to conventional echo-planar spectroscopic imaging (EPSI) and MEGA-editing, SLOW-editing shows robust refocusing and editing performance despite to B₁ ⁺ -inhomogeneity, and robustness to B₀ -inhomogeneities (0.2 ppm ≥ ΔB₀  ≥ -0.2 ppm). The narrow bandwidth (∼0.6-0.8 kHz) CSAP reduces the SAR by 92%, RF peak power by 84%, in-excitation slab CSDA by 77%, and has no in-plane CSDA. Furthermore, the CSAP implicitly dephases water, lipid and all the other signals outside of range (≥ 4.6 ppm and ≤1.4 ppm), resulting in additional water and lipid suppression (factors ≥ 1000s) at zero SAR-cost, and no spectral aliasing artifacts.

CONCLUSION

A new spectral-editing has been developed that is especially suitable for UHF, and was successfully applied for 2HG, GABA+, PE, and Glx-editing within 10 min clinical acceptable measurement time.

The role of MRS-assessed GABA in human behavioral performance

Understanding the neurophysiological mechanisms that drive human behavior has been a long-standing focus of cognitive neuroscience. One well-known neuro-metabolite involved in the creation of optimal behavioral repertoires is GABA, the main inhibitory neurochemical in the human brain. Converging evidence from both animal and human studies indicates that individual variations in GABAergic function are associated with behavioral performance. In humans, one increasingly used in vivo approach to measuring GABA levels is through Magnetic Resonance Spectroscopy (MRS). However, the implications of MRS measures of GABA for behavior remain poorly understood. In this respect, it is yet to be determined how GABA levels within distinct task-related brain regions of interest account for differences in behavioral performance. This review summarizes findings from cross-sectional studies that determined baseline MRS-assessed GABA levels and examined their associations with performance on various behaviors representing the perceptual, motor and cognitive domains, with a particular focus on healthy participants across the lifespan. Overall, the results indicate that MRS-assessed GABA levels play a pivotal role in various domains of behavior. Even though some converging patterns emerge, it is challenging to draw comprehensive conclusions due to differences in behavioral task paradigms, targeted brain regions of interest, implemented MRS techniques and reference compounds used. Across all studies, the effects of GABA levels on behavioral performance point to generic and partially independent functions that refer to distinctiveness, interference suppression and cognitive flexibility. On one hand, higher baseline GABA levels may support the distinctiveness of neural representations during task performance and better coping with interference and suppression of preferred response tendencies. On the other hand, lower baseline GABA levels may support a reduction of inhibition, leading to higher cognitive flexibility. These effects are task-dependent and appear to be mediated by age. Nonetheless, additional studies using emerging advanced methods are required to further clarify the role of MRS-assessed GABA in behavioral performance.

Influence of editing pulse flip angle on J-difference MR spectroscopy

PURPOSE

To investigate the editing-pulse flip angle (FA) dependence of editing efficiency and ultimately to maximize the edited signal of commonly edited MR spectroscopy (MRS) signals, such as gamma-aminobutyric acid (GABA) and lactate.

METHODS

Density-matrix simulations were performed for a range of spin systems to find the editing-pulse FA for maximal editing efficiency. Simulations were confirmed by phantom experiments and in vivo measurements in 10 healthy participants using a 3T Philips scanner. Four MEGA-PRESS in vivo measurements targeting GABA+ and lactate were performed, comparing the conventional editing-pulse FA (FA = 180°) to the optimal one suggested by simulations (FA = 210°).

RESULTS

Simulations and phantom experiments show that edited GABA and lactate signals are maximal at FA = 210°. Compared to conventional editing (FA = 180°), in vivo signals from GABA+ and lactate signals increase on average by 8.5% and 9.3%, respectively.

CONCLUSION

Increasing the FA of editing-pulses in the MEGA-PRESS experiment from 180° to 210° increases the edited signals from GABA+ and lactate by about 9% in vivo.

Edited magnetic resonance spectroscopy in the neonatal brain

J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.

Regional Differences in Gamma-Aminobutyric Acid and Glutamate Concentrations in the Healthy Newborn Brain

BACKGROUND AND PURPOSE

Gamma-aminobutyric acid and glutamate system disruptions may underlie neonatal brain injury. However, in vivo investigations are challenged by the need for special ¹H-MR spectroscopy sequences for the reliable measurement of the neurotransmitters in this population. We used J-edited ¹H-MR spectroscopy (Mescher-Garwood point-resolved spectroscopy) to quantify regional in vivo gamma-aminobutyric acid and glutamate concentrations during the early postnatal period in healthy neonates.

MATERIALS AND METHODS

We prospectively enrolled healthy neonates and acquired Mescher-Garwood point-resolved spectroscopy spectra on a 3T MR imaging scanner from voxels located in the cerebellum, the right basal ganglia, and the right frontal lobe. CSF-corrected metabolite concentrations were compared for regional variations and cross-sectional temporal trends with advancing age.

RESULTS

Fifty-eight neonates with acceptable spectra acquired at postmenstrual age of 39.1 (SD, 1.3) weeks were included for analysis. Gamma-aminobutyric acid (+ macromolecule) (2.56 [SD, 0.1]) i.u., glutamate (3.80 [SD, 0.2]), Cho, and mIns concentrations were highest in the cerebellum, whereas NAA (6.72 [SD, 0.2]), NAA/Cho, Cr/Cho, and Glx/Cho were highest in the basal ganglia. Frontal gamma-aminobutyric acid (1.63 [SD, 0.1]), Glx (4.33 [SD, 0.3]), Cr (3.64 [SD, 0.2]), and Cho concentrations were the lowest among the ROIs. Glx, NAA, and Cr demonstrated a significant adjusted increase with postmenstrual age (β = 0.2-0.35), whereas gamma-aminobutyric acid and Cho did not.

CONCLUSIONS

We report normative regional variations and temporal trends of in vivo gamma-aminobutyric acid and glutamate concentrations reflecting the functional and maturational status of 3 distinct brain regions of the neonate. These measures will serve as important normative values to allow early detection of subtle neurometabolic alterations in high-risk neonates.

The Relationship Between Resting Cerebral Blood Flow, Neurometabolites, Cardio-Respiratory Fitness and Aging-Related Cognitive Decline

Older adults typically experience a decline in cognitive function, but improvements in physical health and lifestyle can be neuroprotective across the human lifespan. The primary objective of this study is to advance our basic understanding of how cardiorespiratory fitness and neurophysiological attributes relate to cognitive decline. While cerebral blood flow (CBF) is critical for the supply of nutrients to the tissue, the brain's major neurotransmitters (i.e., gamma-aminobutyric acid, GABA, and glutamate-glutamine complex, Glx) are closely linked to oxidative metabolism. Within the context of flow-metabolism coupling, the critical question is how these neurophysiological parameters interplay, resulting in cognitive decline. Further, how cardiorespiratory fitness may impact aging neurophysiology and cognition is not well understood. To address these questions, we recruited 10 younger and 12 older cognitively intact participants to collect GABA and Glx using magnetic resonance spectroscopy (MRS), CBF using pseudo-continuous arterial spin labeling Magnetic Resonance Imaging (MRI), VO2max as a measure of cardiorespiratory fitness using the YMCA submax test, and cognitive and motor-cognitive measures using a battery of behavioral assessments. We observed expected differences in GABA+, Glx, and CBF between younger and older participants in pre-SMA, a frontal domain-general region. When GABA+ and Glx were related to CBF via multiple linear regression, Glx was identified as the main contributor to the model. For higher-order executive function (i.e., inhibition versus color naming), GABA*Glx*CBF interaction was critical in younger, while only Glx was involved in older participants. For unimanual motor dexterity, GABA*Glx interaction was the common denominator across both groups, but younger participants' brain also engages CBF. In terms of selective motor inhibition, CBF from younger participants was the only major neurophysiological factor. In terms of fitness, cardiorespiratory fitness was significantly related to GABA, Glx, and motor performance when combining cohorts, but no group-specific relationships were observed. Taken together, our results indicate that Glx and CBF coupling decreases with aging, perhaps due to altered glial oxidative metabolism. Our data suggest that GABA, Glx, and CBF are engaged and weighted differently for different cognitive measures sensitized to aging, and higher fitness allows for a more efficient metabolic shift that facilitates improved performance on cognitive-motor tasks.

The association between language-based task-functional magnetic resonance imaging hemodynamics and baseline GABA+ and glutamate-glutamine measured in pre-supplementary motor area: A pilot study in an aging model

Aging is a natural phenomenon that elicits slow and progressive cerebrovascular and neurophysiological changes that eventually lead to cognitive decline. The objective of this pilot study is to examine the association of GABA+ and glutamate-glutamine (Glx) complex with language-based blood oxygen level dependent (BOLD) hemodynamics in an aging model. More specifically, using standard BOLD we will first attempt to validate whether previously reported findings for BOLD amplitude and resting neurochemical relationships hold in an aging model. Secondly, we will investigate how our recently established neurosensitized task-BOLD energetics relate to resting GABA+ and Glx, especially accounting for titration of task difficulty. To support the above endeavors, we optimize the baseline fitting for edited magnetic resonance spectroscopy (MRS) difference spectra to sensitize GABA+ and Glx concentrations to aging-related differences. We identify a spline-knot spacing of 0.6ppm to yield the optimal aging-related differences in GABA+ and Glx. The optimized MRS values were then graduated to relate to task-BOLD hemodynamics. Our results did not replicate previous findings that relate task-BOLD amplitude and resting GABA+ and Glx. However, we did identify neurochemistry relationships with the vascularly-driven dispersion component of the hemodynamic response function, specifically in older participants. In terms of neuro-sensitized BOLD energetics and the underlying role of GABA+ and Glx, our data suggests that the task demands are supported by both neurometabolites depending on the difficulty of the task stimuli. Another novelty is that we developed task-based functional parcellation of pre-SMA using both groups. In sum, we are the first to demonstrate that multimodal task-fMRI and MRS studies are beneficial to improve our understanding of the aging brain physiology, and to set the platform to better inform approaches for clinical care in aging-related neurovascular diseases. We also urge future studies to replicate our findings in a larger population incorporating a lifespan framework.

Comparison of linear combination modeling strategies for edited magnetic resonance spectroscopy at 3 T

J-difference-edited spectroscopy is a valuable approach for the in vivo detection of γ-aminobutyric-acid (GABA) with magnetic resonance spectroscopy (MRS). A recent expert consensus article recommends linear combination modeling (LCM) of edited MRS but does not give specific details regarding implementation. This study explores different modeling strategies to adapt LCM for GABA-edited MRS. Sixty-one medial parietal lobe GABA-edited MEGA-PRESS spectra from a recent 3-T multisite study were modeled using 102 different strategies combining six different approaches to account for co-edited macromolecules (MMs), three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, standard deviations and coefficients of variation (CVs), and Akaike information criteria, were used to evaluate the models' performance. Significantly different GABA+ and GABA estimates were found when a well-parameterized MM_3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM_3co , while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range-only including the signals of interest-did not substantially improve or degrade modeling performance. Additionally, the results suggest that LCM can separate GABA and the underlying co-edited MM_3co . Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. In conclusion, GABA-edited MRS is most appropriately quantified by LCM with a well-parameterized co-edited MM_3co basis function with a constraint to the nonoverlapped MM_0.93 , in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range of 0.5-4 ppm.