In vivo estimation of transverse relaxation time constant (T2 ) of 17 human brain metabolites at 3T

Multi-Parametric Molecular Imaging of the Brain Using Optimized Multi-TE Subspace MRSI

OBJECTIVE

To develop a novel multi-TE MR spectroscopic imaging (MRSI) approach to enable label-free, simultaneous, high-resolution mapping of several molecules and their biophysical parameters in the brain.

METHODS

The proposed method uniquely integrated an augmented molecular-component-specific subspace model for multi-TE 1H-MRSI signals, an estimation-theoretic experiment optimization (nonuniform TE selection) for molecule separation and parameter estimation, a physics-driven subspace learning strategy for spatiospectral reconstruction and molecular quantification, and a new accelerated multi-TE MRSI acquisition for generating high-resolution data in clinically relevant times. Numerical studies, phantom and in vivo experiments were conducted to validate the optimized experiment design and demonstrate the imaging capability offered by the proposed method.

RESULTS

The proposed TE optimization improved estimation of metabolites, neurotransmitters and their T2's over conventional TE choices, e.g., reducing variances of neurotransmitter concentration by  ∼  40% and metabolite T2 by  ∼  60%. Simultaneous metabolite and neurotransmitter mapping of the brain can be achieved at a nominal resolution of 3.4 × 3.4 × 6.4 mm 3. High-resolution, 3D metabolite T2 mapping was made possible for the first time. The translational potential of the proposed method was demonstrated by mapping biochemical abnormality in a post-traumatic epilepsy (PTE) patient.

CONCLUSION

The feasibility for high-resolution mapping of metabolites/neurotransmitters and metabolite T2's within clinically relevant time was demonstrated. We expect our method to offer richer information for revealing and understanding metabolic alterations in neurological diseases.

SIGNIFICANCE

A novel multi-TE MRSI approach was presented that enhanced the technological capability of multi-parametric molecular imaging of the brain. The proposed method presents new technology development and application opportunities for providing richer molecular level information to uncover and comprehend metabolic changes relevant in various neurological applications.

Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for Advanced MRS

Background

To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study.

Methods

ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T2 correction based on the dual-TE water integrals were compared with: 1) T2 correction based the default white matter and gray matter T2 reference values in Osprey; 2) shorter WM and GM T2 values from recent literature; and 3) reduced CSF fractions.

Results

No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p<0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T2 correction based on shorter T2 values showed better agreement to the dual-TE water integral ratio.

Conclusions

ISTHMUS facilitated and standardized acquisition and post-processing and reduced operator workload to eliminate potential human error.

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

Introduction

Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations.

Methods

In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values.

Results

Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature.

Discussion

In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

Multi-echo single-shot spectroscopy combined with simultaneous 2D model fitting for fast and accurate measurement of metabolite-specific concentrations and T2 relaxation times

The purpose of the current study was to develop a novel single-voxel MR spectroscopy acquisition scheme to simultaneously determine metabolite-specific concentrations and transverse relaxation times within realistic clinical scan times. Partly truncated multi-TE data are acquired as an echo train in a single acquisition (multi-echo single-shot [MESS]). A 2D multiparametric model fitting approach combines truncated, low-resolved short TE data with fully sampled, highly resolved, longer TE data to yield concentration and T2 estimates for major brain metabolites simultaneously. Cramer-Rao lower bounds (CRLB) are used as a measure of performance. The novel scheme was compared with traditional multi-echo multi-shot methods. In silico, in vitro, and in vivo experiments support the findings. MESS schemes, requiring only 2 min 12 s for the acquisition of three echo times, provide valid concentration and relaxation estimates for multiple metabolites and outperform traditional methods for simultaneous determinations of metabolite-specific T2 s and concentrations, with improvements ranging from 5% to 30% for T2 s and from 10% to 50% for concentrations. However, substantial unsuppressed residual water signals may hamper the method's reproducibility, as observed in an initial experiment setup that prioritizes short TEs with severely truncated acquisition for the benefit of signal-to-noise ratio (SNR). Nevertheless, CRLB have been confirmed to be well suited as design criteria, and within-session repeatability approaches CRLB when residual water is removed in postprocessing by exploiting longer and less truncated data recordings. MESS MRS combined with 2D model fitting promises comparable accuracy, increased precision, or inversely shorter experimental times compared with traditional approaches. However, the optimal design must be investigated as a trade-off between SNR, the truncation factor, and TE batch selections, all of which influence the robustness of estimations.

Impact of cannabis use on brain metabolism using 31P and 1H magnetic resonance spectroscopy

PURPOSE

This prospective cross-sectional study investigated the influence of regular cannabis use on brain metabolism in young cannabis users by using combined proton and phosphorus magnetic resonance spectroscopy.

METHODS

The study was performed in 45 young cannabis users aged 18-30, who had been using cannabis on a regular basis over a period of at least 2 years and in 47 age-matched controls. We acquired 31P MRS data in different brain regions at 3T with a double-resonant 1H/31P head coil, anatomic images, and 1H MRS data with a standard 20-channel 1H head coil. Absolute concentration values of proton metabolites were obtained via calibration from tissue water as an internal reference, whereas a standard solution of 75 mmol/l KH2PO4 was used as an external reference for the calibration of phosphorus signals.

RESULTS

We found an overall but not statistically significant lower concentration level of several proton and phosphorus metabolites in cannabis users compared to non-users. In particular, energy-related phosphates such as adenosine triphosphate (ATP) and inorganic phosphate (Pi) were reduced in all regions under investigation. Phosphocreatine (PCr) showed lowered values mainly in the left basal ganglia and the left frontal white matter.

CONCLUSION

The results suggest that the increased risk of functional brain disorders observed in long-term cannabis users could be caused by an impairment of the energy metabolism of the brain, but this needs to be verified in future studies.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

In vivo magnetic resonance spectroscopy by transverse relaxation encoding with narrowband decoupling

Cell pathology in neuropsychiatric disorders has mainly been accessible by analyzing postmortem tissue samples. Although molecular transverse relaxation informs local cellular microenvironment via molecule-environment interactions, precise determination of the transverse relaxation times of molecules with scalar couplings (J), such as glutamate and glutamine, has been difficult using in vivo magnetic resonance spectroscopy (MRS) technologies, whose approach to measuring transverse relaxation has not changed for decades. We introduce an in vivo MRS technique that utilizes frequency-selective editing pulses to achieve homonuclear decoupled chemical shift encoding in each column of the acquired two-dimensional dataset, freeing up the entire row dimension for transverse relaxation encoding with J-refocusing. This results in increased spectral resolution, minimized background signals, and markedly broadened dynamic range for transverse relaxation encoding. The in vivo within-subject coefficients of variation for the transverse relaxation times of glutamate and glutamine, measured using the proposed method in the human brain at 7 T, were found to be approximately 4%. Since glutamate predominantly resides in glutamatergic neurons and glutamine in glia in the brain, this noninvasive technique provides a way to probe cellular pathophysiology in neuropsychiatric disorders for characterizing disease progression and monitoring treatment response in a cell type-specific manner in vivo.

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.

Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease

Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Adaptive model-based Magnetic Resonance

PURPOSE

Conventional sequences are static in nature, fixing measurement parameters in advance in anticipation of a wide range of expected tissue parameter values. We set out to design and benchmark a new, personalized approach-termed adaptive MR-in which incoming subject data is used to update and fine-tune the pulse sequence parameters in real time.

METHODS

We implemented an adaptive, real-time multi-echo (MTE) experiment for estimating T₂ s. Our approach combined a Bayesian framework with model-based reconstruction. It maintained and continuously updated a prior distribution of the desired tissue parameters, including T₂ , which was used to guide the selection of sequence parameters in real time.

RESULTS

Computer simulations predicted accelerations between 1.7- and 3.3-fold for adaptive multi-echo sequences relative to static ones. These predictions were corroborated in phantom experiments. In healthy volunteers, our adaptive framework accelerated the measurement of T₂ for n-acetyl-aspartate by a factor of 2.5.

CONCLUSION

Adaptive pulse sequences that alter their excitations in real time could provide substantial reductions in acquisition times. Given the generality of our proposed framework, our results motivate further research into other adaptive model-based approaches to MRI and MRS.

sLASER and PRESS Perform Similarly at Revealing Metabolite-Age Correlations

Purpose

To compare the respective ability of PRESS and sLASER to reveal biological relationships, using age as a validation covariate.

Methods

MRS data were acquired from 102 healthy volunteers using PRESS and sLASER in centrum semiovale (CSO) and posterior cingulate cortex (PCC) regions. Acquisition parameters included TR/TE 2000/30 ms; 96 transients; 2048 datapoints sampled at 2 kHz.Spectra were analyzed using Osprey. Signal-to-noise ratio (SNR), full-width-half-maximum linewidth of tCr, and metabolite concentrations were extracted. A linear model was used to compare SNR and linewidth. Paired t-tests were used to assess differences in metabolite measurements between PRESS and sLASER. Correlations were used to evaluate the relationship between PRESS and sLASER metabolite estimates, as well as the strength of each metabolite-age relationship. Coefficients of variation were calculated to assess inter-subject variability in each metabolite measurement.

Results

SNR and linewidth were significantly higher (p<0.05) for sLASER than PRESS. Paired t-tests showed significant differences between PRESS and sLASER in most metabolite measurements. Metabolite measures were significantly correlated (p<0.05) for most metabolites between the two methods except GABA, Gln and Lac in CSO and GSH, Lac and NAAG in PCC. Metabolite-age relationships were consistently identified using both PRESS and sLASER. Similar CVs were observed for most metabolites.

Conclusion

The study results suggest strong agreement between PRESS and sLASER in identifying relationships between brain metabolites and age in CSO and PCC data acquired at 3T. sLASER is technically desirable due to the reduced chemical shift displacement artifact; however, PRESS performed similarly in 'good' brain regions at clinical field strength.

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

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

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.

MR Spectroscopy of the Insula: Within- and between-Session Reproducibility of MEGA-PRESS Measurements of GABA+ and Other Metabolites

The insula plays a critical role in many neuropsychological disorders. Research investigating its neurochemistry with magnetic resonance spectroscopy (MRS) has been limited compared with cortical regions. Here, we investigate the within-session and between-session reproducibility of metabolite measurements in the insula on a 3T scanner. We measure N-acetylaspartate + N-acetylaspartylglutamate (tNAA), creatine + phosphocreatine (tCr), glycerophosphocholine + phosphocholine (tCho), myo-inositol (Ins), glutamate + glutamine (Glx), and γ-aminobutyric acid (GABA) in one cohort using a j-edited MEGA-PRESS sequence. We measure tNAA, tCr, tCho, Ins, and Glx in another cohort with a standard short-TE PRESS sequence as a reference for the reproducibility metrics. All participants were scanned 4 times identically: 2 back-to-back scans each day, on 2 days. Preprocessing was done using LCModel and Gannet. Reproducibility was determined using Pearson’s r, intraclass-correlation coefficients (ICC), coefficients of variation (CV%), and Bland–Altman plots. A MEGA-PRESS protocol requiring averaged results over two 6:45-min scans yielded reproducible GABA measurements (CV% = 7.15%). This averaging also yielded reproducibility metrics comparable to those from PRESS for the other metabolites. Voxel placement inconsistencies did not affect reproducibility, and no sex differences were found. The data suggest that MEGA-PRESS can reliably measure standard metabolites and GABA in the insula.

Hippocampal single-voxel MR spectroscopy with a long echo time at 3 T using semi-LASER sequence

The hippocampus is one of the most challenging brain regions for proton MR spectroscopy (MRS) applications. Moreover, quantification of J-coupled species such as myo-inositol (m-Ins) and glutamate + glutamine (Glx) is affected by the presence of macromolecular background. While long echo time (TE) MRS eliminates the macromolecules, it also decreases the m-Ins and Glx signal and, as a result, these metabolites are studied mainly with short TE. Here, we investigate the feasibility of reproducibly measuring their concentrations at a long TE of 120 ms, using a semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence, as this sequence was recently recommended as a standard for clinical MRS. Gradient offset-independent adiabatic refocusing pulses were implemented, and an optimal long TE for the detection of m-Ins and Glx was determined using the T2 relaxation times of macromolecules. Metabolite concentrations and their coefficients of variation (CVs) were obtained for a 3.4-mL voxel centered on the left hippocampus on 3-T MR systems at two different sites with three healthy subjects (aged 32.5 ± 10.2 years [mean ± standard deviation]) per site, with each subject scanned over two sessions, and with each session comprising three scans. Concentrations of m-Ins, choline, creatine, Glx and N-acetyl-aspartate were 5.4 ± 1.5, 1.7 ± 0.2, 5.8 ± 0.3, 11.6 ± 1.2 and 5.9 ± 0.4 mM (mean ± standard deviation), respectively. Their respective mean within-session CVs were 14.5% ± 5.9%, 6.5% ± 5.3%, 6.0% ± 3.4%, 10.6% ± 6.2% and 3.5% ± 1.4%, and their mean within-subject CVs were 17.8% ± 18.2%, 7.5% ± 6.3%, 7.4% ± 6.4%, 12.4% ± 5.3% and 4.8% ± 3.0%. The between-subject CVs were 25.0%, 12.3%, 5.3%, 10.7% and 6.4%, respectively. Hippocampal long-TE sLASER single voxel spectroscopy can provide macromolecule-independent assessment of all major metabolites including Glx and m-Ins.

Are Cramér-Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy?

Due to inherent time constraints for in vivo experiments, it is infeasible to repeat multiple MRS scans to estimate standard deviations on the desired measured parameters. As such, the Cramér-Rao lower bounds (CRLBs) have become the routine method to approximate standard deviations for in vivo experiments. Cramér-Rao lower bounds, however, as the name suggests, are theoretically a lower bound on the standard deviation and it is not clear if and under what circumstances this approximation is valid. Realistic synthetic 3 T spectra were used to investigate the relationship between estimated CRLBs, true CRLBs and standard deviations. Here we demonstrate that, although the CRLBs are theoretically truly a lower bound on the standard deviation (not an equality) for the problem typically encountered in quantification, they are still an adequate approximation to standard deviation as long as the model perfectly characterizes the data. In the case when the macromolecule basis deviates from the measured macromolecules it was shown that the CRLBs can deviate from standard deviations by approximately 50% for N-acetylaspartic acid, creatine and glutamate and of the order of 100% or more for myo-inositol and γ-aminobutyric acid. In the case when the model perfectly reflects the data the CRLBs are within approximately 10% of standard deviations for all metabolites. The result of the CRLB being within 10% of standard deviations means that, for an accurate model, novel quantification methods such as machine learning or deep learning will not be able to obtain substantially more precise estimates for the desired parameters than traditional maximum-likelihood estimation.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Measuring transverse relaxation rates of the major brain metabolites from single-voxel PRESS acquisitions at a single TE

PURPOSE

To compare transverse relaxation rates of brain metabolites estimated from single-TE PRESS acquisitions with more conventionally derived rates estimated from multiple-TE PRESS acquisitions.

METHODS

Single-voxel (8 mL) PRESS data within white matter from 6 subjects were acquired at five different TEs. Transverse relaxation rates R₂ of N-acetylaspartate, creatine, and choline were estimated from a single TE using full versus right-side-only sampling of the echo. These R₂ values were compared with R_2Hahn values obtained from the multiple-TE PRESS acquisitions.

RESULTS

Following baseline subtraction and RMS weighting, interindividual mean R₂ values from TE = 288 ms magnitude spectra for choline, creatine, and N-acetylaspartate were highly correlated with respective R_2Hahn values (r² = 0.99). Paired individual measurements at this TE showed less correlation (r² = 0.48), primarily due to the N-acetylaspartate resonance. Using TE = 360 ms data for N-acetylaspartate and 288 ms for choline and creatine resulted in an improved correlation coefficient (r² = 0.80). The average absolute intra-individual differences in the estimated R₂ s between single-TE and Hahn method was 9.6 ± 7.7%.

CONCLUSION

For the major brain metabolite singlets, R_2Hahn values showed correlations with more fragile measurements of R₂ from a single TE that are worthy of interest. Because the left side of long-TE spin echoes is available "for free" from an acquisition perspective, and although the single-TE method for estimating R₂ values is associated with lower precision, the reduction in scan time may be clinically helpful.

Cortical Glutamate and GABA Changes During Early Abstinence in Alcohol Dependence and Their Associations With Benzodiazepine Medication

In this report, we present cross-sectional and longitudinal findings from single-voxel MEGA-PRESS MRS of GABA as well as Glu, and Glu + glutamine (Glx) concentrations in the ACC of treatment-seeking alcohol-dependent patients (ADPs) during detoxification (first 2 weeks of abstinence). The focus of this study was to examine whether the amount of benzodiazepine administered to treat withdrawal symptoms was associated with longitudinal changes in Glu, Glx, and GABA. The tNAA levels served as an internal quality reference; in agreement with the vast majority of previous reports, these levels were initially decreased and normalized during the course of abstinence in ADPs. Our results on Glu and Glx support hyperglutamatergic functioning during alcohol withdrawal, by showing higher ACC Glu and Glx levels on the first day of detoxification in ADPs. Withdrawal severity is reflected in cumulative benzodiazepine requirements throughout the withdrawal period. The importance of withdrawal severity for the study of GABA and Glu changes in early abstinence is emphasized by the benzodiazepine-dependent Glu, Glx, and GABA changes observed during the course of abstinence.

Brain Metabolite Levels in Sedentary Women and Non-contact Athletes Differ From Contact Athletes

White matter tracts are known to be susceptible to injury following concussion. The objective of this study was to determine whether contact play in sport could alter white matter metabolite levels in female varsity athletes independent of changes induced by long-term exercise. Metabolite levels were measured by single voxel proton magnetic resonance spectroscopy (MRS) in the prefrontal white matter at the beginning (In-Season) and end (Off-Season) of season in contact (N = 54, rugby players) and non-contact (N = 23, swimmers and rowers) varsity athletes. Sedentary women (N = 23) were scanned once, at a time equivalent to the Off-Season time point. Metabolite levels in non-contact athletes did not change over a season of play, or differ from age matched sedentary women except that non-contact athletes had a slightly lower myo-inositol level. The contact athletes had lower levels of myo-inositol and glutamate, and higher levels of glutamine compared to both sedentary women and non-contact athletes. Lower levels of myo-inositol in non-contact athletes compared to sedentary women indicates long-term exercise may alter glial cell profiles in these athletes. The metabolite differences observed between contact and non-contact athletes suggest that non-contact athletes should not be used as controls in studies of concussion in high-impact sports because repetitive impacts from physical contact can alter white matter metabolite level profiles. It is imperative to use athletes engaged in the same contact sport as controls to ensure a matched metabolite profile at baseline.

Sample size estimation: Current practice and considerations for original investigations in MRI technical development studies

PURPOSE

To investigate and to provide guidance for sample size selection based on the current practice in MR technical development studies in which healthy volunteers are examined.

METHODS

All original articles published in Magnetic Resonance in Medicine between 2017 and 2019 were investigated and categorized according to technique, anatomical region, and magnetic field strength. The number of examined healthy volunteers (ie, the sample size) was collected and evaluated, whereas the number of patients was not considered. Papers solely measuring patients, animals, phantoms, specimens, or studies using existing data, for example, from an open databank, or consisting only of theoretical work or simulations were excluded.

RESULTS

The median sample size of the 882 included studies was 6. There were some peaks in the sample size distribution (eg, 1, 5, and 10). In 49.9%, 82.1%, and 95.6% of the studies, the sample size was smaller or equal to 5, 10, and 20, respectively.

CONCLUSION

We observed a large variance in sample sizes reflecting the variety of studies published in Magnetic Resonance in Medicine. Therefore, it can be concluded that it is current practice to balance the need for statistical power with the demand to minimize experiments involving healthy humans, often by choosing small sample sizes between 1 and 10. Naturally, this observation does not release an investigator from ensuring that sufficient data are acquired to reach statistical conclusions.

Flexible MEGA editing scheme with asymmetric adiabatic pulses applied for T 2 measurement of lactate in human brain

PURPOSE

A flexible MEGA editing scheme which decouples the editing efficiency from TE is proposed and the utility of asymmetric adiabatic pulses for this new technique is explored. It is demonstrated that the method enables robust T 2 measurement of lactate in healthy human brain.

METHODS

The proposed variation of the MEGA scheme applies editing pulses in both acquired spectra, ensuring that the difference in J-evolution of the target resonance leads to maximal signal yield in the difference spectrum for arbitrary TE. A MEGA-sLASER sequence is augmented with asymmetric adiabatic editing pulses for enhanced flexibility and immunity to B 1 + miscalibration and inhomogeneities. The technique is validated and optimized for flexible lactate editing via a simple analytical model, numerical simulations and in vitro experiments. The T 2 relaxation constant of lactate is determined in vivo via multiple-TE measurements with the proposed method and a dedicated postprocessing and quantification approach.

RESULTS

Asymmetric adiabatic editing pulses improve robustness and facilitate efficient J-editing in sequences or protocols with strong timing constraints. Single voxel measurements using the proposed MEGA scheme in the occipital cortex of six healthy subjects yield a relaxation constant of T 2 = 171 ± 19  ms for the methyl resonance of lactate at a field strength of 3T.

CONCLUSIONS

The proposed MEGA editing scheme allows for novel kinds of J-editing experiments and promises to be an asset to robust T 2 measurement of lactate and potentially other J-coupled metabolites in vivo.

Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data

BACKGROUND

Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization.

NEW METHOD

Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects.

RESULTS

Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques.

COMPARISON WITH EXISTING METHOD(S)

Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey's open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis.

CONCLUSIONS

Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.

A semi-LASER, single-voxel spectroscopic sequence with a minimal echo time of 20.1 ms in the human brain at 3 T

An optimized semi-LASER sequence that is capable of acquiring artefact-free data with an echo time (TE) of 20.1 ms on a standard clinical 3 T MR system was developed. Simulations were performed to determine the optimal TEs that minimize the expected Cramér-Rao lower bound (CRLB) as proxy for quantification accuracy of metabolites. Optimized RF pulses, crusher gradients and phase cycling were used to achieve the shortest TE in a semi-LASER sequence to date on a clinical system. Synthetic spectra were simulated using the density matrix formalism for TEs spanning from 20.1 to 220.1 ms. These simulations were used to calculate the expected CRLB for each of the 18 metabolites typically considered in ¹ H MRS. High quality spectra were obtained in six healthy volunteers in the prefrontal cortex, which is known for spurious echoes due to its proximity to the paranasal sinuses, and in the parietal-occipital cortex. Spectral transients were sufficient in quality to enable phase and frequency alignment prior to summation over all repetitions. Automated high-quality water suppression was obtained for all voxels without manual adjustment. The shortest TE minimized the CRLB for all brain metabolites except glycine due to its overlap with myo-inositol at this TE. It is also demonstrated that the CRLBs increase rapidly with TE for certain coupled metabolites.

Parameterization of metabolite and macromolecule contributions in interrelated MR spectra of human brain using multidimensional modeling

Macromolecular signals are crucial constituents of short echo-time ¹ H MR spectra with potential clinical implications in themselves as well as essential ramifications for the quantification of the usually targeted metabolites. Their parameterization, needed for general fitting models, is difficult because of their unknown composition. Here, a macromolecular signal parameterization together with metabolite signal quantification including relaxation properties is investigated by multidimensional modeling of interrelated 2DJ inversion-recovery (2DJ-IR) datasets. Simultaneous and iterative procedures for defining the macromolecular background (MMBG) as mono-exponentially or generally decaying signals over TE are evaluated. Varying prior knowledge and restrictions in the metabolite evaluation are tested to examine their impact on results and fitting stability for two sets of three-dimensional spectra acquired with metabolite-cycled PRESS from cerebral gray and white matter locations. One dataset was used for model optimization, and also examining the influence of prior knowledge on estimated parameters. The most promising model was applied to a second dataset. It turned out that the mono-exponential decay model appears to be inadequate to represent TE-dependent signal features of the MMBG. TE-adapted MMBG spectra were therefore determined. For a reliable overall quantification of implicated metabolite concentrations and relaxation times, a general fitting model had to be constrained in terms of the number of fitting variables and the allowed parameter space. With such a model in place, fitting precision for metabolite contents and relaxation times was excellent, while fitting accuracy is difficult to judge and bias was likely influenced by the type of fitting constraints enforced. In summary, the parameterization of metabolite and macromolecule contributions in interrelated MR spectra has been examined by using multidimensional modeling on complex 2DJ-IR datasets. A tightly restricted model allows fitting of individual subject data with high fitting precision documented in small Cramér-Rao lower bounds, good repeatability values and a relatively small spread of estimated concentration and relaxation values for a healthy subject cohort.

UTE-SPECIAL for3D localization at an echo time of 4 ms on a clinical 3 T scanner

Reducing the echo time of magnetic resonance spectroscopy experiments is appealing because it increases the available signal and reduces J-evolution of coupled metabolites. In this manuscript a novel sequence, referred to as Ultrashort echo TimE, SPin ECho, full Intensity Acquired Localized (UTE-SPECIAL), is described which is able to achieve ultrashort echo times (4 ms) on a standard clinical 3 T MR system while recovering the entirety of the available magnetization. UTE-SPECIAL obtains full 3D spatial localization through a 2D adiabatic inversion pulse which is cycled "on" and "off" every other repetition, in combination with a slice-selective excitation pulse. In addition to an ultrashort echo time, UTE-SPECIAL has negligible chemical shift displacement artefact and, because it uses no slice-selective refocusing pulse, has no signal cancellation at the borders for J-coupled metabolites. Spectra with an ultrashort echo time of 4 ms are demonstrated in vivo at 3 T, as well as J-resolved spectra obtained in a phantom and a healthy volunteer.

Validation of in vivo MRS measures of metabolite concentrations in the human brain

PURPOSE

In vivo magnetic resonance spectroscopy (MRS) is the only technique capable of non-invasively assessing metabolite concentrations in the brain. The lack of alternative methods makes validation of MRS measures challenging. The aim of this study is to assess the validity of MRS measures of human brain metabolite concentrations by comparing multiple MRS measures acquired using different MRS acquisition sequences.

METHODS

Single-voxel SPECIAL and MEGA-PRESS MR spectra were acquired from both the dorsolateral prefrontal cortex and primary motor cortices in 15 healthy subjects. The SPECIAL spectrum, as well as both the edit-off and difference spectra of MEGA-PRESS were each analyzed in LCModel to obtain estimates of the absolute concentrations of total choline (TCh; glycerophosphocholine + phosphocholine), total creatine (TCr; creatine + phosphocreatine), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), NAA + NAAG, glutamate (Glu), glutamine (Gln), Glu + Gln, scyllo-inositol (Scyllo), myo-inositol (Ins), glutathione (GSH), γ-aminobutyric acid (GABA), lactate (Lac) and aspartate (Asp). Then, having obtained up to three independent measures of each metabolite per brain region per subject, correlations between the different measures were assessed.

RESULTS

The degree of correlation between measures varied greatly across both the metabolites and sequences tested. As expected, metabolites with the most prominent spectral peaks (TCh, TCr, NAA + NAAG, Ins and Glu) had the most well-correlated measures between methods, while metabolites with less prominent spectral peaks (Lac, Gln, GABA, Asp, and NAAG) tended to have poorly-correlated measures between methods. Some metabolites with relatively less prominent spectral peaks (GSH, Scyllo) had fairly well-correlated measures between some methods. Combining metabolites improved the agreement between methods for measures of NAA + NAAG, but not for Glu + Gln.

CONCLUSIONS

Given that the ground truth for in vivo MRS measures is never known, the method proposed here provides a promising means to assess the validity of in vivo MRS measures, which has not yet been explored widely.

Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES

PURPOSE

To demonstrate the framework of a novel Hadamard-encoded spectral editing approach for simultaneously detecting multiple low-concentration brain metabolites in vivo at 3T.

METHODS

HERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) is a four-step Hadamard-encoded editing scheme. 20-ms editing pulses are applied at: (A) 4.58 and 1.9 ppm; (B) 4.18 and 1.9 ppm; (C) 4.58 ppm; and (D) 4.18 ppm. Edited signals from γ-aminobutyric acid (GABA), glutathione (GSH), ascorbate (Asc), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), aspartate (Asp), lactate (Lac), and likely 2-hydroxyglutarate (2-HG) are separated with reduced signal overlap into distinct Hadamard combinations: (A+B+C+D); (A+B-C-D); and (A-B+C-D). HERCULES uses a novel multiplexed linear-combination modeling approach, fitting all three Hadamard combinations at the same time, maximizing the amount of information used for model parameter estimation, in order to quantify the levels of these compounds. Fitting also allows estimation of the levels of total choline (tCho), myo-inositol (Ins), glutamate (Glu), and glutamine (Gln). Quantitative HERCULES results were compared between two grey- and white-matter-rich brain regions (11 min acquisition time each) in 10 healthy volunteers. Coefficients of variation (CV) of quantified measurements from the HERCULES fitting approach were compared against those from a single-spectrum fitting approach, and against estimates from short-TE PRESS data.

RESULTS

HERCULES successfully segregates overlapping resonances into separate Hadamard combinations, allowing for the estimation of levels of seven coupled metabolites that would usually require a single 11-min editing experiment each. Metabolite levels and CVs agree well with published values. CVs of quantified measurements from the multiplexed HERCULES fitting approach outperform single-spectrum fitting and short-TE PRESS for most of the edited metabolites, performing only slightly to moderately worse than the fitting method that gives the lowest CVs for tCho, NAA, NAAG, and Asp.

CONCLUSION

HERCULES is a new experimental approach with the potential for simultaneous editing and multiplexed fitting of up to seven coupled low-concentration and six high-concentration metabolites within a single 11-min acquisition at 3T.

Working Memory Modulates Glutamate Levels in the Dorsolateral Prefrontal Cortex during 1H fMRS

Glutamate is involved in excitatory neurotransmission and metabolic processes related to brain function. Previous studies using proton functional magnetic resonance spectroscopy (¹H fMRS) have demonstrated elevated cortical glutamate levels by 2-4% during visual and motor stimulation, relative to periods of no stimulation. Here, we extended this approach to working memory cognitive task performance, which has been consistently associated with dorsolateral prefrontal cortex (dlPFC) activation. Sixteen healthy adult volunteers completed a continuous visual fixation "rest" task followed by a letter 2-back working memory task during ¹H fMRS acquisition of the left dlPFC, which encompassed Brodmann areas 45 and 46 over a 4.5-cm³ volume. Using a 100% automated fitting procedure integrated with LCModel, raw spectra were eddy current-, phase-, and shift-corrected prior to quantification resulting in a 32s temporal resolution or 8 averages per spectra. Task compliance was high (95 ± 11% correct) and the mean Cramer-Rao Lower Bound of glutamate was 6.9 ± 0.9%. Relative to continuous passive visual fixation, left dlPFC glutamate levels were significantly higher by 2.7% (0.32 mmol/kg wet weight) during letter 2-back performance. Elevated dlPFC glutamate levels reflect increased metabolic activity and excitatory neurotransmission driven by working memory-related cognitive demands. These results provide the first in vivo demonstration of elevated dlPFC glutamate levels during working memory.