ProFit revisited

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation

PURPOSE

The interest in applying and modeling dynamic MRS has recently grown. Two-dimensional modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to one-dimensional (1D) modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches.

METHODS

Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multitransient linear-combination modeling (LCM) with 1D-LCM of the average. A total of 2,500 data sets per condition with different noise representations of a 64-transient MRS experiment at six signal-to-noise levels for two separate spin systems (scyllo-inositol and gamma-aminobutyric acid) were analyzed. Additional data sets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by SDs and Cramér-Rao lower bounds (CRLBs).

RESULTS

Amplitude estimates for 1D- and 2D-LCM agreed well and showed a similar level of bias compared with the ground truth. Estimated CRLBs agreed well between both models and with ground-truth CRLBs. For correlated noise, the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM.

CONCLUSION

Our results indicate that the model performance of 2D multitransient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as a necessary basis for further applications of 2D modeling.

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.

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.

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation

Purpose

The interest in applying and modeling dynamic MRS has recently grown. 2D modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to 1D modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches.

Methods

Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multi-transient LCM with 1D-LCM of the average. 2,500 datasets per condition with different noise representations of a 64-transient MRS experiment at 6 signal-to-noise levels for two separate spin systems (scyllo-inositol and GABA) were analyzed. Additional datasets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by standard deviations and Cramér-Rao Lower Bounds (CRLB).

Results

Amplitude estimates for 1D- and 2D-LCM agreed well and showed similar level of bias compared to the ground truth. Estimated CRLBs agreed well between both models and with ground truth CRLBs. For correlated noise the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM.

Conclusion

Our results indicate that the model performance of 2D multi-transient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as necessary basis for further applications of 2D modeling.

Quantification of spatially localized MRS by a novel deep learning approach without spectral fitting

PURPOSE

To propose a novel end-to-end deep learning model to quantify absolute metabolite concentrations from in vivo J-point resolved spectroscopy (JPRESS) without using spectral fitting.

METHODS

A novel encoder-decoder-style neural network was created, which was trained to predict metabolite concentrations and individual component signals concurrently from 3T JPRESS data in the time domain. The training data set contained 100 000 samples created by spin-density simulations using experimentally used RF pulses. Concentrations, phase, frequencies, linewidths, and T2 relaxation times in the training data set were varied over a large range with uniform distributions. Random synthesized noise and extraneous signals were added to the data set. Two thousand validation samples were created similarly to the training data set but with mean concentrations close to in vivo values. An in vivo test was conducted with 20 samples acquired from the human brain.

RESULTS

Both validation and in vivo test results showed that the proposed model successfully predicted metabolite concentrations as well as individual metabolite signals without involving spectral fitting, while extraneous peaks or unregistered signals were filtered out. Compared with the short-TE spectral fitting by LCModel, the proposed method had the advantage that the undesired correlations between the estimated concentrations and noise levels and between metabolites were eliminated or substantially reduced.

CONCLUSION

The proposed method provides a working deep learning model that directly maps in vivo JPRESS data to metabolite concentrations. Because spectral fitting is not used, the trained model does not depend on the assumptions associated with parameter tuning when applied to in vivo data.

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.

GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters

Rationale and objectives

Macromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated.

Materials and methods

Twenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV).

Results

CRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2-3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR.

Conclusion

Neurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.

Effects of Psychotherapy on Glutamatergic Neurotransmission

INTRODUCTION

Psychodynamic psychotherapy is an effective and widely used treatment for major depressive disorder (MDD); however, little is known about neurobiological changes associated with induced symptom improvement.

METHODS

Proton magnetic resonance spectroscopy with a two-dimensional J-resolved sequence served to test the relationship between glutamate (Glu) and glutamine (Gln) levels, measured separately in pregenual anterior cingulate cortex (pgACC) and the anterior midcingulate cortex (aMCC) as a control region, with change in depression symptoms after 6 months of weekly psychodynamic psychotherapy sessions in MDD patients. Depressed (N = 45) and healthy (N = 30) subjects participated in a baseline proton magnetic resonance spectroscopy measurement and a subgroup of MDD subjects (N = 21) then received once-a-week psychodynamic psychotherapy and participated in a second proton magnetic resonance spectroscopy measurement after 6 months. Change in depression symptoms was assessed using the Hamilton Depression Rating Scale (HAMD).

RESULTS

Higher pretreatment pgACC Gln concentrations in MDD patients compared to healthy controls were associated with symptom severity. Patients and controls did not differ regarding Gln levels in aMCC nor regarding Glu levels in both regions. The association of pgACC Gln concentration and severity of depressive symptoms was reversed after 6 months of psychotherapy in MDD subjects. Regarding Gln in aMCC as well as Glu in both regions, there were no significant associations with improvement of depressive symptoms in the course of psychotherapy.

DISCUSSION

Findings indicate specific regional effects of psychodynamic psychotherapy on glutamatergic neurotransmission and thereby highlight the key role of the pgACC in both depression pathophysiology and recovery.

Nocturnal sodium oxybate increases the anterior cingulate cortex magnetic resonance glutamate signal upon awakening

Clinical guidelines recommend sodium oxybate (SXB; the sodium salt of γ-hydroxybutyrate) for the treatment of disturbed sleep and excessive daytime sleepiness in narcolepsy, yet the underlying mode of action is elusive. In a randomised controlled trial in 20 healthy volunteers, we aimed at establishing neurochemical changes in the anterior cingulate cortex (ACC) following SXB-enhanced sleep. The ACC is a core neural hub regulating vigilance in humans. At 2:30 a.m., we administered in a double-blind cross-over manner an oral dose of 50 mg/kg SXB or placebo, to enhance electroencephalography-defined sleep intensity in the second half of nocturnal sleep (11:00 p.m. to 7:00 a.m.). Upon scheduled awakening, we assessed subjective sleepiness, tiredness and mood and measured two-dimensional, J-resolved, point-resolved magnetic resonance spectroscopy (PRESS) localisation at 3-Tesla field strength. Following brain scanning, we used validated tools to quantify psychomotor vigilance test (PVT) performance and executive functioning. We analysed the data with independent t tests, false discovery rate (FDR) corrected for multiple comparisons. The morning glutamate signal (at 8:30 a.m.) in the ACC was specifically increased after SXB-enhanced sleep in all participants in whom good-quality spectroscopy data were available (n = 16; p_FDR  < 0.002). Further, global vigilance (10th-90th inter-percentile range on the PVT) was improved (p_FDR  < 0.04) and median PVT response time was shorter (p_FDR  < 0.04) compared to placebo. The data indicate that elevated glutamate in the ACC could provide a neurochemical mechanism underlying SXB's pro-vigilant efficacy in disorders of hypersomnolence.

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.

Predicting Antidepressant Effects of Ketamine: the Role of the Pregenual Anterior Cingulate Cortex as a Multimodal Neuroimaging Biomarker

BACKGROUND

Growing evidence underscores the utility of ketamine as an effective and rapid-acting treatment option for major depressive disorder (MDD). However, clinical outcomes vary between patients. Predicting successful response may enable personalized treatment decisions and increase clinical efficacy.

METHODS

We here explored the potential of pregenual anterior cingulate cortex (pgACC) activity to predict antidepressant effects of ketamine in relation to ketamine-induced changes in glutamatergic metabolism. Prior to a single i.v. infusion of ketamine, 24 patients with MDD underwent functional magnetic resonance imaging during an emotional picture-viewing task and magnetic resonance spectroscopy. Changes in depressive symptoms were evaluated using the Beck Depression Inventory measured 24 hours pre- and post-intervention. A subsample of 17 patients underwent a follow-up magnetic resonance spectroscopy scan.

RESULTS

Antidepressant efficacy of ketamine was predicted by pgACC activity during emotional stimulation. In addition, pgACC activity was associated with glutamate increase 24 hours after the ketamine infusion, which was in turn related to better clinical outcome.

CONCLUSIONS

Our results add to the growing literature implicating a key role of the pgACC in mediating antidepressant effects and highlighting its potential as a multimodal neuroimaging biomarker of early treatment response to ketamine.

Lower glutamate and GABA levels in auditory cortex of tinnitus patients: a 2D-JPRESS MR spectroscopy study

We performed magnetic resonance spectroscopy (MRS) on healthy individuals with tinnitus and no hearing loss (n = 16) vs. a matched control group (n = 17) to further elucidate the role of excitatory and inhibitory neurotransmitters in tinnitus. Two-dimensional J-resolved spectroscopy (2D-JPRESS) was applied to disentangle Glutamate (Glu) from Glutamine and to estimate GABA levels in two bilateral voxels in the primary auditory cortex. Results indicated a lower Glu concentration (large effect) in right auditory cortex and lower GABA concentration (medium effect) in the left auditory cortex of the tinnitus group. Within the tinnitus group, Glu levels positively correlated with tinnitus loudness measures. While the GABA difference between groups is in line with former findings and theories about a dysfunctional auditory inhibition system in tinnitus, the novel finding of reduced Glu levels came as a surprise and is discussed in the context of a putative framework of inhibitory mechanisms related to Glu throughout the auditory pathway. Longitudinal or interventional studies could shed more light on interactions and causality of Glu and GABA in tinnitus neurochemistry.

Acute effects of ketamine on the pregenual anterior cingulate: linking spontaneous activation, functional connectivity, and glutamate metabolism

Ketamine exerts its rapid antidepressant effects via modulation of the glutamatergic system. While numerous imaging studies have investigated the effects of ketamine on a functional macroscopic brain level, it remains unclear how altered glutamate metabolism and changes in brain function are linked. To shed light on this topic we here conducted a multimodal imaging study in healthy volunteers (N = 23) using resting state fMRI and proton (¹H) magnetic resonance spectroscopy (MRS) to investigate linkage between metabolic and functional brain changes induced by ketamine. Subjects were investigated before and during an intravenous ketamine infusion. The MRS voxel was placed in the pregenual anterior cingulate cortex (pgACC), as this region has been repeatedly shown to be involved in ketamine's effects. Our results showed functional connectivity changes from the pgACC to the right frontal pole and anterior mid cingulate cortex (aMCC). Absolute glutamate and glutamine concentrations in the pgACC did not differ significantly from baseline. However, we found that stronger pgACC activation during ketamine was linked to lower glutamine concentration in this region. Furthermore, reduced functional connectivity between pgACC and aMCC was related to increased pgACC activation and reduced glutamine. Our results thereby demonstrate how multimodal investigations in a single brain region could help to advance our understanding of the association between metabolic and functional changes.

ProFit-1D-A 1D fitting software and open-source validation data sets

PURPOSE

Accurate and precise MRS fitting is crucial for metabolite concentration quantification of ¹ H-MRS spectra. LCModel, a spectral fitting software, has shown to have certain limitations to perform advanced spectral fitting by previous literature. Herein, we propose an open-source spectral fitting algorithm with adaptive spectral baseline determination and more complex cost functions.

THEORY

The MRS spectra are characterized by several parameters, which reflect the environment of the contributing metabolites, properties of the acquisition sequence, or additional disturbances. Fitting parameters should accurately describe these parameters. Baselines are also a major contributor to MRS spectra, in which smoothness of the spline baselines used for fitting can be adjusted based on the properties of the spectra. Three different cost functions used for the minimization problem were also investigated.

METHODS

The newly developed ProFit-1D fitting algorithm is systematically evaluated for simulations of several types of possible in vivo parameter variations. Although accuracy and precision are tested with simulated spectra, spectra measured in vivo at 9.4 T are used for testing precision using subsets of averages. ProFit-1D fitting results are also compared with LCModel.

RESULTS

Both ProFit-1D and LCModel fitted the spectra well with induced parameter and baseline variations. ProFit-1D proved to be more accurate than LCModel for simulated spectra. However, LCModel showed a somewhat increased precision for some spectral simulations and for in vivo data.

CONCLUSION

The open-source ProFit-1D fitting algorithm demonstrated high accuracy while maintaining precise metabolite concentration quantification. Finally, through the newly proposed cost functions, new ways to improve fitting were shown.

Deep learning can accelerate and quantify simulated localized correlated spectroscopy

Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic structures and concentrations of different chemicals in a biochemical sample of interest. MRS is used in vivo clinically to aid in the diagnosis of several pathologies that affect metabolic pathways in the body. Typically, this experiment produces a one dimensional (1D) 1H spectrum containing several peaks that are well associated with biochemicals, or metabolites. However, since many of these peaks overlap, distinguishing chemicals with similar atomic structures becomes much more challenging. One technique capable of overcoming this issue is the localized correlated spectroscopy (L-COSY) experiment, which acquires a second spectral dimension and spreads overlapping signal across this second dimension. Unfortunately, the acquisition of a two dimensional (2D) spectroscopy experiment is extremely time consuming. Furthermore, quantitation of a 2D spectrum is more complex. Recently, artificial intelligence has emerged in the field of medicine as a powerful force capable of diagnosing disease, aiding in treatment, and even predicting treatment outcome. In this study, we utilize deep learning to: (1) accelerate the L-COSY experiment and (2) quantify L-COSY spectra. All training and testing samples were produced using simulated metabolite spectra for chemicals found in the human body. We demonstrate that our deep learning model greatly outperforms compressed sensing based reconstruction of L-COSY spectra at higher acceleration factors. Specifically, at four-fold acceleration, our method has less than 5% normalized mean squared error, whereas compressed sensing yields 20% normalized mean squared error. We also show that at low SNR (25% noise compared to maximum signal), our deep learning model has less than 8% normalized mean squared error for quantitation of L-COSY spectra. These pilot simulation results appear promising and may help improve the efficiency and accuracy of L-COSY experiments in the future.

ACC Glu/GABA ratio is decreased in euthymic bipolar disorder I patients: possible in vivo neurometabolite explanation for mood stabilization

Bipolar disorder (BD) is characterized by unstable mood states ranging from mania to depression. Although there is some evidence that mood instability may result from an imbalance between excitatory glutamatergic and inhibitory GABA-ergic neurotransmission, few proton magnetic resonance spectroscopy (¹H-MRS) studies have measured these two neurometabolites simultaneously in BD. The enzyme glutamic acid decarboxylase (GAD1) catalyzes the decarboxylation of glutamate (Glu) to GABA, and its single nucleotide polymorphisms (SNPs) might influence Glu/GABA ratio. Thus, we investigated Glu/GABA ratio in the dorsal anterior cingulate cortex (dACC) of euthymic BD type I patients and healthy controls (HC), and assessed the influence of both mood stabilizers and GAD1 SNPs on this ratio. Eighty-eight subjects (50 euthymic BD type I patients and 38 HC) underwent 3T ¹H-MRS in the dACC (2 × 2 × 4.5 cm³) using a two-dimensional JPRESS sequence and all subjects were genotyped for 4 SNPs in the GAD1 gene. BD patients had lower dACC Glu/GABA ratio compared to HC, where this was influenced by anticonvulsant and antipsychotic medications, but not lithium. The presence of GAD1 rs1978340 allele A was associated with higher Glu/GABA ratio in BD, while patients without this allele taking mood stabilizers had a lower Glu/GABA ratio. The lowering of dACC Glu/GABA could be one explanation for the mood stabilizing action of anticonvulsants and antipsychotics in BD type I euthymia. Therefore, this putative role of Glu/GABA ratio and the influence of GAD1 genotype interacting with mood stabilization medication should be confirmed by further studies involving larger samples and other mood states.ClincalTrials.gov registration: NCT01237158.

Lower Ventromedial Prefrontal Cortex Glutamate Levels in Patients With Obsessive-Compulsive Disorder

Background: Recent studies using magnetic resonance spectroscopy (¹H-MRS) indicate that patients with obsessive-compulsive disorder (OCD) present abnormal levels of glutamate (Glu) and gamma aminobutyric acid (GABA) in the frontal and striatal regions of the brain. These abnormalities could be related to the hyperactivation observed in cortico-striatal circuits of patients with OCD. However, most of the previous ¹H-MRS studies were not capable of differentiating the signal from metabolites that overlap in the spectrum, such as Glu and glutamine (Gln), and referred to the detected signal as the composite measure-Glx (sum of Glu and Gln). In this study, we used a two-dimensional JPRESS ¹H-MRS sequence that allows the discrimination of overlapping metabolites by observing the differences in J-coupling, leading to higher accuracy in the quantification of all metabolites. Our objective was to identify possible alterations in the neurometabolism of OCD, focusing on Glu and GABA, which are key neurotransmitters in the brain that could provide insights into the underlying neurochemistry of a putative excitatory/inhibitory imbalance. Secondary analysis was performed including metabolites such as Gln, creatine (Cr), N-acetylaspartate, glutathione, choline, lactate, and myo-inositol. Methods: Fifty-nine patients with OCD and 42 healthy controls (HCs) underwent 3T ¹H-MRS in the ventromedial prefrontal cortex (vmPFC, 30 × 25 × 25 mm³). Metabolites were quantified using ProFit (version 2.0) and Cr as a reference. Furthermore, Glu/GABA and Glu/Gln ratios were calculated. Generalized linear models (GLMs) were conducted using each metabolite as a dependent variable and age, sex, and gray matter fraction (fGM) as confounding factors. GLM analysis was also used to test for associations between clinical symptoms and neurometabolites. Results: The GLM analysis indicated lower levels of Glu/Cr in patients with OCD (z = 2.540; p = 0.011). No other comparisons reached significant differences between groups for all the metabolites studied. No associations between metabolites and clinical symptoms were detected. Conclusions: The decreased Glu/Cr concentrations in the vmPFC of patients with OCD indicate a neurochemical imbalance in the excitatory neurotransmission that could be associated with the neurobiology of the disease and may be relevant for the pathophysiology of OCD.

Improved detection of lactate and β-hydroxybutyrate using MEGA-sLASER at 3 T

Lactate and β-hydroxybutyrate are important MRS-visible biomarkers for the energy metabolism of the human brain. A major obstacle for their unambiguous detection and quantification in vivo is their inherently low concentration and spectral overlap with resonances from lipids and macromolecules. In this work, we demonstrate the improved detectability of lactate and β-hydroxybutyrate with MEGA-sLASER compared to MEGA-PRESS at the clinical field strength of 3 T. The method is validated by numerical simulations, in vitro measurements and in vivo experiments on healthy subjects. It is demonstrated that MEGA-sLASER offers an SNR increase of approximately 70% for lactate and β-hydroxybutyrate detection compared to MEGA-PRESS in various brain regions. This increased SNR translates into reduced Cramér-Rao lower bounds for quantification and enables a more robust detection of subtle changes in the (brain) energy metabolism. The sensitivity of the method for detection of β-hydroxybutyrate concentration changes is demonstrated through measurements before and during a ketogenic diet while the sensitivity for detection of lactate concentration changes is shown by measurements before and after an intensive anaerobic exercise.

Short-acquisition-time JPRESS and its application to paediatric brain tumours

OBJECTIVE

To develop and assess a short-duration JPRESS protocol for detection of overlapping metabolite biomarkers and its application to paediatric brain tumours at 3 Tesla.

MATERIALS AND METHODS

The short-duration protocol (6 min) was optimised and compared for spectral quality to a high-resolution (38 min) JPRESS protocol in a phantom and five healthy volunteers. The 6-min JPRESS was acquired from four paediatric brain tumours and compared with short-TE PRESS.

RESULTS

Metabolite identification between the 6- and 38-min protocols was comparable in phantom and volunteer data. For metabolites with Cramer-Rao lower bounds > 50%, interpretation of JPRESS increased confidence in assignment of lactate, myo-Inositol and scyllo-Inositol. JPRESS also showed promise for the detection of glycine and taurine in paediatric brain tumours when compared to short-TE MRS.

CONCLUSION

A 6-min JPRESS protocol is well tolerated in paediatric brain tumour patients. Visual inspection of a 6-min JPRESS spectrum enables identification of a range of metabolite biomarkers of clinical interest.

Quantitative magnetic resonance spectroscopy at 3T based on the principle of reciprocity

Quantification of magnetic resonance spectroscopy signals using the phantom replacement method requires an adequate correction of differences between the acquisition of the reference signal in the phantom and the measurement in vivo. Applying the principle of reciprocity, sensitivity differences can be corrected at low field strength by measuring the RF transmitter gain needed to obtain a certain flip angle in the measured volume. However, at higher field strength the transmit sensitivity may vary from the reception sensitivity, which leads to wrongly estimated concentrations. To address this issue, a quantification approach based on the principle of reciprocity for use at 3T is proposed and validated thoroughly. In this approach, the RF transmitter gain is determined automatically using a volume-selective power optimization and complemented with information from relative reception sensitivity maps derived from contrast-minimized images to correct differences in transmission and reception sensitivity. In this way, a reliable measure of the local sensitivity was obtained. The proposed method is used to derive in vivo concentrations of brain metabolites and tissue water in two studies with different coil sets in a total of 40 healthy volunteers. Resulting molar concentrations are compared with results using internal water referencing (IWR) and Electric REference To access In vivo Concentrations (ERETIC). With the proposed method, changes in coil loading and regional sensitivity due to B₁ inhomogeneities are successfully corrected, as demonstrated in phantom and in vivo measurements. For the tissue water content, coefficients of variation between 2% and 3.5% were obtained (0.6-1.4% in a single subject). The coefficients of variation of the three major metabolites ranged from 3.4-14.5%. In general, the derived concentrations agree well with values estimated with IWR. Hence, the presented method is a valuable alternative for IWR, without the need for additional hardware such as ERETIC and with potential advantages in diseased tissue.

Obstructive sleep apnea is associated with altered midbrain chemical concentrations

Obstructive sleep apnea (OSA) is accompanied by altered structure and function in cortical, limbic, brainstem, and cerebellar regions. The midbrain is relatively unexamined, but contains many integrative nuclei which mediate physiological functions that are disrupted in OSA. We therefore assessed the chemistry of the midbrain in OSA in this exploratory study. We used a recently developed accelerated 2D magnetic resonance spectroscopy (2D-MRS) technique, compressed sensing-based 4D echo-planar J-resolved spectroscopic imaging (4D-EP-JRESI), to measure metabolites in the midbrain of 14 OSA (mean age±SD:54.6±10.6years; AHI:35.0±19.4; SAO2 min:83±7%) and 26 healthy control (50.7±8.5years) subjects. High-resolution T1-weighted scans allowed voxel localization. MRS data were processed with custom MATLAB-based software, and metabolite ratios calculated with respect to the creatine peak using a prior knowledge fitting (ProFit) algorithm. The midbrain in OSA showed decreased N-acetylaspartate (NAA; OSA:1.24±0.43, Control:1.47±0.41; p=0.03; independent samples t-test), a marker of neuronal viability. Increased levels in OSA over control subjects appeared in glutamate (Glu; OSA:1.23±0.57, Control:0.98±0.33; p=0.03), ascorbate (Asc; OSA:0.56±0.28, Control:0.42±0.20; (50.7±8.5years; p=0.03), and myo-inositol (mI; OSA:0.96±0.48, Control:0.72±0.35; p=0.03). No differences between groups appeared in γ-aminobutyric acid (GABA) or taurine. The midbrain in OSA patients shows decreased NAA, indicating neuronal injury or dysfunction. Higher Glu levels may reflect excitotoxic processes and astrocyte activation, and higher mI is also consistent with glial activation. Higher Asc levels may result from oxidative stress induced by intermittent hypoxia in OSA. Additionally, Asc and Glu are involved with glutamatergic processes, which are likely upregulated in the midbrain nuclei of OSA patients. The altered metabolite levels help explain dysfunction and structural deficits in the midbrain of OSA patients.

Localized MRS reliability of in vivo glutamate at 3 T in shortened scan times: a feasibility study

Glutamate is the prime excitatory neurotransmitter in the mammalian brain and has been implicated in a wide range of psychiatric conditions. To improve the applicability and clinical reach of magnetic resonance spectroscopy (MRS), research is needed to develop shortened, yet reliable, MRS scanning procedures for standard 1.5-3-T clinical magnetic resonance imaging (MRI) systems, particularly with young or vulnerable populations unable to tolerate longer protocols. To this end, we evaluated the test-retest reliability of a shortened J-resolved MRS sequence in healthy adolescents (n = 22) aged 12-14 years. Participants underwent a series of sequential 6-min MRS scans, with the participants remaining in situ between successive scans. Glutamate and other metabolites were acquired from the rostral anterior cingulate cortex, as glutamatergic function in this region has been implicated in a number of psychiatric illnesses. Thirteen neurochemicals were quantified as ratios to total creatine, and reliability scores were expressed as the percentage difference between the two scans for each metabolite. Test-retest assessment of glutamate was reliable, as scores were less than 10% different (7.1 ± 4.2%), and glutamate values across scans were significantly correlated (Pearson r = 0.680, p < 10^-4 ). Several other neurochemicals demonstrated satisfactory reliability, including choline (Cho) (7.4 ± 5.6%), glutathione (GSH) (8.6 ± 4.1%), myo-inositol (mI) (6.5 ± 7.1%) and N-acetylaspartate (NAA) (3.5 ± 3.6%), with test-retest correlations ranging from 0.747 to 0.953. A number of metabolites, however, did not demonstrate acceptable test-retest reliability using the current J-resolved MRS sequence, ranging from 13.8 ± 13.7% (aspartate, Asp) to 45.9 ± 38.3% (glycine, Gly). Collectively, test-retest analyses suggest that clinically viable quantitative data can be obtained on standard MRI systems for glutamate, as well as the other metabolites, during short scan times in a traditionally challenging brain region.

Cerebral mGluR5 availability contributes to elevated sleep need and behavioral adjustment after sleep deprivation

Increased sleep time and intensity quantified as low-frequency brain electrical activity after sleep loss demonstrate that sleep need is homeostatically regulated, yet the underlying molecular mechanisms remain elusive. We here demonstrate that metabotropic glutamate receptors of subtype 5 (mGluR5) contribute to the molecular machinery governing sleep-wake homeostasis. Using positron emission tomography, magnetic resonance spectroscopy, and electroencephalography in humans, we find that increased mGluR5 availability after sleep loss tightly correlates with behavioral and electroencephalographic biomarkers of elevated sleep need. These changes are associated with altered cortical myo-inositol and glycine levels, suggesting sleep loss-induced modifications downstream of mGluR5 signaling. Knock-out mice without functional mGluR5 exhibit severe dysregulation of sleep-wake homeostasis, including lack of recovery sleep and impaired behavioral adjustment to a novel task after sleep deprivation. The data suggest that mGluR5 contribute to the brain's coping mechanisms with sleep deprivation and point to a novel target to improve disturbed wakefulness and sleep.

Covariance J-resolved spectroscopy: Theory and application in vivo

Magnetic resonance spectroscopy (MRS) is a powerful tool capable of investigating the metabolic status of several tissues in vivo. In particular, single-voxel-based ¹ H spectroscopy provides invaluable biochemical information from a volume of interest (VOI) and has therefore been used in a variety of studies. Unfortunately, typical one-dimensional MRS data suffer from severe signal overlap and thus important metabolites are difficult to distinguish. One method that is used to disentangle overlapping resonances is the two-dimensional J-resolved spectroscopy (JPRESS) experiment. Due to the long acquisition duration of the JPRESS experiment, a limited number of points are acquired in the indirect dimension, leading to poor spectral resolution along this dimension. Poor spectral resolution is problematic because proper peak assignment may be hindered, which is why the zero-filling method is often used to improve resolution as a post-processing step. However, zero-filling leads to spectral artifacts, which may affect visualization and quantitation of spectra. A novel method utilizing a covariance transformation, called covariance J-resolved spectroscopy (CovJ), was developed in order to improve spectral resolution along the indirect dimension (F₁ ). Comparison of simulated data demonstrates that peak structures remain qualitatively similar between JPRESS and the novel method along the diagonal region (F₁ = 0 Hz), whereas differences arise in the cross-peak (F₁ ≠0 Hz) regions. In addition, quantitative results of in vivo JPRESS data acquired on a 3T scanner show significant correlations (r² >0.86, p<0.001) when comparing the metabolite concentrations between the two methods. Finally, a quantitation algorithm, 'COVariance Spectral Evaluation of ¹ H Acquisitions using Representative prior knowledge' (Cov-SEHAR), was developed in order to quantify γ-aminobutyric acid and glutamate from the CovJ spectra. These preliminary findings indicate that the CovJ method may be used to improve spectral resolution without hindering metabolite quantitation for J-resolved spectra.

Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation

¹H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.

Proton and multinuclear magnetic resonance spectroscopy in the human brain at ultra-high field strength: A review

Magnetic Resonance Spectroscopy (MRS) allows for a non-invasive and non-ionizing determination of in vivo tissue concentrations and metabolic turn-over rates of more than 20 metabolites and compounds in the central nervous system of humans. The aim of this review is to give a comprehensive overview about the advantages, challenges and advances of ultra-high field MRS with regard to methodological development, discoveries and applications from its beginnings around 15 years ago up to the current state. The review is limited to human brain and spinal cord application at field strength of 7T and 9.4T and includes all relevant nuclei (¹H, ³¹P, ¹³C).

Echo-Planar J-resolved Spectroscopic Imaging using Dual Read-outs: Implementation and Quantitation of Human Brain Metabolites

Attempts have been made to reduce the total scan time in multi-dimensional J-resolved spectroscopic imaging (JRESI) using an echo-planar (EP) readout gradient, but acquisition duration remains a limitation for routine clinical use in the brain. We present here a significant acceleration achieved with a 4D EP-JRESI sequence that collects dual phase encoded lines within a single repetition time (TR) using two bipolar read-out trains. The performance and reliability of this novel 4D sequence, called Multi-Echo based Echo-Planar J-resolved Spectroscopic Imaging (ME-EP-JRESI), was evaluated in 10 healthy controls and a brain phantom using a 3 T MRI/MRS scanner. The prior knowledge fitting (ProFit) algorithm, with a new simulated basis set consisting of macromolecules and lipids apart from metabolites of interest, was used for quantitation. Both phantom and in-vivo data demonstrated that localization and spatial/spectral profiles of metabolites from the ME-EP-JRESI sequence were in good agreement with that of the EP-JRESI sequence. Both in the occipital and temporal lobe, metabolites with higher physiological concentrations including Glx (Glu+Gln), tNAA (NAA+NAAG), mI all had coefficient of variations between 9-25%. In summary, we have implemented, validated and tested the ME-EP-JRESI sequence, demonstrating that multi-echo acquisition can successfully reduce the total scan duration for EP-JRESI sequences.

Increased pregenual anterior cingulate glucose and lactate concentrations in major depressive disorder

There is ample evidence that glucose metabolism in the pregenual anterior cingulate cortex (PACC) is increased in major depressive disorder (MDD), whereas it is still unknown whether glucose levels per se are also elevated. Elevated cerebrospinal fluid (CSF) lactate concentrations in MDD patients might indicate that increased glycolytical metabolization of glucose to lactate in astrocytes either alone or in conjunction with mitochondrial dysfunction results in an accumulation of lactate and contributes to pathophysiological mechanisms of MDD. However, until now, no study investigated in vivo PACC glucose and lactate levels in MDD. Proton magnetic resonance spectroscopy was therefore used to test the hypothesis that patients with MDD have increased PACC glucose and lactate levels. In 40 healthy and depressed participants, spectra were acquired from the PACC using a maximum echo J-resolved spectroscopy protocol. Results show significant increases of glucose and lactate in patients, which are also associated with depression severity. These findings indicate impaired brain energy metabolism in MDD with increased fraction of energy utilization via glycolysis and reduced mitochondrial oxidative clearance of lactate. Targeting these metabolic disturbances might affect the balance of metabolic pathways regulating neuronal energetics and result in an attenuation of the elevated basal activity of brain regions within the neural circuitry of depression.

Diffusion-weighted J-resolved spectroscopy

PURPOSE

To develop a novel diffusion-weighted magnetic resonance spectroscopy (DW-MRS) technique in conjunction with J-resolved spatially localized spectroscopy (JPRESS) to measure the apparent diffusion coefficients (ADCs) of brain metabolites beyond N-acetylaspartic acid (NAA), creatine (Cr), and choline (Cho) at 3T. This technique will be useful to probe tissue microstructures in vivo, as the various metabolites have different physiological characteristics.

METHODS

Two JPRESS spectra were collected (high b-value and low b-value), and the ADCs of 16 different metabolites were estimated. Two analysis pipelines were developed: 1) a 2D pipeline that uses ProFit software to extract ADCs from metabolites not typically accessible at 3T and 2) a 1D pipeline that uses TARQUIN software to extract the metabolite concentrations from each line in the 2D dataset, allowing for scaling as well as validation.

RESULTS

The ADCs of 16 different metabolites were estimated from within six subjects in parietal white matter. There was excellent agreement between the results obtained from the 1D and 2D pipelines for NAA, Cr, and Cho.

CONCLUSION

The proposed technique provided consistent estimates for the ADCs of NAA, Cr, Cho, glutamate + glutamine, and myo-inositol in all subjects and additionally glutathione and scyllo-inositol in all but one subject. Magn Reson Med 78:1235-1245, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Neurochemical profile of the human cervical spinal cord determined by MRS

MRS enables insight into the chemical composition of central nervous system tissue. However, technical challenges degrade the data quality when applied to the human spinal cord. Therefore, to date detection of only the most prominent metabolite resonances has been reported in the healthy human spinal cord. The aim of this investigation is to provide an extended metabolic profile including neurotransmitters and antioxidants in addition to metabolites involved in the energy and membrane metabolism of the human cervical spinal cord in vivo. To achieve this, data quality was improved by using a custom-made, cervical detector array together with constructive averaging of a high number of echo signals, which is enabled by the metabolite cycling technique at 3T. In addition, the improved spinal cord spectra were extensively cross-validated, in vivo, post-mortem in situ and ex vivo. Reliable identification of up to nine metabolites was achieved in group analyses for the first time. Distinct features of the spinal cord neurochemical profile, in comparison with the brain neurotransmission system, include decreased concentrations of the sum of glutamate and glutamate and increased concentrations of aspartate, γ-amino-butyric acid, scyllo-inositol and the sum of myo-inositol and glycine.

Pilot Assessment of Brain Metabolism in Perinatally HIV-Infected Youths Using Accelerated 5D Echo Planar J-Resolved Spectroscopic Imaging

Purpose

To measure cerebral metabolite levels in perinatally HIV-infected youths and healthy controls using the accelerated five dimensional (5D) echo planar J-resolved spectroscopic imaging (EP-JRESI) sequence, which is capable of obtaining two dimensional (2D) J-resolved spectra from three spatial dimensions (3D).

Materials and Methods

After acquisition and reconstruction of the 5D EP-JRESI data, T₁-weighted MRIs were used to classify brain regions of interest for HIV patients and healthy controls: right frontal white (FW), medial frontal gray (FG), right basal ganglia (BG), right occipital white (OW), and medial occipital gray (OG). From these locations, respective J-resolved and TE-averaged spectra were extracted and fit using two different quantitation methods. The J-resolved spectra were fit using prior knowledge fitting (ProFit) while the TE-averaged spectra were fit using the advanced method for accurate robust and efficient spectral fitting (AMARES).

Results

Quantitation of the 5D EP-JRESI data using the ProFit algorithm yielded significant metabolic differences in two spatial locations of the perinatally HIV-infected youths compared to controls: elevated NAA/(Cr+Ch) in the FW and elevated Asp/(Cr+Ch) in the BG. Using the TE-averaged data quantified by AMARES, an increase of Glu/(Cr+Ch) was shown in the FW region. A strong negative correlation (r < -0.6) was shown between tCh/(Cr+Ch) quantified using ProFit in the FW and CD4 counts. Also, strong positive correlations (r > 0.6) were shown between Asp/(Cr+Ch) and CD4 counts in the FG and BG.

Conclusion

The complimentary results using ProFit fitting of J-resolved spectra and AMARES fitting of TE-averaged spectra, which are a subset of the 5D EP-JRESI acquisition, demonstrate an abnormal energy metabolism in the brains of perinatally HIV-infected youths. This may be a result of the HIV pathology and long-term combinational anti-retroviral therapy (cART). Further studies of larger perinatally HIV-infected cohorts are necessary to confirm these findings.

Effects of serotonin 2A/1A receptor stimulation on social exclusion processing

Social ties are crucial for physical and mental health. However, psychiatric patients frequently encounter social rejection. Moreover, an increased reactivity to social exclusion influences the development, progression, and treatment of various psychiatric disorders. Nevertheless, the neuromodulatory substrates of rejection experiences are largely unknown. The preferential serotonin (5-HT) 2A/1A receptor agonist, psilocybin (Psi), reduces the processing of negative stimuli, but whether 5-HT2A/1A receptor stimulation modulates the processing of negative social interactions remains unclear. Therefore, this double-blind, randomized, counterbalanced, cross-over study assessed the neural response to social exclusion after the acute administration of Psi (0.215 mg/kg) or placebo (Pla) in 21 healthy volunteers by using functional magnetic resonance imaging (fMRI) and resting-state magnetic resonance spectroscopy (MRS). Participants reported a reduced feeling of social exclusion after Psi vs. Pla administration, and the neural response to social exclusion was decreased in the dorsal anterior cingulate cortex (dACC) and the middle frontal gyrus, key regions for social pain processing. The reduced neural response in the dACC was significantly correlated with Psi-induced changes in self-processing and decreased aspartate (Asp) content. In conclusion, 5-HT2A/1A receptor stimulation with psilocybin seems to reduce social pain processing in association with changes in self-experience. These findings may be relevant to the normalization of negative social interaction processing in psychiatric disorders characterized by increased rejection sensitivity. The current results also emphasize the importance of 5-HT2A/1A receptor subtypes and the Asp system in the control of social functioning, and as prospective targets in the treatment of sociocognitive impairments in psychiatric illnesses.

Dorsal Anterior Cingulate Lactate and Glutathione Levels in Euthymic Bipolar I Disorder: 1H-MRS Study

OBJECTIVE

Oxidative stress and mitochondrial dysfunction are 2 closely integrated processes implicated in the physiopathology of bipolar disorder. Advanced proton magnetic resonance spectroscopy techniques enable the measurement of levels of lactate, the main marker of mitochondrial dysfunction, and glutathione, the predominant brain antioxidant. The objective of this study was to measure brain lactate and glutathione levels in bipolar disorder and healthy controls.

METHODS

Eighty-eight individuals (50 bipolar disorder and 38 healthy controls) underwent 3T proton magnetic resonance spectroscopy in the dorsal anterior cingulate cortex (2x2x4.5cm(3)) using a 2-D JPRESS sequence. Lactate and glutathione were quantified using the ProFit software program.

RESULTS

Bipolar disorder patients had higher dorsal anterior cingulate cortex lactate levels compared with controls. Glutathione levels did not differ between euthymic bipolar disorder and controls. There was a positive correlation between lactate and glutathione levels specific to bipolar disorder. No influence of medications on metabolites was observed.

CONCLUSION

This is the most extensive magnetic resonance spectroscopy study of lactate and glutathione in bipolar disorder to date, and results indicated that euthymic bipolar disorder patients had higher levels of lactate, which might be an indication of altered mitochondrial function. Moreover, lactate levels correlated with glutathione levels, indicating a compensatory mechanism regardless of bipolar disorder diagnosis.

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd.

Glutamatergic and neurometabolic alterations in chronic cocaine users measured with (1) H-magnetic resonance spectroscopy

Cocaine addiction is a chronically relapsing disorder that is associated with harmful consequences. Relapses occur frequently and effective pharmacotherapies are currently sparse. Preclinical studies suggest that altered glutamatergic signaling is crucial for the maintenance of cocaine self-administration. However, the translational validity of these models is currently unknown. Therefore, we investigated potential differences of glutamate, glutamine and further metabolite levels in the pregenual anterior cingulate cortex (pgACC) and the right dorsolateral prefrontal cortex (rDLPFC) of chronic cocaine users and controls using the PRior knOwledge FITting 2.0 tool in combination with two-dimensional J-resolved single-voxel (1) H-magnetic resonance spectroscopy at 3T and voxel tissue composition and relaxation correction. Glutamate and glutamine levels did not differ between cocaine users and controls, but higher weekly cocaine use and higher cocaine hair concentrations were associated with lower glutamine/creatine ratios in the pgACC. Interestingly, cocaine users exhibited higher glucose/total creatine ratios than controls in the pgACC and higher choline/creatine ratios in the pgACC and rDLPFC. These results imply that cocaine use is associated with altered cortical glucose metabolism and membrane turnover. Finally, cocaine use over the past 6 months appears to decrease cortical glutamine levels indicating changes in glutamate cycling.

Anterior cingulate Glutamate-Glutamine cycle metabolites are altered in euthymic bipolar I disorder

Bipolar disorder (BD) has been consistently associated with abnormalities in the Glutamate/GABA-Glutamine cycle. Magnetic resonance spectroscopy (MRS) studies have reported increased brain Glutamate (Glu) and Glx (Glu+Glutamine) in subjects with BD. However, data on separate measures of GABA and Glutamine (Gln) in BD are sparse due to overlapping resonant signals. The development of new sequence methods in the quantification of these metabolites has allowed a better understanding of the Glu/GABA-Gln cycle but data on this field of research remains sparse in BD. Eighty-eight subjects (50 euthymic BD and 38 HC) underwent 3T proton magnetic resonance spectroscopy (1H MRS) in the anterior cingulate cortex (ACC; 2×2×4.5cm(3)) using a two-dimensional JPRESS sequence. GABA, Glutamine (Gln) and Glutamate (Glu) were quantified with the ProFit program. Using image segmentation and known creatine (Cre) concentrations for white and grey matter, metabolite concentrations were calculated for the excited MRS voxel. GABA levels did not differ between groups. Gln level was higher in euthymic BD patients than in healthy controls. The Glu level and Glu/Gln ratio were lower in BD patients than in controls. The use of anticonvulsants was associated with Gln increase but did not affect Glu or Glu/Gln. Neither lithium nor antipsychotic use influenced metabolite levels. The ACC MRS findings indicate that the glutamatergic function in euthymic medicated BD patients is altered relative to controls. Whether this feature is a metabolic signature of euthymic BD subjects should be the focus of future studies.

Localized 2D COSY sequences: Method and experimental evaluation for a whole metabolite quantification approach

Two-dimensional spectroscopy offers the possibility to unambiguously distinguish metabolites by spreading out the multiplet structure of J-coupled spin systems into a second dimension. Quantification methods that perform parametric fitting of the 2D MRS signal have recently been proposed for resolved PRESS (JPRESS) but not explicitly for Localized Correlation Spectroscopy (LCOSY). Here, through a whole metabolite quantification approach, correlation spectroscopy quantification performances are studied. The ability to quantify metabolite relaxation constant times is studied for three localized 2D MRS sequences (LCOSY, LCTCOSY and the JPRESS) in vitro on preclinical MR systems. The issues encountered during implementation and quantification strategies are discussed with the help of the Fisher matrix formalism. The described parameterized models enable the computation of the lower bound for error variance--generally known as the Cramér Rao bounds (CRBs), a standard of precision--on the parameters estimated from these 2D MRS signal fittings. LCOSY has a theoretical net signal loss of two per unit of acquisition time compared to JPRESS. A rapid analysis could point that the relative CRBs of LCOSY compared to JPRESS (expressed as a percentage of the concentration values) should be doubled but we show that this is not necessarily true. Finally, the LCOSY quantification procedure has been applied on data acquired in vivo on a mouse brain.

Posterior cingulate γ-aminobutyric acid and glutamate/glutamine are reduced in amnestic mild cognitive impairment and are unrelated to amyloid deposition and apolipoprotein E genotype

The biomarker potential of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) for the in vivo characterization of preclinical stages in Alzheimer's disease has not yet been explored. We measured GABA, glutamate + glutamine (Glx), and N-acetyl-aspartate (NAA) levels by single-voxel MEGA-PRESS magnetic resonance spectroscopy in the posterior cingulate cortex of 21 elderly subjects and 15 patients with amnestic mild cognitive impairment. Participants underwent Pittsburgh Compound B positron emission tomography, apolipoprotein E (APOE) genotyping, and neuropsychological examination. GABA, Glx, and NAA levels were significantly lower in patients. NAA was lower in Pittsburgh Compound B-positive subjects and APOE ε4 allele carriers. GABA, Glx, and NAA levels were positively correlated to CERAD word learning scores. Reductions in GABA, Glx, and NAA levels may serve as metabolic biomarkers for cognitive impairment in amnestic mild cognitive impairment. Because GABA and Glx do not seem to reflect amyloid β deposition or APOE genotype, they are less likely biomarker candidates for preclinical Alzheimer's disease.