Methodological consensus on clinical proton MRS of the brain: Review and recommendations

Early Noninvasive Metabolic Biomarkers of Mutant IDH Inhibition in Glioma

Approximately 80% of low-grade glioma (LGGs) harbor mutant isocitrate dehydrogenase 1/2 (IDH1/2) driver mutations leading to accumulation of the oncometabolite 2-hydroxyglutarate (2-HG). Thus, inhibition of mutant IDH is considered a potential therapeutic target. Several mutant IDH inhibitors are currently in clinical trials, including AG-881 and BAY-1436032. However, to date, early detection of response remains a challenge. In this study we used high resolution ¹H magnetic resonance spectroscopy (¹H-MRS) to identify early noninvasive MR (Magnetic Resonance)-detectable metabolic biomarkers of response to mutant IDH inhibition. In vivo ¹H-MRS was performed on mice orthotopically-implanted with either genetically engineered (U87IDHmut) or patient-derived (BT257 and SF10417) mutant IDH1 cells. Treatment with either AG-881 or BAY-1436032 induced a significant reduction in 2-HG. Moreover, both inhibitors led to a significant early and sustained increase in glutamate and the sum of glutamate and glutamine (GLX) in all three models. A transient early increase in N-acetylaspartate (NAA) was also observed. Importantly, all models demonstrated enhanced animal survival following both treatments and the metabolic alterations were observed prior to any detectable differences in tumor volume between control and treated tumors. Our study therefore identifies potential translatable early metabolic biomarkers of drug delivery, mutant IDH inhibition and glioma response to treatment with emerging clinically relevant therapies.

Gamma-aminobutyric acid (GABA) changes in the hippocampus and anterior cingulate cortex in patients with temporal lobe epilepsy

PURPOSE

To explore the changes of gamma-aminobutyric acid (GABA) levels in the bilateral hippocampus and anterior cingulate cortex (ACC) of healthy control subjects and patients with temporal lobe epilepsy (TLE) and the correlation of GABA levels with the clinical symptoms by quantitative magnetic resonance spectroscopy (MRS).

METHODS

N-acetylaspartate (NAA), creatine (Cr) as well as choline (Cho) and GABA levels in the bilateral hippocampus and ACC were measured in 40 patients with TLE and 26 healthy control (NC) subjects with quantitative Meshcher-Garwood point resolved spectroscopy (MEGA-PRESS). The NAA/(Cho + Cr) and GABA/Cr ratios were compared between the NC and TLE groups. Comparisons were also made between the subgroups with lateralization (left TLE, right TLE and uncertain), short (<10 years) and longer (≥10 years) clinical seizure history (CSH), low (<1/month) and higher (≥1/month) seizure frequency (SF), with and without cognitive impairment (CI) in the patients with TLE, and by antiepileptic medications. Further analyses of the clinical information and metabolite ratios between the patients with TLE with and without CI were preformed.

RESULTS

The GABA/Cr ratio was significantly decreased in the bilateral hippocampus (left: P = 0.028, right: P = 0.035), while the NAA/(Cho + Cr) ratio was decreased only in the right hippocampus (RH) (P = 0.004) in patients with TLE compared with that of the NCs. Whereas the NAA/(Cho + Cr) ratio showed a consistent decreasing trend in bilateral hippocampus during the CSH, it only showed a significant difference in the RH. The GABA changes in the hippocampal and ACC regions were not consistent during different stages of the disease. In the bilateral hippocampus, the GABA/Cr ratio was decreased in the short seizure history (<10 years) patients with TLE compared with NCs (left: P = 0.018, right: P = 0.012), whereas the long seizure history (≥10 years) patients with TLE showed no difference with the NCs. However, in the ACC, the GABA/Cr ratio of the CI group was significantly decreased compared with that of NCs (P = 0.015). Further analysis showed that the patients with TLE with CI had obvious atrophy of the gray matter volume (GMV) and total parenchymal brain volume (PBV); GABA/Cr ratio was decreased in ACC, but increased in bilateral hippocampus compared with that of the no cognitive impairment (NOCI) group.

CONCLUSION

The GABA/Cr ratio was more valuable than the NAA/(Cho + Cr) ratio in evaluating the dynamic metabolite changes in patients with TLE. Importantly, the GABA changes in the hippocampal and ACC regions were not consistent during different stages of the disease. In the bilateral hippocampus, the GABA/Cr ratio was decreased at the early stage, but recovered to normal levels later. The decreased GABA/Cr ratio in the ACC might indicate more cerebral cortex was involved, resulting in more CI in patients with TLE.

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

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

ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI

A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B₁⁺ field and lipid T₁ heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.

GABA Measurement in a Neonatal Fragile X Syndrome Mouse Model Using 1H-Magnetic Resonance Spectroscopy and Mass Spectrometry

Fragile X syndrome (FXS) is the leading monogenetic cause of autism spectrum disorder and inherited cause of intellectual disability that affects approximately one in 7,000 males and one in 11,000 females. In FXS, the Fmr1 gene is silenced and prevents the expression of the fragile X mental retardation protein (FMRP) that directly targets mRNA transcripts of multiple GABAA subunits. Therefore, FMRP loss adversely impacts the neuronal firing of the GABAergic system which creates an imbalance in the excitatory/inhibitory ratio within the brain. Current FXS treatment strategies focus on curing symptoms, such as anxiety or decreased social function. While treating symptoms can be helpful, incorporating non-invasive imaging to evaluate how treatments change the brain's biology may explain what molecular aberrations are associated with disease pathology. Thus, the GABAergic system is suitable to explore developing novel therapeutic strategies for FXS. To understand how the GABAergic system may be affected by this loss-of-function mutation, GABA concentrations were examined within the frontal cortex and thalamus of 5-day-old wild type and Fmr1 knockout mice using both 1H magnetic resonance imaging (1H-MRS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Our objective was to develop a reliable scanning method for neonatal mice in vivo and evaluate whether 1H-MRS is suitable to capture regional GABA concentration differences at the front end of the critical cortical period where abnormal neurodevelopment occurs due to FMRP loss is first detected. 1H-MRS quantified GABA concentrations in both frontal cortex and thalamus of wild type and Fmr1 knockout mice. To substantiate the results of our 1H-MRS studies, in vitro LC-MS/MS was also performed on brain homogenates from age-matched mice. We found significant changes in GABA concentration between the frontal cortex and thalamus within each mouse from both wild type and Fmr1 knockout mice using 1H-MRS and LC-MS/MS. Significant GABA levels were also detected in these same regions between wild type and Fmr1 knockout mice by LC-MS/MS, validating that FMRP loss directly affects the GABAergic system. Thus, these new findings support the need to develop an effective non-invasive imaging method to monitor novel GABAergic strategies aimed at treating patients with FXS.

Combined application of MRS and DWI can effectively predict cell proliferation and assess the grade of glioma: A prospective study

In order to assess combined application of MRS and DWI for prediction cell proliferation and grade diagnosis of glioma, We prospectively collected the Cho/Cr, Cho/NAA, Cr/NAA of MRS and tumor parenchyma ADC (ADC_T), contralateral mirror brain tissue ADC (ADC_H), rADC (rADC = ADC_T/ADC_H). According to postoperative pathology, the patients were divided into two groups: LGG group and HGG group, compared differences of age, gender, Ki67, MRS, DWI between two groups. Next, we analyzed the correlation between MRS, DWI and Ki67. On this basis, the sensitivity and specificity of MRS, DWI and MRS combined with DWI (MRS + DWI) in diagnosis of glioma grade were evaluated. The differences of Ki67, Cho/Cr, Cho/NAA, Cr/NAA, ADC_T, rADC between LGG group and HGG group were statistically significant (p = 0.000, 0.000, 0.000, 0.008, 0.000, and 0.000 respectively). From ROC curve, area under the curve (AUC), sensitivity and specificity of Cho/Cr, Cho/NAA, Cr/NAA, ADC_T, rADC, PRE (MRS + DWI) were (0.901, 86.7%, 85.7%), (0.876, 80.0%, 82.1%), (0.704, 63.3%, 71.4%), (0.862, 82.1%, 83.3%), (0.820, 75.0%, 76.7%), (0.920, 86.7%, 89.3%), respectively. Fisher's linear discriminant functions results suggest: Y₁ = -20.447 + 3.46•X₁ + 17.141•X₂ (LGG), Y₂ = -19.415 + 4.828•X₁ + 14.543•X₂ (HGG). Our study suggested that MRS and DWI can effectively predict cell proliferation preoperative. MRS combined with DWI can further improve sensitivity and specificity in assessing the grade of glioma.

GABA and glutamate deficits from frontotemporal lobar degeneration are associated with disinhibition

Behavioural disinhibition is a common feature of the syndromes associated with frontotemporal lobar degeneration (FTLD). It is associated with high morbidity and lacks proven symptomatic treatments. A potential therapeutic strategy is to correct the neurotransmitter deficits associated with FTLD, thereby improving behaviour. Reductions in the neurotransmitters glutamate and GABA correlate with impulsive behaviour in several neuropsychiatric diseases and there is post-mortem evidence of their deficit in FTLD. Here, we tested the hypothesis that prefrontal glutamate and GABA levels are reduced by FTLD in vivo, and that their deficit is associated with impaired response inhibition. Thirty-three participants with a syndrome associated with FTLD (15 patients with behavioural variant frontotemporal dementia and 18 with progressive supranuclear palsy, including both Richardson's syndrome and progressive supranuclear palsy-frontal subtypes) and 20 healthy control subjects were included. Participants undertook ultra-high field (7 T) magnetic resonance spectroscopy and a stop-signal task of response inhibition. We measured glutamate and GABA levels using semi-LASER magnetic resonance spectroscopy in the right inferior frontal gyrus, because of its strong association with response inhibition, and in the primary visual cortex, as a control region. The stop-signal reaction time was calculated using an ex-Gaussian Bayesian model. Participants with frontotemporal dementia and progressive supranuclear palsy had impaired response inhibition, with longer stop-signal reaction times compared with controls. GABA concentration was reduced in patients versus controls in the right inferior frontal gyrus, but not the occipital lobe. There was no group-wise difference in partial volume corrected glutamate concentration between patients and controls. Both GABA and glutamate concentrations in the inferior frontal gyrus correlated inversely with stop-signal reaction time, indicating greater impulsivity in proportion to the loss of each neurotransmitter. We conclude that the glutamatergic and GABAergic deficits in the frontal lobe are potential targets for symptomatic drug treatment of frontotemporal dementia and progressive supranuclear palsy.

Frequency and phase correction of J-difference edited MR spectra using deep learning

PURPOSE

To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data.

METHODS

Two neural networks (1 for frequency, 1 for phase) consisting of fully connected layers were trained and validated using simulated MEGA-edited MRS data. This DL-FPC was subsequently tested and compared to a conventional approach (spectral registration [SR]) and to a model-based SR implementation (mSR) using in vivo MEGA-edited MRS datasets. Additional artificial offsets were added to these datasets to further investigate performance.

RESULTS

The validation showed that DL-based FPC was capable of correcting within 0.03 Hz of frequency and 0.4°of phase offset for unseen simulated data. DL-based FPC performed similarly to SR for the unmanipulated in vivo test datasets. When additional offsets were added to these datasets, the networks still performed well. However, although SR accurately corrected for smaller offsets, it often failed for larger offsets. The mSR algorithm performed well for larger offsets, which was because the model was generated from the in vivo datasets. In addition, the computation times were much shorter using DL-based FPC or mSR compared to SR for heavily distorted spectra.

CONCLUSION

These results represent a proof of principle for the use of DL for preprocessing MRS data.

Interaction of dopamine transporter and metabolite ratios underpinning the cognitive dysfunction in patients with carbon monoxide poisoning: A combined SPECT and MRS study

Cognitive dysfunction has been reported in patients with carbon monoxide (CO) poisoning. However, the underpinning mechanism remained unclear. This study examined dopamine transporter (DAT) and metabolite ratios concurrently and their relationships with cognitive dysfunction in CO poisoning. Eighteen suicide attempters with charcoal burning which results in CO poisoning and 18 age- and gender- matched normal controls were recruited. A battery of cognitive assessments including attention, memory, and executive function was administered. Each participant received one single photon emission computed tomography with ^99mTc-TRODAT for measuring striatal DAT availability and proton magnetic resonance spectroscopy to determine N-acetyl aspartate/creatine (NAA/Cr), choline-containing compounds/creatine (Cho/Cr) and myo-inositol/creatine (mI/Cr) in the left parietal white matter and mid-occipital gray matter (OGM). CO poisoning patients had significant impairments in memory and executive function. Compared to normal, CO poisoning patients had lower striatal DAT availability, lower NAA/Cr levels in both regions and higher Cho/Cr levels in both regions. In CO poisoning patients, the altered left striatal DAT availability and Cho/Cr level in OGM were significantly associated with executive dysfunction in the expected directions. Moreover, there was a significant interaction between these two imaging indices on their relationships with executive dysfunction and combination of them could adequately predict executive dysfunction in more CO poisoning cases than either alone. The current results suggested that both alterations in DAT availability and metabolite ratios might play crucial roles in executive dysfunction in CO poisoning. This research also highlights the importance of multimodal imaging approaches for studying neurotoxicity effects.

Metabolite activity in the anterior cingulate cortex during a painful stimulus using functional MRS

To understand neurochemical brain responses to pain, proton magnetic resonance spectroscopy (1H-MRS) is used in humans in vivo to examine various metabolites. Recent MRS investigations have adopted a functional approach, where acquisitions of MRS are performed over time to track task-related changes. Previous studies suggest glutamate is of primary interest, as it may play a role during cortical processing of noxious stimuli. The objective of this study was to examine the metabolic effect (i.e., glutamate) in the anterior cingulate cortex during noxious stimulation using fMRS. The analysis addressed changes in glutamate and glutamate + glutamine (Glx) associated with the onset of pain, and the degree by which fluctuations in metabolites corresponded with continuous pain outcomes. Results suggest healthy participants undergoing tonic noxious stimulation demonstrated increased concentrations of glutamate and Glx at the onset of pain. Subsequent reports of pain were not accompanied by corresponding changes in glutamate of Glx concentrations. An exploratory analysis on sex revealed large effect size changes in glutamate at pain onset in female participants, compared with medium-sized effects in male participants. We propose a role for glutamate in the ACC related to the detection of a noxious stimulus.

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

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

A Review of Translational Magnetic Resonance Imaging in Human and Rodent Experimental Models of Small Vessel Disease

Cerebral small vessel disease (SVD) is a major health burden, yet the pathophysiology remains poorly understood with no effective treatment. Since much of SVD develops silently and insidiously, non-invasive neuroimaging such as MRI is fundamental to detecting and understanding SVD in humans. Several relevant SVD rodent models are established for which MRI can monitor in vivo changes over time prior to histological examination. Here, we critically review the MRI methods pertaining to salient rodent models and evaluate synergies with human SVD MRI methods. We found few relevant publications, but argue there is considerable scope for greater use of MRI in rodent models, and opportunities for harmonisation of the rodent-human methods to increase the translational potential of models to understand SVD in humans. We summarise current MR techniques used in SVD research, provide recommendations and examples and highlight practicalities for use of MRI SVD imaging protocols in pre-selected, relevant rodent models.

High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI

OBJECTIVES

Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in a patient cohort of 23 high-grade gliomas (HGG).

MATERIALS AND METHODS

We preoperatively measured 23 patients with histologically verified HGGs (17 male, 8 female, age 53 ± 15) with an MRSI sequence based on concentric ring trajectories with a 64 × 64 × 39 measurement matrix, and a 3.4 × 3.4 × 3.4 mm3 nominal voxel volume in 15 min. Quantification used a basis-set of 17 components including N-acetyl-aspartate (NAA), total choline (tCho), total creatine (tCr), glutamate (Glu), glutamine (Gln), glycine (Gly) and 2-hydroxyglutarate (2HG). The resultant metabolic images were evaluated for their reliability as well as their quality and compared to spatially segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast enhanced + edema, peritumoral) based on clinical data and also compared to histopathology (e.g., grade, IDH-status).

RESULTS

Eighteen of the patient measurements were considered usable. In these patients, ten metabolites were quantified with acceptable quality. Gln, Gly, and tCho were increased and NAA and tCr decreased in nearly all tumor regions, with other metabolites such as serine, showing mixed trends. Overall, there was a reliable characterization of metabolic tumor areas. We also found heterogeneity in the metabolic images often continued into the peritumoral region. While 2HG could not be satisfyingly quantified, we found an increase of Glu in the contrast-enhancing region of IDH-wildtype HGGs and a decrease of Glu in IDH1-mutant HGGs.

CONCLUSIONS

We successfully demonstrated high-resolution 7T 3D-MRSI in HGG patients, showing metabolic differences between tumor regions and peritumoral tissue for multiple metabolites. Increases of tCho, Gln (related to tumor metabolism), Gly (related to tumor proliferation), as well as decreases in NAA, tCr, and others, corresponded very well to clinical tumor segmentation, but were more heterogeneous and often extended into the peritumoral region.

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.

Quantitative 1 H MRI and MRS of fatty acid composition

Adipose tissue as well as other depots of fat (triglycerides) are increasingly being recognized as active contributors to the human function and metabolism. In addition to the fat concentration, also the fatty acid chemical composition (FAC) of the triglyceride molecules may play an important part in diseases such as obesity, insulin resistance, hepatic steatosis, osteoporosis, and cancer. MR spectroscopy and chemical-shift-encoded imaging (CSE-MRI) are established methods for non-invasive quantification of fat concentration in tissue. More recently, similar techniques have been developed for assessment also of the FAC in terms of the number of double bonds, the fraction of saturated, monounsaturated, and polyunsaturated fatty acids, or semi-quantitative unsaturation indices. The number of papers focusing on especially CSE-MRI-based techniques has steadily increased during the past few years, introducing a range of acquisition protocols and reconstruction algorithms. However, a number of potential sources of bias have also been identified. Furthermore, the measures used to characterize the FAC using both MRI and MRS differ, making comparisons between different techniques difficult. The aim of this paper is to review MRS- and MRI-based methods for in vivo quantification of the FAC. We describe the chemical composition of triglycerides and discuss various potential FAC measures. Furthermore, we review acquisition and reconstruction methodology and finally, some existing and potential applications are summarized. We conclude that both MRI and MRS provide feasible non-invasive alternatives to the gold standard gas chromatography for in vivo measurements of the FAC. Although both are associated with gas chromatography, future studies are warranted.

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

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

Adaptive baseline fitting for 1 H MR spectroscopy analysis

PURPOSE

Accurate baseline modeling is essential for reliable MRS analysis and interpretation-particularly at short echo-times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study, a new method is presented to estimate its optimal value.

METHODS

An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency-domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a 4-stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI-both at a field strength of 3 Tesla.

RESULTS

Simulated analyses demonstrate metabolite errors result from 2 main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline, ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue.

CONCLUSIONS

ABfit has been shown to perform accurate baseline estimation and is suitable for fully automated routine MRS analysis.

Suggestions for improving the visualization of magnetic resonance spectroscopy voxels and spectra

Magnetic resonance spectroscopy (MRS) has seen an increase in popularity as a method for studying the human brain. This approach is dependent on voxel localization and spectral quality, knowledge of which are essential for judging the validity and robustness of any analysis. As such, visualization plays a central role in appropriately communicating MRS studies. The quality of data visualization has been shown to be poor in a number of biomedical fields and so we sought to appraise this in MRS papers. To do this, we conducted a survey of the psychiatric single-voxel MRS literature. This revealed a generally low standard, with a significant proportion of papers not providing the voxel location and spectral quality information required to judge their validity or replicate the experiment. Based on this, we then present a series of suggestions for a minimal standard for MRS data visualization. The primary point of these is that both voxel location and MRS spectra be presented from all participants. Participant group membership should be indicated where more than one is included in the experiment (e.g. patients and controls). A set of suggested figure layouts that fulfil these requirements are presented with sample code provided to produce these (github.com/nwd2918/MRS-voxel-plot).

Hyperpolarized 13C MRI: A novel approach for probing cerebral metabolism in health and neurological disease

Cerebral metabolism is tightly regulated and fundamental for healthy neurological function. There is increasing evidence that alterations in this metabolism may be a precursor and early biomarker of later stage disease processes. Proton magnetic resonance spectroscopy (1H-MRS) is a powerful tool to non-invasively assess tissue metabolites and has many applications for studying the normal and diseased brain. However, the technique has limitations including low spatial and temporal resolution, difficulties in discriminating overlapping peaks, and challenges in assessing metabolic flux rather than steady-state concentrations. Hyperpolarized carbon-13 magnetic resonance imaging is an emerging clinical technique that may overcome some of these spatial and temporal limitations, providing novel insights into neurometabolism in both health and in pathological processes such as glioma, stroke and multiple sclerosis. This review will explore the growing body of pre-clinical data that demonstrates a potential role for the technique in assessing metabolism in the central nervous system. There are now a number of clinical studies being undertaken in this area and this review will present the emerging clinical data as well as the potential future applications of hyperpolarized 13C magnetic resonance imaging in the brain, in both clinical and pre-clinical studies.

Hippocampal glutamate and hippocampus subfield volumes in antipsychotic-naive first episode psychosis subjects and relationships to duration of untreated psychosis

Evidence points toward a relationship between longer duration of untreated psychosis (DUP) and worse long-term outcomes in patients with first episode psychosis (FEP), but the underlying neurobiology remains poorly understood. Proton magnetic resonance spectroscopy studies have reported altered hippocampus glutamatergic neurotransmission, and structural MRI as reported hippocampal atrophy that may be associated with memory impairment in schizophrenia. Here, we quantify left hippocampus glutamate (Glx) and left hippocampus subfield volumes in 54 antipsychotic-naive FEP and 41 healthy controls (HC), matched on age, sex, and parental occupation. While there were no significant group difference in Glx levels, hippocampal Glx levels were significantly higher in those who underwent a long DUP (>12 months) compared to those with a short DUP, and compared to HC. Compared to HC, FEP had significantly reduced whole hippocampus volume, as well as of CA1, CA4, granule cell layer, subiculum, and presubiculum subfields. Smaller whole hippocampal volume, as well as CA1, molecular layer, subiculum, presubiculum, and hippocampal tail volumes were significantly associated with longer DUP. However, we found no significant association between hippocampal Glx levels and hippocampal volume or subfields, suggesting that these alterations are not related, or their relationship does not follow a linear pattern. However, our results strongly suggest that one or several pathophysiological processes underlie the DUP. Importantly, our data highlight the critical need for reducing the DUP and for early pharmacological intervention with the hope to prevent structural deficits and, hopefully, improve clinical outcomes.

Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer among women worldwide, and early detection remains a principal factor for improved patient outcomes and reduced mortality. Clinically, magnetic resonance imaging (MRI) techniques are routinely used in determining benign and malignant tumor phenotypes and for monitoring treatment outcomes. Static MRI techniques enable superior structural contrast between adipose and fibroglandular tissues, while dynamic MRI techniques can elucidate functional characteristics of malignant tumors. The preferred clinical procedure-dynamic contrast-enhanced MRI-illuminates the hypervascularity of breast tumors through a gadolinium-based contrast agent; however, accumulation of the potentially toxic contrast agent remains a major limitation of the technique, propelling MRI research toward finding an alternative, noninvasive method. Three such techniques are magnetic resonance spectroscopy, chemical exchange saturation transfer, and non-contrast diffusion weighted imaging. These methods shed light on underlying chemical composition, provide snapshots of tissue metabolism, and more pronouncedly characterize microstructural heterogeneity. This review article outlines the present state of clinical MRI for breast cancer and examines several research techniques that demonstrate capacity for clinical translation. Ultimately, multi-parametric MRI-incorporating one or more of these emerging methods-presently holds the best potential to afford improved specificity and deliver excellent accuracy to clinics for the prediction, detection, and monitoring of breast cancer.

Italian consensus and recommendations on diagnosis and treatment of low-grade gliomas. An intersociety (SINch/AINO/SIN) document

In 2018, the SINch (Italian Society of Neurosurgery) Neuro-Oncology Section, AINO (Italian Association of Neuro-Oncology) and SIN (Italian Association of Neurology) Neuro-Oncology Section formed a collaborative Task Force to look at the diagnosis and treatment of low-grade gliomas (LGGs). The Task Force included neurologists, neurosurgeons, neuro-oncologists, pathologists, radiologists, radiation oncologists, medical oncologists, a neuropsychologist and a methodologist. For operational purposes, the Task Force was divided into five Working Groups: diagnosis, surgical treatment, adjuvant treatments, supportive therapies, and follow-up. The resulting guidance document is based on the available evidence and provides recommendations on diagnosis and treatment of LGG patients, considering all aspects of patient care along their disease trajectory.

Intermittent theta-burst stimulation moderates interaction between increment of N-Acetyl-Aspartate in anterior cingulate and improvement of unipolar depression

BACKGROUND

Intermittent theta-burst stimulation (iTBS), a novel repetitive transcranial magnetic stimulation (rTMS) technique, appears to have antidepressant effects when applied over left dorsolateral prefrontal cortex (DLPFC). However, its underlying neurobiological mechanisms are unclear. Proton magnetic resonance spectroscopy (¹H-MRS) provides in vivo measurements of cerebral metabolites altered in major depressive disorder (MDD) like N-acetyl-aspartate (NAA) and choline-containing compounds (Cho). We used MRS to analyse effects of iTBS on the associations between the shifts in the NAA and Cho levels during therapy and MDD improvement.

METHODS

In-patients with unipolar MDD (N = 57), in addition to treatment as usual, were randomized to receive 20 iTBS or sham stimulations applied over left DLPFC over four weeks. Single-voxel ¹H-MRS of the anterior cingulate cortex (ACC) was performed at baseline and follow-up. Increments of concentrations, as well as MDD improvement, were defined as endpoints. We tested a moderated mediation model of effects using the PROCESS macro (an observed variable ordinary least squares and logistic regression path analysis modeling tool) for SPSS.

RESULTS

Improvement of depressive symptoms was significantly associated with decrease of Cho/NAA ratio, mediated by NAA. iTBS had a significant moderating effect enhancing the relationship between NAA change and depression improvement.

CONCLUSIONS

Our findings suggest a potential neurochemical pathway and mechanisms of antidepressant action of iTBS, which may moderate the improvement of metabolic markers of neuronal viability. iTBS might increase neuroplasticity, thus facilitating normalization of neuronal circuit function.

Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain

PURPOSE

The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy (¹ H-MRS).

METHODS

The reliability of metabolite quantification depends on signal-to-noise ratio (SNR), linewidth, and degree of spectral overlap (DSO), and therefore knowledge about these factors may be utilized in measurement uncertainty estimation in deep learning-based ¹ H-MRS. While SNR and linewidth are typically estimated from a representative singlet, DSO needs to be estimated metabolite-specifically. We developed convolutional neural networks (CNNs) capable of isolating target metabolite signal on simulated rat brain spectra at 9.4T, such that, in addition to metabolite content, the signal-to-background ratio (SBR) as a quantitative metric of DSO can be estimated directly from CNN-output for each metabolite. The CNN-predicted SBR was adjusted according to its pre-defined relationship to the ground-truth SBR by exploiting the big spectral data (N = 80 000), and used for measurement uncertainty estimation together with the SNR and linewidth from the CNN-input spectrum. The proposed method was tested first on the simulated spectra in comparison with LCModel and jMRUI and further on in vivo spectra.

RESULTS

The proposed method outperformed LCModel and jMRUI in both quantitative accuracy and measurement uncertainty estimation. Using in vivo data, the metabolite concentrations from the proposed method were close to the reported ranges with the measurement uncertainty of glutamine, glutamate, myo-inositol, N-acetylaspartate, and Tau less than 10%.

CONCLUSION

The proposed method may be used for metabolite quantification with measurement uncertainty estimation in rat brain at 9.4T by exploiting the spectral isolation capability of the CNNs and the availability of big spectral data.

Super-Resolution Whole-Brain 3D MR Spectroscopic Imaging for Mapping D-2-Hydroxyglutarate and Tumor Metabolism in Isocitrate Dehydrogenase 1-mutated Human Gliomas

Background Isocitrate dehydrogenase (IDH) mutations are highly frequent in glioma, producing high levels of the oncometabolite D-2-hydroxyglutarate (D-2HG). Hence, D-2HG represents a valuable imaging marker for IDH-mutated human glioma. Purpose To develop and evaluate a super-resolution three-dimensional (3D) MR spectroscopic imaging strategy to map D-2HG and tumor metabolism in IDH-mutated human glioma. Materials and Methods Between March and September 2018, participants with IDH1-mutated gliomas and healthy participants were prospectively scanned with a 3-T whole-brain 3D MR spectroscopic imaging protocol optimized for D-2HG. The acquired D-2HG maps with a voxel size of 5.2 × 5.2 × 12 mm were upsampled to a voxel size of 1.7 × 1.7 × 3 mm using a super-resolution method that combined weighted total variation, feature-based nonlocal means, and high-spatial-resolution anatomic imaging priors. Validation with simulated healthy and patient data and phantom measurements was also performed. The Mann-Whitney U test was used to check that the proposed super-resolution technique yields the highest peak signal-to-noise ratio and structural similarity index. Results Three participants with IDH1-mutated gliomas (mean age, 50 years ± 21 [standard deviation]; two men) and three healthy participants (mean age, 32 years ± 3; two men) were scanned. Twenty healthy participants (mean age, 33 years ± 5; 16 men) underwent a simulation of upsampled MR spectroscopic imaging. Super-resolution upsampling improved peak signal-to-noise ratio and structural similarity index by 62% (P < .05) and 7.3% (P < .05), respectively, for simulated data when compared with spline interpolation. Correspondingly, the proposed method significantly improved tissue contrast and structural information for the acquired 3D MR spectroscopic imaging data. Conclusion High-spatial-resolution whole-brain D-2-hydroxyglutarate imaging is possible in isocitrate dehydrogenase 1-mutated human glioma by using a super-resolution framework to upsample three-dimensional MR spectroscopic images acquired at lower resolution. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Huang and Lin in this issue.

MR spectroscopy using static higher order shimming with dynamic linear terms (HOS-DLT) for improved water suppression, interleaved MRS-fMRI, and navigator-based motion correction at 7T

PURPOSE

To interleave global and local higher order shimming for single voxel MRS. Single voxel MR spectroscopy requires optimization of the B₀ field homogeneity in the region of the voxel to obtain a narrow linewidth and provide high data quality. However, the optimization of local higher order fields on a localized MRS voxel typically leads to large field offsets outside that volume. This compromises interleaved MR sequence elements that benefit from global field homogeneity such as water suppression, interleaved MRS-fMRI, and MR motion correction.

METHODS

A shimming algorithm was developed to optimize the MRS voxel homogeneity and the whole brain homogeneity for interleaved sequence elements, using static higher order shims and dynamic linear terms (HOS-DLT). Shimming performance was evaluated using 6 brain regions and 10 subjects. Furthermore, the benefits of HOS-DLT was demonstrated for water suppression, MRS-fMRI, and motion corrected MRS using fat-navigators.

RESULTS

The HOS-DLT algorithm was shown to improve the whole brain homogeneity compared to an MRS voxel-based shim, without compromising the MRS voxel homogeneity. Improved water suppression over the brain, reduced image distortions in MRS-fMRI, and improved quality of motion navigators were demonstrated using the HOS-DLT method.

CONCLUSION

HOS-DLT shimming allowed for both local and global field homogeneity, providing excellent MR spectroscopy data quality, as well as good field homogeneity for interleaved sequence elements, even without the need for dynamic higher order shimming capabilities.

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.

1H magnetic resonance spectroscopy of 2H-to-1H exchange quantifies the dynamics of cellular metabolism in vivo

The quantitative mapping of the in vivo dynamics of cellular metabolism via non-invasive imaging contributes to the understanding of the initiation and progression of diseases associated with dysregulated metabolic processes. Current methods for imaging cellular metabolism are limited by low sensitivities, by costs, or by the use of specialized hardware. Here, we introduce a method that captures the turnover of cellular metabolites by quantifying signal reductions in proton magnetic resonance spectroscopy (MRS) resulting from the replacement of ¹H with ²H. The method, which we termed quantitative exchanged-label turnover MRS, only requires deuterium-labelled glucose and standard MRI scanners, and with a single acquisition provides steady-state information and metabolic rates for several metabolites. We used the method to monitor glutamate, glutamine, γ-aminobutyric acid and lactate in the brains of normal and glioma-bearing rats following the administration of ²H₂-labelled glucose and ²H₃-labelled acetate. Quantitative exchanged-label turnover MRS should broaden the applications of routine ¹H MRS.

Advanced single voxel 1 H magnetic resonance spectroscopy techniques in humans: Experts' consensus recommendations

Conventional proton MRS has been successfully utilized to noninvasively assess tissue biochemistry in conditions that result in large changes in metabolite levels. For more challenging applications, namely, in conditions which result in subtle metabolite changes, the limitations of vendor-provided MRS protocols are increasingly recognized, especially when used at high fields (≥3 T) where chemical shift displacement errors, B0 and B1 inhomogeneities and limitations in the transmit B1 field become prominent. To overcome the limitations of conventional MRS protocols at 3 and 7 T, the use of advanced MRS methodology, including pulse sequences and adjustment procedures, is recommended. Specifically, the semiadiabatic LASER sequence is recommended when TE values of 25-30 ms are acceptable, and the semiadiabatic SPECIAL sequence is suggested as an alternative when shorter TE values are critical. The magnetic field B0 homogeneity should be optimized and RF pulses should be calibrated for each voxel. Unsuppressed water signal should be acquired for eddy current correction and preferably also for metabolite quantification. Metabolite and water data should be saved in single shots to facilitate phase and frequency alignment and to exclude motion-corrupted shots. Final averaged spectra should be evaluated for SNR, linewidth, water suppression efficiency and the presence of unwanted coherences. Spectra that do not fit predefined quality criteria should be excluded from further analysis. Commercially available tools to acquire all data in consistent anatomical locations are recommended for voxel prescriptions, in particular in longitudinal studies. To enable the larger MRS community to take advantage of these advanced methods, a list of resources for these advanced protocols on the major clinical platforms is provided. Finally, a set of recommendations are provided for vendors to enable development of advanced MRS on standard platforms, including implementation of advanced localization sequences, tools for quality assurance on the scanner, and tools for prospective volume tracking and dynamic linear shim corrections.

A Magnetic Resonance Spectroscopy Study of Superior Visual Search Abilities in Children with Autism Spectrum Disorder

Although diagnosed on the basis of deficits in social communication and interaction, autism spectrum disorder (ASD) is also characterized by superior performance on a variety of visuospatial tasks, including visual search. In neurotypical individuals, region-specific concentrations of the inhibitory neurotransmitter gamma-aminobutyric acid (GABA) are associated with individual differences in attention and perception. While it has been hypothesized that ASD may be associated with an excitatory-inhibitory imbalance, it remains unclear how this may contribute to accelerated visual search performance in individuals with ASD. To investigate this, 21 children with ASD and 20 typically developing children participated in a visual search task and a magnetic resonance spectroscopy study to detect neurochemical concentrations, including GABA. Region-specific neurochemicals were examined in the right frontal eye fields, right temporal-parietal junction (rTPJ), and bilateral visual cortex (VIS). GABA concentrations did not differ between groups; however, in children with ASD, greater GABA concentration in the VIS was related to more efficient search. Additionally, lower VIS GABA levels were also associated with increased social impairment. Finally, we found reduced N-acetyl aspartate, total creatine, glutamate and glutamine (Glx), GABA/Glx in the rTPJ, suggestive of neuronal dysfunction in a critical network hub. Our results show that GABA concentrations in the VIS are related to efficient search in ASD, thus providing further evidence of enhanced discrimination in ASD. Autism Res 2020, 13: 550-562. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Children with autism spectrum disorder (ASD) often perform better than their non-ASD peers on visual search tasks; however, it is unclear how they achieve this superior performance. Using magnetic resonance spectroscopy to measure neurochemicals in the brain, we found that the level of one, gamma-aminobutyric acid, in the visual cortex was directly related to search abilities in children with ASD. These results suggest that faster search may relate to enhanced perceptual functioning in children with ASD.

Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus

In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (¹H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM). We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel ¹H-MRS in our hospitals. One hundred and seventeen metabolic features were extracted from the multivoxel ¹H-MRS image. Thirty-three metabolic features selected by the Mann-Whitney U test were considered to have a statistically significant difference (p < 0.05). However, the best accuracy achieved by conventional statistical methods using these 33 metabolic features was only 77%. We turned to develop a support vector machine broad learning system (BL-SVM) to quantitatively analyse the metabolic features from ¹H-MRS. Although not all the individual features manifested statistics significantly, the BL-SVM could still learn to distinguish the NPSLE from the healthy controls. The area under the receiver operating characteristic curve (AUC), the sensitivity, and the specificity of our BL-SVM in predicting NPSLE were 95%, 95.8%, and 93%, respectively, by 3-fold cross-validation. We consequently conclude that the proposed system effectively and efficiently working on limited and noisy samples may brighten a noinvasive in vivo instrument for early diagnosis of NPSLE.

Reduced Glutamate in the Medial Prefrontal Cortex Is Associated With Emotional and Cognitive Dysregulation in People With Chronic Pain

A decrease in glutamate in the medial prefrontal cortex (mPFC) has been extensively found in animal models of chronic pain. Given that the mPFC is implicated in emotional appraisal, cognition and extinction of fear, could a potential decrease in glutamate be associated with increased pessimistic thinking, fear and worry symptoms commonly found in people with chronic pain? To clarify this question, 19 chronic pain subjects and 19 age- and gender-matched control subjects without pain underwent magnetic resonance spectroscopy. Both groups also completed the Temperament and Character, the Beck Depression and the State Anxiety Inventories to measure levels of harm avoidance, depression, and anxiety, respectively. People with chronic pain had significantly higher scores in harm avoidance, depression and anxiety compared to control subjects without pain. High levels of harm avoidance are characterized by excessive worry, pessimism, fear, doubt and fatigue. Individuals with chronic pain showed a significant decrease in mPFC glutamate levels compared to control subjects without pain. In people with chronic pain mPFC glutamate levels were significantly negatively correlated with harm avoidance scores. This means that the lower the concentration of glutamate in the mPFC, the greater the total scores of harm avoidance. High scores are associated with fearfulness, pessimism, and fatigue-proneness. We suggest that chronic pain, particularly the stress-induced release of glucocorticoids, induces changes in glutamate transmission in the mPFC, thereby influencing cognitive, and emotional processing. Thus, in people with chronic pain, regulation of fear, worry, negative thinking and fatigue is impaired.

Quantifying the Metabolic Signature of Multiple Sclerosis by in vivo Proton Magnetic Resonance Spectroscopy: Current Challenges and Future Outlook in the Translation From Proton Signal to Diagnostic Biomarker

Proton magnetic resonance spectroscopy (¹H-MRS) offers a growing variety of methods for querying potential diagnostic biomarkers of multiple sclerosis in living central nervous system tissue. For the past three decades, ¹H-MRS has enabled the acquisition of a rich dataset suggestive of numerous metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord of individuals with multiple sclerosis, but this body of information is not free of seeming internal contradiction. The use of ¹H-MRS signals as diagnostic biomarkers depends on reproducible and generalizable sensitivity and specificity to disease state that can be confounded by a multitude of influences, including experiment group classification and demographics; acquisition sequence; spectral quality and quantifiability; the contribution of macromolecules and lipids to the spectroscopic baseline; spectral quantification pipeline; voxel tissue and lesion composition; T₁ and T₂ relaxation; B₁ field characteristics; and other features of study design, spectral acquisition and processing, and metabolite quantification about which the experimenter may possess imperfect or incomplete information. The direct comparison of ¹H-MRS data from individuals with and without multiple sclerosis poses a special challenge in this regard, as several lines of evidence suggest that experimental cohorts may differ significantly in some of these parameters. We review the existing findings of in vivo¹H-MRS on central nervous system metabolic abnormalities in multiple sclerosis and its subtypes within the context of study design, spectral acquisition and processing, and metabolite quantification and offer an outlook on technical considerations, including the growing use of machine learning, by future investigations into diagnostic biomarkers of multiple sclerosis measurable by ¹H-MRS.

Noninvasive analysis and identification of an intramuscular fluid collection by postmortem 1H-MRS in a case of a fatal motor vehicle accident

In a case of a fatal traffic accident, a suspicious finding was identified in the muscular tissue of the left thigh by whole-body postmortem computed tomography. To better interpret the finding, the lower extremities were investigated by magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (¹H-MRS). MRI revealed the presence of an evenly distributed intramuscular fluid and ¹H-MRS of a volume within the fluid detected concentrations of acetate and lactate. The fluid was assumed to be an extravasation of an intraosseous infusion, erroneously administered to the intermediate vastus of the left thigh during resuscitation, which was later confirmed when access to resuscitation protocols was granted. Further ex situ ¹H-MRS investigations of five different infusion fluids showed the possible discrimination of the fluids and further indicated the unknown fluid to be a Ringer's acetate solution. This paper presents the case-based application of postmortem intramuscular 1H-MRS and introduces the possibility of its use to differentiate exo- and endogenic fluids for forensic interpretation. Further research for this method regarding problems in forensic pathology is needed.

Hyperpolarized MR - What's up Doc?

Hyperpolarized MR by dissolution Dynamic Nuclear Polarization (dDNP) appeared on the scene in 2003. Since then, it has been translated to the clinic and several sites are now conducting human studies. This has happened at record pace despite all its complexities. The method has reached a pivotal point, and the coming years will be critical in realizing its full potential. Though the field has been characterized by strong collaboration between academia, government and industry, the key message of this perspective paper is that accelerated consensus building is of the essence in fulfilling the original vision for the method and ensuring widespread adoption. The challenge is to gain acceptance among clinicians based on strong indications and clear evidence. The future appears bright; initial clinical data looks promising and the scope for improvement is significant.

In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound

Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.

Analysis of metabolic abnormalities in high-grade glioma using MRSI and convex NMF

Clinical use of MRSI is limited by the level of experience required to properly translate MRSI examinations into relevant clinical information. To solve this, several methods have been proposed to automatically recognize a predefined set of reference metabolic patterns. Given the variety of metabolic patterns seen in glioma patients, the decision on the optimal number of patterns that need to be used to describe the data is not trivial. In this paper, we propose a novel framework to (1) separate healthy from abnormal metabolic patterns and (2) retrieve an optimal number of reference patterns describing the most important types of abnormality. Using 41 MRSI examinations (1.5 T, PRESS, T_E 135 ms) from 22 glioma patients, four different patterns describing different types of abnormality were detected: edema, healthy without Glx, active tumor and necrosis. The identified patterns were then evaluated on 17 MRSI examinations from nine different glioma patients. The results were compared against BraTumIA, an automatic segmentation method trained to identify different tumor compartments on structural MRI data. Finally, the ability to predict future contrast enhancement using the proposed approach was also evaluated.

Association between Brain and Plasma Glutamine Levels in Healthy Young Subjects Investigated by MRS and LC/MS

Both glutamine (Gln) and glutamate (Glu) are known to exist in plasma and brain. However, despite the assumed relationship between brain and plasma, no studies have clarified the association between them. Proton magnetic resonance spectroscopy (MRS) was sequentially performed twice, with a 60-min interval, on 10 males and 10 females using a 3T scanner. Blood samples for liquid chromatography-mass spectrometry (LC/MS) to measure Gln and Glu concentrations in plasma were collected during the time interval between the two MRS sessions. MRS voxels of interest were localized at the posterior cingulate cortex (PCC) and cerebellum (Cbll) and measured by the SPECIAL sequence. Spearman's correlation coefficient was used to examine the association between brain and plasma metabolites. The Gln concentrations in PCC (mean of two measurements) were positively correlated with Gln concentrations in plasma (p < 0.01, r = 0.72). However, the Glu concentrations in the two regions were not correlated with those in plasma. Consideration of the different dynamics of Gln and Glu between plasma and brain is crucial when addressing the pathomechanism and therapeutic strategies for brain disorders such as Alzheimer's disease and hepatic encephalopathy.