Clinical proton MR spectroscopy in central nervous system disorders

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

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

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

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

Neuroimaging Patterns of Intracranial Infections: Meningitis, Cerebritis, and Their Complications

Neuroimaging provides rapid, noninvasive visualization of central nervous system infections for optimal diagnosis and management. Generalizable and characteristic imaging patterns help radiologists distinguish different types of intracranial infections including meningitis and cerebritis from a variety of bacterial, viral, fungal, and/or parasitic causes. Here, we describe key radiologic patterns of meningeal enhancement and diffusion restriction through profiles of meningitis, cerebritis, abscess, and ventriculitis. We discuss various imaging modalities and recent diagnostic advances such as deep learning through a survey of intracranial pathogens and their radiographic findings. Moreover, we explore critical complications and differential diagnoses of intracranial infections.

Hyperpolarized 13C-Pyruvate to Assess Response to Anti-PD1 Immune Checkpoint Inhibition in YUMMER 1.7 Melanoma Xenografts

There is currently no consensus to determine which advanced melanoma patients will benefit from immunotherapy, highlighting the critical need to identify early-response biomarkers to immune checkpoint inhibitors. The aim of this work was to evaluate in vivo metabolic spectroscopy using hyperpolarized (HP) ¹³C-pyruvate and ¹³C-glucose to assess early response to anti-PD1 therapy in the YUMMER1.7 syngeneic melanoma model. The xenografts showed a significant tumor growth delay when treated with two cycles of an anti-PD1 antibody compared to an isotype control antibody. ¹³C-MRS was performed in vivo after the injection of hyperpolarized ¹³C-pyruvate, at baseline and after one cycle of immunotherapy, to evaluate early dynamic changes in ¹³C-pyruvate-¹³C-lactate exchange. Furthermore, ex vivo ¹³C-MRS metabolic tracing experiments were performed after U-¹³C-glucose injection following one cycle of immunotherapy. A significant decrease in the ratio of HP ¹³C-lactate to ¹³C-pyruvate was observed in vivo in comparison with the isotype control group, while there was a lack of change in the levels of ¹³C lactate and ¹³C alanine issued from ¹³C glucose infusion, following ex vivo assessment on resected tumors. Thus, these results suggest that hyperpolarized ¹³C-pyruvate could be used to assess early response to immune checkpoint inhibitors in melanoma patients.

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.

MR-spectroscopy in metachromatic leukodystrophy: A model free approach and clinical correlation

BACKGROUND AND PURPOSE

Metachromatic leukodystrophy (MLD) is a lysosomal enzyme deficiency disorder leading to demyelination and subsequently to a progressive decline in cognitive and motor function. It affects mainly white matter where changes during the course of the disease can be visualized on T2-weighted MRI as hyperintense areas. Associated changes in brain metabolism can be quantified by MR spectroscopy (MRS) and may give complementary information as biomarkers for disease characterisation and progression. Our study aimed to further investigate the correlation of MRS with clinical parameters for motor and cognitive function by using a model free MRS analysis approach that would be precise and straightforward to implement.

MATERIALS AND METHODS

53 MRS datasets derived from 29 patients (10 late-infantile, 19 juvenile) and 12 controls were acquired using a semi-LASER CSI sequence covering a slice through the centrum semiovale above the corpus callosum. We defined four regions of interest in the white matter (frontal white matter [FWM] and the cortico-spinal tract [CST] area, each left and right) and one in cortical grey matter. Spectra were analysed using a model and fitting free approach by calculating the definite integral of 10 intervals which were distributed along the whole spectrum. These 10 intervals were orientated towards the main peaks of the metabolites N-acetylaspartate (NAA), creatine, myo-inositol, choline, glutamine/glutamate and aspartate to approximately attribute changes in the intervals to corresponding metabolites. Their ratios to the main creatine peak integral were correlated with clinical parameters assessing motor and cognitive abilities. Furthermore, in a post-hoc analysis, NAA levels of a subset of 21 MR datasets were correlated to NAA levels in urine measured by ¹H (proton) nuclear magnetic resonance (NMR) spectroscopy. The applied interval integration method was validated in the control cohort against the standard approach, using spectral profile templates of known metabolites (LCModel). Both methods showed good agreement, with coefficients of variance being slightly lower for our approach compared to the related LCModel results. Moreover, the new approach was able to extract information out of the frequency range around the main peaks of aspartate and glutamine where LCModel showed only few usable values for the respective metabolites.

RESULTS

MLD spectra clearly differed from controls. The most pronounced differences were found in white matter (much less in grey matter), with larger values corresponding to main peaks of myo-inositol, choline and aspartate, and smaller values associated with NAA and glutamine. Late-infantile patients had more severe changes compared to later-onset patients, especially in intervals corresponding to NAA, aspartate, myo-inositol, choline and glutamine. There was a high correlation of several intervals in the corticospinal tract region with motor function (with the most relevant interval corresponding to NAA peak with a correlation coefficient of -0.75; p < 0.001), while cognitive function, by means of IQ, was found to be most correlating in frontal white matter corresponding to the NAA peak (r = 0.84, p < 0.001). The post-hoc analysis showed that the main NAA peak interval correlated negatively with the NAA in urine (r = -0.584, p < 0.001).

CONCLUSION

The applied model and fitting free interval integration approach to analyse MRS data of a semi-LASER sequence at 3T suits well to detect and quantify pathological changes in MLD patients through the different courses of the disease and correlates well with clinical symptoms while showing smaller dimensions of variation compared to the more sophisticated single metabolite analysis using LCModel. NAA seems the most clinically meaningful biomarker to use in this context. Its correlation with urine measurements further underlines its potential as a clinically and biologically useful parameter of disease progression in MLD.

Improved detection limits of J-coupled neurometabolites in the human brain at 7 T with a J-refocused sLASER sequence

In a standard spin echo, the time evolution due to homonuclear couplings is not reversed, leading to echo time (TE)-dependent modulation of the signal amplitude and signal loss in the case of overlapping multiplet resonances. This has an adverse effect on quantification of several important metabolites such as glutamate and glutamine. Here, we propose a J-refocused variant of the sLASER sequence (J-sLASER) to improve quantification of J-coupled metabolites at ultrahigh field (UHF). The use of the sLASER sequence is particularly advantageous at UHF as it minimizes chemical shift displacement error and results in relatively homogenous refocusing. We simulated the MRS signal from brain metabolites over a broad range of TE values with sLASER and J-sLASER, and showed that the signal of J-coupled metabolites was increased with J-sLASER with TE values up to ~80 ms. We further simulated "brain-like" spectra with both sequences at the shortest TE available on our scanner. We showed that, despite the slightly longer TE, the J-sLASER sequence results in significantly lower Cramer-Rao lower bounds (CRLBs) for J-coupled metabolites compared with those obtained with sLASER. Following phantom validation, we acquired spectra from two brain regions in 10 healthy volunteers (age 38 ± 15 years) using both sequences. We showed that using J-sLASER results in a decrease of CRLBs for J-coupled metabolites. In particular, we measured a robust ~38% decrease in the mean CRLB (glutamine) in parietal white matter and posterior cingulate cortex (PCC). We further showed, in 10 additional healthy volunteers (age 34 ± 15 years), that metabolite quantification following two separate acquisitions with J-sLASER in the PCC was repeatable. The improvement in quantification of glutamine may in turn improve the independent quantification of glutamate, the main excitatory neurotransmitter in the brain, and will simultaneously help to track possible modulations of glutamine, which is a key player in the glutamatergic cycle in astrocytes.

Quantitative magnetic resonance spectroscopy of depression: The value of short-term metabolite changes in predicting treatment response

BACKGROUND

Although various prediction models of the antidepressant response have been established, the results have not been effectively applied to heterogeneous depression populations, which has seriously limited their clinical value. This study tried to build a more specific and stable model to predict treatment response in depression based on short-term changes in hippocampal metabolites.

MATERIALS AND METHODS

Seventy-four major depressive disorder (MDD) patients and 20 healthy controls in the test set were prospectively collected and retrospectively analyzed. Subjects underwent magnetic resonance spectroscopy (MRS) once a week during 6 weeks of treatment. Hippocampal regions of interest (ROIs) were extracted by using a voxel iteration scheme combined with standard brain templates. The short-term differences in hippocampal metabolites between and within groups were screened. Then, the association between hippocampal metabolite changes and clinical response was analyzed, and a prediction model based on logistic regression was constructed. In addition, a validation set (n = 60) was collected from another medical center to validate the predictive abilities.

RESULTS

After 2-3 weeks of antidepressant treatment, the differences in indicators (tCho wee0-2, tCho wee0-3 and NAA week0-3) were successfully screened. Then, the predictive abilities of these three indicators were revealed in the logistic regression model, and the optimal prediction effect was found in d(tCho) week0-3-d(NAA) week0-3 (AUC = 0.841, 95%CI = 0.736-0.946). In addition, their predictive abilities were further confirmed with the validation set.

LIMITATIONS

The small sample size and the need for multiple follow-ups limited the statistical ability to detect other findings.

CONCLUSION

The predictive model in this study presented accurate prediction and strong verification effects, which may provide early guidance for adjusting the treatment regimens of depression and serve as a checkpoint at which the eventual treatment outcome can be predicted.

Mapping the effects of pregnancy on resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture

While animal studies have demonstrated a unique reproduction-related neuroplasticity, little is known on the effects of pregnancy on the human brain. Here we investigated whether pregnancy is associated with changes to resting state brain activity, white matter microstructure, neural metabolite concentrations and grey matter architecture using a comprehensive pre-conception cohort study. We show that pregnancy leads to selective and robust changes in neural architecture and neural network organization, which are most pronounced in the Default Mode Network. These neural changes correlated with pregnancy hormones, primarily third-trimester estradiol, while no associations were found with other factors such as osmotic effects, stress and sleep. Furthermore, the changes related to measures of maternal-fetal bonding, nesting behavior and the physiological responsiveness to infant cues, and predicted measures of mother-infant bonding and bonding impairments. These findings suggest there are selective pregnancy-related modifications in brain structure and function that may facilitate peripartum maternal processes of key relevance to the mother-infant dyad.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Interleaved and simultaneous multi-nuclear magnetic resonance in vivo. Review of principles, applications and potential

Magnetic resonance signals from different nuclei can be excited or received at the same time,rendering simultaneous or rapidly interleaved multi-nuclear acquisitions feasible. The advan-tages are a reduction of total scan time compared to sequential multi-nuclear acquisitions or that additional information from heteronuclear data is obtained at thesame time and anatomical position. Information content can be qualitatively increased by delivering a more comprehensive MR-based picture of a transient state (such as an exercise bout). Also, combiningnon-proton MR acquisitions with 1 Hinformation (e.g., dynamic shim updates and motion correction) can be used to improve data quality during long scans and benefits image coregistration. This work reviews the literature on interleaved and simultaneous multi-nuclear MRI and MRS in vivo. Prominent use cases for this methodology in clinical and research applications are brain and muscle, but studies have also been carried out in other targets, including the lung, knee, breast and heart. Simultaneous multi-nuclear measurements in the liver and kidney have also been performed, but exclusively in rodents. In this review, a consistent nomenclature is proposed, to help clarify the terminology used for this principle throughout the literature on in-vivo MR. An overview covers the basic principles, the technical requirements on the MR scanner and the implementations realised either by MR system vendors or research groups, from the early days until today. Considerations regarding the multi-tuned RF coils required and heteronuclear polarisation interactions are briefly discussed, and fields for future in-vivo applications for interleaved multi-nuclear MR pulse sequences are identified.

Updates in IDH-Wildtype Glioblastoma

Glioblastoma is the most aggressive primary brain tumor with a poor prognosis. The 2021 WHO CNS5 classification has further stressed the importance of molecular signatures in diagnosis although therapeutic breakthroughs are still lacking. In this review article, updates on the current and novel therapies in IDH-wildtype GBM will be discussed.

Cerebral hemodynamic and metabolic dysregulation in the postradiation brain

Technological advances in the delivery of radiation and other novel cancer therapies have significantly improved the 5-year survival rates over the last few decades. Although recent developments have helped to better manage the acute effects of radiation, the late effects such as impairment in cognition continue to remain of concern. Accruing data in the literature have implicated derangements in hemodynamic parameters and metabolic activity of the irradiated normal brain as predictive of cognitive impairment. Multiparametric imaging modalities have allowed us to precisely quantify functional and metabolic information, enhancing the anatomic and morphologic data provided by conventional MRI sequences, thereby contributing as noninvasive imaging-based biomarkers of radiation-induced brain injury. In this review, we have elaborated on the mechanisms of radiation-induced brain injury and discussed several novel imaging modalities, including MR spectroscopy, MR perfusion imaging, functional MR, SPECT, and PET that provide pathophysiological and functional insights into the postradiation brain, and its correlation with radiation dose as well as clinical neurocognitive outcomes. Additionally, we explored some innovative imaging modalities, such as quantitative blood oxygenation level-dependent imaging, susceptibility-based oxygenation measurement, and T2-based oxygenation measurement, that hold promise in delineating the potential mechanisms underlying deleterious neurocognitive changes seen in the postradiation setting. We aim that this comprehensive review of a range of imaging modalities will help elucidate the hemodynamic and metabolic injury mechanisms underlying cognitive impairment in the irradiated normal brain in order to optimize treatment regimens and improve the quality of life for these patients.

In Vivo Parieto-Occipital White Matter Metabolism Is Correlated with Visuospatial Deficits in Adult DM1 Patients

Myotonic dystrophy type 1 (DM1) is a genetic disorder caused by a (CTG) expansion in the DM protein kinase (DMPK) gene, representing the most common adult muscular dystrophy, characterized by a multisystem involvement with predominantly skeletal muscle and brain affection. Neuroimaging studies showed widespread white matter changes and brain atrophy in DM1, but only a few studies investigated the role of white matter metabolism in the pathophysiology of central nervous system impairment. We aim to reveal the relationship between the metabolic profile of parieto-occipital white matter (POWM) as evaluated with proton MR spectroscopy technique, with the visuoperceptual and visuoconstructional dysfunctions in DM1 patients. MR spectroscopy (3 Tesla) and neuropsychological evaluations were performed in 34 DM1 patients (19 F, age: 46.4 ± 12.1 years, disease duration: 18.7 ± 11.6 years). The content of neuro-axonal marker N-acetyl-aspartate, both relative to Creatine (NAA/Cr) and to myo-Inositol (NAA/mI) resulted significantly lower in DM1 patients compared to HC (p-values < 0.0001). NAA/Cr and NAA/mI correlated with the copy of the Rey-Osterrieth complex figure (r = 0.366, p = 0.033; r = 0.401, p = 0.019, respectively) and with Street’s completion tests scores (r = 0.409, p = 0.016; r = 0.341, p = 0.048 respectively). The proportion of white matter hyperintensities within the MR spectroscopy voxel did not correlate with the metabolite content. In this study, POWM metabolic alterations in DM1 patients were not associated with the white matter morphological changes and correlated with specific neuropsychological deficits.

Proton magnetic resonance spectroscopy assessment of neonatal brain metabolism during cardiopulmonary bypass surgery

Here, we report on the development and performance of a robust 3-T single-voxel proton magnetic resonance spectroscopy (¹ H MRS) experimental protocol and data analysis pipeline for quantifying brain metabolism during cardiopulmonary bypass (CPB) surgery in a neonatal porcine model, with the overall goal of elucidating primary mechanisms of brain injury associated with these procedures. The specific aims were to assess which metabolic processes can be reliably interrogated by ¹ H MRS on a 3-T clinical scanner and to provide an initial assessment of brain metabolism during deep hypothermia cardiac arrest (DHCA) surgery and recovery. Fourteen neonatal pigs underwent CPB surgery while placed in a 3-T MRI scanner for 18, 28, and 37°C DHCA studies under hyperglycemic, euglycemic, and hypoglycemic conditions. Total imaging times, including baseline measurements, circulatory arrest (CA), and recovery averaged 3 h/animal, during which 30-40 single-voxel ¹ H MRS spectra (sLASER pulse sequence, TR/TE = 2000/30 ms, 64 or 128 averages) were acquired from a 2.2-cc right midbrain voxel. ¹ H MRS at 3 T was able to reliably quantify (1) anaerobic metabolism via depletion of brain glucose and the associated build-up of lactate during CA, (2) phosphocreatine (PCr) to creatine (Cr) conversion during CA and subsequent recovery upon reperfusion, (3) a robust increase in the glutamine-to-glutamate (Gln/Glu) ratio during the post-CA recovery period, and (4) a broadening of the water peak during CA. In vivo ¹ H MRS at 3 T can reliably quantify subtle metabolic brain changes previously deemed challenging to interrogate, including brain glucose concentrations even under hypoglycemic conditions, ATP usage via the conversion of PCr to Cr, and differential changes in Glu and Gln. Observed metabolic changes during CPB surgery of a neonatal porcine model provide new insights into possible mechanisms for prevention of neuronal injury.

Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging have shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, ¹H FID MRSI by correcting for T₁-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg^-1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T₁-corrections for water are common in MRSI studies; however, most studies use either averaged T₁-relaxation times to correct for T₁-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T₁-corrections for metabolites in addition to water. Utilizing averaged T₁-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T₁-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works.

Convolutional neural networks to predict brain tumor grades and Alzheimer’s disease with MR spectroscopic imaging data

Purpose

To evaluate the value of convolutional neural network (CNN) in the diagnosis of human brain tumor or Alzheimer’s disease by MR spectroscopic imaging (MRSI) and to compare its Matthews correlation coefficient (MCC) score against that of other machine learning methods and previous evaluation of the same data. We address two challenges: 1) limited number of cases in MRSI datasets and 2) interpretability of results in the form of relevant spectral regions.

Methods

A shallow CNN with only one hidden layer and an ad-hoc loss function was constructed involving two branches for processing spectral and image features of a brain voxel respectively. Each branch consists of a single convolutional hidden layer. The output of the two convolutional layers is merged and fed to a classification layer that outputs class predictions for the given brain voxel.

Results

Our CNN method separated glioma grades 3 and 4 and identified Alzheimer’s disease patients using MRSI and complementary MRI data with high MCC score (Area Under the Curve were 0.87 and 0.91 respectively). The results demonstrated superior effectiveness over other popular methods as Partial Least Squares or Support Vector Machines. Also, our method automatically identified the spectral regions most important in the diagnosis process and we show that these are in good agreement with existing biomarkers from the literature.

Conclusion

Shallow CNNs models integrating image and spectral features improved quantitative and exploration and diagnosis of brain diseases for research and clinical purposes. Software is available at https://bitbucket.org/TeslaH2O/cnn_mrsi.

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of "radiomics and genomics" has been considered under the umbrella of "radiogenomics". Furthermore, AI in a radiogenomics' environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor's characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them.

Higher glutamatergic activity in the medial prefrontal cortex in chronic ketamine users

BACKGROUND

The medial prefrontal cortex (mPFC) plays an important role in depression and addiction. Previous studies have shown alterations in glutamatergic activity in the mPFC following the administration of ketamine in patients with depression and healthy controls. However, it remains unclear whether chronic, nonmedical use of ketamine affects metabolites in the mPFC.

METHODS

Using proton magnetic resonance spectroscopy, we measured metabolites (glutamate and glutamine [Glx]; phosphocreatine and creatine [PCr+Cr]; myo-inositol; N-acetyl-aspartate; and glycerophosphocholine and phosphocholine [GPC+PC]) in the mPFC of chronic ketamine users (n = 20) and healthy controls (n = 43). Among ketamine users, 60% consumed ketamine once per day or more, 10% consumed it every 2 days and 30% consumed it every 3 or more days. Using analysis of covariance, we evaluated between-group differences in the ratios of Glx:PCr+Cr, myo-inositol:PCr+Cr, N-acetyl-aspartate:PCr+Cr and GPC+PC:PCr+Cr.

RESULTS

Chronic ketamine users showed significantly higher Glx:PCr+Cr ratios than healthy controls (median 1.05 v. 0.95, p = 0.008). We found no significant differences in myoinositol:PCr+Cr, N-acetyl-aspartate:PCr+Cr or GPC+PC:PCr+Cr ratios between the 2 groups. We found a positive relationship between N-acetyl-aspartate:PCr+Cr and Glx:PCr+Cr ratios in the healthy control group (R = 0.345, p = 0.023), but the ketamine use group failed to show such an association (ρ = 0.197, p = 0.40).

LIMITATIONS

The cross-sectional design of this study did not permit causal inferences related to higher Glx:PCr+Cr ratios and chronic ketamine use.

CONCLUSION

This study provides the first evidence that chronic ketamine users have higher glutamatergic activity in the mPFC than healthy controls; this finding may provide new insights relevant to the treatment of depression with ketamine.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting

Purpose

Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy.

Methods

Short echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm² at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal.

Results

The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum.

Conclusion

The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

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Magnetic Resonance Spectroscopy in Diagnosis and Follow-Up of Gliomas: State-of-the-Art

Preoperative grade prediction is important in diagnostics of glioma. Even more important can be follow-up after chemotherapy and radiotherapy of high grade gliomas. In this review we provide an overview of MR-spectroscopy (MRS), technical aspects, and different clinical scenarios in the diagnostics and follow-up of gliomas in pediatric and adult populations. Furthermore, we provide a recap of the current research utility and possible future strategies regarding proton- and phosphorous-MRS in glioma research.

Lactylation may be a Novel Posttranslational Modification in Inflammation in Neonatal Hypoxic-Ischemic Encephalopathy

Perinatal hypoxia-ischemia remains the most common cause of acute neonatal brain injury and is associated with a high death rate and long-term neurological abnormalities such as memory and cognitive deficits and dyskinesia. Hypoxia-ischemia triggers an inflammatory cascade in the brain that is amplified by the activation of immune cells and the influx of peripheral immune cells into the brain parenchyma in response to cellular injury. Thus, acute cerebral hypoxic-ischemic inflammation is a major contributor to the pathogenesis of newborn hypoxic-ischemic brain injury. Lactate is a glycolysis end product that can regulate inflammation through histone lactylation, a unique posttranslational modification that was identified in recent studies. The purpose of this review is to outline the recent improvements in our understanding of microglia-mediated hypoxic-ischemic inflammation and to further discuss how histone lactylation regulates inflammation by affecting macrophage activation. These findings may suggest that epigenetic reprogramming-associated lactate input is linked to disease outcomes such as acute neonatal brain injury pathogenesis and the therapeutic effects of drugs and other strategies in relieving neonatal hypoxic-ischemic brain injury. Therefore, improving our knowledge of the reciprocal relationships between histone lactylation and inflammation could lead to the development of new immunomodulatory therapies for brain damage in newborns.

The Distribution of Major Brain Metabolites in Normal Adults: Short Echo Time Whole-Brain MR Spectroscopic Imaging Findings

This prospective study aimed to evaluate the variation in magnetic resonance spectroscopic imaging (MRSI)-observed brain metabolite concentrations according to anatomical location, sex, and age, and the relationships among regional metabolite distributions, using short echo time (TE) whole-brain MRSI (WB-MRSI). Thirty-eight healthy participants underwent short TE WB-MRSI. The major metabolite ratios, i.e., N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, glutamate + glutamine (Glx)/Cr, and myoinositol (mI)/Cr, were calculated voxel-by-voxel. Their variations according to anatomical regions, sex, and age, and their relationship to each other were evaluated by using repeated-measures analysis of variance, t-tests, and Pearson’s product-moment correlation analyses. All four metabolite ratios exhibited widespread regional variation across the cerebral hemispheres (corrected p < 0.05). Laterality between the two sides and sex-related variation were also shown (p < 0.05). In several regions, NAA/Cr and Glx/Cr decreased and mI/Cr increased with age (corrected p < 0.05). There was a moderate positive correlation between NAA/Cr and mI/Cr in the insular lobe and thalamus and between Glx/Cr and mI/Cr in the parietal lobe (r ≥ 0.348, corrected p ≤ 0.025). These observations demand age- and sex- specific regional reference values in interpreting these metabolites, and they may facilitate the understanding of glial-neuronal interactions in maintaining homeostasis.

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

Effects of Moxa Cone Moxibustion Therapy on Cognitive Function and Brain Metabolic Changes in MCI Patients: A Pilot 1H-MRS Study

Objective

To explore the effect of moxa cone moxibustion on N-acetyl aspartate/total creatinine (NAA/tCr) and choline/total creatinine (Cho/tCr) in the bilateral hippocampus (HIP) and bilateral posterior cingulate gyrus (PCG) in patients with mild cognitive impairment (MCI) using hydrogen proton magnetic resonance spectroscopy (¹H-MRS) and to provide imaging basis for moxa cone moxibustion treatment for MCI.

Methods

One hundred eight patients with MCI were served as the MCI group, and 67 age-matched subjects were enrolled as the normal control group. The MCI group was randomized and allocated into acupoint group, drug group, and sham acupoint group, with 36 cases in each group. Some patients in each group withdrew. Finally, 25 cases were included in the acupoint group, 24 cases in the drug group, and 20 cases in the sham acupoint group. The drug group was treated with oral donepezil hydrochloride. The acupoint group and sham acupoint group received moxa cone moxibustion treatment. Mini-mental state exam (MMSE) and Montreal cognitive assessment (MoCA) scores were recorded before intervention, at the end of the first and the second months of intervention, and in the 5th month of follow-up. The NAA/tCr and Cho/tCr ratios in the HIP and PCG were bilaterally measured by ¹H-MRS before and after intervention.

Results

Before intervention, compared with the normal control group, the MMSE and MoCA scores, the Cho/tCr ratio in the right HIP, the NAA/tCr ratio in the bilateral HIP, and the NAA/tCr ratio in the left PCG in the three treatment groups decreased significantly (both p < 0.01), and the NAA/tCr ratio in the right PCG significantly reduced in the acupoint and drug groups (p < 0.05). After two months of treatment, compared with the normal control group, there were no differences in the MoCA scores, the NAA/tCr, and Cho/tCr ratios in the bilateral PCG and bilateral HIP in the three treatment groups (p > 0.05). However, the MMSE scores in the drug group decreased when compared with the acupoint group and normal control group (p < 0.05, p < 0.01). The scores of MMSE and MoCA in the acupoint group and sham acupoint group at all time points were better than those in the drug group, which were similar to those in the normal control group.

Conclusion

Our findings suggest that moxibustion could improve the cognitive function of patients with MCI. The mechanism may be related to the improvement of abnormal brain metabolism in HIP and PCG.

Astrocytic function is associated with both amyloid-β and tau pathology in non-demented APOE ε4 carriers

A growing body of evidence suggests that astrocytes play a major role in the pathophysiology of Alzheimer’s disease. Given that APOE is primarily expressed in astrocytes, these cells might be an important link between the APOE ε4 allele and development of Alzheimer’s disease pathology. Here, we investigate this hypothesis in vivo by measuring myo-Inositol, a metabolite involved in astrocytic functions, with magnetic resonance spectroscopy. Currently, there are conflicting evidence regarding the relationship between APOE ε4 and myo-Inositol concentration. Furthermore, data supporting a relationship between APOE ε4, myo-Inositol and Alzheimer’s disease pathology (amyloid-beta and tau proteins) in the preclinical stage of Alzheimer’s disease are limited. A previous study revealed differences in myo-Inositol levels between APOE ε4 carriers and noncarriers already in preclinical Alzheimer’s disease participant. However, other reports showed no impact of APOE genotype on the association between myo-Inositol and rate of amyloid-beta accumulation. In the present study we determined the effect of APOE genotype on the association between myo-Inositol and both amyloid-β and tau deposition quantified by PET in 428 cognitively unimpaired elderly and patients with mild cognitive impairment from the Swedish BioFINDER-2 cohort.

APOE genotype impacted the associations between myo-Inositol and amyloid-β pathology as revealed by an interaction effect between APOE genotype and levels of myo-inositol (p &lt; 0.001) such that higher myo-Inositol concentration was related to more amyloid-beta pathology in APOE ε4 carriers only. A similar interaction effect was also found when investigating the effect of APOE on the association between myo-inositol and tau pathology (p &lt; 0.01). Focusing on the APOE ε4 subsample, myo-Inositol partially (17%) mediated the association between amyloid-beta and tau pathology (p &lt; 0.05). Further, in a subgroup of participants with available plasma levels of glial fibrillary acidic protein, a marker of astroglial activation and astrocytosis, we found that glial fibrillary acidic protein correlated with myo-inositol only in APOE e4 carriers (APOE ε4 carriers: p &lt; 0.01; APOE ε4 non carriers: p &gt; 0.8), suggesting that myo-Inosotol might reflect an aspect of the astrocytic involvement in Alzheimer’s pathology which is specific to the impact of APOE ε4. Therefore, we suggest that myo-Inositol is a candidate in vivo marker to study the impact of APOE ε4 on the interplay between astrocytes and the pathophysiology of Alzheimer’s disease.

Cerebellar Abnormalities on Proton MR Spectroscopy and Imaging in Patients With Gluten Ataxia: A Pilot Study

Gluten ataxia is a rare immune-mediated neurological disorder caused by the ingestion of gluten. The diagnosis is not straightforward as antibodies are present in only up to 38% of patients, but often at lower titers. The symptoms of ataxia may be mild at the onset but lead to permanent damage if remain untreated. It is characterized by damage to the cerebellum however, the pathophysiology of the disease is not clearly understood. The present study investigated the neurochemical profile of vermis and right cerebellum and structural changes in various brain regions of patients with gluten ataxia (n = 6, age range 40-65 years) and compared it with healthy controls (n = 10, 40-55 years). Volumetric 3-D T1 and T1-weighted magnetic resonance imaging (MRI) in the three planes (axial, coronal, and sagittal) of the whole brain and single-voxel 1H- magnetic resonance spectroscopy (MRS) of the vermis and right cerebellum were acquired on 3 T human MR scanner. The metabolite concentrations were estimated using LC Model (6.1-4A) while brain volumes were estimated using the online tool volBrain pipeline and CERES and corrected for partial volumes. The levels of neuro-metabolites (N-acetyl aspartate + N-acetyl aspartate glutamate, glycerophosphocholine + phosphocholine, and total creatine) were found to be significantly lower in vermis, while N-acetyl aspartate + N-acetyl aspartate glutamate and glycerophosphocholine + phosphocholine was lower in cerebellum regions in the patients with gluten ataxia compared to healthy controls. A significant reduction in the white matter of (total brain, cerebellum, and cerebrum); reduction in the volumes of cerebellum lobe (X) and thalamus while lateral ventricles were increased in the patients with gluten ataxia compared to healthy controls. The reduced neuronal metabolites along with structural changes in the brain suggested neuronal degeneration in the patients with gluten ataxia. Our preliminary findings may be useful in understanding the gluten-induced cerebral damage and indicated that MRI and MRS may serve as a non-invasive useful tool in the early diagnosis, thereby enabling better management of these patients.

Neuroplasticity of Glioma Patients: Brain Structure and Topological Network

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.

Neurochemical Alterations in Social Anxiety Disorder (SAD): A Systematic Review of Proton Magnetic Resonance Spectroscopic Studies

(1) Objective: Considering that current knowledge of mechanisms involved in the molecular pathogenesis of Social Anxiety Disorder (SAD) is limited, we conducted a systematic review to evaluate cumulative data obtained by Proton Magnetic Resonance Spectroscopic (¹H MRS) studies. (2) Methods: A computer-based literature search of Medline, EMBASE, PsycInfo, and ProQuest was performed. Only cross-sectional studies using ¹H MRS techniques in participants with SAD and healthy controls (HCs) were selected. (3) Results: The search generated eight studies. The results indicated regional abnormalities in the ‘fear neurocircuitry’ in patients with SAD. The implicated regions included the anterior cingulate cortex (ACC), dorsomedial prefrontal cortex (dmPFC), dorsolateral prefrontal cortex (dlPFC), insula, occipital cortex (OC), as well as the subcortical regions, including the thalamus, caudate, and the putamen. (4) Conclusions: The evidence derived from eight studies suggests that possible pathophysiological mechanisms of SAD include impairments in the integrity and function of neurons and glial cells, including disturbances in energy metabolism, maintenance of phospholipid membranes, dysregulations of second messenger systems, and excitatory/inhibitory neurocircuitry. Conducting more cross-sectional studies with larger sample sizes is warranted given the limited evidence in this area of research.

In Vivo Renal Lipid Quantification by Accelerated Magnetic Resonance Spectroscopic Imaging at 3T: Feasibility and Reliability Study

A reliable and practical renal-lipid quantification and imaging method is needed. Here, the feasibility of an accelerated MRSI method to map renal fat fractions (FF) at 3T and its repeatability were investigated. A 2D density-weighted concentric-ring-trajectory MRSI was used for accelerating the acquisition of 48 × 48 voxels (each of 0.25 mL spatial resolution) without respiratory navigation implementations. The data were collected over 512 complex-FID timepoints with a 1250 Hz spectral bandwidth. The MRSI sequence was designed with a metabolite-cycling technique for lipid–water separation. The in vivo repeatability performance of the sequence was assessed by conducting a test–reposition–retest study within healthy subjects. The coefficient of variation (CV) in the estimated FF from the test–retest measurements showed a high degree of repeatability of MRSI-FF (CV = 4.3 ± 2.5%). Additionally, the matching level of the spectral signature within the same anatomical region was also investigated, and their intrasubject repeatability was also high, with a small standard deviation (8.1 ± 6.4%). The MRSI acquisition duration was ~3 min only. The proposed MRSI technique can be a reliable technique to quantify and map renal metabolites within a clinically acceptable scan time at 3T that supports the future application of this technique for the non-invasive characterization of heterogeneous renal diseases and tumors.

Ultra-High-Field MRI in the Diagnosis and Management of Gliomas: A Systematic Review

Importance:

Gliomas, tumors of the central nervous system, are classically diagnosed through invasive surgical biopsy and subsequent histopathological study. Innovations in ultra-high field (UHF) imaging, namely 7-Tesla magnetic resonance imaging (7T MRI) are advancing preoperative tumor grading, visualization of intratumoral structures, and appreciation of small brain structures and lesions.

Objective

Summarize current innovative uses of UHF imaging techniques in glioma diagnostics and treatment.

Methods

A systematic review in accordance with PRISMA guidelines was performed utilizing PubMed. Case reports and series, observational clinical trials, and randomized clinical trials written in English were included. After removing unrelated studies and those with non-human subjects, only those related to 7T MRI were independently reviewed and summarized for data extraction. Some preclinical animal models are briefly described to demonstrate future usages of ultra-high-field imaging.

Results

We reviewed 46 studies (43 human and 3 animal models) which reported clinical usages of UHF MRI in the diagnosis and management of gliomas. Current literature generally supports greater resolution imaging from 7T compared to 1.5T or 3T MRI, improving visualization of cerebral microbleeds and white and gray matter, and providing more precise localization for radiotherapy targeting. Additionally, studies found that diffusion or susceptibility-weighted imaging techniques applied to 7T MRI, may be used to predict tumor grade, reveal intratumoral structures such as neovasculature and microstructures like axons, and indicate isocitrate dehydrogenase 1 mutation status in preoperative imaging. Similarly, newer imaging techniques such as magnetic resonance spectroscopy and chemical exchange saturation transfer imaging can be performed on 7T MRI to predict tumor grading and treatment efficacy. Geometrical distortion, a known challenge of 7T MRI, was at a tolerable level in all included studies.

Conclusion

UHF imaging has the potential to preoperatively and non-invasively grade gliomas, provide precise therapy target areas, and visualize lesions not seen on conventional MRI.

Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review

Degenerative spinal cord compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical spinal cord compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, and magnetic resonance spectroscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients consistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels, caused by demyelination and axonal injury, MT and 1H-MRS, along with advanced and tract-specific diffusion MRI, recently revealed microstructural alterations, also rostrally pointing to Wallerian degeneration. Recent studies also disclosed a significant relationship between microstructural damage and functional deficits, as assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI, in combination with electrophysiology, critically extends our understanding of the underlying pathophysiology of degenerative spinal cord compression and may provide predictive markers of DCM development for accurate patient management. However, the prognostic value must be validated in longitudinal studies.

Does Prefrontal Glutamate Index Cognitive Changes in Parkinson's Disease?

Introduction

Cognitive impairment is a highly prevalent non-motor feature of Parkinson's disease (PD). A better understanding of the underlying pathophysiology may help in identifying therapeutic targets to prevent or treat dementia. This study sought to identify metabolic alterations in the prefrontal cortex (PFC), a key region for cognitive functioning that has been implicated in cognitive dysfunction in PD.

Methods

Proton Magnetic Resonance Spectroscopy was used to investigate metabolic changes in the PFC of a cohort of cognitively normal individuals without PD (CTL), as well as PD participants with either normal cognition (PD-NC), mild cognitive impairment (PD-MCI), or dementia (PDD). Ratios to Creatine (Cre) resonance were obtained for glutamate (Glu), glutamine and glutamate combined (Glx), N-acetylaspartate (NAA), myoinositol (mI), and total choline (Cho), and correlated with cognitive scores across multiple domains (executive function, learning and memory, language, attention, visuospatial function, and global cognition) administered to the PD participants only.

Results

When individuals retain cognitive capabilities, the presence of Parkinson's disease does not create metabolic disturbances in the PFC. However, when cognitive symptoms are present, PFC Glu/Cre ratios decrease with significant differences between the PD-NC and PPD groups. In addition, Glu/Cre ratios and memory scores were marginally associated, but not after Bonferroni correction.

Conclusion

These preliminary findings indicate that fluctuations in prefrontal glutamate may constitute a biomarker for the progression of cognitive impairments in PD. We caution for larger MRS investigations of carefully defined PD groups.

1H MR spectroscopy biomarkers of neuronal and synaptic function are associated with tau deposition in cognitively unimpaired older adults

Proton magnetic resonance spectroscopy (1H MRS) may provide information on pathophysiological changes associated with tau deposition in cognitively unimpaired older adults. In this study, the associations of posterior cingulate gyrus tau and amyloid beta (Aβ) deposition on PET with 1H MRS metabolite ratios acquired from bilateral posterior cingulate gyri were investigated in cognitively unimpaired older adults. Participants (n = 40) from the Mayo Clinic Study of Aging underwent single-voxel sLASER 1H MRS from the posterior cingulate gyrus at 3 Tesla, 18F-flortaucipir, and 11C- Pittsburgh Compound B (PiB) PET. An increase in posterior cingulate gyrus tau deposition, but not elevated Aβ, was associated with lower N-acetylaspartate/total creatine (tCr) and glutamate (Glu)/tCr ratios, and sex by tau interaction was observed in association with Glu/tCr. Higher tau levels in cognitively unimpaired older adults are associated with biomarkers of neural and synaptic injury even in the absence of cognitive impairment and these relationships appear to be stronger in women than in men.

Glutamic Acid and Total Creatine as Predictive Markers for Epilepsy in Glioblastoma by Using Magnetic Resonance Spectroscopy Before Surgery

OBJECTIVE

Epilepsy in glioblastoma patients significantly reduces their quality of life; however, little is known about the association between predicting epilepsy and metabolites in tumors. In this study, we used 3.0-T magnetic resonance imaging and ¹H-magnetic resonance spectroscopy (MRS) to quantify metabolite concentrations in patients with varying epilepsy histories.

METHODS

Fifty-one patients with glioblastoma underwent pretreatment 3.0-T MRI/¹H-MRS scanning. Single-voxel (1.5 cm³) MRS, in an enhanced lesion, was acquired using a double-echo point-resolved spectroscopic sequence with chemical-shift selective water suppression. MRS data were quantified with linear combination model (LC-Model) software. We compared the MRS data between groups with and without epilepsy during the postoperative course (EP).

RESULTS

The ratios of glutamate (Glu) and glutamate + glutamine (Glx) to total creatine (Glu/tCr and Glx/tCr) in the tumor were associated with epilepsy history. The receiver operating characteristic curve analysis showed that a Glu/tCr value of 1.81 was 70% sensitive and 90% specific for the prediction of EP (area under curve: 0.82). In the analysis excluding patients with preoperative epilepsy, a Glu/tCr value of 1.81 was 75% sensitive and 88% specific for the prediction (area under curve: 0.87).

CONCLUSIONS

Intratumoral metabolite concentrations measured using pretreatment 3.0-T MRI/¹H-MRS changed characteristically in the group with EP. Our study suggests that the Glu/tCr ratio in tumors has adequate reliability in predicting EP. Pretreatment MRS is a minimally invasive and simple procedure that can provide useful information on glioblastoma patients.

Identifying the source of spurious signals caused by B0 inhomogeneities in single-voxel 1 H MRS

Purpose

Single‐voxel MRS (SV MRS) requires robust volume localization as well as optimized crusher and phase‐cycling schemes to reduce artifacts arising from signal outside the volume of interest. However, due to local magnetic field gradients (B₀ inhomogeneities), signal that was dephased by the crusher gradients during acquisition might rephase, leading to artifacts in the spectrum. Here, we analyzed this mechanism, aiming to identify the source of signals arising from unwanted coherence pathways (spurious signals) in SV MRS from a B₀ map.

Methods

We investigated all possible coherence pathways associated with imperfect localization in a semi‐localized by adiabatic selective refocusing (semi‐LASER) sequence for potential rephasing of signals arising from unwanted coherence pathways by a local magnetic field gradient. We searched for locations in the B₀ map where the signal dephasing due to external (crusher) and internal (B₀) field gradients canceled out. To confirm the mechanism, SV‐MR spectra (TE = 31 ms) and 3D‐CSI data with the same volume localization as the SV experiments were acquired from a phantom and 2 healthy volunteers.

Results

Our analysis revealed that potential sources of spurious signals were scattered over multiple locations throughout the brain. This was confirmed by 3D‐CSI data. Moreover, we showed that the number of potential locations where spurious signals could originate from monotonically decreases with crusher strength.

Conclusion

We proposed a method to identify the source of spurious signals in SV ¹H MRS using a B₀ map. This can facilitate MRS sequence design to be less sensitive to experimental artifacts.

New Insight in Hyperinsulinism/Hyperammonemia Syndrome by Magnetic Resonance Imaging and Spectroscopy

Hyperinsulinism/hyperammonemia syndrome (HI/HA) is an autosomal dominant disorder caused by monoallelic activating mutations in the glutamate dehydrogenase 1 (GLUD1) gene. While hyperinsulinism may be explained by a reduction in the allosteric inhibition of GLUD1, the pathogenesis of HA in HI/HA remains uncertain; interestingly, HA in the HI/HA syndrome is not associated with acute hyperammonemic intoxication events. We obtained a brain magnetic resonance (MR) in a woman with HI/HA syndrome with chronic asymptomatic HA. On MR spectroscopy, choline and myoinositol were decreased as in other HA disorders. In contrast, distinct from other HA disorders, combined glutamate and glutamine levels were normal (not increased). This observation suggests that brain biochemistry in HI/HA may differ from that of other HA disorders. In HI/HA, ammonia overproduction may come to the expense of glutamate levels, and this seems to prevent the condensation of ammonia with glutamate to produce glutamine that is typical of the other HA disorders. The absence of combined glutamate and glutamine elevation might be correlated to the absence of acute cerebral ammonia toxicity.

1H-MR spectroscopy in grading of cerebral glioma: A new view point, MRS image quality assessment

Background

Noninvasive preoperative prediction of histological grading is essential for clinical management of cerebral glioma.

Purpose

This study aimed to investigate the association between the image quality assessment of 1H magnetic resonance spectroscopy and accurate grading of glioma.

Materials and Methods

98 glioma patients confirmed by pathology were retrospectively recruited in this single-center study. All patients underwent 1H-MRS examination at 3.0T before surgery. According to WHO standards, all cases were divided into two groups: low-grade glioma (grade I and II, 48 cases) and high-grade glioma (grades III and IV, 50 cases). The metabolite ratios in both grades were calculated before and after image quality assessment. The area under the receiver operating characteristic (ROC) curve was used to evaluate the capacity of each ratio in glioma grading.

Results

The Cho/Cr, Cho/NAA and NAA/Cr metabolite ratios had certain differences in each glioma group before and after MRS image quality assessment. In the low-grade glioma group, there was a dramatic difference in the Cho/Cr ratio before and after image quality assessment (p = 0.011). After MRS image quality assessment, the accuracy of glioma grading was significantly improved. The Cho/Cr ratio with 83.3% sensitivity and 93.7% specificity is the best index of glioma grading, with the optimal cutoff value of the Cho/Cr ratio being 3.72.

Conclusion

The image quality of MRS does affect the metabolite ratios and the results of glioma grading. MRS image quality assessment can observably improve the accuracy rate of glioma grading. The Cho/Cr ratio has the best diagnostic performance in differentiating high-grade from low-grade glioma.

In vivo Human MR Spectroscopy Using a Clinical Scanner: Development, Applications, and Future Prospects

MR spectroscopy (MRS) is a unique and useful method for noninvasively evaluating biochemical metabolism in human organs and tissues, but its clinical dissemination has been slow and often limited to specialized institutions or hospitals with experts in MRS technology. The number of 3-T clinical MR scanners is now increasing, representing a major opportunity to promote the use of clinical MRS. In this review, we summarize the theoretical background and basic knowledge required to understand the results obtained with MRS and introduce the general consensus on the clinical utility of proton MRS in routine clinical practice. In addition, we present updates to the consensus guidelines on proton MRS published by the members of a working committee of the Japan Society of Magnetic Resonance in Medicine in 2013. Recent research into multinuclear MRS equipped in clinical MR scanners is explained with an eye toward future development. This article seeks to provide an overview of the current status of clinical MRS and to promote the understanding of when it can be useful. In the coming years, MRS-mediated biochemical evaluation is expected to become available for even routine clinical practice.

The potential of advanced MR techniques for precision radiotherapy of glioblastoma

As microscopic tumour infiltration of glioblastomas is not visible on conventional magnetic resonance (MR) imaging, an isotropic expansion of 1-2 cm around the visible tumour is applied to define the clinical target volume for radiotherapy. An opportunity to visualize microscopic infiltration arises with advanced MR imaging. In this review, various advanced MR biomarkers are explored that could improve target volume delineation for radiotherapy of glioblastomas. Various physiological processes in glioblastomas can be visualized with different advanced MR techniques. Combining maps of oxygen metabolism (CMRO₂), relative cerebral blood volume (rCBV), vessel size imaging (VSI), and apparent diffusion coefficient (ADC) or amide proton transfer (APT) can provide early information on tumour infiltration and high-risk regions of future recurrence. Oxygen consumption is increased 6 months prior to tumour progression being visible on conventional MR imaging. However, presence of the Warburg effect, marking a switch from an infiltrative to a proliferative phenotype, could result in CMRO₂ to appear unaltered in high-risk regions. Including information on biomarkers representing angiogenesis (rCBV and VSI) and hypercellularity (ADC) or protein concentration (APT) can omit misinterpretation due to the Warburg effect. Future research should evaluate these biomarkers in radiotherapy planning to explore the potential of advanced MR techniques to personalize target volume delineation with the aim to improve local tumour control and/or reduce radiation-induced toxicity.

Plug-and-play advanced magnetic resonance spectroscopy

PURPOSE

Advanced MRS protocols improve data quality and reproducibility relative to vendor-provided protocols; however, they are challenging to incorporate into the clinical workflow and require local MRS expertise for successful implementation. Here, we developed an automated advanced MRS acquisition protocol at 3T to facilitate acquisition of high-quality spectroscopic data without local MRS expertise.

METHODS

First, a B₀ shimming protocol was selected for automation by comparing 3 widely used B₀ algorithms (2 vendor protocols and FAST(EST)MAP). Next, voxel-based B₀ and B₁ calibrations were incorporated into the consensus-recommended semi-LASER sequence and combined with an automated VOI prescription tool, a recently developed method for automated voxel prescription. The efficiency of collecting single-voxel data from a clinical cohort (N = 40) with the automated protocol (calibration time and fraction of usable datasets) was compared with the nonautomated semi-LASER protocol (N = 35) whereby all prescan calibrations were executed manually in the academic hospital setting with rotating MR technologists in the neuroradiology unit.

RESULTS

A multi-iteration FAST(EST)MAP protocol resulted in narrower water linewidths than vendor's B₀ shim protocols for data acquired from 6 brain locations (p < 1e-5) and was selected for automation. The automated B₀ and B₁ calibrations resulted in a time saving of ~4.5 minutes per voxel relative to the same advanced protocol executed manually. All spectra acquired with the automated protocol were usable, whereas only 86% of those collected with the manual protocol were usable and spectral quality was more variable.

CONCLUSION

The plug-and-play advanced MRS protocol allows automated acquisition of high-quality MRS data with high success rate and consistency on a clinical 3T platform.

Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review

Background: Glioblastoma is the most frequent malignant primitive brain tumor in adults. The treatment includes surgery, radiotherapy, and chemotherapy. During follow-up, combined chemoradiotherapy can induce treatment-related changes mimicking tumor progression on medical imaging, such as pseudoprogression (PsP). Differentiating PsP from true progression (TP) remains a challenge for radiologists and oncologists, who need to promptly start a second-line treatment in the case of TP. Advanced magnetic resonance imaging (MRI) techniques such as diffusion-weighted imaging, perfusion MRI, and proton magnetic resonance spectroscopic imaging are more efficient than conventional MRI in differentiating PsP from TP. None of these techniques are fully effective, but current advances in computer science and the advent of artificial intelligence are opening up new possibilities in the imaging field with radiomics (i.e., extraction of a large number of quantitative MRI features describing tumor density, texture, and geometry). These features are used to build predictive models for diagnosis, prognosis, and therapeutic response. Method: Out of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, we screened 574 papers. A total of 228 were eligible, and we analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis.

Magnetic Resonance Imaging in Tauopathy Animal Models

The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer's disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.

Expert consensus on the clinical practice of neonatal brain magnetic resonance imaging

In recent years, magnetic resonance imaging (MRI) has been widely used in evaluating neonatal brain development, diagnosing neonatal brain injury, and predicting neurodevelopmental prognosis. Based on current research evidence and clinical experience in China and overseas, the Neonatologist Society of Chinese Medical Doctor Association has developed a consensus on the indications and standardized clinical process of neonatal brain MRI. The consensus has the following main points. (1) Brain MRI should be performed for neonates suspected of hypoxic-ischemic encephalopathy, intracranial infection, stroke and unexplained convulsions; brain MRI is not considered a routine in the management of preterm infants, but it should be performed for further evaluation when cranial ultrasound finds evidence of brain injury; as for extremely preterm or extremely low birth weight infants without abnormal ultrasound findings, it is recommended that they should undergo MRI examination at term equivalent age once. (2) Neonates should undergo MRI examination in a non-sedated state if possible. (3) During MRI examination, vital signs should be closely monitored to ensure safety; the necessity of MRI examination should be strictly evaluated for critically ill neonates, and magnetic resonance compatible incubator and ventilator can be used. (4) At present, 1.5 T or 3.0 T equipment can be used for neonatal brain MRI examination, and the special coil for the neonatal head should be used to improve signal-to-noise ratio; routine neonatal brain MRI sequences should at least include axial T1 weighted image (T1WI), axial T2 weighted imaging (T2WI), diffusion-weighted imaging, and sagittal T1WI or T2WI. (5) It is recommended to use a structured and graded reporting system, and reports by at least two reviewers and multi-center collaboration are recommended to increase the reliability of the report.

Evidence for distinct neuro-metabolic phenotypes in humans

Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however, remains largely unexplored - despite the potential for the discovery of novel behavioural and disease phenotypes. In this study, we measured 14 metabolite levels, normalised as ratios to total-creatine, with ¹H magnetic resonance spectroscopy (MRS) acquired from the bilateral anterior cingulate cortices of six healthy participants, repeatedly over a period of four months. ANOVA tests revealed statistically significant differences of 3 metabolites and 3 commonly used combinations (total-choline, glutamate + glutamine and total-N-acetylaspartate) between the participants, with scyllo-inositol (F=85, p=6e-26) and total-choline (F=39, p=1e-17) having the greatest discriminatory power. This was not attributable to structural differences. When predicting individuals from the repeated MRS measurements, a leave-one-out classification accuracy of 88% was achieved using a support vector machine based on scyllo-inositol and total-choline levels. Accuracy increased to 98% with the addition of total-N-acetylaspartate and myo-inositol - demonstrating the efficacy of combining MRS with machine learning and metabolomic methodology. These results provide evidence for the existence of neuro-metabolic phenotypes, which may be non-invasively measured using widely available 3 Tesla MRS. Establishing these phenotypes in a larger cohort and investigating their connection to brain health and function presents an important area for future study.

Mapping an Extended Metabolic Profile of Gliomas Using High-Resolution 31P MRSI at 7T

Phosphorus magnetic resonance spectroscopic imaging (³¹P MRSI) is of particular interest for investigations of patients with brain tumors as it enables to non-invasively assess altered energy and phospholipid metabolism in vivo. However, the limited sensitivity of ³¹P MRSI hampers its broader application at clinical field strengths. This study aimed to identify the additional value of ³¹P MRSI in patients with glioma at ultra-high B₀ = 7T, where the increase in signal-to-noise ratio may foster its applicability for clinical research. High-quality, 3D ³¹P MRSI datasets with an effective voxel size of 5.7 ml were acquired from the brains of seven patients with newly diagnosed glioma. An optimized quantification model was implemented to reliably extract an extended metabolic profile, including low-concentrated metabolites such as extracellular inorganic phosphate, nicotinamide adenine dinucleotide [NAD(H)], and uridine diphosphoglucose (UDPG), which may act as novel tumor markers; a background signal was extracted as well, which affected measures of phosphomonoesters beneficially. Application of this model to the MRSI datasets yielded high-resolution maps of 12 different ³¹P metabolites, showing clear metabolic differences between white matter (WM) and gray matter, and between healthy and tumor tissues. Moreover, differences between tumor compartments in patients with high-grade glioma (HGG), i.e., gadolinium contrast-enhancing/necrotic regions (C+N) and peritumoral edema, could also be suggested from these maps. In the group of patients with HGG, the most significant changes in metabolite intensities were observed in C+N compared to WM, i.e., for phosphocholine +340%, UDPG +54%, glycerophosphoethanolamine −45%, and adenosine-5′-triphosphate −29%. Furthermore, a prominent signal from mobile phospholipids appeared in C+N. In the group of patients with low-grade glioma, only the NAD(H) intensity changed significantly by −28% in the tumor compared to WM. Besides the potential of ³¹P MRSI at 7T to provide novel insights into the biochemistry of gliomas in vivo, the attainable spatial resolutions improve the interpretability of ³¹P metabolite intensities obtained from malignant tissues, particularly when only subtle differences compared to healthy tissues are expected. In conclusion, this pilot study demonstrates that ³¹P MRSI at 7T has potential value for the clinical research of glioma.

Magnetic resonance spectroscopic imaging for detecting metabolic changes in glioblastoma after anti-angiogenic therapy—a systematic literature review

Background

The impact of anti-angiogenic therapy (AAT) on patients with glioblastoma (GBM) is unclear due to a disconnect between radiographic findings and overall survivorship. MR spectroscopy (MRS) can provide clinically relevant information regarding tumor metabolism in response to AAT. This review explores the use of MRS to track metabolic changes in patients with GBM treated with AAT.

Methods

We conducted a systematic literature review in accordance with PRISMA guidelines to identify primary research articles that reported metabolic changes in GBMs treated with AAT. Collected variables included single or multi-voxel MRS acquisition parameters, metabolic markers, reported metabolic changes in response to AAT, and survivorship data.

Results

Thirty-five articles were retrieved in the initial query. After applying inclusion and exclusion criteria, 11 studies with 262 patients were included for qualitative synthesis with all studies performed using multi-voxel 1H MRS. Two studies utilized 31P MRS. Post-AAT initiation, shorter-term survivors had increased choline (cellular proliferation marker), increased lactate (a hypoxia marker), and decreased levels of the short echo time (TE) marker, myo-inositol (an osmoregulator and gliosis marker). MRS detected metabolic changes as soon as 1-day after AAT, and throughout the course of AAT, to predict survival. There was substantial heterogeneity in the timing of scans, which ranged from 1-day to 6–9 months after AAT initiation.

Conclusions

Multi-voxel MRS at intermediate and short TE can serve as a robust prognosticator of outcomes of patients with GBM who are treated with AAT.

Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI

There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian ¹ H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D ¹ H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.

Glutamine Imaging: A New Avenue for Glioma Management

The glutamine pathway is emerging as an important marker of cancer prognosis and a target for new treatments. In gliomas, the most common type of brain tumors, metabolic reprogramming leads to abnormal consumption of glutamine as an energy source, and increased glutamine concentrations are associated with treatment resistance and proliferation. A key challenge in the development of glutamine-based biomarkers and therapies is the limited number of in vivo tools to noninvasively assess local glutamine metabolism and monitor its changes. In this review, we describe the importance of glutamine metabolism in gliomas and review the current landscape of translational and emerging imaging techniques to measure glutamine in the brain. These techniques include MRS, PET, SPECT, and preclinical methods such as fluorescence and mass spectrometry imaging. Finally, we discuss the roadblocks that must be overcome before incorporating glutamine into a personalized approach for glioma management.