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

Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases

Among the most critical health issues, brain illnesses, such as neurodegenerative conditions and tumors, lower quality of life and have a significant economic impact. Implantable technology and nano-drug carriers have enormous promise for cerebral brain activity sensing and regulated therapeutic application in the treatment and detection of brain illnesses. Flexible materials are chosen for implantable devices because they help reduce biomechanical mismatch between the implanted device and brain tissue. Additionally, implanted biodegradable devices might lessen any autoimmune negative effects. The onerous subsequent operation for removing the implanted device is further lessened with biodegradability. This review expands on current developments in diagnostic technologies such as magnetic resonance imaging, computed tomography, mass spectroscopy, infrared spectroscopy, angiography, and electroencephalogram while providing an overview of prevalent brain diseases. As far as we are aware, there hasn't been a single review article that addresses all the prevalent brain illnesses. The reviewer also looks into the prospects for the future and offers suggestions for the direction of future developments in the treatment of brain diseases.

Insights Into the Metabolic Aspects of Aortic Stenosis With the Use of Magnetic Resonance Imaging

Pressure overload in aortic stenosis (AS) encompasses both structural and metabolic remodeling and increases the risk of decompensation into heart failure. A major component of metabolic derangement in AS is abnormal cardiac substrate use, with down-regulation of fatty acid oxidation, increased reliance on glucose metabolism, and subsequent myocardial lipid accumulation. These changes are associated with energetic and functional cardiac impairment in AS and can be assessed with the use of cardiac magnetic resonance spectroscopy (MRS). Proton MRS allows the assessment of myocardial triglyceride content and creatine concentration. Phosphorous MRS allows noninvasive in vivo quantification of the phosphocreatine-to-adenosine triphosphate ratio, a measure of cardiac energy status that is reduced in patients with severe AS. This review summarizes the changes to cardiac substrate and high-energy phosphorous metabolism and how they affect cardiac function in AS. The authors focus on the role of MRS to assess these metabolic changes, and potentially guide future (cellular) metabolic therapy in AS.

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.

Neurometabolic timecourse of healthy aging

PURPOSE

The neurometabolic timecourse of healthy aging is not well-established, in part due to diversity of quantification methodology. In this study, a large structured cross-sectional cohort of male and female subjects throughout adulthood was recruited to investigate neurometabolic changes as a function of age, using consensus-recommended magnetic resonance spectroscopy quantification methods.

METHODS

102 healthy volunteers, with approximately equal numbers of male and female participants in each decade of age from the 20s, 30s, 40s, 50s, and 60s, were recruited with IRB approval. MR spectroscopic data were acquired on a 3T MRI scanner. Metabolite spectra were acquired using PRESS localization (TE=30 ms; 96 transients) in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Water-suppressed spectra were modeled using the Osprey algorithm, employing a basis set of 18 simulated metabolite basis functions and a cohort-mean measured macromolecular spectrum. Pearson correlations were conducted to assess relationships between metabolite concentrations and age for each voxel; Spearman correlations were conducted where metabolite distributions were non-normal. Paired t-tests were run to determine whether metabolite concentrations differed between the PCC and CSO. Finally, robust linear regressions were conducted to assess both age and sex as predictors of metabolite concentrations in the PCC and CSO and separately, to assess age, signal-noise ratio, and full width half maximum (FWHM) linewidth as predictors of metabolite concentrations.

RESULTS

Data from four voxels were excluded (2 ethanol; 2 unacceptably large lipid signal). Statistically-significant age*metabolite Pearson correlations were observed for tCho (r(98)=0.33, p<0.001), tCr (r(98)=0.60, p<0.001), and mI (r(98)=0.32, p=0.001) in the CSO and for NAAG (r(98)=0.26, p=0.008), tCho(r(98)=0.33, p<0.001), tCr (r(98)=0.39, p<0.001), and Gln (r(98)=0.21, p=0.034) in the PCC. Spearman correlations for non-normal variables revealed a statistically significant correlation between sI and age in the CSO (r(86)=0.26, p=0.013). No significant correlations were seen between age and tNAA, NAA, Glx, Glu, GSH, PE, Lac, or Asp in either region (all p>0.20). Age associations for tCho, tCr, mI and sI in the CSO and for NAAG, tCho, and tCr in the PCC remained when controlling for sex in robust regressions. CSO NAAG and Asp, as well as PCC tNAA, sI, and Lac were higher in women; PCC Gln was higher in men. When including an age*sex interaction term in robust regression models, a significant age*sex interaction was seen for tCho (F(1,96)=11.53, p=0.001) and GSH (F(1,96)=7.15, p=0.009) in the CSO and tCho (F(1,96)=9.17, p=0.003), tCr (F(1,96)=9.59, p=0.003), mI (F(1,96)=6.48, p=0.012), and Lac (F(1,78)=6.50, p=0.016) in the PCC. In all significant interactions, metabolite levels increased with age in females, but not males. There was a significant positive correlation between linewidth and age. Age relationships with tCho, tCr, and mI in the CSO and tCho, tCr, mI, and sI in the PCC were significant after controlling for linewidth and FWHM in robust regressions.

CONCLUSION

The primary (correlation) results indicated age relationships for tCho, tCr, mI, and sI in the CSO and for NAAG, tCho, tCr, and Gln in the PCC, while no age correlations were found for tNAA, NAA, Glx, Glu, GSH, PE, Lac, or Asp in either region. Our results provide a normative foundation for future work investigating the neurometabolic time course of healthy aging using MRS.

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.

Short symmetric and highly selective asymmetric first and second order gradient modulated offset independent adiabaticity (GOIA) pulses for applications in clinical MRS and MRSI

Gradient modulated RF pulses, especially gradient offset independent adiabaticity (GOIA) pulses, are increasingly gaining attention for high field clinical magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) due to the lower peak B₁ amplitude and associated power demands achievable relative to its non-modulated adiabatic full passage counterparts. In this work we describe the development of two GOIA RF pulses: 1) A power efficient, 3.0 ms wideband uniform rate with smooth truncation (WURST) modulated RF pulse with 15 kHz bandwidth compatible with a clinically feasible peak B₁ amplitude of 0.87 kHz (or 20 µT), and 2) A highly selective asymmetric 6.66 ms RF pulse with 20 kHz bandwidth designed to achieve a single-sided, fractional transition width of only 1.7%. Effects of potential asynchrony between RF and gradient-modulated (GM) waveforms for 3 ms GOIA-WURST RF pulses was evaluated by simulation and experimentally. Results demonstrate that a 20+ µs asynchrony between RF and GM functions substantially degrades inversion performance when using large RF offsets to achieve translation. A projection-based method is presented that allows a quick calibration of RF and GM asynchrony on pre-clinical/clinical MR systems. The asymmetric GOIA pulse was implemented within a multi-pulse OVS sequence to achieve power efficient, highly-selective, and B₁ and T₁-independent signal suppression for extracranial lipid suppression. The developed GOIA pulses were utilized with linear gradient modulation (X, Y, Z gradient fields), and with second-order-field modulations (Z2, X2Y2 gradient fields) to provide elliptically-shaped regions-of-interest for MRS and MRSI acquisitions. Both described GOIA-RF pulses have substantial clinical value; specifically, the 3.0 ms GOIA-WURST pulse is beneficial to realize short TE sLASER localized proton MRS/MRSI sequences, and the asymmetric GOIA RF pulse has applications in highly selective outer volume signal suppression to allow interrogation of tissue proximal to extracranial lipids with full-intensity.

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

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

Magnetic resonance spectroscopy of traumatic brain injury and subconcussive hits: A systematic review and meta-analysis

Magnetic resonance spectroscopy (MRS) is a non-invasive technique used to study metabolites in the brain. MRS findings in traumatic brain injury (TBI) and subconcussive hit literature have been mixed. The most common observation is a decrease in N-acetyl-aspartate (NAA), traditionally considered a marker of neuronal integrity. Other metabolites, however, such as creatine (Cr), choline (Cho), glutamate+glutamine (Glx) and myo-inositol (mI) have shown inconsistent changes in these populations. The objective of this systematic review and meta-analysis was to synthesize MRS literature in head injury and explore factors (brain region, injury severity, time since injury, demographic, technical imaging factors, etc.) that may contribute to differential findings. One hundred and thirty-eight studies met inclusion criteria for the systematic review and of those, 62 NAA, 24 Cr, 49 Cho, 18 Glx and 21 mI studies met inclusion criteria for meta-analysis. A random effects model was used for meta-analyses with brain region as a subgroup for each of the five metabolites studied. Meta-regression was used to examine the influence of potential moderators including injury severity, time since injury, age, sex, tissue composition and methodological factors. In this analysis of 1428 unique head-injured subjects and 1132 controls, the corpus callosum was identified as a brain region highly susceptible to metabolite alteration. NAA was consistently decreased in TBI of all severity, but not in subconcussive hits. Cho and mI were found to be increased in moderate-to-severe TBI but not mild TBI. Glx and Cr were largely unaffected, however did show alterations in certain conditions.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.

Metabolite selection for machine learning in childhood brain tumour classification

MRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi-class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi-site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi-class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave-one-out and k-fold cross-validation. Metabolites identified as crucial in tumour classification include myo-inositol (P < 0.05, AUC = 0 . 81 ± 0 . 01 ), total lipids and macromolecules at 0.9 ppm (P < 0.05, AUC = 0 . 78 ± 0 . 01 ) and total creatine (P < 0.05, AUC = 0 . 77 ± 0 . 01 ) for the 1.5 T cohort, and glycine (P < 0.05, AUC = 0 . 79 ± 0 . 01 ), total N-acetylaspartate (P < 0.05, AUC = 0 . 79 ± 0 . 01 ) and total choline (P < 0.05, AUC = 0 . 75 ± 0 . 01 ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave-one-out cross-validation was 85% for 1.5 T 1 H-MRS through support vector machine and 75% for 3 T 1 H-MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours.

Glutamate cycle changes in the putamen of patients with de novo Parkinson's disease using 1H MRS

INTRODUCTION

To investigate glutamatergic metabolism changes in the putamen of patients with de novo Parkinson's Disease (PD) and test the hypothesis that glutamate (Glu) levels are abnormally elevated in the putamen contralateral to where the motor clinical signs predominate as expected from observations in animal models.

METHODS

¹H NMR spectra from 17 healthy control volunteers were compared with spectra from 17 de novo PD patients of who 14 were evaluated again after 2-3 years of disease progression. Statistical analysis used random-effects models.

RESULTS

The only significant difference between PD patients and controls was a higher glutamine (Gln) concentration in the putamen ipsilateral to the hemibody with predominant motor signs (Visit 1: 6.0 ± 0.4 mM vs. 5.2 ± 0.2 mM, p < 0.05; Visit 2: 6.2 ± 0.3 mM vs. 5.2 ± 0.2 mM, p < 0.05). At Visit 1, PD patients had higher Glu and Gln levels in the putamen ipsilateral versus contralateral to dominant clinical signs (Glu: 12.2 ± 0.6 mM vs. 10.4 ± 0.6 mM, p < 0.05; Gln: 6.0 ± 0.4 mM vs. 4.8 ± 0.4 mM, p < 0.05; Glu and Gln pool (Glx): 17.9 ± 0.8 mM vs. 14.7 ± 1.1 mM, p < 0.05). At Visit 2, the sum of the two metabolites remained significantly higher in the ipsilateral versus contralateral putamen (Glx: 18.3 ± 0.6 mM vs. 16.1 ± 0.9 mM, p < 0.05).

CONCLUSION

In de novo PD patients, the putamen ipsilateral to the more affected hemibody showed elevated Gln versus controls and elevated Glu and Gln concentrations versus the contralateral side. Abnormalities in Glu metabolism therefore occur early in PD but unexpectedly in the putamen contralateral to the more damaged hemisphere, suggesting they are not dependent solely on dopamine loss.

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.

Brain temperature as an indicator of neuroinflammation induced by typhoid vaccine: Assessment using whole-brain magnetic resonance spectroscopy in a randomised crossover study

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MRSI-derived whole-brain temperature did not detect low-level neuroinflammation.

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Regional brain temperature was a more sensitive measure of neuroinflammation.

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MRSI/EPSI might be a useful measure of neuroinflammation in psychiatric disorders.

Prior studies indicate a pathogenic role of neuroinflammation in psychiatric disorders; however, there are no accepted methods that can reliably measure low-level neuroinflammation non-invasively in these individuals. Magnetic resonance spectroscopic imaging (MRSI) is a versatile, non-invasive neuroimaging technique that demonstrates sensitivity to brain inflammation. MRSI in conjunction with echo-planar spectroscopic imaging (EPSI) measures brain metabolites to derive whole-brain and regional brain temperatures, which may increase in neuroinflammation. The validity of MRSI/EPSI for measurement of low level neuroinflammation was tested using a safe experimental model of human brain inflammation – intramuscular administration of typhoid vaccine. Twenty healthy volunteers participated in a double-blind, placebo-controlled crossover study including MRSI/EPSI scans before and 3 h after vaccine/placebo administration. Body temperature and mood, assessed using the Profile of Mood States, were measured every hour up to four hours post-treatment administration. A mixed model analysis of variance was used to test for treatment effects. A significant proportion of brain regions (44/47) increased in temperature post-vaccine compared to post-placebo (p < 0.0001). For temperature change in the brain as a whole, there was no significant treatment effect. Significant associations were seen between mood scores assessed at 4 h and whole brain and regional temperatures post-treatment. Findings indicate that regional brain temperature may be a more sensitive measure of low-level neuroinflammation than whole-brain temperature. Future work where these measurement techniques are applied to populations with psychiatric disorders would be of clinical interest.

Neurometabolite Levels and Relevance to Central Sensitization in Chronic Orofacial Pain Patients: A Magnetic Resonance Spectroscopy Study

Background

Patients and Methods

Results

Conclusion

Brain proton magnetic resonance spectroscopy and neurodevelopment after preterm birth: a systematic review

BACKGROUND

Preterm infants are at risk of neurodevelopmental impairments. At present, proton magnetic resonance spectroscopy (¹H-MRS) is used to evaluate brain metabolites in asphyxiated term infants. The aim of this review is to assess associations between cerebral ¹H-MRS and neurodevelopment after preterm birth.

METHODS

PubMed and Embase were searched to identify studies using ¹H-MRS and preterm birth. Eligible studies for this review included ¹H-MRS of the brain, gestational age ≤32 weeks, and neurodevelopment assessed at a corrected age (CA) of at least 12 months up to the age of 18 years.

RESULTS

Twenty papers evaluated ¹H-MRS in preterm infants at an age between near-term and 18 years and neurodevelopment. ¹H-MRS was performed in both white (WM) and gray matter (GM) in 12 of 20 studies. The main regions were frontal and parietal lobe for WM and basal ganglia for GM. N-acetylaspartate/choline (NAA/Cho) measured in WM and/or GM is the most common metabolite ratio associated with motor, language, and cognitive outcome at 18-24 months CA.

CONCLUSIONS

NAA/Cho in WM assessed at term-equivalent age was associated with motor, cognitive, and language outcome, and NAA/Cho in deep GM was associated with language outcome at 18-24 months CA.

IMPACT

In preterm born infants, brain metabolism assessed using ¹H-MRS at term-equivalent age is associated with motor, cognitive, and language outcomes at 18-24 months. ¹H-MRS at term-equivalent age in preterm born infants may be used as an early indication of brain development. Specific findings relating to NAA were most predictive of outcome.

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.

American football position-specific neurometabolic changes in high school athletes - a magnetic resonance spectroscopic study

Reports estimate between 1.6-3.8 million sports-related concussions occur annually, with 30% occurring in youth male American football athletes. Many studies report neurophysiological changes in these athletes, but the exact reasons for these changes remain elusive. Investigation of injury mechanics highlights a need to address how player position might impact these changes. Here, 55 high school American football athletes (20 linemen; 35 non-linemen) underwent magnetic resonance spectroscopy four times over the course of a football season (once prior to the season (Pre), twice during (In1, In2), and once following (Post)) to quantify metabolites (N-acetyl aspartate, choline, creatine, myo-inositol, and glutamate/glutamine) in the dorsolateral prefrontal cortex (DLPFC) and primary motor cortex (M1). Head acceleration events (HAEs) were monitored at each practice and game. Spectroscopic and HAE data were analyzed by imaging session and player position. Linear regression analyses were conducted between metabolite levels and HAEs, and metabolite levels in football athletes were compared to age-and gender-matched non-contact athletes. Across-season (i.e., between Pre and In1, In2, Post), different DLPFC and M1 metabolites decreased (p<0.05) according to player position (i.e., linemen vs. non-linemen). The majority of regression results involved DLPFC metabolites in linemen, where metabolite levels were higher, from Pre to Post, with increasing HAE load. Comparisons with control athletes revealed higher metabolite levels in football athletes both before and after the season. This study highlights the importance of player position when conducting analyses on American football athletes and demonstrates elevated DLPFC and M1 brain metabolites in football athletes compared to control athletes at both Pre and Post, suggesting potential HAE-related neurocompensatory mechanisms.

Quantitative magnetization transfer imaging in relapsing-remitting multiple sclerosis: a systematic review and meta-analysis

Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [β = 0.12 (-0.56 to 0.80), t-value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [β = 0.037 (-0.14 to 0.22), t-value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [r = -0.32 (95% CI -0.46 to -0.17); z-value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio.

MR Neuroimaging in Pediatric Inborn Errors of Metabolism

Inborn errors of metabolism (IEM) are a group of disorders due to functional defects in one or more metabolic pathways that can cause considerable morbidity and death if not diagnosed early. While individually rare, the estimated global prevalence of IEMs comprises a substantial number of neonatal and infantile disorders affecting the central nervous system. Clinical manifestations of IEMs may be nonspecific. Newborn metabolic screens do not capture all IEMs, and likewise, genetic testing may not always detect pathogenic variants. Neuroimaging is a critical component of the work-up, given that imaging sometimes occurs before prenatal screen results are available, which may allow for recognition of imaging patterns that lead to early diagnosis and treatment of IEMs. This review will demonstrate the role of magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (¹H MRS) in the evaluation of IEMs. The focus will be on scenarios where MRI and ¹H MRS are suggestive of or diagnostic for IEMs, or alternatively, refute the diagnosis.

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.

Characterizing cerebral metabolite profiles in anorexia and bulimia nervosa and their associations with habitual behavior

Anorexia nervosa (AN) and bulimia nervosa (BN) are associated with altered brain structure and function, as well as increased habitual behavior. This neurobehavioral profile may implicate neurochemical changes in the pathogenesis of these illnesses. Altered glutamate, myo-inositol and N-acetyl aspartate (NAA) concentrations are reported in restrictive AN, yet whether these extend to binge-eating disorders, or relate to habitual traits in affected individuals, remains unknown. We therefore used single-voxel proton magnetic resonance spectroscopy to measure glutamate, myo-inositol, and NAA in the right inferior lateral prefrontal cortex and the right occipital cortex of 85 women [n = 22 AN (binge-eating/purging subtype; AN-BP), n = 33 BN, n = 30 controls]. To index habitual behavior, participants performed an instrumental learning task and completed the Creature of Habit Scale. Women with AN-BP, but not BN, had reduced myo-inositol and NAA concentrations relative to controls in both regions. Although patient groups had intact instrumental learning task performance, both groups reported increased routine behaviors compared to controls, and automaticity was related to reduced prefrontal glutamate and NAA participants with AN-BP. Our findings extend previous reports of reduced myo-inositol and NAA levels in restrictive AN to AN-BP, which may reflect disrupted axonal-glial signaling. Although we found inconsistent support for increased habitual behavior in AN-BP and BN, we identified preliminary associations between prefrontal metabolites and automaticity in AN-BP. These results provide further evidence of unique neurobiological profiles across binge-eating disorders.

Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Objective

To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.

Methods

The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).

Results

The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.

Conclusion

Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Insight Into the Effects of Clinical Repetitive Transcranial Magnetic Stimulation on the Brain From Positron Emission Tomography and Magnetic Resonance Imaging Studies: A Narrative Review

Repetitive transcranial magnetic stimulation (rTMS) has been proposed as a therapeutic tool to alleviate symptoms for neurological and psychiatric diseases such as chronic pain, stroke, Parkinson’s disease, major depressive disorder, and others. Although the therapeutic potential of rTMS has been widely explored, the neurological basis of its effects is still not fully understood. Fortunately, the continuous development of imaging techniques has advanced our understanding of rTMS neurobiological underpinnings on the healthy and diseased brain. The objective of the current work is to summarize relevant findings from positron emission tomography (PET) and magnetic resonance imaging (MRI) techniques evaluating rTMS effects. We included studies that investigated the modulation of neurotransmission (evaluated with PET and magnetic resonance spectroscopy), brain activity (evaluated with PET), resting-state connectivity (evaluated with resting-state functional MRI), and microstructure (diffusion tensor imaging). Overall, results from imaging studies suggest that the effects of rTMS are complex and involve multiple neurotransmission systems, regions, and networks. The effects of stimulation seem to not only be dependent in the frequency used, but also in the participants characteristics such as disease progression. In patient populations, pre-stimulation evaluation was reported to predict responsiveness to stimulation, while post-stimulation neuroimaging measurements showed to be correlated with symptomatic improvement. These studies demonstrate the complexity of rTMS effects and highlight the relevance of imaging techniques.

Decreased in vivo glutamate/GABA ratio correlates with the social behavior deficit in a mouse model of autism spectrum disorder

To diagnose autism spectrum disorder (ASD), researchers have sought biomarkers whose alterations correlate with the susceptibility to ASD. However, biomarkers closely related to the pathophysiology of ASD are lacking. Even though excitation/inhibition (E/I) imbalance has been suggested as an underlying mechanism of ASD, few studies have investigated the actual ratio of glutamate (Glu) to γ-aminobutyric acid (GABA) concentration in vivo. Moreover, there are controversies in the directions of E/I ratio alterations even in extensively studied ASD animal models. Here, using proton magnetic resonance spectroscopy (¹H-MRS) at 9.4T, we found significant differences in the levels of different metabolites or their ratios in the prefrontal cortex and hippocampus of Cntnap2^−/− mice compared to their wild-type littermates. The Glu/GABA ratio, N-acetylaspartate (NAA)/total creatine (tCr) ratio, and tCr level in the prefrontal cortex were significantly different in Cntnap2^−/− mice compared to those in wild-type mice, and they significantly correlated with the sociability of mice. Moreover, receiver operating characteristic (ROC) analyses indicated high specificity and selectivity of these metabolites in discriminating genotypes. These results suggest that the lowered Glu/GABA ratio in the prefrontal cortex along with the changes in the other metabolites might contribute to the social behavior deficit in Cntnap2^−/− mice. Our results also demonstrate the utility of ¹H-MRS in investigating the underlying mechanisms or the diagnosis of ASD.

Clinical 1H MRS in childhood neurometabolic diseases-part 1: technique and age-related normal spectra

Despite its vigorous ability to detect and measure metabolic disturbances, ¹H MRS remains underutilized in clinical practice. MRS increases diagnostic yield and provides therapeutic measures. Because many inborn metabolic errors are now treatable, early diagnosis is crucial to prevent or curb permanent brain injury. Therefore, patients with known or suspected inborn metabolic errors stand to benefit from the addition of MRS. With education and practice, all neuroradiologists can perform and interpret MRS notwithstanding their training and prior experience. In this two-part review, we cover the requisite concepts for clinical MRS interpretation including technical considerations and normal brain spectral patterns based on age, location, and methodology.

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.

Edited magnetic resonance spectroscopy in the neonatal brain

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

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as 'chemo fog'. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

Emerging methods and applications of ultra-high field MR spectroscopic imaging in the human brain

Magnetic Resonance Spectroscopic Imaging (MRSI) of the brain enables insights into the metabolic changes and fluxes in diseases such as tumors, multiple sclerosis, epilepsy, or hepatic encephalopathy, as well as insights into general brain functionality. However, the routine application of MRSI is mostly hampered by very low signal-to-noise ratios (SNR) due to the low concentrations of metabolites, about 10000 times lower than water. Furthermore, MRSI spectra have a dense information content with many overlapping metabolite resonances, especially for proton MRSI. MRI scanners at ultra-high field strengths, like 7 T or above, offer the opportunity to increase SNR, as well as the separation between resonances, thus promising to solve both challenges. Yet, MRSI at ultra-high field strengths is challenged by decreased B0- and B1-homogeneity, shorter T2 relaxation times, stronger chemical shift displacement errors, and aggravated lipid contamination. Therefore, to capitalize on the advantages of ultra-high field strengths, these challenges must be overcome. This review focuses on the challenges MRSI of the human brain faces at ultra-high field strength, as well as the possible applications to this date.

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.

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.

GABAB receptor modulation of visual sensory processing in adults with and without autism spectrum disorder

[Figure: see text].

Hippocampal Dysconnectivity and Altered Glutamatergic Modulation of the Default Mode Network: A Combined Resting-State Connectivity and Magnetic Resonance Spectroscopy Study in Schizophrenia

BACKGROUND

Converging lines of evidence point to hippocampal dysfunction in schizophrenia. It is thought that hippocampal dysfunction spreads across hippocampal subfields and to cortical regions by way of long-range efferent projections. Importantly, abnormalities in the excitation/inhibition balance could impair the long-range modulation of neural networks. The goal of this project was twofold. First, we sought to identify replicable patterns of hippocampal dysconnectivity in patients with a psychosis spectrum disorder. Second, we aimed to investigate a putative link between glutamatergic metabolism and hippocampal connectivity alterations.

METHODS

We evaluated resting-state hippocampal functional connectivity alterations in two cohorts of patients with a psychosis spectrum disorder. The first cohort consisted of 55 medication-naïve patients with first-episode psychosis and 41 matched healthy control subjects, and the second cohort consisted of 42 unmedicated patients with schizophrenia and 41 matched control subjects. We also acquired measurements of glutamate + glutamine in the left hippocampus using magnetic resonance spectroscopy for 42 patients with first-episode psychosis and 37 healthy control subjects from our first cohort.

RESULTS

We observed a pattern of hippocampal functional hypoconnectivity to regions of the default mode network and hyperconnectivity to the lateral occipital cortex in both cohorts. We also show that in healthy control subjects, greater hippocampal glutamate + glutamine levels predicted greater hippocampal functional connectivity to the anterior default mode network. Furthermore, this relationship was reversed in medication-naïve subjects with first-episode psychosis.

CONCLUSIONS

These results suggest that an alteration in the relationship between glutamate and functional connectivity may disrupt the dynamic of major neural networks.

In vivo spectral editing of phosphorylethanolamine

PURPOSE

To demonstrate J-difference editing of phosphorylethanolamine (PE) with chemical shifts at 3.22 (PE3.22 ) and 3.98 (PE3.98 ) ppm, and compare the merits of two editing strategies.

METHODS

Density-matrix simulations of MEGA-PRESS (Mescher-Garwood PRESS) for PE were performed at TEs ranging from 80 to 200 ms in steps of 2 ms, applying 20-ms editing pulses (ON/OFF) at (1) 3.98/7.5 ppm to detect PE3.22 and (2) 3.22/7.5 ppm to detect PE3.98 . Phantom experiments were performed using a PE phantom to validate simulation results. Ten subjects were scanned using a Philips 3T MRI scanner at TEs of 90 ms and 110 ms to edit PE3.22 and PE3.98 . Osprey was used for data processing, modeling, and quantification.

RESULTS

Simulations show substantial TE modulation of the intensity and shape of the edited signals due to coupling evolution. Simulated and phantom integrals suggest that TEs of 110 ms and 90 ms were optimal for the edited detection of PE3.22 and PE3.98 , respectively. Phantom results indicated strong agreement with the simulated spectra and integrals. In vivo quantification of the PE3.22 /total creatine and PE3.98 /total creatine concentration ratio yielded values of 0.26 ± 0.04 (between-subject coefficient of variation [CV]: 15.4%) and 0.18 ± 0.04 (CV: 22.8%), respectively, at TE = 90 ms, and 0.24 ± 0.02 (CV: 8.2%) and 0.23 ± 0.04 (CV: 18.0%), respectively, at TE = 110 ms.

CONCLUSION

Simulations and in vivo MEGA-PRESS of PE demonstrate that both PE3.22 and PE3.98 are potential candidates for editing, but PE3.22 at TE = 110 ms yields lower variation across TEs.

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

BACKGROUND AND PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Motor Cortex Excitation/Inhibition Imbalance in Young Adults With Autism Spectrum Disorder: A MRS-TMS Approach

Excitatory/inhibitory imbalance has been suggested as a neurobiological substrate of the cognitive symptomatology in Autism Spectrum Disorder (ASD). Studies using magnetic resonance spectroscopy (MRS) attempted to characterize GABA and Glutamate brain levels in ASD. However mixed findings have been reported. Here, we characterize both neurochemical and physiological aspects of GABA system in ASD by implementing a more comprehensive approach combining MRS and transcranial magnetic stimulation (TMS). A group of 16 young ASD adults and a group of 17 controls participated in this study. We employed one MRS session to assess motor cortex GABA+ and Glutamate+Glutamine (Glx) levels using MEGAPRESS and PRESS sequences, respectively. Additionally, a TMS experiment was implemented including paired-pulse (SICI, ICF and LICI), input-output curve and cortical silent period to probe cortical excitability. Our results showed a significantly increased Glx, with unchanged GABA+ levels in the ASD group compared with controls. Single TMS measures did not differ between groups, although exploratory within-group analysis showed impaired inhibition in SICI5ms, in ASD. Importantly, we observed a correlation between GABA levels and measures of the input-output TMS recruitment curve (slope and MEP amplitude) in the control group but not in ASD, as further demonstrated by direct between group comparisons. In this exploratory study, we found evidence of increased Glx levels which may contribute to ASD excitatory/inhibitory imbalance while highlighting the relevance of conducting further larger-scale studies to investigate the GABA system from complementary perspectives, using both MRS and TMS techniques.

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.

Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma

BACKGROUND

Magnetic resonance spectroscopic imaging (MRSI) can be used in glioma patients to map the metabolic alterations associated with IDH1,2 mutations that are central criteria for glioma diagnosis. The aim of this study was to achieve super-resolution (SR) MRSI using deep learning to image tumor metabolism in patients with mutant IDH glioma.

METHODS

We developed a deep learning method based on generative adversarial network (GAN) using Unet as generator network to upsample MRSI by a factor of 4. Neural networks were trained on simulated metabolic images from 75 glioma patients. The performance of deep neuronal networks was evaluated on MRSI data measured in 20 glioma patients and 10 healthy controls at 3T with a whole-brain 3D MRSI protocol optimized for detection of d-2-hydroxyglutarate (2HG). To further enhance structural details of metabolic maps we used prior information from high-resolution anatomical MR imaging. SR MRSI was compared to ground truth by Mann-Whitney U-test of peak signal-to-noise ratio (PSNR), structure similarity index measure (SSIM), feature-based similarity index measure (FSIM), and mean opinion score (MOS).

RESULTS

Deep learning SR improved PSNR by 17%, SSIM by 5%, FSIM by 7%, and MOS by 30% compared to conventional interpolation methods. In mutant IDH glioma patients proposed method provided the highest resolution for 2HG maps to clearly delineate tumor margins and tumor heterogeneity.

CONCLUSIONS

Our results indicate that proposed deep learning methods are effective in enhancing spatial resolution of metabolite maps. Patient results suggest that this may have great clinical potential for image guided precision oncology therapy.

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

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

The Role of Molecular Imaging as a Marker of Remyelination and Repair in Multiple Sclerosis

The appearance of new disease-modifying therapies in multiple sclerosis (MS) has revolutionized our ability to fight inflammatory relapses and has immensely improved patients’ quality of life. Although remarkable, this achievement has not carried over into reducing long-term disability. In MS, clinical disability progression can continue relentlessly irrespective of acute inflammation. This “silent” disease progression is the main contributor to long-term clinical disability in MS and results from chronic inflammation, neurodegeneration, and repair failure. Investigating silent disease progression and its underlying mechanisms is a challenge. Standard MRI excels in depicting acute inflammation but lacks the pathophysiological lens required for a more targeted exploration of molecular-based processes. Novel modalities that utilize nuclear magnetic resonance’s ability to display in vivo information on imaging look to bridge this gap. Displaying the CNS through a molecular prism is becoming an undeniable reality. This review will focus on “molecular imaging biomarkers” of disease progression, modalities that can harmoniously depict anatomy and pathophysiology, making them attractive candidates to become the first valid biomarkers of neuroprotection and remyelination.

Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.

MR spectroscopy frequency and phase correction using convolutional neural networks

PURPOSE

To introduce a novel convolutional neural network (CNN)-based approach for frequency-and-phase correction (FPC) of MR spectroscopy (MRS) spectra to achieve fast and accurate FPC of single-voxel MEGA-PRESS MRS data.

METHODS

Two neural networks (one for frequency and one for phase) were trained and validated using published simulated and in vivo MEGA-PRESS MRS dataset with wide-range artificial frequency and phase offsets applied. The CNN-based approach was subsequently tested and compared to the current deep learning solution: multilayer perceptrons (MLP). Furthermore, random noise was added to the original simulated dataset to further investigate the model performance at varied signal-to-noise ratio (SNR) levels (i.e., 10, 5, and 2.5). Additional frequency and phase offsets (i.e., small, moderate, large) were also applied to the in vivo dataset, and the CNN model was compared to the conventional approach SR and model-based SR implementation (mSR).

RESULTS

The CNN model is more robust to noise compared to the MLP-based approach due to having smaller mean absolute errors in both frequency (0.01 ± 0.01 Hz at SNR = 10 and 0.01 ± 0.02 Hz at SNR = 2.5) and phase (0.12 ± 0.09° at SNR = 10 and -0.07 ± 0.44° at SNR = 2.5) offset prediction. Furthermore, better performance was demonstrated for FPC when compared to the MLP-based approach, and SR when applied to the in vivo dataset for both with and without additional offsets.

CONCLUSION

A CNN-based approach provides a solution to the automated preprocessing of MRS data, and the experimental results demonstrate the quantitatively improved spectra quality compared to the state-of-the-art approach.

Evidence against altered excitatory/inhibitory balance in the posteromedial cortex of young adult APOE E4 carriers: A resting state 1H-MRS study

A strategy to gain insight into early changes that may predispose people to Alzheimer's disease (AD) is to study the brains of younger cognitively healthy people that are at increased genetic risk of AD. The Apolipoprotein (APOE) E4 allele is the strongest genetic risk factor for AD, and several neuroimaging studies comparing APOE E4 carriers with non-carriers at age ∼20-30 years have detected hyperactivity (or reduced deactivation) in posteromedial cortex (PMC), a key hub of the default network (DN), which has a high susceptibility to early amyloid deposition in AD. Transgenic mouse models suggest such early network activity alterations may result from altered excitatory/inhibitory (E/I) balance, but this is yet to be examined in humans. Here we test the hypothesis that PMC fMRI hyperactivity could be underpinned by altered levels of excitatory (glutamate) and/or inhibitory (GABA) neurotransmitters in this brain region. Forty-seven participants (20 APOE E4 carriers and 27 non-carriers) aged 18-25 years underwent resting-state proton magnetic resonance spectroscopy (1H-MRS), a non-invasive neuroimaging technique to measure glutamate and GABA in vivo. Metabolites were measured in a PMC voxel of interest and in a comparison voxel in the occipital cortex (OCC). There was no difference in either glutamate or GABA between the E4 carriers and non-carriers in either MRS voxel, or in the ratio of glutamate to GABA, a measure of E/I balance. Default Bayesian t-tests revealed evidence in support of this null finding. Our findings suggest that PMC hyperactivity in APOE E4 carriers is unlikely to be associated with, or possibly may precede, alterations in local resting-state PMC neurotransmitters, thus informing our understanding of the spatio-temporal sequence of early network alterations underlying APOE E4 related AD risk.

Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T

PURPOSE

Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach.

METHODS

We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs.

RESULTS

Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate.

DISCUSSION

We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.

Method for fast lipid reconstruction and removal processing in 1 H MRSI of the brain

PURPOSE

To develop a new rapid spatial filtering method for lipid removal, fast lipid reconstruction and removal processing (FLIP), which selectively isolates and removes interfering lipid signals from outside the brain in a full-FOV 2D MRSI and whole-brain 3D echo planar spectroscopic imaging (EPSI).

THEORY AND METHODS

FLIP uses regularized least-squares regression based on spatial prior information from MRI to selectively remove lipid signals originating from the scalp and measure the brain metabolite signals with minimum cross contamination. FLIP is a noniterative approach, thus allowing a rapid processing speed, and uses only spatial information without any spectral priors. The performance of FLIP was compared with the Papoulis-Gerchberg algorithm (PGA), Hankel singular value decomposition (HSVD), and fast image reconstruction with L2 regularization (L2).

RESULTS

FLIP in both 2D and 3D MRSI resulted in consistent metabolite quantification in a greater number of voxels with less concentration variation than other algorithms, demonstrating effective and robust lipid-removal performance. The percentage of voxels that met quality criteria with FLIP, PGA, HSVD, and L2 processing were 90%, 57%, 29%, and 42% in 2D MRSI, and 80%, 75%, 76%, and 74% in 3D EPSI, respectively. The quantification results of full-FOV MRSI using FLIP were comparable to those of volume-localized MRSI, while allowing significantly increased spatial coverage. FLIP performed the fastest in 2D MRSI.

CONCLUSION

FLIP is a new lipid-removal algorithm that promises fast and effective lipid removal with improved volume coverage in MRSI.