Magnetic resonance spectroscopy of the brain: a review of physical principles and technical methods

Gender-related alterations of serum trace elements and neurometabolism in the anterior cingulate cortex of patients with major depressive disorder

BACKGROUND

It is widely known that sex differences have a significant impact on patients with major depressive disorder (MDD). This study aims to evaluate the sex-related connection between serum trace elements and changes in neurometabolism in the anterior cingulate cortex (ACC) of MDD patients.

METHODS

109 untreated MDD patients and 59 healthy controls underwent proton magnetic resonance spectroscopy (1H-MRS) under resting conditions. We measured metabolic ratios in the ACC from both sides. Additionally, venous blood samples were taken from all participants to detect calcium (Ca), phosphorus, magnesium (Mg), copper (Cu), ceruloplasmin (CER), zinc (Zn), and iron (Fe) levels. We performed association and interaction analyses to explore the connections between the disease and gender.

RESULTS

In individuals with MDD, the Cu/Zn ratio increased, while the levels of Mg, CER, Zn and Fe decreased. Male MDD patients had lower Cu levels, while female patients had an increased Cu/Zn ratio. We observed significant gender differences in Cu, CER and the Cu/Zn ratio in MDD. Male patients showed a reduced N-acetyl aspartate (NAA)/phosphocreatine + creatine (PCr + Cr) ratio in the left ACC. The NAA/PCr + Cr ratio decreased in the right ACC in patients with MDD. In the left ACC of male MDD patients, the Cu/Zn ratio was inversely related to the NAA/PCr + Cr ratio, and Fe levels were negatively associated with the GPC + PC/PCr + Cr ratio.

CONCLUSIONS

Our findings highlight gender-specific changes in Cu homeostasis among male MDD patients. The Cu/Zn ratio and Fe levels in male MDD patients were significantly linked to neurometabolic alterations in the ACC.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Super-resolution techniques for biomedical applications and challenges

Super-resolution (SR) techniques have revolutionized the field of biomedical applications by detailing the structures at resolutions beyond the limits of imaging or measuring tools. These techniques have been applied in various biomedical applications, including microscopy, magnetic resonance imaging (MRI), computed tomography (CT), X-ray, electroencephalogram (EEG), ultrasound, etc. SR methods are categorized into two main types: traditional non-learning-based methods and modern learning-based approaches. In both applications, SR methodologies have been effectively utilized on biomedical images, enhancing the visualization of complex biological structures. Additionally, these methods have been employed on biomedical data, leading to improvements in computational precision and efficiency for biomedical simulations. The use of SR techniques has resulted in more detailed and accurate analyses in diagnostics and research, essential for early disease detection and treatment planning. However, challenges such as computational demands, data interpretation complexities, and the lack of unified high-quality data persist. The article emphasizes these issues, underscoring the need for ongoing development in SR technologies to further improve biomedical research and patient care outcomes.

Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning

BACKGROUND

Deep learning-based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning-based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR).

PURPOSE

To investigate a convolutional neural network-based SR (CNN-SR) approach for simultaneous frequency-and-phase correction (FPC) of single-voxel Meshcher-Garwood point-resolved spectroscopy (MEGA-PRESS) MRS data.

STUDY TYPE

Retrospective.

SUBJECTS

Forty thousand simulated MEGA-PRESS datasets generated from FID Appliance (FID-A) were used and split into the following: 32,000/4000/4000 for training/validation/testing. A 101 MEGA-PRESS medial parietal lobe data retrieved from the Big GABA were used as the in vivo datasets.

FIELD STRENGTH/SEQUENCE

3T, MEGA-PRESS.

ASSESSMENT

Evaluation of frequency and phase offsets mean absolute errors were performed for the simulation dataset. Evaluation of the choline interval variance was performed for the in vivo dataset. The magnitudes of the offsets introduced were -20 to 20 Hz and -90° to 90° and were uniformly distributed for the simulation dataset at different signal-to-noise ratio (SNR) levels. For the in vivo dataset, different additional magnitudes of offsets were introduced: small offsets (0-5 Hz; 0-20°), medium offsets (5-10 Hz; 20-45°), and large offsets (10-20 Hz; 45-90°).

STATISTICAL TESTS

Two-tailed paired t-tests for model performances in the simulation and in vivo datasets were used and a P-value <0.05 was considered statistically significant.

RESULTS

CNN-SR model was capable of correcting frequency offsets (0.014 ± 0.010 Hz at SNR 20 and 0.058 ± 0.050 Hz at SNR 2.5 with line broadening) and phase offsets (0.104 ± 0.076° at SNR 20 and 0.416 ± 0.317° at SNR 2.5 with line broadening). Using in vivo datasets, CNN-SR achieved the best performance without (0.000055 ± 0.000054) and with different magnitudes of additional frequency and phase offsets (i.e., 0.000062 ± 0.000068 at small, -0.000033 ± 0.000023 at medium, 0.000067 ± 0.000102 at large) applied.

DATA CONCLUSION

The proposed CNN-SR method is an efficient and accurate approach for simultaneous FPC of single-voxel MEGA-PRESS MRS data.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

A prospective study of MRI biomarkers in the brain and lower limb muscles for prediction of lower limb motor recovery following stroke

The aim of this prospective observational longitudinal study was to explore and decipher the predictive value of prospective MRI biomarkers in the brain and lower limb muscles for 3-month lower limb motor recovery following stroke. In the brain, we measured the integrity of the corticospinal tract (fractional anisotropy/"FA"). In the muscles, we measured volume, fatty replacement (fat fraction analysis and proton spectroscopy) and oedema. Measurements were taken at two time points: (1) within 4 weeks of stroke (baseline measurement, clinical and imaging) and (2) 3 months following stroke (follow up measurement, clinical only). Clinical measurements consisted of assessments of functional ability and strength (Fugl-Meyer score, motor NIHSS, Functional Ambulation Category/"FAC", and muscle dynamometry). Twenty-three patients completed imaging and clinical assessments at baseline and follow-up; five patients had partial imaging assessment. The results provided some evidence that damage to the corticospinal tract would result in less motor recovery: recovery of the Fugl-Meyer score and dynamometric ankle plantarflexion, ankle dorsiflexion, and knee extension correlated positively and significantly with fractional anisotropy (0.406-0.457; p = 0.034-p = 0.016). However, fractional anisotropy demonstrated a negative correlation with recovery of the Functional Ambulation Category (-0.359, p = 0.046). For the muscle imaging, significant inverse correlation was observed between vastus lateralis fat fraction vs. NIHSS recovery (-0.401, p = 0.04), and a strong positive correlation was observed between ratio of intra- to extra-myocellular lipid concentrations and the recovery of knee flexion (0.709, p = 0.007). This study supports previous literature indicating a positive correlation between the integrity of the corticospinal tract and motor recovery post-stroke, expanding the limited available literature describing this relationship specifically for the lower limb. However, recovery of functional ambulation behaved differently to other clinical recovery markers by demonstrating an inverse relationship with corticospinal tract integrity. The study also introduces some muscle imaging biomarkers as potentially valuable in the prediction of 3-month lower limb motor recovery following stroke.

Protocol to conduct functional magnetic resonance spectroscopy in different age groups of human participants

We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022).1.

Metabolite Variations in the Hippocampus and Corpus Callosum of Patients with Mild Cognitive Impairment Using Magnetic Resonance Spectroscopy with Three-Dimensional Chemical Shift Images

This study compared the metabolites in the brain regions of hippocampus and corpus callosum between patients with mild cognitive impairment (MCI) and healthy controls using no-radiation and high-sensitivity magnetic resonance spectroscopy (MRS) with three-dimensional chemical shift images (3D-CSI). Twenty volunteers (seven patients with MCI and 13 healthy controls) aged 50-71 years were recruited for this prospective study. MRS with 3D-CSI images of a variety of metabolites was collected from the hippocampus and corpus callosum. Sex and weight showed no significant differences between the two groups. The metabolite levels in the hippocampus and corpus callosum of the MCI group were generally lower than in those of the healthy group, especially for creatine (p < 0.001 in the hippocampus and p = 0.020 in the corpus callosum) and N-acetyl aspartate/creatine (p < 0.001 in the hippocampus and p = 0.020 in the corpus callosum); however, choline/creatine showed a significant difference (p < 0.001) only in the hippocampus, and myo-inositol/creatine showed a significant difference (p < 0.001) only in the corpus callosum. Our study demonstrated that MRS with 3D-CSI can be used to measure these metabolite levels to determine the differences between patients with MCI and healthy individuals. This would aid early diagnosis of MCI in clinical practice, and patients could receive prompt intervention to improve their quality of life.

A review of machine learning applications for the proton MR spectroscopy workflow

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.

Non-linear variations in glutamate dynamics during a cognitive task engagement in schizophrenia

To investigate the role of glutamate in psychosis, we employ functional magnetic resonance spectroscopy at an ultra-high magnetic field (7T) and employ fuzzy-approximate entropy (F-ApEn) and Hurst Exponent (HE) to capture time-varying nature of glutamate signaling during a cognitive task. We recruited thirty first-episode psychosis patients (FEP) with age- and gender-matched healthy controls (HC) and administered the Color-Word Stroop paradigm, providing 128 raw MRS time-points per subject over a period of 16 min. We then performed metabolite quantification of glutamate in the dorsal anterior cingulate cortex, a region reliably activated during the Stroop task. Symptoms/cognitive functioning was measured using Positive and Negative Syndrome Scale-8 score, Social and Occupational Functioning (SOFAS) score, digit symbol) coding score, and Stroop accuracy. These scores were related to the Entropy/HE data from the overall glutamate time-series. Patients with FEP had significantly higher HE compared to HC, with individuals displaying significantly higher HE having lower functional performance (SOFAS) in both HC and FEP groups. Among healthy individuals, higher HE also indicated significantly lower cognitive function through Stroop accuracy and DSST scores. F-ApEn had an inverse Pearson correlation with HE, and tracked diagnosis, cognition and function as expected, but with lower effect sizes not reaching statistical significance. We demonstrate notable diagnostic differences in the temporal course of glutamate signaling during a cognitive task in psychosis.

Early metabolic alterations in the normal‑appearing grey and white matter of patients with clinically isolated syndrome suggestive of multiple sclerosis: A proton MR spectroscopic study

Proton magnetic resonance spectroscopy (¹H-MRS) is an advanced method of examining metabolic profiles. The present study aimed to assess in vivo metabolite levels in areas of normal-appearing grey (thalamus) and white matter (centrum semiovale) using ¹H-MRS in patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis and compare them to healthy controls (HCs). Data from 35 patients with CIS (CIS group), of which 23 were untreated (CIS-untreated group) and 12 were treated (CIS-treated group) with disease-modifying-therapies (DMTs) at the time of ¹H-MRS, and from 28 age- and sex-matched HCs were collected using a 3.0 T MRI and single-voxel ¹H-MRS (point resolved spectroscopy sequence; repetition time, 2,000 msec; time to echo, 35 msec). Concentrations and ratios of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline (tCho), myoinositol, glutamate (Glu), glutamine (Gln), Glu + Gln (Glx) and glutathione (Glth) were estimated in the thalamic-voxel (th) and centrum semiovale-voxel (cs). For the CIS group, the median duration from the first clinical attack to ¹H-MRS was 102 days (interquartile range, 89.5.-131.5). Compared with HCs, significantly lower Glx(cs) (P=0.014) and ratios of tCho/tCr(th) (P=0.026), Glu/tCr(cs) (P=0.040), Glx/tCr(cs) (P=0.004), Glx/tNAA(th) (P=0.043) and Glx/tNAA(cs) (P=0.015) were observed in the CIS group. No differences in tNAA levels were observed between the CIS and the HC groups; however, tNAA(cs) was higher in the CIS-treated than in the CIS-untreated group (P=0.028). Compared with those in HC group, decreased Glu(cs) (P=0.019) and Glx(cs) levels (P=0.014) and lower ratios for tCho/tCr(th) (P=0.015), Gln/tCr(th) (P=0.004), Glu/tCr(cs) (P=0.021), Glx/tCr(th) (P=0.041), Glx/tCr(cs) (P=0.003), Glx/tNAA(th) (P=0.030) and Glx/tNAA(cs) (P=0.015) were found in the CIS-untreated group. The present findings showed alterations in the normal-appearing grey and white matter of patients with CIS; moreover, the present results suggested an early indirect treatment effect of DMTs on the brain metabolic profile of these patients.

Spectroscopic meta-analyses reveal novel metabolite profiles across methamphetamine and cocaine substance use disorder

BACKGROUND

Although proton magnetic resonance spectroscopy (MRS) has been used to study metabolite alterations in stimulant (methamphetamine and cocaine) substance use disorders (SUDs) for over 25 years, data-driven consensus regarding the nature and magnitude of these alterations is lacking.

METHOD

In this meta-analysis, we examined associations between SUD and regional metabolites (N-acetyl aspartate (NAA), choline, myo-inositol, creatine, glutamate, and glutamate+glutamine (glx)) in the medial prefrontal cortex (mPFC), frontal white matter (FWM), occipital cortex, and basal ganglia as measured by 1 H-MRS. We also examined moderating effects of MRS acquisition parameters (echo time (TE), field strength), data quality (coefficient of variation (COV)), and demographic/clinical variables.

RESULTS

A MEDLINE search revealed 28 articles that met meta-analytic criteria. Significant effects included lower mPFC NAA, higher mPFC myo-inositol, and lower mPFC creatine in SUD relative to people without SUD. mPFC NAA effects were moderated by TE, with larger effects at longer TEs. For choline, although no group effects were observed, effect sizes in the mPFC were related to MRS technical indicators (field strength, COV). No effects of age, sex, primary drug of use (methamphetamine vs. cocaine), duration of use, or duration of abstinence were observed. Evidence for moderating effects of TE and COV may have implications for future MRS studies in SUDs.

CONCLUSIONS

The observed metabolite profile in methamphetamine and cocaine SUD (lower NAA and creatine with higher myo-inositol) parallels that observed in Alzheimer's disease and mild cognitive impairment, suggesting these drugs are associated with neurometabolic differences similar to those characterizing these neurodegenerative conditions.

Altered behavior, brain structure, and neurometabolites in a rat model of autism-specific maternal autoantibody exposure

Maternal immune dysregulation is a prenatal risk factor for autism spectrum disorder (ASD). Importantly, a clinically relevant connection exists between inflammation and metabolic stress that can result in aberrant cytokine signaling and autoimmunity. In this study we examined the potential for maternal autoantibodies (aAbs) to disrupt metabolic signaling and induce neuroanatomical changes in the brains of exposed offspring. To accomplish this, we developed a model of maternal aAb exposure in rats based on the clinical phenomenon of maternal autoantibody-related ASD (MAR-ASD). Following confirmation of aAb production in rat dams and antigen-specific immunoglobulin G (IgG) transfer to offspring, we assessed offspring behavior and brain structure longitudinally. MAR-ASD rat offspring displayed a reduction in pup ultrasonic vocalizations and a pronounced deficit in social play behavior when allowed to freely interact with a novel partner. Additionally, longitudinal in vivo structural magnetic resonance imaging (sMRI) at postnatal day 30 (PND30) and PND70, conducted in a separate cohort of animals, revealed sex-specific differences in total and regional brain volume. Treatment-specific effects by region appeared to converge on midbrain and cerebellar structures in MAR-ASD offspring. Simultaneously, in vivo 1H magnetic resonance spectroscopy (1H-MRS) data were collected to examine brain metabolite levels in the medial prefrontal cortex. Results showed that MAR-ASD offspring displayed decreased levels of choline-containing compounds and glutathione, accompanied by increased taurine compared to control animals. Overall, we found that rats exposed to MAR-ASD aAbs present with alterations in behavior, brain structure, and neurometabolites; reminiscent of findings observed in clinical ASD.

Cross-sectional Exploration of the Relationship Between Glutamate Abnormalities and Tic Disorder Severity Using Proton Magnetic Resonance Spectroscopy

Glutamate (Glu) has been reported to be closely related to the pathophysiology of Tic Disorders (TD). By using proton magnetic resonance spectroscopy (1H-MRS), we aimed to investigate the relationship between in vivo Glu levels and the severity of TD. We performed a cross-sectional study in medication-free patients with TD and healthy controls aged between 5 and 13 years using 1H-MRS at 3 T. First, we measured the Glu levels in both patients and controls and observed the difference in subgroups, including mild TD patients and moderate TD patients. We then examined the correlations between the Glu levels and clinical features of the patients. Finally, we assessed the diagnostic value of 1H-MRS and the influencing factors. Our results show that the Glu levels in the striatum of all patients with TD were not significantly different from those of the healthy controls. Subgroup analysis revealed that the Glu levels in the moderate TD group were higher than those in the mild TD group and healthy controls. The correlation analysis showed that Glu levels are strongly positive correlated with TD severity. The optimal cutoff value of Glu levels to differentiate mild tics from moderate tics was 1.244, with a sensitivity of 88.2% and a specificity of 94.7%. Multiple linear regression models revealed that the severity of TD is one of the important factors that affect Glu levels. We conclude that Glu levels are mainly associated with the severity of tics, thus it could serve as a key biomarker for TD classification.

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate

ABSTRACT

Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

Cognitive dysfunction and neurometabolic alternations in major depressive disorder with gastrointestinal symptoms

BACKGROUND

Brain biochemical abnormalities have been associated with major depressive disorder (MDD) and cognitive impairments. However, the cognitive performance and neurometabolic alterations of MDD patients accompanied by gastrointestinal (GI) symptoms remain to be elucidated. We aimed to reveal the features and correlation between cognitive impairments and brain biochemical abnormalities of depressed patients with GI symptoms.

METHODS

Fifty MDD patients with GI symptoms (GI group), 46 patients without GI symptoms (NGI group) and 50 demographically matched healthy controls (HCs) underwent Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) assessments. In addition, proton magnetic resonance spectroscopy (¹H-MRS) was used to obtain ratios of N-acetyl aspartate to creatine (NAA/Cr) and choline-containing compounds to creatine (Cho/Cr) in the thalamus, putamen and anterior cingulate cortex (ACC). Finally, association analysis was conducted to investigate the relationships of these measurements.

RESULTS

Compared to HCs, participants in both the GI and NGI groups had significantly reduced performance in the six MCCB cognitive domains (all p < 0.05), except for reasoning and problem solving. Higher Cho/Cr ratios in the right thalamus (p < 0.05) and lower NAA/Cr ratios in the left putamen (p < 0.05) were found in the NGI group than in the GI group. The severity of GI symptoms was negatively correlated with Cho/Cr ratios in the right ACC (r = -0.288, p = 0.037). In addition, the T-scores of visual learning were negatively correlated with NAA/Cr ratios in the right ACC (r = -0.443, p = 0.001) and right thalamus (r = -0.335, p = 0.015).

CONCLUSION

Our findings suggest that MDD patients with GI symptoms may exhibit greater neurometabolic alternations than those without GI symptoms, while both show similar cognitive dysfunction. In addition, neurometabolic alterations in the ACC and thalamus may underlie the neural basis of GI symptoms and cognitive impairment in MDD.

BDNF rs6265 differentially influences neurometabolites in the anterior cingulate of healthy and bipolar disorder subjects

Brain-derived neurotrophic factor (BDNF) is the most abundant brain neurotrophin and plays a critical role in neuronal growth, survival and plasticity, implicated in the pathophysiology of Bipolar Disorders (BD). The single-nucleotide polymorphism in the BDNF gene (BDNF rs6265) has been associated with decreased hippocampal BDNF secretion and volume in met carriers in different populations, although the val allele has been reported to be more frequent in BD patients. The anterior cingulate cortex (ACC) is a key center integrating cognitive and affective neuronal connections, where consistent alterations in brain metabolites such as Glx (Glutamate + Glutamine) and N-acetylaspartate (NAA) have been consistently reported in BD. However, little is known about the influence of BDNF rs6265 on neurochemical profile in the ACC of Healthy Controls (HC) and BD subjects. The aim of this study was to assess the influence of BDNF rs6265 on ACC neurometabolites (Glx, NAA and total creatine- Cr) in 124 euthymic BD type I patients and 76 HC, who were genotyped for BDNF rs6265 and underwent a 3-Tesla proton magnetic resonance imaging and spectroscopy scan (¹ H-MRS) using a PRESS ACC single-voxel (8cm³) sequence. BDNF rs6265 polymorphism showed a significant two-way interaction (diagnosis × genotype) in relation to NAA/Cr and total Cr. While met carriers presented increased NAA/Cr in HC, BD-I subjects with the val allele revealed higher total Cr, denoting an enhanced ACC metabolism likely associated with increased glutamatergic metabolites observed in BD-I val carriers. However, these results were replicated only in men. Therefore, our results support evidences that the BDNF rs6265 polymorphism exerts a complex pleiotropic effect on ACC metabolites influenced by the diagnosis and sex.

Iron- and Neuromelanin-Weighted Neuroimaging to Study Mitochondrial Dysfunction in Patients with Parkinson's Disease

The underlying causes of Parkinson's disease are complex, and besides recent advances in elucidating relevant disease mechanisms, no disease-modifying treatments are currently available. One proposed pathophysiological hallmark is mitochondrial dysfunction, and a plethora of evidence points toward the interconnected nature of mitochondria in neuronal homeostasis. This also extends to iron and neuromelanin metabolism, two biochemical processes highly relevant to individual disease manifestation and progression. Modern neuroimaging methods help to gain in vivo insights into these intertwined pathways and may pave the road to individualized medicine in this debilitating disorder. In this narrative review, we will highlight the biological rationale for studying these pathways, how distinct neuroimaging methods can be applied in patients, their respective limitations, and which challenges need to be overcome for successful implementation in clinical studies.

Revisiting the use of proton magnetic resonance spectroscopy in distinguishing between primary and secondary malignant tumors of the central nervous system

BACKGROUND AND PURPOSE

Conventional magnetic resonance images (MRI) has limitations in distinguishing primary from secondary brain tumors. Proton magnetic resonance spectroscopy (1H-MRS) allows evaluation of the concentration of metabolites in a brain lesion and, hence, better characterization of the tumor. Considering that an accurate diagnosis determines the choice of treatment, our purpose was to assess the usefulness of spectroscopy data for differentiating between primary and secondary brain neoplasms.

MATERIALS AND METHODS

We undertook a retrospective analysis of 61 MRI and 1H-MRS images of patients with histologically confirmed tumors (30 primary tumors and 31 metastatic tumors). The metabolite ratios of Cho/Cr and NAA/Cr at short TE were determined from spectroscopic curves, with a single voxel positioned in the enhancing tumor. Additional variables analyzed along with the metabolites, like as age and gender, allowed the construction of a logistic regression model to predict the tumor's nature. The statistical analysis was done using the R software (version 4.0.3 R Core Team, 2020).

RESULTS

The mean NAA/Cr and Cho/Cr ratios were higher in secondary tumors, with a good correlation between NAA/Cr and Cho/Cr (r = 0.61). The mean age of patients with primary tumors was lower than for secondary tumors (43.9 vs 55.9, respectively). Receiver operating characteristic analysis yielded a cut-off value of 0.4 for the NAA/Cr ratio with an accuracy of 73.8%, a sensitivity of 73.3% and a specificity of 74.2% in predicting metastatic tumors.

CONCLUSION

The model was reasonable in predicting the nature of the tumor and provides an additional tool for analyzing brain tumors.

Neuroinflammation in HIV-associated depression: evidence and future perspectives

People living with HIV face a high risk of mental illness, especially depression. We do not yet know the precise neurobiological mechanisms underlying HIV-associated depression. Depression severity in the general population has been linked to acute and chronic markers of systemic inflammation. Given the associations between depression and peripheral inflammation, and since HIV infection in the brain elicits a neuroinflammatory response, it is possible that neuroinflammation contributes to the high prevalence of depression amongst people living with HIV. The purpose of this review was to synthesise existing evidence for associations between inflammation, depression, and HIV. While there is strong evidence for independent associations between these three conditions, few preclinical or clinical studies have attempted to characterise their interrelationship, representing a major gap in the literature. This review identifies key areas of debate in the field and offers perspectives for future investigations of the pathophysiology of HIV-associated depression. Reproducing findings across diverse populations will be crucial in obtaining robust and generalisable results to elucidate the precise role of neuroinflammation in this pathophysiology.

A novel method for Magnetic Resonance Spectroscopy lipid signal suppression using Semi-classical signal analysis and Bidirectional Long short-term memory

Magnetic resonance spectroscopy (MRS) is a non-invasive method that enables the analysis and quantification of brain metabolites, which provide useful information about the neuro-biological substrates of brain function. Lactate plays a pivotal role in the diagnosis of various brain diseases. However, accurate lactate quantification is generally difficult to achieve due to the presence of large lipid peaks resonating at a similar spectral position. To overcome this problem several techniques have been proposed. However, most of them suffer from lactate signal loss or poor lipid peak removal. In this paper, a novel method for lipid suppression for MRS signal is proposed. The method combines a semi-classical signal analysis method and a bidirectional long short term memory technique. The method is validated using simulated data that mimics real MRS data.

Neuroimaging Methods to Map In Vivo Changes of OXPHOS and Oxidative Stress in Neurodegenerative Disorders

Mitochondrial dysfunction is a pathophysiological hallmark of most neurodegenerative diseases. Several clinical trials targeting mitochondrial dysfunction have been performed with conflicting results. Reliable biomarkers of mitochondrial dysfunction in vivo are thus needed to optimize future clinical trial designs. This narrative review highlights various neuroimaging methods to probe mitochondrial dysfunction. We provide a general overview of the current biological understanding of mitochondrial dysfunction in degenerative brain disorders and how distinct neuroimaging methods can be employed to map disease-related changes. The reviewed methodological spectrum includes positron emission tomography, magnetic resonance, magnetic resonance spectroscopy, and near-infrared spectroscopy imaging, and how these methods can be applied to study alterations in oxidative phosphorylation and oxidative stress. We highlight the advantages and shortcomings of the different neuroimaging methods and discuss the necessary steps to use these for future research. This review stresses the importance of neuroimaging methods to gain deepened insights into mitochondrial dysfunction in vivo, its role as a critical disease mechanism in neurodegenerative diseases, the applicability for patient stratification in interventional trials, and the quantification of individual treatment responses. The in vivo assessment of mitochondrial dysfunction is a crucial prerequisite for providing individualized treatments for neurodegenerative disorders.

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.

Magnetic Resonance Spectroscopy and Bipolar Disorder: How Feasible Is This Pairing?

Bipolar disorder is a psychiatric disorder that affects a significant part of the world's population; however, its diagnosis is difficult, mainly because of the lack of biomarkers and objective tests that aid the clinical evaluation. Proton magnetic resonance spectroscopy (MRS) is a tool that is relatively unused in the medical field. Its application arises from conventional magnetic resonance, and allows non-invasive, in vivo, the study of various metabolites and compounds in the human brain. This method may allow the assessment of neurobiochemical alterations in bipolar patients. One of the main advantages of this study type is the simplicity in its use since it only needs a standard magnetic resonator. All these characteristics make it an attractive diagnostic tool that can be used anywhere, including in low-middle-income countries. In conclusion, MRS has potential as a diagnostic tool for bipolar disorder; nevertheless, using it for this purpose still requires additional steps.

Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review

Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.

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.

31-Phosphorus Magnetic Resonance Spectroscopy in Evaluation of Glioma and Metastases in 3T MRI

Background:  31-Phosphorus magnetic resonance spectroscopy (31-P MRS) has excellent potential for clinical neurological practice because of its noninvasive in-vivo assessment of cellular energy metabolism and the indirect evaluation of the phospholipid composition of the cell membrane, intracellular pH, and intracellular Mg2+ concentration.

Purpose:  The aim of this study was to evaluate the metabolic characteristics of glioma and metastases using 31-P MRS and assess utility to differentiate both.

Study Type:  Prospective study.

Population:  Fifteen consecutive patients with brain tumor.

Field Strength/Sequence:  Three-tesla magnetic resonance imaging/three-dimensional MRS imaging sequence.

Statistical Tests:  Unpaired sample t -test, and one-way analysis of variance with Tukey's post-hoc test.

Results:  Significantly decreased values of phosphomonoesters/inorganic phosphate (PME/Pi) in the tumor group (1.22 ± 0.72) compared with controls (2.28 ± 1.44) with a p -value of 0.041 were observed. There is a significant decrease in phosphocreatine (PCr)/Pi values (energy demand) in the tumor group (2.76 ± 0.73) compared with controls (4.13 ± 1.75) with a p -value of 0.050. Significant increase in Pi/adenosine triphosphate (ATP) was noted in tumor group (0.28 ± 0.09) compared with controls (0.22 ± 0.08) with p -value 0.049. Among tumor group, PME/PCr values were significantly decreased in gliomas (0.35 ± 0.17) than metastasis (0.58 ± 0.23) compared with controls with a p -value of 0.047. A significant decrease in PME/ATP was noted in gliomas (0.25 ± 0.12) than metastasis (0.41 ± 0.14) compared with controls with a p -value of 0.034. The tumor group exhibits alkaline pH (7.12 ± 0.10) compared with the normal parenchyma (7.04 ± 0.06) with a significant p -value of 0.025. Glioma and metastasis could not be differentiated with pH. However, the perilesional edema of glioma shows alkaline pH (7.09 ± 0.06) and metastasis shows acidic pH (7.02 ± 0.05) with a significant p -value of 0.030.

Conclusion:  Our study provides new insight into the cellular constituents and pH of gliomas and metastases and results were significant in differentiation between these two. However, due to the additional high expense, it is available as a research tool in very few institutions in India.

Tapentadol and oxycodone reduce cingulate glutamate in healthy volunteers

Tapentadol and oxycodone are commonly used analgesics. Preclinical studies have shown that oxycodone modulates brain metabolites related to opioid pathways, whereas tapentadol also affects noradrenergic activity. However, knowledge about the function of the medications in the human brain is limited. The aim was to investigate effects of tapentadol and oxycodone on brain glutamate, the most important neurotransmitter in pain processing. Magnetic resonance spectroscopy was obtained in 21 healthy subjects from the anterior cingulate cortex, prefrontal cortex, and insula at baseline and after 14 days of treatment with either 50 mg tapentadol, 10 mg oxycodone (equipotent dose, both extended release) or placebo twice daily in a randomized double-blind cross-over study. Compared to baseline, decreased glutamate/creatine levels were identified in anterior cingulate cortex after tapentadol (1.26 ± 0.14 vs. 1.35 ± 0.18, P = .04) and oxycodone (1.26 ± 0.10 vs. 1.35 ± 0.12, P = .05) treatments, both with 7% reduction. This indicates that both analgesics modulate the glutamatergic system at the supraspinal level in humans.

Application of Magnetic Resonance Imaging in the Evaluation of Nutritional Status: A Literature Review with Focus on Dialysis Patients

Magnetic resonance imaging (MRI) is indispensable in clinical medicine for the morphological and tomographic evaluation of many parenchymal organs. With varied imaging methods, diverse biological information, such as the perfusion volume and measurements of metabolic products, can be obtained. In addition to conventional MRI for morphological assessment, diffusion-weighted MRI/diffusion tensor imaging is used to evaluate white matter structures in the brain; arterial spin labeling is used for cerebral blood flow evaluation; magnetic resonance elastography for fatty liver and cirrhosis evaluation; magnetic resonance spectroscopy for evaluation of metabolites in specific regions of the brain; and blood oxygenation level-dependent imaging for neurological exploration of eating behavior, obesity, and food perception. This range of applications will continue to expand in the future. Nutritional science is a multidisciplinary and all-inclusive field of research; therefore, there are many different applications of MRI. We present a literature review of MRI techniques that can be used to evaluate the nutritional status, particularly in patients on dialysis. We used MEDLINE as the information source, conducted a keyword search in PubMed, and found that, as a nutritional evaluation method, MRI has been used frequently to comprehensively and quantitatively evaluate muscle mass for the determination of body composition.

Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities

Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient's clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.

Anterior cingulate cortex neurometabolites in bipolar disorder are influenced by mood state and medication: A meta-analysis of 1H-MRS studies

The anterior cingulate cortex (ACC), a brain region that mediates affect and cognition by connecting the frontal cortex to limbic structures, has been consistently implicated in the neurobiology of Bipolar Disorder (BD). Proton magnetic resonance spectroscopy (¹H-MRS) studies have extensively compared in vivo neurometabolite levels of BD patients and healthy controls (HC) in the ACC. However, these studies have not been analyzed in a systematic review or meta-analysis and nor has the influence of mood state and medication on neurometabolites been examined in this cortical region. A systematic review and a meta-analysis of ¹H-MRS studies comparing ACC neurometabolite profiles of adult BD patients and HC subjects was conducted, retrieving 27 articles published between 2000 and 2018. Overall increased ACC levels of Glx [glutamine (Gln) + glutamate)/Creatine], Gln, choline (Cho) and Cho/Creatine were found in BD compared to HC. Bipolar depression was associated with higher Cho levels, while euthymia correlated with higher glutamine (Gln) and Cho. Mood stabilizers appeared to affect ACC Glu and Gln metabolites. Increased ACC Cho observed in euthymia, depression and in medication-free groups could be considered a trait marker in BD and attributed to increased cell membrane phospholipid turnover. Overall increased ACC Glx was associated with elevated Gln levels, particularly influenced by euthymia, but no abnormality in Glu was detected. Further ¹H-MRS studies, on other voxels, should assess more homogeneous (mood state-specific), larger BD samples and account for medication status using more sensitive ¹H-MRS techniques.

Strategies to Understand the Weight-Reduced State: Genetics and Brain Imaging

Most individuals with obesity or overweight have difficulty maintaining weight loss. The weight-reduced state induces changes in many physiological processes that appear to drive weight regain. Here, we review the use of cell biology, genetics, and imaging techniques that are being used to begin understanding why weight regain is the normal response to dieting. As with obesity itself, weight regain has both genetic and environmental drivers. Genetic drivers for "thinness" and "obesity" largely overlap, but there is evidence for specific genetic loci that are different for each of these weight states. There is only limited information regarding the genetics of weight regain. Currently, most genetic loci related to weight point to the central nervous system as the organ responsible for determining the weight set point. Neuroimaging tools have proved useful in studying the contribution of the central nervous system to the weight-reduced state in humans. Neuroimaging technologies fall into three broad categories: functional, connectivity, and structural neuroimaging. Connectivity and structural imaging techniques offer unique opportunities for testing mechanistic hypotheses about changes in brain function or tissue structure in the weight-reduced state.

"Omics" in traumatic brain injury: novel approaches to a complex disease

BACKGROUND

To date, there is neither any pharmacological treatment with efficacy in traumatic brain injury (TBI) nor any method to halt the disease progress. This is due to an incomplete understanding of the vast complexity of the biological cascades and failure to appreciate the diversity of secondary injury mechanisms in TBI. In recent years, techniques for high-throughput characterization and quantification of biological molecules that include genomics, proteomics, and metabolomics have evolved and referred to as omics.

METHODS

In this narrative review, we highlight how omics technology can be applied to potentiate diagnostics and prognostication as well as to advance our understanding of injury mechanisms in TBI.

RESULTS

The omics platforms provide possibilities to study function, dynamics, and alterations of molecular pathways of normal and TBI disease states. Through advanced bioinformatics, large datasets of molecular information from small biological samples can be analyzed in detail and provide valuable knowledge of pathophysiological mechanisms, to include in prognostic modeling when connected to clinically relevant data. In such a complex disease as TBI, omics enables broad categories of studies from gene compositions associated with susceptibility to secondary injury or poor outcome, to potential alterations in metabolites following TBI.

CONCLUSION

The field of omics in TBI research is rapidly evolving. The recent data and novel methods reviewed herein may form the basis for improved precision medicine approaches, development of pharmacological approaches, and individualization of therapeutic efforts by implementing mathematical "big data" predictive modeling in the near future.

Motion correction in magnetic resonance spectroscopy

In vivo proton magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) are valuable tools to study normal and abnormal human brain physiology. However, they are sensitive to motion, due to strong crusher gradients, long acquisition times, reliance on high magnetic field homogeneity, and particular acquisition methods such as spectral editing. The effects of motion include incorrect spatial localization, phase fluctuations, incoherent averaging, line broadening, and ultimately quantitation errors. Several retrospective methods have been proposed to correct motion-related artifacts. Recent advances in hardware also allow prospective (real-time) correction of the effects of motion, including adjusting voxel location, center frequency, and magnetic field homogeneity. This article reviews prospective and retrospective methods available in the literature and their implications for clinical MRS/MRSI. In combination, these methods can attenuate or eliminate most motion-related artifacts and facilitate the acquisition of high-quality data in the clinical research setting.

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

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

Current Methods of Magnetic Resonance for Noninvasive Assessment of Molecular Aspects of Pathoetiology in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disease with expanding axonal and neuronal degeneration in the central nervous system leading to motoric dysfunctions, psychical disability, and cognitive impairment during MS progression. The exact cascade of pathological processes (inflammation, demyelination, excitotoxicity, diffuse neuro-axonal degeneration, oxidative and metabolic stress, etc.) causing MS onset is still not fully understood, although several accompanying biomarkers are particularly suitable for the detection of early subclinical changes. Magnetic resonance (MR) methods are generally considered to be the most sensitive diagnostic tools. Their advantages include their noninvasive nature and their ability to image tissue in vivo. In particular, MR spectroscopy (proton 1H and phosphorus 31P MRS) is a powerful analytical tool for the detection and analysis of biomedically relevant metabolites, amino acids, and bioelements, and thus for providing information about neuro-axonal degradation, demyelination, reactive gliosis, mitochondrial and neurotransmitter failure, cellular energetic and membrane alternation, and the imbalance of magnesium homeostasis in specific tissues. Furthermore, the MR relaxometry-based detection of accumulated biogenic iron in the brain tissue is useful in disease evaluation. The early description and understanding of the developing pathological process might be critical for establishing clinically effective MS-modifying therapies.

Interactions between in vivo neuronal-glial markers, side of hippocampal sclerosis, and pharmacoresponse in temporal lobe epilepsy

OBJECTIVE

To evaluate the interactions of metabolic neuronal-glial changes with the presence and hemispheric-side of hippocampal sclerosis (HS) and its potential role in predicting pharmacoresistance in temporal lobe epilepsy (TLE).

METHODS

We included structural magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (¹ H-MRS) metabolic data for 91 patients with unilateral TLE and 50 healthy controls. We measured the values of total N-acetyl aspartate/total creatine (tNAA/tCr), glutamate/tCr (Glu/tCr), and myo-inositol/tCr (mIns/tCr). To assess the influence of the pharmacoresponse and hemispheric-side of HS on metabolic data, the relationship between clinical and MRI data, and the predictive value of NAA/Cr, we used analysis of variance/covariance and built a logistic regression model. We used bootstrap simulations to evaluate reproducibility.

RESULTS

Bilateral tNAA/tCr reduction was associated with pharmacoresistance and with left HS, a decrease of Glu/tCr ipsilateral to the seizure focus was associated with pharmacoresistance, and ipsilateral mIns/tCr increase was related to pharmacoresistance and the presence of left HS. The logistic regression model containing clinical and ¹ H-MRS data discriminated pharmacoresistance (area under the curve [AUC] = 0.78). However, the reduction of tNAA/tCr was the main predictor, with the odds 2.48 greater for pharmacoresistance.

SIGNIFICANCE

Our study revealed a spectrum of neuronal-glial changes in TLE, which was associated with pharmacoresistance, being more severe in left-sided HS and less severe in MRI-negative TLE. These noninvasive, in vivo biomarkers provide valuable additional information about the interhemispheric differences in metabolic dysfunction, seizure burden, and HS, and may help to predict pharmacoresistance.

Neuroimaging Findings in Chronic Hepatitis C Virus Infection: Correlation with Neurocognitive and Neuropsychiatric Manifestations

Chronic hepatitis C virus (HCV) infection is commonly associated with neurocognitive dysfunction, altered neuropsychological performance and neuropsychiatric symptoms. Quantifiable neuropsychological changes in sustained attention, working memory, executive function, verbal learning and recall are the hallmark of HCV-associated neurocognitive disorder (HCV-AND). This constellation is at variance with the neuropsychological complex that is seen in minimal hepatic encephalopathy, which is typified by an array of alterations in psychomotor speed, selective attention and visuo-constructive function. Noncognitive symptoms, including sleep disturbances, depression, anxiety and fatigue, which are less easily quantifiable, are frequently encountered and can dominate the clinical picture and the clinical course of patients with chronic HCV infection. More recently, an increased vulnerability to Parkinson’s disease among HCV-infected patients has also been reported. The degree to which neurocognitive and neuropsychiatric changes are due to HCV replication within brain tissues or HCV-triggered peripheral immune activation remain to be determined. Without absolute evidence that clearly exonerates or indicts HCV, our understanding of the so-called “HCV brain syndrome”, relies primarily on clinical and neuropsychological assessments, although other comorbidities and substance abuse may impact on neurocognitive function, thus confounding an appropriate recognition. In recent years, a number of functional and structural brain imaging studies have been of help in recognizing possible biological markers of HCV-AND, thus providing a rationale for guiding and justifying antiviral therapy in selected cases. Here, we review clinical, neuroradiological, and therapeutic responses to interferon-based and interferon-free regimens in HCV-related cognitive and neuropsychiatric disorder.

In Vivo Imaging of Neuroinflammatory Targets in Treatment-Resistant Epilepsy

PURPOSE OF REVIEW

Recent evidence indicates that chronic, low-level neuroinflammation underlies epileptogenesis. Targeted imaging of key neuroinflammatory cells, receptors, and tissues may enable localizing epileptogenic onset zone, especially in those patients who are treatment-resistant and considered MRI-negative. Finding a specific, sensitive neuroimaging-based biomarker could aid surgical planning and improve overall prognosis in eligible patients. This article reviews recent research on in vivo imaging of neuroinflammatory targets in patients with treatment-resistant, non-lesional epilepsy.

RECENT FINDINGS

A number of advanced approaches based on imaging neuroinflammation are being implemented in order to assist localization of epileptogenic onset zone. The most exciting tools are based on radioligand-based nuclear imaging or revisiting of existing technology in novel ways. The greatest limitations stem from gaps in knowledge about the exact function of neuroinflammatory targets (e.g., neurotoxic or neuroprotective). Further, lingering questions about each approach's specificity, reliability, and sensitivity must be addressed, and clinical utility must be validated before any novel method is incorporated into mainstream clinical practice. Current applications of imaging neuroinflammation in humans are limited and underutilized, but offer hope for finding sensitive and specific neuroimaging-based biomarker(s). Future work necessitates appreciation of investigations to date, significant findings, and neuroinflammatory targets worth exploring further.

PET/MRI Radiomics in Patients With Brain Metastases

Although a variety of imaging modalities are used or currently being investigated for patients with brain tumors including brain metastases, clinical image interpretation to date uses only a fraction of the underlying complex, high-dimensional digital information from routinely acquired imaging data. The growing availability of high-performance computing allows the extraction of quantitative imaging features from medical images that are usually beyond human perception. Using machine learning techniques and advanced statistical methods, subsets of such imaging features are used to generate mathematical models that represent characteristic signatures related to the underlying tumor biology and might be helpful for the assessment of prognosis or treatment response, or the identification of molecular markers. The identification of appropriate, characteristic image features as well as the generation of predictive or prognostic mathematical models is summarized under the term radiomics. This review summarizes the current status of radiomics in patients with brain metastases.

Magnetic resonance spectroscopy across chronic pain disorders: a systematic review protocol synthesising anatomical and metabolite findings in chronic pain patients

BACKGROUND

Chronic pain is pain greater than 3 months duration that may result from disease, trauma, surgery, or unknown origin. The overlap between the psychological, behavioural, and management aspects of pain suggest that limbic brain neurochemistry plays a role in chronic pain pathology. Proton magnetic resonance spectroscopy (1H-MRS) can evaluate in vivo brain metabolites including creatine, N-acetylaspartate, myo-inositol, choline, glutamate, glutamine, and gamma-aminobutyric acid in chronic pain; however, a comprehensive systemic review of metabolite expression patterns across all brain areas has yet to be performed.

METHODS AND ANALYSIS

Online databases including PubMed/MEDLINE, Google Scholar, EMBASE, the Cochrane Library, OVID, and PsycINFO will be searched for articles relating to 1H-MRS and chronic pain. Study inclusion criteria will include ages of between 18 and 65 years with a definite diagnosis of chronic pain, no comorbidities, clearly stated brain volumes of interest, and imaging protocols, with comparisons to healthy controls. Two reviewers will extract data relating to volumes of interest, metabolites, study participant demographics, diagnostic method and pain scores, treatments and duration of treatment, scanner information, 1H-MRS acquisition protocols, and spectral processing software. Where possible, volumes of interest will be reassigned as regions of interest consistent with known regional anatomical and functional properties to increase the power and relevance of the analysis. Statistical analyses will then be conducted using STATA. A central common pathway may exist for chronic pain due to the behavioural manifestations and management similarities between its different types. The goal of this systemic review is to generate a comprehensive neurochemical theory of chronic pain in different brain compartments.

SYSTEMATIC REVIEW REGISTRATION

This study is registered with PROSPERO CRD42018112640.

Painful and Painless Diabetic Neuropathies: What Is the Difference?

PURPOSE OF REVIEW

The prevalence of diabetes mellitus and its chronic complications are increasing to epidemic proportions. This will unfortunately result in massive increases in diabetic distal symmetrical polyneuropathy (DPN) and its troublesome sequelae, including disabling neuropathic pain (painful-DPN), which affects around 25% of patients with diabetes. Why these patients develop neuropathic pain, while others with a similar degree of neuropathy do not, is not clearly understood. This review will look at recent advances that may shed some light on the differences between painful and painless-DPN.

RECENT FINDINGS

Gender, clinical pain phenotyping, serum biomarkers, brain imaging, genetics, and skin biopsy findings have been reported to differentiate painful- from painless-DPN. Painful-DPN seems to be associated with female gender and small fiber dysfunction. Moreover, recent brain imaging studies have found neuropathic pain signatures within the central nervous system; however, whether this is the cause or effect of the pain is yet to be determined. Further research is urgently required to develop our understanding of the pathogenesis of pain in DPN in order to develop new and effective mechanistic treatments for painful-DPN.

General technical remarks on 1HMRS translational research in 7T

Purpose

The aim of the work was to share the practical experience of preclinical and clinical proton magnetic resonance spectroscopy (¹HMRS) studies conducted using a 7-Tesla magnetic field strength scanner, taking into account the specificity of both settings in the context of translational research.

Material and methods

¹HMRS volunteer studies conducted using a Discovery 950 GE 7T scanner, were carried out with PRESS sequence, and a VOI measuring 2.0 × 2.0 × 2.0 cm³ placed in the white matter at the parietal occipital lobe. Rodent spectra obtained using a 7T Bruker were measured with PRESS, with a VOI 2.0 × 2.0 × 5.5 mm³ placed over the hippocampus.

Results

¹HMRS data from humans and rats show that the brain spectra obtained in the same field are characterised by a similar neurochemical structure and spectral resolution. Spectra obtained from rats demonstrate the following metabolites: NAA, Glu, Gln, Ins, Cho, Cr, PCr, Tau, GABA, Lac, NAAG, and Asp. In turn, spectra from humans allowed estimation of the following metabolites: Ala, NAA, Glu, Gln, Ins, Cho, Cr, PCr, Tau, GABA, Lac, NAAG, and Asp. Signals from Gln, Glu with chemical shift around 2.4 ppm, from Cr, PCr, and GABA at 3 ppm, and signals from Cho and Tau at approximately 3.2 ppm, can be properly separated and estimated both in humans and in rats.

Conclusions

These results are promising in terms of broadening the knowledge of many neurological diseases by inducing them on animal models and then transferring this knowledge to clinical practice. In spite of this, important distinctions in the technical aspects and methodological differences of high-field ¹HMRS in both preclinical and clinical conditions should be taken into account.

Reproducibility of brain MRS in older healthy adults at 7T

To date, the majority of MRS reproducibility studies have been conducted in healthy younger adults, with only a few conducted in older adults at 3 T. With the growing interest in applying MRS methods to study the longitudinal course and effects of treatments in neurodegenerative disease, it is important to establish reproducibility in age-matched controls, especially in older individuals. In this study, spectroscopic data were acquired using a stimulated echo acquisition mode (STEAM) localization technique in two regions (anterior and posterior cingulate cortices-ACC, PCC, respectively) in 10 healthy, cognitively normal older adults (64 ± 8.1 years). Reproducibility was assessed via mean coefficients of variation (CVs) and relative differences (RDs) calculated across two visits performed 2-3 months apart. Metabolites with high signal-to-noise ratio (SNR) such as NAA, tCho, and Glu had mean CVs of 10% or less and mean RDs of 15% or less across both regions. Metabolites with lower SNR such as GABA and Gln had slightly higher mean CVs of 22% or less and mean RDs of 27% or less across both regions. These results demonstrate the feasibility of acquiring MRS data at 7 T in older subjects, and establish that the spectroscopic data are reproducible in both the ACC and PCC in older, healthy subjects to the same extent as in previous studies in young subjects.

A comprehensive regional neurochemical theory in depression: a protocol for the systematic review and meta-analysis of 1H-MRS studies in major depressive disorder

BACKGROUND

Magnetic resonance spectroscopy (MRS) is a non-invasive analytical technique that investigates the presence and concentrations of brain metabolites. In the context of major depressive disorder (MDD), MRS has revealed regional biochemical changes in GABA, glutamate, and choline across different brain compartments. Technical and methodological advances in MRS data acquisition, in particular proton-based 1H-MRS, have resulted in a significant increase in the incidence of reports utilizing the technique for psychiatric disorder research and diagnosis. The most recent comprehensive meta-analysis reviewing MRS in MDD stems from 2006. Using contemporary systemic reviews and meta-analysis, the aim is to first test a neurochemical circuit-based theory of depression and then to determine if clinical scores relate to metabolite concentrations before and during treatment.

METHODS

Region-specific metabolite changes in MDD will be assessed by systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Inclusion criteria will include participant age (18 to 65), English language studies, known regions of interest, and detailed documentation of 1H-MRS procedures. Reported brain regions will be standardized according neuroanatomical expertise allowing increased power of the meta-analysis. Regions of interest will initially include the hippocampus, thalamus, prefrontal cortex, anterior and posterior cingulate gyri, parietal lobe, and basal ganglia. Exclusion criteria will include comorbid psychiatric illness and drug use. Two independent reviewers will undertake all data extraction, while a third reviewer will check for reviewer discrepancies. Statistical analysis will be performed using STATA supplemented by Metan software and SPSS.

DISCUSSION

This data will shed new light on the biochemical basis of depression in different brain regions, thereby highlighting the potential of MRS in identifying biomarkers and generating models of MDD and treatment response.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42018091494.

7T 1H-MRS in major depressive disorder: a Ketamine Treatment Study

The glutamatergic modulator ketamine has striking and rapid antidepressant effects in major depressive disorder (MDD), but its mechanism of action remains unknown. Proton magnetic resonance spectroscopy (1H-MRS) is the only non-invasive method able to directly measure glutamate levels in vivo; in particular, glutamate and glutamine metabolite concentrations are separable by 1H-MRS at 7T. This double-blind, placebo-controlled, crossover study that included ¹H-MRS scans at baseline and at 24 h post ketamine and post-placebo infusions sought to determine glutamate levels in the pregenual anterior cingulate (pgACC) of 20 medication-free MDD subjects and 17 healthy volunteers (HVs) 24 h post ketamine administration, and to evaluate any other measured metabolite changes, correlates, or predictors of antidepressant response. Metabolite levels were compared at three scan times (baseline, post-ketamine, and post-placebo) in HVs and MDD subjects at 7T using a ¹H-MRS sequence specifically optimized for glutamate. No significant between-group differences in ¹H-MRS-measured metabolites were observed at baseline. Antidepressant response was not predicted by baseline glutamate levels. Our results suggest that any infusion-induced increases in glutamate at the 24-h post ketamine time point were below the sensitivity of the current technique; that these increases may occur in different brain regions than the pgACC; or that subgroups of MDD subjects may exist that have a differential glutamate response to ketamine.

Imaging Cancer Metabolism: Underlying Biology and Emerging Strategies

Dysregulated cellular metabolism is a characteristic feature of malignancy that has been exploited for both imaging and targeted therapy. With regard to imaging, deranged glucose metabolism has been leveraged using ¹⁸F-FDG PET. Metabolic imaging with ¹⁸F-FDG, however, probes only the early steps of glycolysis; the complexities of metabolism beyond these early steps in this single pathway are not directly captured. New imaging technologies-both PET with novel radiotracers and MR-based methods-provide unique opportunities to investigate other aspects of cellular metabolism and expand the metabolic imaging armamentarium. This review will discuss the underlying biology of metabolic dysregulation in cancer, focusing on glucose, glutamine, and acetate metabolism. Novel imaging strategies will be discussed within this biologic framework, highlighting particular strengths and limitations of each technique. Emphasis is placed on the role that combining modalities will play in enabling multiparametric imaging to fully characterize tumor biology to better inform treatment.

Single Session Low Frequency Left Dorsolateral Prefrontal Transcranial Magnetic Stimulation Changes Neurometabolite Relationships in Healthy Humans

Background: Dorsolateral prefrontal cortex (DLPFC) low frequency repetitive transcranial magnetic stimulation (LF-rTMS) has shown promise as a treatment and investigative tool in the medical and research communities. Researchers have made significant progress elucidating DLPFC LF-rTMS effects—primarily in individuals with psychiatric disorders. However, more efforts investigating underlying molecular changes and establishing links to functional and behavioral outcomes in healthy humans are needed.

Objective: We aimed to quantify neuromolecular changes and relate these to functional changes following a single session of DLPFC LF-rTMS in healthy participants.

Methods: Eleven participants received sham-controlled neuronavigated 1 Hz rTMS to the region most activated by a 7-letter Sternberg working memory task (SWMT) within the left DLPFC. We quantified SWMT performance, functional magnetic resonance activation and proton Magnetic resonance spectroscopy (MRS) neurometabolite measure changes before and after stimulation.

Results: A single LF-rTMS session was not sufficient to change DLPFC neurometabolite levels and these changes did not correlate with DLPFC activation changes. Real rTMS, however, significantly altered neurometabolite correlations (compared to sham rTMS), both with baseline levels and between the metabolites themselves. Additionally, real rTMS was associated with diminished reaction time (RT) performance improvements and increased activation within the motor, somatosensory and lateral occipital cortices.

Conclusion: These results show that a single session of LF-rTMS is sufficient to influence metabolite relationships and causes widespread activation in healthy humans. Investigating correlational relationships may provide insight into mechanisms underlying LF-rTMS.

Brain microstructure by multi-modal MRI: Is the whole greater than the sum of its parts?

The MRI signal is dependent upon a number of sub-voxel properties of tissue, which makes it potentially able to detect changes occurring at a scale much smaller than the image resolution. This "microstructural imaging" has become one of the main branches of quantitative MRI. Despite the exciting promise of unique insight beyond the resolution of the acquired images, its widespread application is limited by the relatively modest ability of each microstructural imaging technique to distinguish between differing microscopic substrates. This is mainly due to the fact that MRI provides a very indirect measure of the tissue properties in which we are interested. A strategy to overcome this limitation lies in the combination of more than one technique, to exploit the relative contributions of differing physiological and pathological substrates to selected MRI contrasts. This forms the basis of multi-modal MRI, a broad concept that refers to many different ways of effectively combining information from more than one MRI contrast. This paper will review a range of methods that have been proposed to maximise the output of this combination, primarily falling into one of two approaches. The first one relies on data-driven methods, exploiting multivariate analysis tools able to capture overlapping and complementary information. The second approach, which we call "model-driven", aims at combining parameters extracted by existing biophysical or signal models to obtain new parameters, which are believed to be more accurate or more specific than the original ones. This paper will attempt to provide an overview of the advantages and limitations of these two philosophies.