Neurochemical changes in the progression of Huntington's disease: A meta-analysis of in vivo1H-MRS studies.

Proton magnetic resonance spectroscopy (1H-MRS) allows measuring specific brain metabolic alterations in Huntington's disease (HD), and these metabolite profiles may serve as non-invasive biomarkers associated with disease progression. Despite this potential, previous findings are inconsistent. Accordingly, we performed a meta-analysis on available in vivo1H-MRS studies in premanifest (Pre-HD) and symptomatic HD stages (Symp-HD), and quantified neurometabolic changes relative to controls in 9 Pre-HD studies (227 controls and 188 mutation carriers) and 14 Symp-HD studies (326 controls and 306 patients). Our results indicated decreased N-acetylaspartate and creatine in the basal ganglia in both Pre-HD and Symp-HD. The overall level of myo-inositol was decreased in Pre-HD while increased in Symp-HD. Besides, Symp-HD patients showed more severe metabolism disruption than Pre-HD patients. Taken together, 1H-MRS is important for elucidating progressive metabolite changes from Pre-HD to clinical conversion; N-acetylaspartate and creatine in the basal ganglia are already sensitive at the preclinical stage and are promising biomarkers for tracking disease progression; overall myo-inositol is a possible characteristic metabolite for distinguishing HD stages.

Study on the Relationship Between MRI Functional Imaging and Multiple Immunohistochemical Features of Glioma: A Noninvasive and More Precise Glioma Management.

Objective: To investigate the performance of diffusion-tensor imaging (DTI) and hydrogen proton magnetic resonance spectroscopy (1H-MRS) parameters in predicting the immunohistochemistry (IHC) biomarkers of glioma. Methods: Patients with glioma confirmed by pathology from March 2015 to September 2019 were analyzed, the preoperative DTI and 1H-MRS images were collected, apparent diffusion coefficient (ADC) and fractional anisotropy (FA), in the lesion area were measured, the relative values relative ADC (rADC) and relative FA (rFA) were obtained by the ratio of them in the lesion area to the contralateral normal area. The peak of each metabolite in the lesion area of 1H-MRS image: N-acetylaspartate (NAA), choline (Cho), and creatine (Cr), and metabolite ratio: NAA/Cho, NAA/(Cho + Cr) were selected and calculated. The preoperative IHC data were collected including CD34, Ki-67, p53, S-100, syn, vimentin, NeuN, Nestin, and glial fibrillary acidic protein. Results: One predicting parameter of DTI was screened, the rADC of the Ki-67 positive group was lower than that of the negative group. Two parameters of 1H-MRS were found to have significant reference values for glioma grades, the NAA and Cr decreased as the grade of glioma increased, moreover, Ki-67 Li was negatively correlated with NAA and Cr. Conclusion: NAA and Cr have potential application value in predicting glioma grades and tumor proliferation activity. Only rADC has predictive value for Ki-67 expression among DTI parameters.

Impact of therapeutic inhibition of oncogenic cell signaling tyrosine kinase on cell metabolism: in vivo-detectable metabolic biomarkers of inhibition.

BACKGROUND: Inhibition of kinases is the ever-expanding therapeutic approach to various types of cancer. Typically, assessment of the treatment response is accomplished by standard, volumetric imaging procedures, performed weeks to months after the onset of treatment, given the predominantly cytostatic nature of the kinase inhibitors, at least when used as single agents. Therefore, there is a great clinical need to develop new monitoring approaches to detect the response to kinase inhibition much more promptly. Noninvasive 1H magnetic resonance spectroscopy (MRS) can measure in vitro and in vivo concentration of key metabolites which may potentially serve as biomarkers of response to kinase inhibition. METHODS: We employed mantle cell lymphoma (MCL) cell lines demonstrating markedly diverse sensitivity of inhibition of Bruton's tyrosine kinase (BTK) regarding their growth and studied in-depth effects of the inhibition on various aspects of cell metabolism including metabolite synthesis using metabolomics, glucose and oxidative metabolism by Seahorse XF technology, and concentration of index metabolites lactate, alanine, total choline and taurine by 1H MRS. RESULTS: Effective BTK inhibition profoundly suppressed key cell metabolic pathways, foremost pyrimidine and purine synthesis, the citrate (TCA) cycle, glycolysis, and pyruvate and glutamine/alanine metabolism. It also inhibited glycolysis and amino acid-related oxidative metabolism. Finally, it profoundly and quickly decreased concentration of lactate (a product of mainly glycolysis) and alanine (an indicator of amino acid metabolism) and, less universally total choline both in vitro and in vivo, in the MCL xenotransplant model. The decrease correlated directly with the degree of inhibition of lymphoma cell expansion and tumor growth. CONCLUSIONS: Our results indicate that BTK inhibition exerts a broad and profound suppressive effect on cell metabolism and that the affected index metabolites such as lactate, alanine may serve as early, sensitive, and reliable biomarkers of inhibition in lymphoma patients detectable by noninvasive MRS-based imaging method. This kind of imaging-based detection may also be applicable to other kinase inhibitors, as well as diverse lymphoid and non-lymphoid malignancies.

Noise suppression of proton magnetic resonance spectroscopy improves paediatric brain tumour classification.

Proton magnetic resonance spectroscopy (1H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± 5.3/9.3 ± 5.4), a medulloblastoma (ages 6.9 ± 3.5/6.5 ± 4.4), or a pilocytic astrocytoma (8.0 ± 3.6/6.3 ± 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1H-MRS may have better diagnostic performance for paediatric brain tumours.

Automated analysis of the total choline resonance peak in breast proton magnetic resonance spectroscopy.

The aim of the current study was to compare the performance of fully automated software with human expert interpretation of single-voxel proton magnetic resonance spectroscopy (1H-MRS) spectra in the assessment of breast lesions. Breast magnetic resonance imaging (MRI) (including contrast-enhanced T1-weighted, T2-weighted, and diffusion-weighted imaging) and 1H-MRS images of 74 consecutive patients were acquired on a 3-T positron emission tomography-MRI scanner then automatically imported into and analyzed by SpecTec-ULR 1.1 software (LifeTec Solutions GmbH). All ensuing 117 spectra were additionally independently analyzed and interpreted by two blinded radiologists. Histopathology of at least 24 months of imaging follow-up served as the reference standard. Nonparametric Spearman's correlation coefficients for all measured parameters (signal-to-noise ratio [SNR] and integral of total choline [tCho]), Passing and Bablok regression, and receiver operating characteristic analysis, were calculated to assess test diagnostic performance, as well as to compare automated with manual reading. Based on 117 spectra of 74 patients, the area under the curve for tCho SNR and integrals ranged from 0.768 to 0.814 and from 0.721 to 0.784 to distinguish benign from malignant tissue, respectively. Neither method displayed significant differences between measurements (automated vs. human expert readers, p > 0.05), in line with the results from the univariate Spearman's rank correlation coefficients, as well as the Passing and Bablok regression analysis. It was concluded that this pilot study demonstrates that 1H-MRS data from breast MRI can be automatically exported and interpreted by SpecTec-ULR 1.1 software. The diagnostic performance of this software was not inferior to human expert readers.

Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies.

Single-voxel proton magnetic resonance spectroscopy (SV 1 H-MRS) is an in vivo noninvasive imaging technique used to detect neurotransmitters and metabolites. It enables repeated measurements in living participants to build explanatory neurochemical models of psychiatric symptoms and testing of therapeutic approaches. Given the tight link among glutamate, gamma-amino butyric acid (GABA), glutathione and glutamine within the cellular machinery, MRS investigations of neurocognitive and psychiatric disorders must quantify a network of metabolites simultaneously to capture the pathophysiological states of interest. Metabolite-selective sequences typically provide improved metabolite isolation and spectral modelling simplification for a single metabolite at a time. Non-metabolite-selective sequences provide information on all detectable human brain metabolites, but feature many signal overlaps and require complicated spectral modelling. Although there are short-echo time (TE) MRS sequences that do not use spectral editing and are optimised to target either glutamate, GABA or glutathione, these approaches usually imply a precision tradeoff for the remaining two metabolites. Given the interest in assessing psychiatric and neurocognitive diseases that involve excitation-inhibition imbalances along with oxidative stress, there is a need to survey the literature on the quantification precision of current metabolite-selective MRS techniques. In this review, we locate and describe 17 studies that report on the quality of simultaneously acquired MRS metabolite data in the human brain. We note several factors that influence the data quality for single-shot acquisition of multiple metabolites of interest using metabolite-selective MRS: (1) internal in vivo references; (2) brain regions of interests; (3) field strength of scanner; and/or (4) optimised acquisition parameters. We also highlight the strengths and weaknesses of various SV spectroscopy techniques that were able to quantify in vivo glutamate, GABA and glutathione simultaneously. The insights from this review will assist in the development of new MRS pulse sequences for simultaneous, selective measurements of these metabolites and simplified spectral modelling.

Improvements in precision and accuracy of complex- relative to real-domain linear combination model spectral fitting not necessarily recovered by zero filling.

Although the information obtained from in vivo proton magnetic resonance spectroscopy (1H MRS) presents a complex-valued spectrum, spectral quantification generally employs linear combination model (LCM) fitting using the real spectrum alone. There is currently no known investigation comparing fit results obtained from LCM fitting over the full complex data versus the real data and how these results might be affected by common spectral preprocessing procedure zero filling. Here, we employ linear combination modeling of simulated and measured spectral data to examine two major ideas: first, whether use of the full complex rather than real-only data can provide improvements in quantification by linear combination modeling and, second, to what extent zero filling might influence these improvements. We examine these questions by evaluating the errors of linear combination model fits in the complex versus real domains against three classes of synthetic data: simulated Lorentzian singlets, simulated metabolite spectra excluding the baseline, and simulated metabolite spectra including measured in vivo baselines. We observed that complex fitting provides consistent improvements in fit accuracy and precision across all three data types. While zero filling obviates the accuracy and precision benefit of complex fitting for Lorentzian singlets and metabolite spectra lacking baselines, it does not necessarily do so for complex spectra including measured in vivo baselines. Overall, performing linear combination modeling in the complex domain can improve metabolite quantification accuracy relative to real fits alone. While this benefit can be similarly achieved via zero filling for some spectra with flat baselines, this is not invariably the case for all baseline types exhibited by measured in vivo data.

Early rise of glutamate-glutamine levels in mild cognitive impairment: Evidence for emerging excitotoxicity.

BACKGROUND: Use proton magnetic resonance spectroscopy (1H-MRS) non invasive technique to assess the modifications of glutamate-glutamine (Glx) and gammaaminobutyric acid (GABA) brain levels in patients reporting a cognitive complain METHODS: Posterior cingular cortex 1H-MRS spectra of 46 patients (19 male, 27 female) aged 57 to 87 years (mean : 73.32 ± 7.33 years) with a cognitive complaint were examined with a MEGA PRESS sequence at 3T, and compounds Glutamateglutamine (Glx), GABA, Creatine (Cr) and NAA were measured. From this data the metabolite ratios Glx/Cr, GABA/Cr and NAA/Cr were calculated. In addition, all patient performed the Mini Mental State Evaluation (MMSE) and 2 groups were realized with the clinical threshold of 24. RESULTS: 16 patients with MMSE 〈 24 and 30 patients with MMSE 〉 24. Significant increase of Glx/Cr in PCC of patients with MMSE 〈 24 compared to patients with MMSE 〉 24. Moreover, GABA/Cr ratio exhibited a trend for a decrease in PCC between the two groups, while they showed a significant decrease NAA/Cr ratio. CONCLUSION: Our results concerning Glx are in agreement with a physiopathological hypothesis involving a biphasic variation of glutamate levels associated with excitotoxicity, correlated with the clinical evolution of the disease. These observations suggest that MRS assessment of glutamate levels could be helpful for both diagnosis and classification of cognitive impairment in stage.

Neuronal and Glial Metabolite Abnormalities in Participants With Persistent Neuropsychiatric Symptoms After COVID-19: A Brain Proton Magnetic Resonance Spectroscopy Study.

BACKGROUND: The aim of this study was to determine whether neurometabolite abnormalities indicating neuroinflammation and neuronal injury are detectable in individuals post-coronavirus disease 2019 (COVID-19) with persistent neuropsychiatric symptoms. METHODS: All participants were studied with proton magnetic resonance spectroscopy at 3 T to assess neurometabolite concentrations (point-resolved spectroscopy, relaxation time/echo time = 3000/30 ms) in frontal white matter (FWM) and anterior cingulate cortex-gray matter (ACC-GM). Participants also completed the National Institutes of Health Toolbox cognition and motor batteries and selected modules from the Patient-Reported Outcomes Measurement Information System. RESULTS: Fifty-four participants were evaluated: 29 post-COVID-19 (mean ± SD age, 42.4 ± 12.3 years; approximately 8 months from COVID-19 diagnosis; 19 women) and 25 controls (age, 44.1 ± 12.3 years; 14 women). When compared with controls, the post-COVID-19 group had lower total N-acetyl compounds (tNAA; ACC-GM: -5.0%, P = .015; FWM: -4.4%, P = .13), FWM glutamate + glutamine (-9.5%, P = .001), and ACC-GM myo-inositol (-6.2%, P = .024). Additionally, only hospitalized patients post-COVID-19 showed age-related increases in myo-inositol, choline compounds, and total creatine (interaction P = .029 to <.001). Across all participants, lower FWM tNAA and higher ACC-GM myo-inositol predicted poorer performance on several cognitive measures (P = .001-.009), while lower ACC-GM tNAA predicted lower endurance on the 2-minute walk (P = .005). CONCLUSIONS: In participants post-COVID-19 with persistent neuropsychiatric symptoms, the lower-than-normal tNAA and glutamate + glutamine indicate neuronal injury, while the lower-than-normal myo-inositol reflects glial dysfunction, possibly related to mitochondrial dysfunction and oxidative stress in Post-COVID participants with persistent neuropsychiatric symptoms.

Mapping of glutamate metabolism using 1H FID-MRSI after oral administration of [1-13C]Glc at 9.4 T.

Glutamate is the major excitatory transmitter in the brain and malfunction of the related metabolism is associated with various neurological diseases and disorders. The observation of labeling changes in the spectra after the administration of a 13C labelled tracer is a common tool to gain better insights into the function of the metabolic system. But so far, only a very few studies presenting the labeling effects in more than two voxels to show the spatial dependence of metabolism. In the present work, the labeling effects were measured in a transversal plane in the human brain using ultra-short TE and TR 1H FID-MRSI. The measurement set-up was most simple: The [1-13C]Glc was administered orally instead of intravenous and the spectra were measured with a pure 1H technique without the need of a 13C channel (as Boumezbeur et al. demonstrated in 2004). Thus, metabolic maps and enrichment curves could be obtained for more metabolites and in more voxels than ever before in human brain. Labeling changes could be observed in [4-13C]glutamate, [3-13C]glutamate+glutamine, [2-13C]glutamate+glutamine, [4-13C]glutamine, and [3-13C]aspartate with a high temporal (3.6 min) and spatial resolution (32 × 32 grid with nominal voxel size of 0.33 µL) in five volunteers.

Identification of new resonances in downfield 1 H MRS of human calf muscle in vivo: Potentially metabolite precursors for skeletal muscle NAD.

PURPOSE: The purpose of this study was to identify and characterize newly discovered resonances appearing in the downfield proton MR spectrum (DF 1 H MRS) of the human calf muscle in vivo at 7T. METHODS: Downfield 1 H MRS was performed on the calf muscle of five healthy volunteers at 7T. A spectrally selective 90° E-BURP RF pulse with an excitation center frequency at 10.3 ppm and an excitation bandwidth of 2 ppm was used for DF 1 H MRS acquisition. RESULTS: In all participants, we observed new resonances at 9.7, 10.1, 10.3, and 10.9 ppm in the DF 1 H MRS. Phantom experiments at 37°C strongly suggest the new resonance at 9.7 ppm could be from H2-proton of the nicotinamide rings in nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN) while the resonance at 10.1 ppm could be attributed to the indole -NH proton of L-tryptophan. We observed that the resonances at 10.1 and 10.9 ppm are significantly suppressed when the water resonance is saturated, indicating that these peaks have either 1 H chemical exchange or cross-relaxation with water. Conversely, the resonances at 9.7 and 10.3 ppm exhibit moderate signal reduction in the presence of water saturation. CONCLUSION: We have identified new proton resonances in vivo in human calf muscle occurring at chemical shifts of 9.7, 10.1, 10.3, and 10.9 ppm. These preliminary results are promising for investigating the role of NR/NMN and L-tryptophan metabolism in understanding the de novo and salvage pathways of NAD+ synthesis in skeletal muscle.

X-linked creatine transporter (SLC6A8) deficiency in females: Difficult to recognize, but a potentially treatable disease.

Creatine transporter deficiency (CTD), caused by pathogenic variants in SLC6A8, is the second most common cause of X-linked intellectual disability. Symptoms include intellectual disability, epilepsy, and behavioral disorders and are caused by reduced cerebral creatine levels. Targeted treatment with oral supplementation is available, however the treatment efficacy is still being investigated. There are clinical and theoretical indications that heterozygous females with CTD respond better to supplementation treatment than hemizygous males. Unfortunately, heterozygous females with CTD often have more subtle and uncharacteristic clinical and biochemical phenotypes, rendering diagnosis more difficult. We report a new female case who presented with learning disabilities and seizures. After determining the diagnosis with molecular genetic testing confirmed by proton magnetic resonance spectroscopy (1H-MRS), the patient was treated with supplementation treatment including creatine, arginine, and glycine. After 28 months of treatment, the patient showed prominent clinical improvement and increased creatine levels in the brain. Furthermore, we provide a review of the 32 female cases reported in the current literature including a description of phenotypes, genotypes, diagnostic approaches, and effects of supplementation treatment. Based on this, we find that supplementation treatment should be tested in heterozygous female patients with CTD, and a prospective treatment underlines the importance of diagnosing these patients. The diagnosis should be suspected in a broad clinical spectrum of female patients and can only be made by molecular genetic testing. 1H-MRS of cerebral creatine levels is essential for establishing the diagnosis in females, and especially valuable when assessing variants of unknown significance.

More than one-half of the variance in in vivo proton MR spectroscopy metabolite estimates is common to all metabolites.

The present study characterized associations among brain metabolite levels, applying bivariate and multivariate (i.e., factor analysis) statistical methods to total creatine (tCr)-referenced estimates of the major Point RESolved Spectroscopy (PRESS) proton MR spectroscopy (1 H-MRS) metabolites (i.e., total NAA/tCr, total choline/tCr, myo-inositol/tCr, glutamate + glutamine/tCr) acquired at 3 T from medial parietal lobe in a large (n = 299), well-characterized international cohort of healthy volunteers. Results supported the hypothesis that 1 H-MRS-measured metabolite estimates are moderately intercorrelated (Mr = 0.42, SDr = 0.11, ps < 0.001), with more than one-half (i.e., 57%) of the total variability in metabolite estimates explained by a single common factor. Older age was significantly associated with lower levels of the identified common metabolite variance (CMV) factor (ß = -0.09, p = 0.048), despite not being associated with levels of any individual metabolite. Holding CMV factor levels constant, females had significantly lower levels of total choline (i.e., unique metabolite variance; ß = -0.19, p < 0.001), mirroring significant bivariate correlations between sex and total choline reported previously. Supplementary analysis of water-referenced metabolite estimates (i.e., including tCr/water) demonstrated lower, although still substantial, intercorrelations among metabolites, with 37% of total metabolite variance explained by a single common factor. If replicated, these results would suggest that applied 1 H-MRS researchers shift their analytical framework from examining bivariate associations between individual metabolites and specialty-dependent (e.g., clinical, research) variables of interest (e.g., using t-tests) to examining multivariable (i.e., covariate) associations between multiple metabolites and specialty-dependent variables of interest (e.g., using multiple regression).

Performance evaluate of different chemometrics formalisms used for prostate cancer diagnosis by NMR-based metabolomics.

INTRODUCTION: In general, two characteristics are ever present in NMR-based metabolomics studies: (1) they are assays aiming to classify the samples in different groups, and (2) the number of samples is smaller than the feature (chemical shift) number. It is also common to observe imbalanced datasets due to the sampling method and/or inclusion criteria. These situations can cause overfitting. However, appropriate feature selection and classification methods can be useful to solve this issue. OBJECTIVES: Investigate the performance of metabolomics models built from the association between feature selectors, the absence of feature selection, and classification algorithms, as well as use the best performance model as an NMR-based metabolomic method for prostate cancer diagnosis. METHODS: We evaluated the performance of NMR-based metabolomics models for prostate cancer diagnosis using seven feature selectors and five classification formalisms. We also obtained metabolomics models without feature selection. In this study, thirty-eight volunteers with a positive diagnosis of prostate cancer and twenty-three healthy volunteers were enrolled. RESULTS: Thirty-eight models obtained were evaluated using AUROC, accuracy, sensitivity, specificity, and kappa's index values. The best result was obtained when Genetic Algorithm was used with Linear Discriminant Analysis with 0.92 sensitivity, 0.83 specificity, and 0.88 accuracy. CONCLUSION: The results show that the pick of a proper feature selection method and classification model, and a resampling method can avoid overfitting in a small metabolomic dataset. Furthermore, this approach would decrease the number of biopsies and optimize patient follow-up. 1H NMR-based metabolomics promises to be a non-invasive tool in prostate cancer diagnosis.

High field brain proton magnetic resonance spectroscopy and volumetry in children with chronic, compensated liver disease - A pilot study.

BACKGROUND: There is increasing evidence that children or young adults having acquired liver disease in childhood display neurocognitive impairment which may become more apparent as they grow older. The molecular, cellular and morphological underpinnings of this clinical problem are incompletely understood. AIM: Therefore, we used the advantages of highly-resolved proton magnetic resonance spectroscopy at ultra-high magnetic field to analyze the neurometabolic profile and brain morphometry of children with chronic, compensated liver disease, hypothesizing that with high field spectroscopy we would identify early evidence of rising brain glutamine and decreased myoinositol, such as has been described both in animals and humans with more significant liver disease. METHODS: Patients (n = 5) and age-matched controls (n = 19) underwent 7T MR scans and short echo time 1H MR spectra were acquired using the semi-adiabatic SPECIAL sequence in two voxels located in gray and white matter dominated prefrontal cortex, respectively. A 3D MP2RAGE sequence was also acquired for brain volumetry and T1 mapping. Liver disease had to have developed at least 6 months before entering the study. Subjects underwent routine blood analysis and neurocognitive testing using validated methods within 3 months of MRI and MRS. RESULTS: Five children aged 8-16 years with liver disease acquired in childhood were included. Baseline biological characteristics were similar among patients. There were no statistically significant differences between subjects and controls in brain metabolite levels or brain volumetry. Finally, there were minor neurocognitive fluctuations including attention deficit in one child, but none fell in the statistically significant range. CONCLUSION: Children with chronic, compensated liver disease did not display an abnormal neurometabolic profile, neurocognitive abnormalities, or signal intensity changes in the globus pallidus. Despite the absence of neurometabolic changes, it is an opportunity to emphasize that it is only by developing the use of 1H MRS at high field in the clinical arena that we will understand the significance and generalizability of these findings in children with CLD. Healthy children displayed neurometabolic regional differences as previously reported in adult subjects.

Creatine chemical exchange saturation transfer (CEST) CMR imaging reveals myocardial early involvement in idiopathic inflammatory myopathy at 3T: feasibility and initial experience.

OBJECTIVES: To measure creatine distribution in idiopathic inflammatory myopathy (IIM) patients' myocardial segments and investigate whether cardiovascular magnetic resonance (CMR) chemical exchange saturation transfer (CEST) creatine mapping can detect subclinical myocardial changes, CEST's ability was further compared with other conventional CMR mapping sequences. METHODS: Forty IIM patients (53.5 ± 10.5 years, 26 males) and eight healthy controls (35.4 ± 6 years, 5 males) underwent CMR scans on a 3.0-T MR scanner. Patients with IIM were further classified into two subgroups according to cardiac troponin T (cTn-T) values: the elevated cTn-T subgroup (n = 14) and the normal cTn-T subgroup (n = 26). Cine imaging, T2 SPAIR, LGE imaging, T1 mapping, T2 mapping, and Cr (creatine) CEST were performed. RESULTS: Cr mapping showed significantly reduced creatine in IIM patients among global myocardium (IIM: 0.109 ± 0.063, controls: 0.121 ± 0.021, p < 0.05), and decreased creatine signals were detected in all 16 cardiac segments (p < 0.05). Patients also had significantly prolonged native T1 and decreased enhanced T1 values in each cardiac segment (p < 0.05). There was no significant difference of LVEF and T2 values between IIM patients and controls. Between the two subgroups, elevated cTn-T was linked with creatine and extracellular volume fraction (ECV) values, providing a global average creatine signal of 0.107 vs 0.112 (p < 0.05) and 24.7 vs 32.4 (p < 0.05). CONCLUSION: Creatine CEST mapping can detect early-stage heart involvement with negative LGE findings in IIM. Compared with T1 mapping, CEST provides increased sensitivity to ECV measurement, making it significantly better than T1, and a promising CMR sequence for screening subclinical myocardial damage. KEY POINTS: • IIM patients with potential or ongoing heart involvement, elevated ECV, and reduced Cr CEST values could provide valuable information. • ECV and Cr CEST values were closely related to elevated cTn-T.

Effects of Psychotherapy on Glutamatergic Neurotransmission.

INTRODUCTION: Psychodynamic psychotherapy is an effective and widely used treatment for major depressive disorder (MDD); however, little is known about neurobiological changes associated with induced symptom improvement. METHODS: Proton magnetic resonance spectroscopy with a two-dimensional J-resolved sequence served to test the relationship between glutamate (Glu) and glutamine (Gln) levels, measured separately in pregenual anterior cingulate cortex (pgACC) and the anterior midcingulate cortex (aMCC) as a control region, with change in depression symptoms after 6 months of weekly psychodynamic psychotherapy sessions in MDD patients. Depressed (N = 45) and healthy (N = 30) subjects participated in a baseline proton magnetic resonance spectroscopy measurement and a subgroup of MDD subjects (N = 21) then received once-a-week psychodynamic psychotherapy and participated in a second proton magnetic resonance spectroscopy measurement after 6 months. Change in depression symptoms was assessed using the Hamilton Depression Rating Scale (HAMD). RESULTS: Higher pretreatment pgACC Gln concentrations in MDD patients compared to healthy controls were associated with symptom severity. Patients and controls did not differ regarding Gln levels in aMCC nor regarding Glu levels in both regions. The association of pgACC Gln concentration and severity of depressive symptoms was reversed after 6 months of psychotherapy in MDD subjects. Regarding Gln in aMCC as well as Glu in both regions, there were no significant associations with improvement of depressive symptoms in the course of psychotherapy. DISCUSSION: Findings indicate specific regional effects of psychodynamic psychotherapy on glutamatergic neurotransmission and thereby highlight the key role of the pgACC in both depression pathophysiology and recovery.

From Molecular to Behavior: Higher Order Occipital Cortex in Major Depressive Disorder.

Medial prefrontal cortex (MPFC) and other regions like the occipital cortex (OC) exhibit abnormal neural activity in major depressive disorder (MDD). Their relationship to specific biochemical, psychophysical, and psychopathological changes remains unclear, though. For that purpose, we focus on a particular subregion in OC, namely middle temporal (MT) visual area that is known to mediate the perception of visual motion. Using high-field 7 T magnetic resonance imaging (MRI), including resting state functional MRI and proton magnetic resonance spectroscopy, the amplitude of low-frequency fluctuations (ALFF) of the blood oxygen level-dependent signal in MT, MT-seeded functional connectivity (FC), and gamma-aminobutyric acid (GABA) in MT were investigated. Applying the vision motion psychophysical task, the motion suppression index of subjects was also examined. We demonstrate significantly elevated neural variability (as measured by ALFF) in MT together with decreases in both MT GABA and motion suppression in our MDD sample. Unlike in healthy subjects, MT neural variability no longer modulates the relationship of MT GABA and motion suppression in MDD. MT also exhibits reduction in global inter-regional FC to MPFC in MDD. Finally, elevated MT ALFF relates to specifically retardation in behavior as measured by the Hamilton subscore. Together, MT provides a strong candidate for biomarker in MDD.

Prevalence of non-alcoholic fatty liver in the general Dutch population and in groups at increased risk.

BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is defined as a liver fat content ≥5.56%. It is of clinical interest to know the prevalence of NAFLD in people with a combination of metabolic risk factors. We aimed to examine the prevalence of NAFLD, including groups with metabolic risk factors. METHODS AND RESULTS: In this cross-sectional analysis of the Netherlands Epidemiology of Obesity (NEO) study, liver fat content was assessed using proton magnetic resonance spectroscopy (H-MRS). Participants with excessive alcohol consumption or missing values were excluded, leaving a total of 1570 participants for the analyses. Mean (SD) age of the population was 55 years, BMI 25.9 (4.0) kg/m2 and 46% were men. The prevalence of NAFLD was 27% (95% CI 24-30). The prevalence of NAFLD was increased in participants with hypertriglyceridemia (57%, 52-63), obesity (62%, 58-66) and diabetes (69%, 61-77). The prevalence of NAFLD was highest in those with diabetes and obesity (79%, 71-87), obesity and hypertriglyceridemia (81%, 76-86) and with diabetes and hypertriglyceridemia (86%, 77-95). NAFLD was also present in 12% (8-16) of participants without overweight. CONCLUSIONS: The prevalence of NAFLD in a middle-aged population in the Netherlands in 2010 was 27%. The prevalence of NAFLD is particularly increased in individuals with diabetes, obesity, and hypertriglyceridemia. This information may help clinicians and general practitioners in the risk stratification of their patients in daily practice.

In vivo absolute quantification of carnosine in the vastus lateralis muscle with 1H MRS using a surface coil and water as internal reference.

OBJECTIVE: To standardize a method for 1H MRS intramuscular absolute quantification of carnosine in the thigh, using a surface coil and water as internal reference. MATERIALS AND METHODS: Carnosine spectra were acquired in phantoms (5, 10, and 15 mM) as well as in the right gastrocnemius medialis (GM) and right vastus lateralis (VLM) muscles of young team sports athletes, using volume (VC) and surface (SC) coils on a 3 T scanner, with the same receiver gain. Water spectra were used as internal reference for the absolute quantification of carnosine. RESULTS: Phantom's experiments showed a maximum error of 7%, highlighting the validity of the measurements in the study setup. The carnosine concentrations (mmol/kg ww, mean ± SD) measured in the GM were 6.8 ± 2.2 with the VC (CcarVC) and 10.2 ± 3.0 with the SC (CcarSC) (P = 0.013; n = 9). Therefore, a correction was applied to these measurements (CcarVC = 0.6582*CcarSC), to make coils performance comparable (6.8 ± 2.2 for VC and 6.7 ± 2.0 for SC, P = 0.97). After that, only the SC was used to quantify carnosine in the VLM, where a concentration of 5.4 ± 1.5 (n = 30) was found, with significant differences between men (6.2 ± 1.3; n = 15) and women (4.6 ± 1.2; n = 15). The error in quantitation was 5.3-5.5% with both coils. CONCLUSION: The method using the SC and water as internal reference can be used to quantify carnosine in voluminous muscles and regions of the body in humans, where the VC is not suitable, such as the VLM.