Quantification of H217O by 1H-MR imaging at 3 T: a feasibility study.

BACKGROUND: Indirect 1H-magnetic resonance (MR) imaging of 17O-labelled water allows imaging in vivo dynamic changes in water compartmentalisation. Our aim was to describe the feasibility of indirect 1H-MR methods to evaluate the effect of H217O on the MR relaxation rates by using conventional a 3-T equipment and voxel-wise relaxation rates. METHODS: MR images were used to calculate the R1, R2, and R2* relaxation rates in phantoms (19 vials with different H217O concentrations, ranging from 0.039 to 5.5%). Afterwards, an experimental animal pilot study (8 rats) was designed to evaluate the in vivo relative R2 brain dynamic changes related to the intravenous administration of 17O-labelled water in rats. RESULTS: There were no significant changes on the R1 and R2* values from phantoms. The R2 obtained with the turbo spin-echo T2-weighted sequence with 20-ms echo time interval had the higher statistical difference (0.67 s-1, interquartile range 0.34, p < 0.001) and Spearman correlation (rho 0.79). The R2 increase was adjusted to a linear fit between 0.25 and 5.5%, represented with equation R2 = 0.405 concentration + 0.3215. The highest significant differences were obtained for the higher concentrations (3.1-5.5%). The rat brain MR experiment showed a mean 10% change in the R2 value after the H217O injection with progressive normalisation. CONCLUSIONS: Indirect 1H-MR imaging method is able to measure H217O concentration by using R2 values and conventional 3-T MR equipment. Normalised R2 relative dynamic changes after the intravenous injection of a H217O saline solution provide a unique opportunity to map water pathophysiology in vivo, opening the analysis of aquaporins status and modifications by disease at clinically available 3-T proton MR scanners.

Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution.

The metabolic composition and concentration knowledge provided by magnetic resonance spectroscopy (MRS) liquid and high-resolution magic angle spinning spectroscopy (HR-MAS) has a relevant impact in clinical practice during magnetic resonance imaging (MRI) monitoring of human tumors. In addition, the combination of morphological and chemical information by MRI and MRS has been particularly useful for diagnosis and prognosis of tumor evolution. MRI spatial resolution reachable in human beings is limited for safety reasons and the demanding necessary conditions are only applicable on experimental model animals. Nevertheless, MRS and MRI can be performed on human biopsies at high spatial resolution, enough to allow a direct correlation between the chemical information and the histological features observed in such biopsies. Although HR-MAS is nowadays a well-established technique for spectroscopic analysis of tumor biopsies, with this approach just a mean metabolic profile of the whole sample can be obtained and thus the high histological heterogeneity of some important tumors is mostly neglected. The value of metabolic HR-MAS data strongly depends on a wide statistical analysis and usually the microanatomical rationale for the correlation between histology and spectroscopy is lost. We present here a different approach for the combined use of MRI and MRS on fresh human brain tumor biopsies with native contrast. This approach has been designed to achieve high spatial (18 × 18 × 50 µm) and spectral (0.031 µL) resolution in order to obtain as much spatially detailed morphological and metabolical information as possible without any previous treatment that can alter the sample. The preservation of native tissue conditions can provide information that can be translated to in vivo studies and additionally opens the possibility of performing other techniques to obtain complementary information from the same sample.

Development of a three-dimensional cell culture system based on microfluidics for nuclear magnetic resonance and optical monitoring.

A new microfluidic cell culture device compatible with real-time nuclear magnetic resonance (NMR) is presented here. The intended application is the long-term monitoring of 3D cell cultures by several techniques. The system has been designed to fit inside commercially available NMR equipment to obtain maximum readout resolution when working with small samples. Moreover, the microfluidic device integrates a fibre-optic-based sensor to monitor parameters such as oxygen, pH, or temperature during NMR monitoring, and it also allows the use of optical microscopy techniques such as confocal fluorescence microscopy. This manuscript reports the initial trials culturing neurospheres inside the microchamber of this device and the preliminary images and spatially localised spectra obtained by NMR. The images show the presence of a necrotic area in the interior of the neurospheres, as is frequently observed in histological preparations; this phenomenon appears whenever the distance between the cells and fresh nutrients impairs the diffusion of oxygen. Moreover, the spectra acquired in a volume of 8 nl inside the neurosphere show an accumulation of lactate and lipids, which are indicative of anoxic conditions. Additionally, a basis for general temperature control and monitoring and a graphical control software have been developed and are also described. The complete platform will allow biomedical assays of therapeutic agents to be performed in the early phases of therapeutic development. Thus, small quantities of drugs or advanced nanodevices may be studied long-term under simulated living conditions that mimic the flow and distribution of nutrients.

Accurate classification of childhood brain tumours by in vivo ¹H MRS - a multi-centre study.

AIMS: To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy ((1)H MRS) as a non-invasive diagnostic aid for paediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on (1)H MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy. METHODS: Seventy-eight patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas (PILOAs) was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.5 T Point-Resolved Spectroscopy (PRESS), Proton Brain Exam (PROBE) or Stimulated Echo Acquisition Mode (STEAM), echo time (TE) 20-32 ms and 135-136 ms). MRS data were processed using two strategies, determination of metabolite concentrations using TARQUIN software and automatic feature extraction with Peak Integration (PI). Linear Discriminant Analysis (LDA) was applied to this data to produce diagnostic classifiers. An evaluation of the diagnostic accuracy was performed based on resampling to measure the Balanced Accuracy Rate (BAR). RESULTS: The accuracy of the diagnostic classifiers for discriminating the three tumour types was found to be high (BAR 0.98) when a combination of TE was used. The combination of both TEs significantly improved the classification performance (p<0.01, Tukey's test) compared with the use of one TE alone. Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00). CONCLUSION: (1)H MRS has excellent accuracy for the non-invasive diagnosis of common childhood brain tumours particularly if the metabolite information is maximised and should become part of routine clinical assessment for these children.

Strategies for annotation and curation of translational databases: the eTUMOUR project.

The eTUMOUR (eT) multi-centre project gathered in vivo and ex vivo magnetic resonance (MR) data, as well as transcriptomic and clinical information from brain tumour patients, with the purpose of improving the diagnostic and prognostic evaluation of future patients. In order to carry this out, among other work, a database--the eTDB--was developed. In addition to complex permission rules and software and management quality control (QC), it was necessary to develop anonymization, processing and data visualization tools for the data uploaded. It was also necessary to develop sophisticated curation strategies that involved on one hand, dedicated fields for QC-generated meta-data and specialized queries and global permissions for senior curators and on the other, to establish a set of metrics to quantify its contents. The indispensable dataset (ID), completeness and pairedness indices were set. The database contains 1317 cases created as a result of the eT project and 304 from a previous project, INTERPRET. The number of cases fulfilling the ID was 656. Completeness and pairedness were heterogeneous, depending on the data type involved.

Use of 1H and 31P HRMAS to evaluate the relationship between quantitative alterations in metabolite concentrations and tissue features in human brain tumour biopsies.

Quantitative multinuclear high-resolution magic angle spinning was performed in order to determine the tissue pH values of and the absolute metabolite concentrations in 33 samples of human brain tumour tissue. Metabolite concentrations were quantified by 1D (1)H and (31)P HRMAS using the electronic reference to in vivo concentrations (ERETIC) synthetic signal. (1)H-(1)H homonuclear and (1)H-(31)P heteronuclear correlation experiments enabled the direct assessment of the (1)H-(31)P spin systems for signals that suffered from overlapping in the 1D (1)H spectra, and linked the information present in the 1D (1)H and (31)P spectra. Afterwards, the main histological features were determined, and high heterogeneity in the tumour content, necrotic content and nonaffected tissue content was observed. The metabolite profiles obtained by HRMAS showed characteristics typical of tumour tissues: rather low levels of energetic molecules and increased concentrations of protective metabolites. Nevertheless, these characteristics were more strongly correlated with the total amount of living tissue than with the tumour cell contents of the samples alone, which could indicate that the sampling conditions make a significant contribution aside from the effect of tumour development in vivo. The use of methylene diphosphonic acid as a chemical shift and concentration reference for the (31)P HRMAS spectra of tissues presented important drawbacks due to its interaction with the tissue. Moreover, the pH data obtained from (31)P HRMAS enabled us to establish a correlation between the pH and the distance between the N(CH(3))(3) signals of phosphocholine and choline in (1)H spectra of the tissue in these tumour samples.

Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosis.

In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning stops once this set has been processed. Training these classifiers requires a representative amount of data, but the gathering, preprocess, and validation of samples is expensive and time-consuming. Therefore, for a classical, non-incremental approach to ML, it is necessary to wait long enough to collect all the required data. In contrast, an incremental learning approach may allow us to build an initial classifier with a smaller number of samples and update it incrementally when new data are collected. In this study, an incremental learning algorithm for Gaussian Discriminant Analysis (iGDA) based on the Graybill and Deal weighted combination of estimators is introduced. Each time a new set of data becomes available, a new estimation is carried out and a combination with a previous estimation is performed. iGDA does not require access to the previously used data and is able to include new classes that were not in the original analysis, thus allowing the customization of the models to the distribution of data at a particular clinical center. An evaluation using five benchmark databases has been used to evaluate the behaviour of the iGDA algorithm in terms of stability-plasticity, class inclusion and order effect. Finally, the iGDA algorithm has been applied to automatic brain tumour classification with magnetic resonance spectroscopy, and compared with two state-of-the-art incremental algorithms. The empirical results obtained show the ability of the algorithm to learn in an incremental fashion, improving the performance of the models when new information is available, and converging in the course of time. Furthermore, the algorithm shows a negligible instance and concept order effect, avoiding the bias that such effects could introduce.

Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra.

OBJECT: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. MATERIALS AND METHODS: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 155 1.5T and 37 3T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. RESULTS: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 ± 0.03 for 1.5T and 0.88 ± 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. CONCLUSION: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T (1)H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.

Metabolic profile of chronic liver disease by NMR spectroscopy of human biopsies.

Among the different processes occurring during the evolution of liver disease, fibrosis has a predominant role. Liver fibrosis mechanisms are fairly constant irrespective of the underlying etiology. Cirrhosis is the end-stage of this reaction. Metabolic profiles, which are affected by many physiological and pathological processes, may provide further insight into the metabolic consequences of this severe liver disease. The aim of this study was to demonstrate the applicability of 1H high resolution magic angle spinning (HR-MAS) NMR spectroscopy in the biochemical profile determination of human liver needle biopsy samples for the characterization of metabolic alterations related to the severity of liver disease. We recorded and analyzed HR-MAS spectra of 68 liver tissue samples obtained by needle biopsy from patients with chronic liver disease. Multivariate analysis was applied to these data to obtain discrimination patterns and to reveal relevant metabolites. The metabolic characterization of liver tissue from needle biopsies by HR-MAS NMR spectroscopy provided differential patterns for cirrhotic and non-cirrhotic chronic liver disease tissue. Metabolites closely related to the liver metabolism such as some fatty acids, glucose and amino acids show differences between the two groups. Phospholipid precursors, which have been previously correlated with hepatic lesions also show differences. Furthermore, the correlation between histologically assessed liver disease stages and the levels of the most discriminative metabolites show that liver dysfunction is present at the initial stages of chronic hepatic lesions. Overall, this work suggests that the additional information obtained by NMR metabolomics applied to needle biopsies of human liver may be useful for assessing metabolic alterations and liver dysfunction in chronic liver disease.

Magnetic resonance microscopy contribution to interpret high-resolution magic angle spinning metabolomic data of human tumor tissue.

HRMAS NMR is considered a valuable technique to obtain detailed metabolic profile of unprocessed tissues. To properly interpret the HRMAS metabolomic results, detailed information of the actual state of the sample inside the rotor is needed. MRM (Magnetic Resonance Microscopy) was applied for obtaining structural and spatially localized metabolic information of the samples inside the HRMAS rotors. The tissue was observed stuck to the rotor wall under the effect of HRMAS spinning. MRM spectroscopy showed a transference of metabolites from the tissue to the medium. The sample shape and the metabolite transfer after HRMAS indicated that tissue had undergone alterations and it can not be strictly considered as intact. This must be considered when HRMAS is used for metabolic tissue characterization, and it is expected to be highly dependent on the manipulation of the sample. The localized spectroscopic information of MRM reveals the biochemical compartmentalization on tissue samples hidden in the HRMAS spectrum.

Whole-genomic survey of oligodendroglial tumors: correlation between allelic imbalances and gene expression profiles.

Malignant gliomas are the most common subtype of primary central nervous system (CNS) tumors. Their pathological classification, however, remains subjective, stimulating researchers to actively seek objective molecular markers to discover alternative and more reproducible tools for improved subtypification. Herein, we present a global survey of genomic alterations in oligodendroglial tumors (OT). Genetic and epigenetic alterations identified in this study are correlated with OT molecular groups we have recently reported: a neurogenic group composed of tumors with loss of heterozygosity (LOH) at 1p-19q, IDH1 mutations, and MGMT promoter methylation, showing good prognosis; an intermediate group, presenting TP53 mutations or LOH at 17p, IDH1 mutations, and GSTP1 promoter methylation; and a proliferative group, presenting major genetic alterations (LOH at 10q, EGFR amplification, and CDKN2A/ARF deletion) and poor prognosis. These results allowed us to refine our molecular characterization associated with prognosis, referring exclusively to oligodendroglial tumors.

New pattern of EGFR amplification in glioblastoma and the relationship of gene copy number with gene expression profile.

Gene amplification is a process that is characterized by an increase in the copy number of a restricted region in a chromosome arm, and is frequently associated with an overexpression of the corresponding amplified gene. Amplified DNA can be organized either as extrachromosomal elements, repeated units at a single locus or scattered throughout the genome. The amplification of the gene for epidermal growth factor receptor (EGFR) is a common finding in glioblastomas and the amplified gene copies appears as double minutes. The aim of this study was to investigate the different patterns of EGFR amplification in 40 cases of glioblastoma using FISH analysis in metaphases and paraffin sections, and to investigate the relationship of gene copy number with gene expression profile. The analysis of copy number alterations of EGFR was validated by quantitative PCR and SNP microarrays. We observed that in 42% of the cases, the type of amplification of EGFR was as double minute chromosomes. In addition, we detected another type of amplification, with extra copies of EGFR inserted in different loci of chromosome 7, present in 28% of cases. In this form of amplification, the number of copies is small, and the percentage of cells with EGFR amplification is rarely more than 15%. This model of amplification could correspond to a variant of the insertion mechanism, or a consequence of a process of duplication. Our results suggest that this mechanism could represent an early stage of amplification in glioblastomas. Overall, we found a close correlation between EGFR gene copy-number alterations and the level of EGFR protein expression. However, all cases with a high level of mRNA exhibited strong expression for the EGFR protein, and most cases with a low level of mRNA showed no overexpression of EGFR protein.

NMR metabolic profile of human follicular fluid.

The environment of the oocyte during its in vivo maturation consists of follicular fluid (FF) and is surrounded by granulosa cells. The FF is derived from the sanguineous plasma and secretions, synthesised in the follicle wall, that contain a large variety of growth factors, cytokines, amino acids, and other metabolites. These metabolites are presumably involved in the physiology of the oocyte. The identification, quantification and study of FF metabolites can provide additional information about the oocyte state which can be helpful in distinguishing those oocytes that have a greater capacity to be fertilised and to develop properly. The aim of this work is to identify the metabolic profile of FF samples exhaustively using High Resolution Nuclear Magnetic Resonance (NMR). A total of 30 FF samples from oocyte donors (<35 years) were analysed. Different monodimensional (1D) and bidimensional (2D) (homo and heteronuclear) NMR experiments were acquired. A total of 131 chemical shifts were assigned and 42 metabolites, including as example glucose, lactate, acetate, acetoacetate, pyruvate and beta-hydroxybutyrate, were identified. High correlations were found between these important intermediaries of the energetic metabolic pathways of the follicle which can indicate the importance of these pathways in oocyte development. Some of these identified metabolites might be useful as biomarkers of the follicular maturation state, allowing oocytes with a higher fertilisation potential to be selected, thereby increasing pregnancy rates in women following in vitro fertilisation (IVF) treatments.

Loss of heterozygosity at 1p-19q induces a global change in oligodendroglial tumor gene expression.

Oligodendroglial tumors presenting loss of heterozygosity (LOH) at 1p and 19q have been shown to be sensitive to chemotherapy, thus making 1p-19q status testing a key aspect in oligodendroglioma diagnosis and prognosis. Twenty-nine tumor samples (19 oligodendrogliomas, 10 oligoastrocytomas) were analyzed in order to obtain a molecular profile identifying those bearing 1p-19q LOH. Other genomic anomalies usually present in gliomas, such as EGFR amplification, CDKN2A/ARF deletion, 10q LOH and TP53 mutation, were also studied. Tumors with 1p-19q LOH overexpressed genes related to neurogenesis. Genes linked to immune response, proliferation and inflammation were overexpressed in the group with intact 1p-19q; this group could in turn be further divided in two subgroups: one overexpressing genes involved in immune response and inflammation that did not show major genetic aberrations other than the TP53 mutation and EGFR trisomy in a few cases, and another overexpressing genes related to immune response and proliferation that had a predominance of samples carrying several anomalies and presenting worse outcomes. This molecular signature was validated by analyzing a set of ten tumor samples (three oligodendrogliomas, seven oligoastrocytomas); all ten samples were correctly assigned. LOH at 1p-19q results in haploinsufficiency and copy number reduction of several genes, including NOTCH 2; this phenomenon produces a global change in gene expression inducing a pro-neural status that results in restrictions to cell migration and proliferation. Tumors without LOH at 1p-19q exhibit the opposite characteristics, explaining their more aggressive behavior.

Metabolite profiling of fecal water extracts from human colorectal cancer.

Colorectal cancer is the second leading cause of cancer death in developed countries. There is a need for better preventive strategies to improve the outcome of this disease. The increasing availability of high-throughput methodologies opens up new possibilities for screening new markers. The application of NMR metabolic profiling to fecal water extracts has interesting potential as a diagnostic tool for detecting colorectal cancer. We obtained NMR metabolic profiles of fecal water extracts from patients with colorectal cancer and healthy individuals, to characterize possible differences between them and to identify potential diagnostic markers. Our results show that metabolic profiling of fecal water extracts is a cheap, reproducible and effective method for detecting colorectal cancer markers and therefore complements other stool-screening methods. A low concentration of short-chain fatty acids, such as acetate and butyrate, previously associated with the development of colorectal cancer, appears to be the most effective marker. Concentrations of proline and cysteine, which are major components of most colonic epithelium mucus glycoproteins, also display significant changes in samples from colorectal cancer. Differentiation between fecal water extracts from controls and patients with colorectal cancer by NMR spectroscopy combined with chemometric techniques opens up new possibilities for developing new, efficient, high-throughput screening protocols.

Multiproject-multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy.

JUSTIFICATION: Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently acquired in different centers. The multicenter eTUMOUR project (2004-2009), which builds upon previous expertise from the INTERPRET project (2000-2002) has allowed such an evaluation to take place. MATERIALS AND METHODS: A total of 253 pairwise classifiers for glioblastoma, meningioma, metastasis, and low-grade glial diagnosis were inferred based on 211 SV short TE INTERPRET MR spectra obtained at 1.5 T (PRESS or STEAM, 20-32 ms) and automatically pre-processed. Afterwards, the classifiers were tested with 97 spectra, which were subsequently compiled during eTUMOUR. RESULTS: In our results based on subsequently acquired spectra, accuracies of around 90% were achieved for most of the pairwise discrimination problems. The exception was for the glioblastoma versus metastasis discrimination, which was below 78%. A more clear definition of metastases may be obtained by other approaches, such as MRSI + MRI. CONCLUSIONS: The prediction of the tumor type of in-vivo MRS is possible using classifiers developed from previously acquired data, in different hospitals with different instrumentation under the same acquisition protocols. This methodology may find application for assisting in the diagnosis of new brain tumor cases and for the quality control of multicenter MRS databases.

Determination of metabolite concentrations in human brain tumour biopsy samples using HR-MAS and ERETIC measurements.

Accurate determination of the concentration of the metabolites contained in intact human biopsies of 10 glioblastoma multiforme samples was achieved using one-dimensional (1)H high-resolution magic angle spinning (HR-MAS) NMR combined with ERETIC (electronic reference to in vivo concentrations) measurements. The amount of sample used ranged from 6.8 to 12.9 mg. Metabolite concentrations were measured in each sample using two methods: with DSS (2,2-dimethyl-2-silapentane-5-sulfonate sodium salt) as an internal reference and with ERETIC as an external electronically generated reference. The ERETIC signal was shown to be highly reproducible and did not affect the spectral quality. The concentrations calculated by the ERETIC method in model solutions were shown to be independent of the salt concentration in the range typically found in biological samples (0-250 mM). The ERETIC method proved to be straightforward to use in tissues and much more robust than the internal standard method. The concentrations calculated using the internal DSS concentration were systematically found to be higher than those determined using the ERETIC technique. These results indicate a possible interaction of the DSS molecules with the biopsy sample. Moreover, variations in the sample preparation process, with possible loss of DSS solution, may hamper the quantification process, as happens in one of the ten samples analysed. In this study, the ERETIC method was validated on model solutions and used in brain tumour tissues. Calculated metabolite concentrations obtained with the ERETIC procedure matched the values determined in the same type of tumours by in vivo, ex vivo and in vitro methodologies.

Automated quality control protocol for MR spectra of brain tumors.

eTUMOUR (http://www.etumour.net/) is acquiring a large database of brain tumor (1)H MR spectra to develop automated pattern recognition methods and decision support system (DSS) for tumor diagnosis. Development of accurate pattern-recognition algorithms requires spectra undistorted by artifacts, low signal-to-noise, or broad lines. eTUMOUR currently uses panels of expert spectroscopists to subjectively grade spectra as being acceptable or unacceptable. Automated quality control (QC) would be more satisfactory for several reasons: 1) to provide a reproducible objective classification of spectrum quality; 2) for use within the future DSS to prevent misdiagnosis due to poor spectrum quality; 3) to rapidly process the very large datasets of 1H spectra being accrued. An automated QC method using independent component analysis for feature extraction with a least-squares support vector machine classifier is presented. Separate training (n=144) and test sets (n=98) of single-voxel spectra from brain tumors and other lesions were acquired at multiple clinical centers with short and long echo times. Pairs of expert spectroscopists classified the test set an average of 85% the same. The automated QC classification agreed with an expert for 87% of test spectra, on average, suggesting the method classifies spectrum quality as accurately as expert spectroscopists.

Benign and atypical meningioma metabolic signatures by high-resolution magic-angle spinning molecular profiling.

Meningiomas are neoplasms that arise from the leptomeningeal covering of the brain and spinal cord, accounting for 15%-20% of CNS tumors. The WHO classifies meningiomas into three histological grades: benign, atypical, and anaplasic in accordance with the clinical prognosis. Atypical and anaplasic meningiomas tend to recur. Sometimes, meningiomas with histological diagnosis of benign meningioma show clinical characteristics of atypical meningioma. In this context, high-resolution magic-angle spinning (HR-MAS) spectroscopy of intact tissue from brain tumor biopsies has shown great potential as a support diagnostic tool. In this work, we show differences between benign and atypical meningiomas in HR-MAS molecular profiles of meningioma biopsies. Metabolic differences between meningioma grades include changes in the levels of glutathione. Glutathione role in cancer is still unclear, as it may act both as protective and pathogenic factor. Glutamine and glutamate, which are related to glutathione metabolism and have been associated with tumor recurrence, are also increased in atypical meningiomas. Other metabolites associated with tumor malignancy that show statistically significant differences between benign and atypical meningiomas include phosphocholine and phosphoethanolamine. Overall, this work suggests that the additional information obtained by NMR metabolomics applied to biopsies of human meningiomas may be useful for assessing tumor grade and determining optimum treatment strategies.