Tear metabolomics for the diagnosis of primary open-angle glaucoma.

Primary Open-Angle Glaucoma (POAG) is the most prevalent glaucoma type, and the leading cause of irreversible visual impairment and blindness worldwide. Identification of early POAG biomarkers is of enormous value, as there is not an effective treatment for the glaucomatous optic nerve degeneration (OND). In this pilot study, a metabolomic analysis, by using proton (1H) nuclear magnetic resonance (NMR) spectroscopy was conducted in tears, in order to determine the changes of specific metabolites in the initial glaucoma eyes and to discover potential diagnostic biomarkers. A classification model, based on the metabolomic fingerprint in tears was generated as a non-invasive tool to support the preclinical and clinical POAG diagnosis. 1H NMR spectra were acquired from 30 tear samples corresponding to the POAG group (n = 11) and the control group (n = 19). Data were analysed by multivariate statistics (partial least squares-discriminant analysis: PLS-DA) to determine a model capable of differentiating between groups. The whole data set was split into calibration (65%)/validation (35%), to test the performance and the ability for glaucoma discrimination. The calculated PLS-DA model showed an area under the curve (AUC) of 1, as well as a sensitivity of 100% and a specificity of 83.3% to distinguish POAG group versus control group tear data. This model included 11 metabolites, potential biomarkers of the disease. When comparing the study groups, a decrease in the tear concentration of phenylalanine, phenylacetate, leucine, n-acetylated compounds, formic acid, and uridine, was found in the POAG group. Moreover, an increase in the tear concentration of taurine, glycine, urea, glucose, and unsaturated fatty acids was observed in the POAG group. These results highlight the potential of tear metabolomics by 1H NMR spectroscopy as a non-invasive approach to support early POAG diagnosis and in order to prevent visual loss.

Non-invasive biomarkers for mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease is the most common type of dementia in the elderly. It is a progressive degenerative disorder that may begin to develop up to 15 years before clinical symptoms appear. The identification of early biomarkers is crucial to enable a prompt diagnosis and to start effective interventions. In this work, we conducted a metabolomic study using proton Nuclear Magnetic Resonance (1H NMR) spectroscopy in serum samples from patients with neuropathologically confirmed Alzheimer's disease (AD, n = 51), mild cognitive impairment (MCI, n = 27), and cognitively healthy controls (HC, n = 50) to search for metabolites that could be used as biomarkers. Patients and controls underwent yearly clinical follow-ups for up to six years. MCI group included samples from three subgroups of subjects with different disease progression rates. The first subgroup included subjects that remained clinically stable at the MCI stage during the period of study (stable MCI, S-MCI, n = 9). The second subgroup accounted for subjects which were diagnosed with MCI at the moment of blood extraction, but progressed to clinical dementia in subsequent years (MCI-to-dementia, MCI-D, n = 14). The last subgroup was composed of subjects that had been diagnosed as dementia for the first time at the moment of sample collection (incipient dementia, Incp-D, n = 4). Partial Least Square Discriminant Analysis (PLS-DA) models were developed. Three models were obtained, one to discriminate between AD and HC samples with high sensitivity (93.75%) and specificity (94.75%), another model to discriminate between AD and MCI samples (100% sensitivity and 82.35% specificity), and a last model to discriminate HC and MCI with lower sensitivity and specificity (67% and 50%). Differences within the MCI group were further studied in an attempt to determine those MCI subjects that could develop AD-type dementia in the future. The relative concentration of metabolites, and metabolic pathways were studied. Alterations in the pathways of alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and beta-alanine metabolism, were found when HC and MCI- D patients were compared. In contrast, no pathway was found disturbed in the comparison of S-MCI with HC groups. These results highlight the potential of 1H NMR metabolomics to support the diagnosis of dementia in a less invasive way, and set a starting point for the study of potential biomarkers to identify MCI or HC subjects at risk of developing AD in the future.

New bladder cancer non-invasive surveillance method based on voltammetric electronic tongue measurement of urine.

Bladder cancer (BC) is the sixth leading cause of death by cancer. Depending on the invasiveness of tumors, patients with BC will undergo surgery and surveillance lifelong, owing the high rate of recurrence and progression. In this context, the development of strategies to support non-invasive BC diagnosis is focusing attention. Voltammetric electronic tongue (VET) has been demonstrated to be of use in the analysis of biofluids. Here, we present the implementation of a VET to study 207 urines to discriminate BC and non-BC for diagnosis and surveillance to detect recurrences. Special attention has been paid to the experimental setup to improve reproducibility in the measurements. PLSDA analysis together with variable selection provided a model with high sensitivity, specificity, and area under the ROC curve AUC (0.844, 0.882, and 0.917, respectively). These results pave the way for the development of non-invasive low-cost and easy-to-use strategies to support BC diagnosis and follow-up.

A new 8-oxo-7,8-2'deoxyguanosine nanoporous anodic alumina aptasensor for colorectal cancer diagnosis in blood and urine.

Many important human diseases, and especially cancer, have been related to the overproduction of 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG). This molecule is a product of oxidative stress processes over nucleophilic bases in DNA. In this work, an aptasensor for the rapid, selective and accurate detection of this oncomarker is presented. The aptasensor consists of a nanoporous anodic alumina material loaded with a dye and is functionalized with an aptamer-based "molecular gate". In the presence of target 8-oxo-dG, the capping aptamer displaces from the surface due to the high affinity of the analyte with the capping aptamer, thus inducing delivery of the preloaded fluorescent dye. In contrast, in the absence of 8-oxo-dG, a poor payload delivery is accomplished. This aptamer-based nanodevice has great sensitivity for 8-oxo-dG, resulting in a LOD of 1 nM and a detection time of ca. 60 min. Moreover, the aptasensor is able to accurately detect 8-oxo-dG in unmodified urine and serum without pre-concentration treatments. This diagnostic tool is validated in a set of 38 urine and serum samples from patients diagnosed of colorectal cancer and control patients. These samples are also analyzed using a standardized and specific ELISA kit. The aptasensor displays excellent sensitivity (95.83/100%) and specificity (80/100%) for 8-oxo-dG detection in serum and urine samples, respectively. Our results may serve as a basis for the development of generalized fluorogenic diagnostic platforms for the easy diagnosis of cancer in biofluids as well as for monitoring therapeutic treatments and detection of relapses without the use of expensive equipment or trained personnel.

A fluorogenic capped mesoporous aptasensor for gluten detection.

Celiac disease is a complex and autoimmune disorder caused by the ingestion of gluten affecting almost 1% of global population. Nowadays an effective treatment does not exist, and the only way to manage the disease is the removal of gluten from the diet. Owing the key role played by gluten, clear and regulated labelling of foodstuff and smart methods for gluten detection are needed to fight frauds on food industry and to avoid the involuntary ingestion of this protein by celiac patients. On that scope, the development of a novel detection system of gluten is here presented. The sensor consists of nanoporous anodic alumina films loaded with a fluorescent dye and capped with an aptamer that recognizes gliadin (gluten's soluble proteins). In the presence of gliadin, aptamer sequences displace from the surface of anodic alumina resulting in pore opening and dye delivery. The dispositive shows a limit of detection (LOD) of 100 µg kg-1 of gliadin, good selectivity and a detection time of approximately 60 min. Moreover, the sensor is validated in real food samples. This novel probe allows fast gluten detection through a simple signalling process with potential use for food control.

Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer.

Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (1H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of 1H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach.

Integrative Metabolomic and Transcriptomic Analysis for the Study of Bladder Cancer.

Metabolism reprogramming is considered a hallmark of cancer. The study of bladder cancer (BC) metabolism could be the key to developing new strategies for diagnosis and therapy. This work aimed to identify tissue and urinary metabolic signatures as biomarkers of BC and get further insight into BC tumor biology through the study of gene-metabolite networks and the integration of metabolomics and transcriptomics data. BC and control tissue samples (n = 44) from the same patients were analyzed by High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance and microarrays techniques. Besides, urinary profiling study (n = 35) was performed in the same patients to identify a metabolomic profile, linked with BC tissue hallmarks, as a potential non-invasive approach for BC diagnosis. The metabolic profile allowed for the classification of BC tissue samples with a sensitivity and specificity of 100%. The most discriminant metabolites for BC tissue samples reflected alterations in amino acids, glutathione, and taurine metabolic pathways. Transcriptomic data supported metabolomic results and revealed a predominant downregulation of metabolic genes belonging to phosphorylative oxidation, tricarboxylic acid cycle, and amino acid metabolism. The urinary profiling study showed a relation with taurine and other amino acids perturbed pathways observed in BC tissue samples, and classified BC from non-tumor urine samples with good sensitivities (91%) and specificities (77%). This urinary profile could be used as a non-invasive tool for BC diagnosis and follow-up.

Gated Mesoporous Silica Nanocarriers for a "Two-Step" Targeted System to Colonic Tissue.

Colon targeted drug delivery is highly relevant not only to treat colonic local diseases but also for systemic therapies. Mesoporous silica nanoparticles (MSNs) have been demonstrated as useful systems for controlled drug release given their biocompatibility and the possibility of designing gated systems able to release cargo only upon the presence of certain stimuli. We report herein the preparation of three gated MSNs able to deliver their cargo triggered by different stimuli (redox ambient (S1), enzymatic hydrolysis (S2), and a surfactant or being in contact with cell membrane (S3)) and their performance in solution and in vitro with Caco-2 cells. Safranin O dye was used as a model drug to track cargo fate. Studies of cargo permeability in Caco-2 monolayers demonstrated that intracellular safranin O levels were significantly higher in Caco-2 monolayers when using MSNs compared to those of free dye. Internalization assays indicated that S2 nanoparticles were taken up by cells via endocytosis. S2 nanoparticles were selected for in vivo tests in rats. For in vivo assays, capsules were filled with S2 nanoparticles and coated with Eudragit FS 30 D to target colon. The enteric coated capsule containing the MSNs was able to deliver S2 nanoparticles in colon tissue (first step), and then nanoparticles were able to deliver safranin O inside the colonic cells after the enzymatic stimuli (second step). This resulted in high levels of safranin O in colonic tissue combined with low dye levels in plasma and body tissues. The results suggested that this combination of enzyme-responsive gated MSNs and enteric coated capsules may improve the absorption of drugs in colon to treat local diseases with a reduction of systemic effects.

Quantitative Determination of Spring Water Quality Parameters via Electronic Tongue.

The use of a voltammetric electronic tongue for the quantitative analysis of quality parameters in spring water is proposed here. The electronic voltammetric tongue consisted of a set of four noble electrodes (iridium, rhodium, platinum, and gold) housed inside a stainless steel cylinder. These noble metals have a high durability and are not demanding for maintenance, features required for the development of future automated equipment. A pulse voltammetry study was conducted in 83 spring water samples to determine concentrations of nitrate (range: 6.9-115 mg/L), sulfate (32-472 mg/L), fluoride (0.08-0.26 mg/L), chloride (17-190 mg/L), and sodium (11-94 mg/L) as well as pH (7.3-7.8). These parameters were also determined by routine analytical methods in spring water samples. A partial least squares (PLS) analysis was run to obtain a model to predict these parameter. Orthogonal signal correction (OSC) was applied in the preprocessing step. Calibration (67%) and validation (33%) sets were selected randomly. The electronic tongue showed good predictive power to determine the concentrations of nitrate, sulfate, chloride, and sodium as well as pH and displayed a lower R² and slope in the validation set for fluoride. Nitrate and fluoride concentrations were estimated with errors lower than 15%, whereas chloride, sulfate, and sodium concentrations as well as pH were estimated with errors below 10%.

Detection of prostate cancer using a voltammetric electronic tongue.

A simple method based on the multivariate analysis of data from urine using an electronic voltammetric tongue is used to detect patients with prostate cancer. A sensitivity of 91% and a specificity of 73% were obtained to distinguish the urine from cancer patients and the urine from non-cancer patients.

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.

Estudio del colículo inferior de pacientes con esquizofrenia mediante espectroscopía de resonancia magnética / Study of the inferior colliculus in patients with schizophrenia by magnetic resonance spectroscopy

Introducción. Algunos estudios anteriores en pacientes con esquizofrenia han sugerido alteraciones morfométricas y funcionales en el colículo inferior. Las alucinaciones auditivas son uno de los síntomas centrales en la esquizofrenia. Se piensa que en este evento complejo y multidisciplinar, tanto la atención como la emoción desempeñan un papel clave. Objetivo. Estudiar los cambios metabólicos en el colículo inferior, un núcleo integrado en la vía auditiva, en pacientes con esquizofrenia y su posible relación con las alucinaciones auditivas. Sujetos y métodos. Se llevaron a cabo estudios de espectroscopía de resonancia magnética en 30 pacientes diestros con esquizofrenia crónica (19 de ellos con alucinaciones auditivas) y 28 controles. Se adquirió una secuencia 2D de espectroscopía de resonancia magnética y se seleccionaron los vóxeles representativos de ambos colículos inferiores. Se calculó el área de los picos de N-acetilaspartato (NAA), creatina (Cr) y colina (Co). Resultados. Los pacientes con esquizofrenia mostraron una reducción significativa de NAA/Cr en el colículo inferior derecho comparados con los sujetos control. Los datos metabólicos en el colículo inferior derecho se correlacionaron con los ítems emocionales de las alucinaciones auditivas. Conclusiones. La contribución del colículo inferior a las bases neuronales de las alucinaciones auditivas es particularmente relevante para el colículo inferior derecho y se centra en el componente atencional-emocional de este síntoma (AU)

Introduction. Previous studies have suggested morphometric and functional abnormalities in the inferior colliculus in patients with schizophrenia. Auditory hallucinations are one of the central symptoms in schizophrenia. In this complex and multidimensional event both attention and emotion are thought to play a key role. Aim. To study metabolic changes in the inferior colliculus, a nucleus integrated in the auditory pathway, in patients with schizophrenia and the possible relationship with auditory hallucinations. Subjects and methods. Magnetic resonance spectroscopic imaging studies were performed in 30 right-handed patients with chronic schizophrenia (19 of them with auditory hallucinations) and 28 controls. A magnetic resonance spectroscopic imaging 2D slice was acquired and the voxels representative of both inferior colliculi were selected. N-acetylaspartate (NAA), creatine (Cr) and choline (Cho) peak areas were measured. Results. The patients with schizophrenia showed a NAA/Cr significant reduction in the right inferior colliculus compared to the control subjects. The metabolic data in the right inferior colliculus were correlated with emotional auditory hallucinations items (AU. Conclusions. The contribution of the inferior colliculus on neural underpinnings of auditory hallucinations is particularly relevant for the right inferior colliculus and is centered on attention-emotional component of this symptom (AU)

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.

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.

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.

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.