Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review

An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021. A total of 2,048 articles were screened, of which 314 full texts were further assessed resulting in 77 included articles. The most well-studied cancers were colorectal (19.5%), prostate (19.5%), and breast (19.5%). Most studies used a nested case-control design to estimate associations between individual metabolites and cancer risk and a liquid chromatography-tandem mass spectrometry untargeted or semi-targeted approach to measure metabolites in blood. Studies were geographically diverse, including countries in Asia, Europe, and North America; 27.3% of studies reported on participant race, the majority reporting White participants. Most studies (70.2%) included fewer than 300 cancer cases in their main analysis. This scoping review identified key areas for improvement, including needs for standardized race and ethnicity reporting, more diverse study populations, and larger studies.

Evolving Diagnostic and Treatment Strategies for Pediatric CNS Tumors: The Impact of Lipid Metabolism

Pediatric neurological tumors are a heterogeneous group of cancers, many of which carry a poor prognosis and lack a "standard of care" therapy. While they have similar anatomic locations, pediatric neurological tumors harbor specific molecular signatures that distinguish them from adult brain and other neurological cancers. Recent advances through the application of genetics and imaging tools have reshaped the molecular classification and treatment of pediatric neurological tumors, specifically considering the molecular alterations involved. A multidisciplinary effort is ongoing to develop new therapeutic strategies for these tumors, employing innovative and established approaches. Strikingly, there is increasing evidence that lipid metabolism is altered during the development of these types of tumors. Thus, in addition to targeted therapies focusing on classical oncogenes, new treatments are being developed based on a broad spectrum of strategies, ranging from vaccines to viral vectors, and melitherapy. This work reviews the current therapeutic landscape for pediatric brain tumors, considering new emerging treatments and ongoing clinical trials. In addition, the role of lipid metabolism in these neoplasms and its relevance for the development of novel therapies are discussed.

Lipid Alterations in Glioma: A Systematic Review

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

Added value of magnetic resonance spectroscopy for diagnosing childhood cerebellar tumours

1 H-magnetic resonance spectroscopy (MRS) provides noninvasive metabolite profiles with the potential to aid the diagnosis of brain tumours. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. The aim of the current study was to evaluate, prospectively, the diagnostic accuracy of a previously established classifier for diagnosing the three major childhood cerebellar tumours, and to determine added value compared with standard reporting of conventional imaging. Single-voxel MRS (1.5 T, PRESS, TE 30 ms, TR 1500 ms, spectral resolution 1 Hz/point) was acquired prospectively on 39 consecutive cerebellar tumours with histopathological diagnoses of pilocytic astrocytoma, ependymoma or medulloblastoma. Spectra were analysed with LCModel and predefined quality control criteria were applied, leaving 33 cases in the analysis. The MRS diagnostic classifier was applied to this dataset. A retrospective analysis was subsequently undertaken by three radiologists, blind to histopathological diagnosis, to determine the change in diagnostic certainty when sequentially viewing conventional imaging, MRS and a decision support tool, based on the classifier. The overall classifier accuracy, evaluated prospectively, was 91%. Incorrectly classified cases, two anaplastic ependymomas, and a rare histological variant of medulloblastoma, were not well represented in the original training set. On retrospective review of conventional MRI, MRS and the classifier result, all radiologists showed a significant increase (Wilcoxon signed rank test, p < 0.001) in their certainty of the correct diagnosis, between viewing the conventional imaging and MRS with the decision support system. It was concluded that MRS can aid the noninvasive diagnosis of posterior fossa tumours in children, and that a decision support classifier helps in MRS interpretation.

Lipids in Pathophysiology and Development of the Membrane Lipid Therapy: New Bioactive Lipids

Membranes are mainly composed of a lipid bilayer and proteins, constituting a checkpoint for the entry and passage of signals and other molecules. Their composition can be modulated by diet, pathophysiological processes, and nutritional/pharmaceutical interventions. In addition to their use as an energy source, lipids have important structural and functional roles, e.g., fatty acyl moieties in phospholipids have distinct impacts on human health depending on their saturation, carbon length, and isometry. These and other membrane lipids have quite specific effects on the lipid bilayer structure, which regulates the interaction with signaling proteins. Alterations to lipids have been associated with important diseases, and, consequently, normalization of these alterations or regulatory interventions that control membrane lipid composition have therapeutic potential. This approach, termed membrane lipid therapy or membrane lipid replacement, has emerged as a novel technology platform for nutraceutical interventions and drug discovery. Several clinical trials and therapeutic products have validated this technology based on the understanding of membrane structure and function. The present review analyzes the molecular basis of this innovative approach, describing how membrane lipid composition and structure affects protein-lipid interactions, cell signaling, disease, and therapy (e.g., fatigue and cardiovascular, neurodegenerative, tumor, infectious diseases).

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294

A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

Mapping of Metabolic Heterogeneity of Glioma Using MR-Spectroscopy

Simple Summary

Radiomics is a research field that integrates radiological and genetic information, but the application of the techniques that have been developed to this purpose have not been widely established in daily clinical practice. The purpose of our study is the development of a straightforward tool that can easily be used to preoperatively predict and correlate the metabolic signature of different CNS-lesions. Particularly in gliomas, we hope to integrate the molecular profile of these tumors into our prediction model. Our goal is to deliver an open-software tool with the intention of advancing the diagnostic work-up of gliomas to the latest standards.

Abstract

Proton magnetic resonance spectroscopy (¹H-MRS) delivers information about the non-invasive metabolic landscape of brain pathologies. ¹H-MRS is used in clinical setting in addition to MRI for diagnostic, prognostic and treatment response assessments, but the use of this radiological tool is not entirely widespread. The importance of developing automated analysis tools for ¹H-MRS lies in the possibility of a straightforward application and simplified interpretation of metabolic and genetic data that allow for incorporation into the daily practice of a broad audience. Here, we report a prospective clinical imaging trial (DRKS00019855) which aimed to develop a novel MR-spectroscopy-based algorithm for in-depth characterization of brain lesions and prediction of molecular traits. Dimensional reduction of metabolic profiles demonstrated distinct patterns throughout pathologies. We combined a deep autoencoder and multi-layer linear discriminant models for voxel-wise prediction of the molecular profile based on MRS imaging. Molecular subtypes were predicted by an overall accuracy of 91.2% using a classifier score. Our study indicates a first step into combining the metabolic and molecular traits of lesions for advancing the pre-operative diagnostic workup of brain tumors and improve personalized tumor treatment.

Separation of Metabolites and Macromolecules for Short-TE 1H-MRSI Using Learned Component-Specific Representations

Short-echo-time (TE) proton magnetic resonance spectroscopic imaging (MRSI) allows for simultaneously mapping a number of molecules in the brain, and has been recognized as an important tool for studying in vivo biochemistry in various neuroscience and disease applications. However, separation of the metabolite and macromolecule (MM) signals present in the short-TE data with significant spectral overlaps remains a major technical challenge. This work introduces a new approach to solve this problem by integrating imaging physics and representation learning. Specifically, a mixed unsupervised and supervised learning-based strategy was developed to learn the metabolite and MM-specific low-dimensional representations using deep autoencoders. A constrained reconstruction formulation is proposed to integrate the MRSI spatiospectral encoding model and the learned representations as effective constraints for signal separation. An efficient algorithm was developed to solve the resulting optimization problem with provable convergence. Simulation and experimental results have been obtained to demonstrate the component-specific representation power of the learned models and the capability of the proposed method in separating metabolite and MM signals for practical short-TE [Formula: see text]-MRSI data.

Magnetic resonance spectroscopy for the study of cns malignancies

Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.

Radiological Evaluation of Newly Diagnosed Non-Brainstem Pediatric High-Grade Glioma in the HERBY Phase II Trial

PURPOSE

The HERBY trial evaluated the benefit of the addition of the antiangiogenic agent Bevacizumab (BEV) to radiotherapy/temozolomide (RT/TMZ) in pediatric patients with newly diagnosed non-brainstem high-grade glioma (HGG). The work presented here aims to correlate imaging characteristics and outcome measures with pathologic and molecular data.

EXPERIMENTAL DESIGN

Radiological, pathologic, and molecular data were correlated with trial clinical information to retrospectively re-evaluate event-free survival (EFS) and overall survival (OS).

RESULTS

One-hundred thirteen patients were randomized to the RT/TMZ arm (n = 54) or the RT/TMZ+BEV (BEV arm; n = 59). The tumor arose in the cerebral hemispheres in 68 patients (Cerebral group) and a midline location in 45 cases (Midline group). Pathologic diagnosis was available in all cases and molecular data in 86 of 113. H3 K27M histone mutations were present in 23 of 32 Midline cases and H3 G34R/V mutations in 7 of 54 Cerebral cases. Total/near-total resection occurred in 44 of 68 (65%) Cerebral cases but in only 5 of 45 (11%) Midline cases (P < 0.05). Leptomeningeal metastases (27 cases, 13 with subependymal spread) at relapse were more frequent in Midline (17/45) than in Cerebral tumors (10/68, P < 0.05). Mean OS (14.1 months) and EFS (9.0 months) in Midline tumors were significantly lower than mean OS (20.7 months) and EFS (14.9 months) in Cerebral tumors (P < 0.05). Pseudoprogression occurred in 8 of 111 (6.2%) cases.

CONCLUSIONS

This study has shown that the poor outcome of midline tumors (compared with cerebral) may be related to (1) lesser surgical resection, (2) H3 K27M histone mutations, and (3) higher leptomeningeal dissemination.

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

Role of Neuroimaging Modality in the Assessment of Oxidative Stress in Brain: A Comprehensive Review

Background & Objective:

Oxidative stress (OS) is the secondary source of an injury in consequence to the earlier caused primary injury; it is the condition of an imbalance between oxidants and antioxidants within the physiological system. OS causes alterations in proteins and DNA structure, leading to inflammation, apoptotic cell death, and tissue damage. Neurodegenerative diseases (NDDs) such as Alzheimer's disease, Parkinson's disease, Glioma-induced neurodegeneration and the normal aging-related neuro-degeneration are primarily associated with the increased OS. The present review article is committed to delivering a comprehensive overview of the current neuroimaging modalities which estimates an indirect correlate of OS in the brain. OS-induced changes in white matter tracts and the gray matter volumes are reviewed assessing the role of diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) respectively. Further, the role of magnetic resonance spectroscopy (MRS) to assess the OS-induced alterations of chemical moieties, and thus the resultant structural implications in the neurological disorders are also briefly as well as precisely reviewed.

Conclusions:

In the present review article we present an overview of the role of neuroimaging modalities in the diagnosis, and longitudinal assessment during treatment of the OS induced changes.

Ex vivo metabolite profiling of paediatric central nervous system tumours reveals prognostic markers

Brain tumours are the most common cause of cancer death in children. Molecular studies have greatly improved our understanding of these tumours but tumour metabolism is underexplored. Metabolites measured in vivo have been reported as prognostic biomarkers of these tumours but analysis of surgically resected tumour tissue allows a more extensive set of metabolites to be measured aiding biomarker discovery and providing validation of in vivo findings. In this study, metabolites were quantified across a range of paediatric brain tumours using 1H-High-Resolution Magic Angle Spinning nuclear magnetic resonance spectroscopy (HR-MAS) and their prognostic potential investigated. HR-MAS was performed on pre-treatment frozen tumour tissue from a single centre. Univariate and multivariate Cox regression was used to examine the ability of metabolites to predict survival. The models were cross validated using C-indices and further validated by splitting the cohort into two. Higher concentrations of glutamine were predictive of a longer overall survival, whilst higher concentrations of lipids were predictive of a shorter overall survival. These metabolites were predictive independent of diagnosis, as demonstrated in multivariate Cox regression models. Whilst accurate quantification of metabolites such as glutamine in vivo is challenging, metabolites show promise as prognostic markers due to development of optimised detection methods and increasing use of 3 T clinical scanners.

Short-acquisition-time JPRESS and its application to paediatric brain tumours

OBJECTIVE

To develop and assess a short-duration JPRESS protocol for detection of overlapping metabolite biomarkers and its application to paediatric brain tumours at 3 Tesla.

MATERIALS AND METHODS

The short-duration protocol (6 min) was optimised and compared for spectral quality to a high-resolution (38 min) JPRESS protocol in a phantom and five healthy volunteers. The 6-min JPRESS was acquired from four paediatric brain tumours and compared with short-TE PRESS.

RESULTS

Metabolite identification between the 6- and 38-min protocols was comparable in phantom and volunteer data. For metabolites with Cramer-Rao lower bounds > 50%, interpretation of JPRESS increased confidence in assignment of lactate, myo-Inositol and scyllo-Inositol. JPRESS also showed promise for the detection of glycine and taurine in paediatric brain tumours when compared to short-TE MRS.

CONCLUSION

A 6-min JPRESS protocol is well tolerated in paediatric brain tumour patients. Visual inspection of a 6-min JPRESS spectrum enables identification of a range of metabolite biomarkers of clinical interest.

Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours

BACKGROUND

A tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data.

OBJECTIVE

To determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset.

MATERIALS AND METHODS

Magnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total.

RESULTS

Of the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features.

CONCLUSION

The original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data.

What is MR spectroscopy?

¹H-Magnetic Resonance Spectroscopy (MRS) is a novel advanced imaging technique used as an adjunct to MRI to reveal complementary non-invasive information about the biochemical composition of imaged tissue. Clinical uses in paediatrics include aiding diagnosis of brain tumours, neonatal disorders such as hypoxic-ischaemic encephalopathy, inherited metabolic diseases, traumatic brain injury, demyelinating conditions and infectious brain lesions. MRS has potential to improve diagnosis and treatment monitoring of childhood brain tumours and other CNS diseases, facilitate biopsy and surgical planning, and provide prognostic biomarkers. MRS is employed as a research tool outside the brain in liver disease and disorders of muscle metabolism. The range of clinical uses is likely to increase with growing evidence for added value. Multicentre trials are needed to definitively establish the benefits of MRS in specific clinical scenarios and integrate this promising new technique into routine practice to improve patient care. This article gives a brief overview of MRS and its potential clinical applications, and addresses challenges surrounding translation into practice.

Variation of T2 relaxation times in pediatric brain tumors and their effect on metabolite quantification

Background

Metabolite concentrations are fundamental biomarkers of disease and prognosis. Magnetic resonance spectroscopy (MRS) is a noninvasive method for measuring metabolite concentrations; however, quantitation is affected by T₂ relaxation.

Purpose

To estimate T₂ relaxation times in pediatric brain tumors and assess how variation in T₂ relaxation affects metabolite quantification.

Study Type

Retrospective.

Population

Twenty‐seven pediatric brain tumor patients (n = 17 pilocytic astrocytoma and n = 10 medulloblastoma) and 24 age‐matched normal controls.

Field Strength/Sequence

Short‐ (30 msec) and long‐echo (135 msec) single‐voxel MRS acquired at 1.5T.

Assessment

T₂ relaxation times were estimated by fitting signal amplitudes at two echo times to a monoexponential decay function and were used to correct metabolite concentration estimates for relaxation effects.

Statistical Tests

One‐way analysis of variance (ANOVA) on ranks were used to analyze the mean T₂ relaxation times and metabolite concentrations for each tissue group and paired Mann–Whitney U‐tests were performed.

Results

The mean T₂ relaxation of water was measured as 181 msec, 123 msec, 90 msec, and 86 msec in pilocytic astrocytomas, medulloblastomas, basal ganglia, and white matter, respectively. The T₂ of water was significantly longer in both tumor groups than normal brain (P < 0.001) and in pilocytic astrocytomas compared with medulloblastomas (P < 0.01). The choline T₂ relaxation time was significantly longer in medulloblastomas compared with pilocytic astrocytomas (P < 0.05), while the T₂ relaxation time of NAA was significantly shorter in pilocytic astrocytomas compared with normal brain (P < 0.001). Overall, the metabolite concentrations were underestimated by ∼22% when default T₂ values were used compared with case‐specific T₂ values at short echo time. The difference was reduced to 4% when individually measured water T₂s were used.

Data Conclusion

Differences exist in water and metabolite T₂ relaxation times for pediatric brain tumors, which lead to significant underestimation of metabolite concentrations when using default water T₂ relaxation times.

Level of Evidence: 3

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2019;49:195–203.

Glycine: a non-invasive imaging biomarker to aid magnetic resonance spectroscopy in the prediction of survival in paediatric brain tumours

Paediatric brain tumours have a high mortality rate and are the most common solid tumour of childhood. Identification of high risk patients may allow for better treatment stratification. Magnetic Resonance Spectroscopy (MRS) provides a non-invasive measure of brain tumour metabolism and quantifies metabolite survival markers to aid in the clinical management of patients. Glycine can be identified using MRS and has been recently found to be important for cancer cell proliferation in tumours making it a valuable prognostic marker. The aims of this study were to investigate glycine and its added value to MRS as a prognostic marker for paediatric brain tumours in a clinical setting.

116 children with newly diagnosed brain tumours were examined with short echo-time MRS at the Birmingham Children’s Hospital and followed up for five years. Survival analysis was performed using Cox regression on the entire metabolite basis set with focus on glycine and three other established survival markers for comparison: n-acetylaspartate, scyllo-inositol and lipids at 1.3 ppm. Multivariate Cox regression was used in conjunction with risk values to establish if glycine added prognostic power when combined to the established survival markers.

Glycine was found to be a marker of poor prognosis in the cohort (p < 0.05) and correlated with tumour grade (p < 0.01). The addition of glycine improved the prognostic power of MRS compared to using the combination of established survival markers alone.

Tumour glycine was found to improve the MRS prediction of reduced survival in paediatric brain tumours aiding the non-invasive assessment of these children.

Metabolic profiling of the three neural derived embryonal pediatric tumors retinoblastoma, neuroblastoma and medulloblastoma, identifies distinct metabolic profiles

The rare pediatric embryonal tumors retinoblastoma, medulloblastoma and neuroblastoma derive from neuroectodermal tissue and share similar histopathological features despite different anatomical locations and diverse clinical outcomes. As metabolism can reflect genetic and histological features, we investigated whether the metabolism of embryonal tumors reflects their similar histology, shared developmental and neural origins, or tumor location. We undertook metabolic profiling on 50 retinoblastoma, 39 medulloblastoma and 70 neuroblastoma using high resolution magic angle spinning magnetic resonance spectroscopy (1H-MRS). Mean metabolite concentrations identified several metabolites that were significantly different between the tumor groups including taurine, hypotaurine, glutamate, glutamine, GABA, phosphocholine, N-acetylaspartate, creatine, glycine and myoinositol, p < 0.0017. Unsupervised multivariate analysis found that each tumor group clustered separately, with a unique metabolic profile, influenced by their underlying clinical diversity. Taurine was notably high in all tumors consistent with prior evidence from embryonal tumors. Retinoblastoma and medulloblastoma were more metabolically similar, sharing features associated with the central nervous system (CNS). Neuroblastoma had features consistent with neural tissue, but also contained significantly higher myoinositol and altered glutamate-glutamine ratio, suggestive of differences in the underlying metabolism of embryonal tumors located outside of the CNS. Despite the histological similarities and shared neural metabolic features, we show that individual neuroectodermal derived embryonal tumors can be distinguished by tissue metabolic profile. Pathway analysis suggests the alanine-aspartate-glutamate and taurine-hypotaurine metabolic pathways may be the most pertinent pathways to investigate for novel therapeutic strategies. This work strengthens our understanding of the biology and metabolic pathways underlying neuroectodermal derived embryonal tumors of childhood.

Simultaneous QSM and metabolic imaging of the brain using SPICE

PURPOSE

To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three-dimensional 1 H-MRSI acquisition without water suppression.

METHODS

The proposed technique builds on a subspace imaging method called spectroscopic imaging by exploiting spatiospectral correlation (SPICE), which enables ultrashort echo time (TE)/short pulse repetition time (TR) acquisitions for 1 H-MRSI without water suppression. This data acquisition scheme simultaneously captures both the spectral information of brain metabolites and the phase information of the water signals that is directly related to tissue magnetic susceptibility variations. In extending this scheme for simultaneous QSM and metabolic imaging, we increase k-space coverage by using dual density sparse sampling and ramp sampling to achieve spatial resolution often required by QSM, while maintaining a reasonable signal-to-noise ratio (SNR) for the spatiospectral data used for metabolite mapping. In data processing, we obtain high-quality QSM from the unsuppressed water signals by taking advantage of the larger number of echoes acquired and any available anatomical priors; metabolite spatiospectral distributions are reconstructed using a union-of-subspaces model.

RESULTS

In vivo experimental results demonstrate that the proposed method can produce susceptibility maps at a resolution higher than 1.8 × 1.8 × 2.4 mm3 along with metabolite spatiospectral distributions at a nominal spatial resolution of 2.4 × 2.4 × 2.4 mm3 from a single 7-min MRSI scan. The estimated susceptibility values are consistent with those obtained using the conventional QSM method with 3D multi-echo gradient echo acquisitions.

CONCLUSION

This article reports a new capability for simultaneous susceptibility mapping and metabolic imaging of the brain from a single 1 H-MRSI scan, which has potential for a wide range of applications. Magn Reson Med 79:13-21, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Application of pattern recognition techniques for classification of pediatric brain tumors by in vivo 3T 1 H-MR spectroscopy-A multi-center study

Purpose

3T magnetic resonance scanners have boosted clinical application of ¹H‐MR spectroscopy (MRS) by offering an improved signal‐to‐noise ratio and increased spectral resolution, thereby identifying more metabolites and extending the range of metabolic information. Spectroscopic data from clinical 1.5T MR scanners has been shown to discriminate between pediatric brain tumors by applying machine learning techniques to further aid diagnosis. The purpose of this multi‐center study was to investigate the discriminative potential of metabolite profiles obtained from 3T scanners in classifying pediatric brain tumors.

Methods

A total of 41 pediatric patients with brain tumors (17 medulloblastomas, 20 pilocytic astrocytomas, and 4 ependymomas) were scanned across four different hospitals. Raw spectroscopy data were processed using TARQUIN. Borderline synthetic minority oversampling technique was used to correct for the data skewness. Different classifiers were trained using linear discriminative analysis, support vector machine, and random forest techniques.

Results

Support vector machine had the highest balanced accuracy for discriminating the three tumor types. The balanced accuracy achieved was higher than the balanced accuracy previously reported for similar multi‐center dataset from 1.5T magnets with echo time 20 to 32 ms alone.

Conclusion

This study showed that 3T MRS can detect key differences in metabolite profiles for the main types of childhood tumors. Magn Reson Med 79:2359–2366, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Metabolomic signature of brain cancer

Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed.

Evaluation of the added value of 1H-magnetic resonance spectroscopy for the diagnosis of pediatric brain lesions in clinical practice

Background

Magnetic resonance spectroscopy (MRS) aids noninvasive diagnosis of pediatric brain tumors, but use in clinical practice is not well documented. We aimed to review clinical use of MRS, establish added value in noninvasive diagnosis, and investigate potential impact on patient care.

Methods

Sixty-nine children with lesions imaged using MRS and reviewed by the tumor board from 2014 to 2016 met inclusion criteria. Contemporaneous MRI diagnosis, spectroscopy analysis, histopathology, and clinical information were reviewed. Final diagnosis was agreed on by the tumor board at study end.

Results

Five cases were excluded for lack of documented MRI diagnosis. The principal MRI diagnosis by pediatric radiologists was correct in 59%, increasing to 73% with addition of MRS. Of the 73%, 19.1% (95% CI, 9.1%-33.3%) were incorrectly diagnosed with MRI alone. MRS led to a significant improvement in correct diagnosis over all tumor types (P = .012). Of diagnoses correctly made with MRI, confidence increased by 37% when adding MRS, with no patients incorrectly re-diagnosed. Indolent lesions were diagnosed noninvasively in 85% of cases, with MRS a major contributor to 91% of these diagnoses. Of all patients, 39% were managed without histopathological diagnosis. MRS contributed to diagnosis in 68% of this group, modifying it in 12%. MRS influenced management in 33% of cases, mainly through avoiding and guiding biopsy and aiding tumor characterization.

Conclusion

MRS can improve accuracy and confidence in noninvasive diagnosis of pediatric brain lesions in clinical practice. There is potential to improve outcomes through avoiding biopsy of indolent lesions, aiding tumor characterization, and facilitating earlier family discussions and treatment planning.

Magnetic resonance imaging based functional imaging in paediatric oncology

Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice.

Prediction of genetic subgroups in adult supra tentorial gliomas by pre- and intraoperative parameters

Recent progress in neuro-oncology has validated the significance of genetic diagnosis in gliomas. We previously investigated IDH1/2 and TP53 mutations via Sanger sequencing for adult supratentorial gliomas and reported that PCR-based sequence analysis classified gliomas into three genetic subgroups that have a strong association with patient prognosis: IDH mutant gliomas without TP53 mutations, IDH and TP53 mutant gliomas, and IDH wild-type gliomas. Furthermore, this analysis had a strong association with patient prognosis. To predict genetic subgroups prior to initial surgery, we retrospectively investigated preoperative radiological data using CT and MRI, including MR spectroscopy (MRS), and evaluated positive 5-aminolevulinic acid (5-ALA) fluorescence as an intraoperative factor. We subsequently compared these factors to differentiate each genetic subgroup. Multiple factors such as age at diagnosis, tumor location, gadolinium enhancement, 5-ALA fluorescence, and several tumor metabolites according to MRS, such as myo-inositol (myo-inositol/total choline) or lipid20, were statistically significant factors for differentiating IDH mutant and wild-type, suggesting that these two subtypes have totally distinct characteristics. In contrast, only calcification, laterality, and lipid13 (lipid13/total Choline) were statistically significant parameters for differentiating TP53 wild-type and mutant in IDH mutant gliomas. In this study, we detected several pre- and intraoperative factors that enabled us to predict genetic subgroups for adult supratentorial gliomas and clarified that lipid13 quantified by MRS is the key tumor metabolite that differentiates TP53 wild-type and mutant in IDH mutant gliomas. These results suggested that each genetic subtype in gliomas selects the distinct lipid synthesis pathways in the process of tumorigenesis.

Clinical Imaging of Tumor Metabolism with ¹H Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a noninvasive functional technique to evaluate the biochemical behavior of human tissues. This property has been widely used in assessment and therapy monitoring of brain tumors. MRS studies can be implemented outside the brain, with successful and promising results in the evaluation of prostate and breast cancer, although still with limited reproducibility. As a result of technical improvements, malignancies of the musculoskeletal system and abdominopelvic organs can benefit from the molecular information that MRS provides. The technical challenges and main applications in oncology of (1)H MRS in a clinical setting are the focus of this review.

Proton MRS imaging in pediatric brain tumors

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors.

Influence of macromolecule baseline on 1 H MR spectroscopic imaging reproducibility

Purpose

Poorly characterized macromolecular (MM) and baseline artefacts are known to reduce metabolite quantitation accuracy in ¹H MR spectroscopic imaging (MRSI). Increasing echo time (TE) and improvements in MM analysis schemes have both been proposed as strategies to improve metabolite measurement reliability. In this study, the influence of TE and two MM analysis schemes on MRSI reproducibility are investigated.

Methods

An experimentally acquired baseline was collected using an inversion recovery sequence (TI = 750 ms) and incorporated into the analysis method. Intrasubject reproducibility of MRSI scans, acquired at 3 Tesla, was assessed using metabolite coefficients of variance (COVs) for both experimentally acquired and simulated MM analysis schemes. In addition, the reproducibility of TE = 35 ms, 80 ms, and 144 ms was evaluated.

Results

TE = 80 ms was the most reproducible for singlet metabolites with COVs < 6% for total N‐acetyl‐aspartate, total creatine, and total choline; however, moderate multiplet dephasing was observed. Analysis incorporating the experimental baseline achieved higher Glu and Glx reproducibility at TE = 35 ms, and showed improvements over the simulated baseline, with higher efficacy for poorer data.

Conclusion

Overall, TE = 80 ms yielded the most reproducible singlet metabolite estimates. However, combined use of a short TE sequence and the experimental baseline may be preferred as a compromise between accuracy, multiplet dephasing, and T2 bias on metabolite estimates. Magn Reson Med 77:34–43, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups

BACKGROUND

Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis.

METHODS

High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group.

RESULTS

Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis.

CONCLUSIONS

We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification.

Diagnostic and prognostic value of 18F-DOPA PET and 1H-MR spectroscopy in pediatric supratentorial infiltrative gliomas: a comparative study

BACKGROUND

(1)H-MR spectroscopy (MRS) and (18)F-dihydroxyphenylalanine (DOPA) PET are noninvasive imaging techniques able to assess metabolic features of brain tumors. The aim of this study was to compare diagnostic and prognostic information gathered by (18)F-DOPA PET and (1)H-MRS in children with supratentorial infiltrative gliomas or nonneoplastic brain lesions suspected to be gliomas.

METHODS

We retrospectively analyzed 27 pediatric patients with supratentorial infiltrative brain lesions on conventional MRI (21 gliomas and 6 nonneoplastic lesions) who underwent (18)F-DOPA PET and (1)H-MRS within 2 weeks of each other. (1)H-MRS data (choline/N-acetylaspartate, choline-to-creatine ratios, and presence of lactate) and (18)F-DOPA uptake parameters (lesion-to-normal tissue and lesion-to-striatum ratios) were compared and correlated with histology, WHO tumor grade, and patient outcome.

RESULTS

(1)H-MRS and (18)F-DOPA PET data were positively correlated. Sensitivity, specificity, and accuracy in distinguishing gliomas from nonneoplastic lesions were 95%, 83%, and 93% for (1)H-MRS and 76%, 83%, and 78% for (18)F-DOPA PET, respectively. No statistically significant differences were found between the 2 techniques (P > .05). Significant differences regarding (18)F-DOPA uptake and (1)H-MRS ratios were found between low-grade and high-grade gliomas (P≤.001 and P≤.04, respectively). On multivariate analysis, (18)F-DOPA uptake independently correlated with progression-free survival (P≤.05) and overall survival (P = .04), whereas (1)H-MRS did not show significant association with outcome.

CONCLUSIONS

(1)H-MRS and (18)F-DOPA PET provide useful complementary information for evaluating the metabolism of pediatric brain lesions. (1)H-MRS represents the method of first choice for differentiating brain gliomas from nonneoplastic lesions.(18)F-DOPA uptake better discriminates low-grade from high-grade gliomas and is an independent predictor of outcome.

Inhibition of Pediatric Glioblastoma Tumor Growth by the Anti-Cancer Agent OKN-007 in Orthotopic Mouse Xenografts

Pediatric glioblastomas (pGBM), although rare, are one of the leading causes of cancer-related deaths in children, with tumors essentially refractory to existing treatments. Here, we describe the use of conventional and advanced in vivo magnetic resonance imaging (MRI) techniques to assess a novel orthotopic xenograft pGBM mouse (IC-3752GBM patient-derived culture) model, and to monitor the effects of the anti-cancer agent OKN-007 as an inhibitor of pGBM tumor growth. Immunohistochemistry support data is also presented for cell proliferation and tumor growth signaling. OKN-007 was found to significantly decrease tumor volumes (p<0.05) and increase animal survival (p<0.05) in all OKN-007-treated mice compared to untreated animals. In a responsive cohort of treated animals, OKN-007 was able to significantly decrease tumor volumes (p<0.0001), increase survival (p<0.001), and increase diffusion (p<0.01) and perfusion rates (p<0.05). OKN-007 also significantly reduced lipid tumor metabolism in responsive animals [(Lip1.3 and Lip0.9)-to-creatine ratio (p<0.05)], as well as significantly decrease tumor cell proliferation (p<0.05) and microvessel density (p<0.05). Furthermore, in relationship to the PDGFRα pathway, OKN-007 was able to significantly decrease SULF2 (p<0.05) and PDGFR-α (platelet-derived growth factor receptor-α) (p<0.05) immunoexpression, and significantly increase decorin expression (p<0.05) in responsive mice. This study indicates that OKN-007 may be an effective anti-cancer agent for some patients with pGBMs by inhibiting cell proliferation and angiogenesis, possibly via the PDGFRα pathway, and could be considered as an additional therapy for pediatric brain tumor patients.

Glycemic modulation in neuro-oncology: experience and future directions using a modified Atkins diet for high-grade brain tumors

Dietary glycemic modulation through high-fat, low-carbohydrate diets, which induce a state of systemic ketosis and alter systemic metabolic signaling, have been incorporated into the clinical management of patients with neurological disease for more than a century. Mounting preclinical evidence supports the antitumor, proapoptotic, and antiangiogenic effects of disrupting glycolytic metabolism through dietary intervention. In recent years, interest in incorporating such novel therapeutic strategies in neuro-oncology has increased. To date, 3 published studies incorporating novel dietary therapies in oncology have been reported, including one phase I study in neuro-oncology, and have set the stage for further study in this field. In this article, we review the biochemical pathways, preclinical data, and early clinical translation of dietary interventions that modulate systemic glycolytic metabolism in the management of primary malignant brain tumors. We introduce the modified Atkins diet (MAD), a novel dietary alternative to the classic ketogenic diet, and discuss the critical issues facing future study.

Sensitivity encoding for fast (1) H MR spectroscopic imaging water reference acquisition

PURPOSE

Accurate and fast (1) H MR spectroscopic imaging (MRSI) water reference scans are important for absolute quantification of metabolites. However, the additional acquisition time required often precludes the water reference quantitation method for MRSI studies. Sensitivity encoding (SENSE) is a successful MR technique developed to reduce scan time. This study quantitatively assesses the accuracy of SENSE for water reference MRSI data acquisition, compared with the more commonly used reduced resolution technique.

METHODS

2D MRSI water reference data were collected from a phantom and three volunteers at 3 Tesla for full acquisition (306 s); 2× reduced resolution (64 s) and SENSE R = 3 (56 s) scans. Water amplitudes were extracted using MRS quantitation software (TARQUIN). Intensity maps and Bland-Altman statistics were generated to assess the accuracy of the fast-MRSI techniques.

RESULTS

The average mean and standard deviation of differences from the full acquisition were 2.1 ± 3.2% for SENSE and 10.3 ± 10.7% for the reduced resolution technique, demonstrating that SENSE acquisition is approximately three times more accurate than the reduced resolution technique.

CONCLUSION

SENSE was shown to accurately reconstruct water reference data for the purposes of in vivo absolute metabolite quantification, offering significant improvement over the more commonly used reduced resolution technique.

Noninvasive detection of glutamate predicts survival in pediatric medulloblastoma

PURPOSE

Medulloblastoma is the most common malignant brain tumor occurring in childhood and is a significant cause of morbidity and mortality in pediatric oncology. More intense treatment strategies are recommended for patients displaying high-risk factors; however, considerable variation in outcome remains, indicating a need for improved predictive markers. In this study, 1H magnetic resonance spectroscopy (MRS) was used to investigate noninvasive molecular biomarkers of survival in medulloblastoma.

EXPERIMENTAL DESIGN

MRS was performed on a series of 35 biopsy-confirmed medulloblastoma cases. One case was excluded because of poor quality MRS. The prognostic value of MRS detectable biomarkers was investigated using Cox regression, retrospectively (N=15). A subsequent validation analysis (N=19) was also performed to reduce the chance of type I errors. Where available, high-resolution ex vivo MRS of biopsy tissue was used to confirm biomarker assignments.

RESULTS

The retrospective analysis revealed that creatine, glutamate, and glycine were markers of survival (P<0.01). The validation analysis showed that glutamate was a robust marker, with a hazard ration (HR) of 8.0 for the full dataset (P=0.0003, N=34). A good correlation between in vivo and ex vivo MRS glutamate/total-choline was found (P=0.001), validating the in vivo assignment. Ex vivo glutamate/total-choline was also associated with survival (P<0.01).

CONCLUSION

The identification of glutamate as a predictive biomarker of survival in pediatric medulloblastoma provides a clinically viable risk factor and highlights the importance of more detailed studies into the metabolism of this disease. Noninvasive biomarker detection using MRS may offer improved disease monitoring and potential for widespread use following multicenter validation.

Clinical proton MR spectroscopy in central nervous system disorders

A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units.

Blast neurotrauma impairs working memory and disrupts prefrontal myo-inositol levels in rats

Working memory, which is dependent on higher-order executive function in the prefrontal cortex, is often disrupted in patients exposed to blast overpressure. In this study, we evaluated working memory and medial prefrontal neurochemical status in a rat model of blast neurotrauma. Adult male Sprague-Dawley rats were anesthetized with 3% isoflurane and exposed to calibrated blast overpressure (17 psi, 117 kPa) while sham animals received only anesthesia. Early neurochemical effects in the prefrontal cortex included a significant decrease in betaine (trimethylglycine) and an increase in GABA at 24 h, and significant increases in glycerophosphorylcholine, phosphorylethanolamine, as well as glutamate/creatine and lactate/creatine ratios at 48 h. Seven days after blast, only myo-inositol levels were altered showing a 15% increase. Compared to controls, short-term memory in the novel object recognition task was significantly impaired in animals exposed to blast overpressure. Working memory in control animals was negatively correlated with myo-inositol levels (r=-.759, p<0.05), an association that was absent in blast exposed animals. Increased myo-inositol may represent tardive glial scarring in the prefrontal cortex, a notion supported by GFAP changes in this region after blast overexposure as well as clinical reports of increased myo-inositol in disorders of memory.

Diagnosing relapse in children's brain tumors using metabolite profiles

BACKGROUND

Malignant brain tumors in children generally have a very poor prognosis when they relapse and improvements are required in their management. It can be difficult to accurately diagnose abnormalities detected during tumor surveillance, and new techniques are required to aid this process. This study investigates how metabolite profiles measured noninvasively by (1)H magnetic resonance spectroscopy (MRS) at relapse reflect those at diagnosis and may be used in this monitoring process.

METHODS

Single-voxel MRS (1.5 T, point-resolved spectroscopy, echo time 30 ms, repetition time 1500 ms was performed on 19 children with grades II-IV brain tumors during routine MRI scans prior to treatment for a suspected brain tumor and at suspected first relapse. MRS was analyzed using TARQUIN software to provide metabolite concentrations. Paired Student's t-tests were performed between metabolite profiles at diagnosis and at first relapse.

RESULTS

There was no significant difference (P > .05) in the level of any metabolite, lipid, or macromolecule from tumors prior to treatment and at first relapse. This was true for the whole group (n = 19), those with a local relapse (n = 12), and those with a distant relapse (n = 7). Lipids at 1.3 ppm were close to significance when comparing the level at diagnosis with that at distant first relapse (P = .07, 6.5 vs 12.9). In 5 cases the MRS indicative of tumor preceded a formal diagnosis of relapse.

CONCLUSIONS

Tumor metabolite profiles, measured by MRS, do not change greatly from diagnosis to first relapse, and this can aid the confirmation of the presence of tumor.