Characterisation of paediatric brain tumours by their MRS metabolite profiles

1H-magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single-voxel MRS (point-resolved single-voxel spectroscopy sequence, 1.5 T: echo time [TE] 23-37 ms/135-144 ms, repetition time [TR] 1500 ms; 3 T: TE 37-41 ms/135-144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann-Whitney U-tests and Kruskal-Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours.

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

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

Metabolite selection for machine learning in childhood brain tumour classification

MRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi-class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi-site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi-class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave-one-out and k-fold cross-validation. Metabolites identified as crucial in tumour classification include myo-inositol (P < 0.05, AUC = 0 . 81 ± 0 . 01 ), total lipids and macromolecules at 0.9 ppm (P < 0.05, AUC = 0 . 78 ± 0 . 01 ) and total creatine (P < 0.05, AUC = 0 . 77 ± 0 . 01 ) for the 1.5 T cohort, and glycine (P < 0.05, AUC = 0 . 79 ± 0 . 01 ), total N-acetylaspartate (P < 0.05, AUC = 0 . 79 ± 0 . 01 ) and total choline (P < 0.05, AUC = 0 . 75 ± 0 . 01 ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave-one-out cross-validation was 85% for 1.5 T 1 H-MRS through support vector machine and 75% for 3 T 1 H-MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours.

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.

New variants and in silico analyses in GRK1 associated Oguchi disease

Biallelic mutations in G-Protein coupled receptor kinase 1 (GRK1) cause Oguchi disease, a rare subtype of congenital stationary night blindness (CSNB). The purpose of this study was to identify disease causing GRK1 variants and use in-depth bioinformatic analyses to evaluate how their impact on protein structure could lead to pathogenicity. Patients' genomic DNA was sequenced by whole genome, whole exome or focused exome sequencing. Disease associated variants, published and novel, were compared to nondisease associated missense variants. The impact of GRK1 missense variants at the protein level were then predicted using a series of computational tools. We identified twelve previously unpublished cases with biallelic disease associated GRK1 variants, including eight novel variants, and reviewed all GRK1 disease associated variants. Further structure-based scoring revealed a hotspot for missense variants in the kinase domain. In addition, to aid future clinical interpretation, we identified the bioinformatics tools best able to differentiate disease associated from nondisease associated variants. We identified GRK1 variants in Oguchi disease patients and investigated how disease-causing variants may impede protein function in-silico.

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.

Diagnostic accuracy and added value of qualitative radiological review of 1H-magnetic resonance spectroscopy in evaluation of childhood brain tumors

Background

¹H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI.

Methods

Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end.

Results

Radiologists' principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology.

Conclusions

MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

Hepatitis C virus infection is associated with hepatic and adipose tissue insulin resistance that improves after viral cure

BACKGROUND

Chronic hepatitis C (CHC) is associated with systemic insulin resistance, yet there are limited data on the tissue-specific contribution in vivo to this adverse metabolic phenotype, and the effect of HCV cure.

METHODS

We examined tissue-specific insulin sensitivity in a cohort study involving 13 patients with CHC compared to 12 BMI-matched healthy control subjects. All subjects underwent a two-step clamp incorporating the use of stable isotopes to measure carbohydrate and lipid flux (hepatic and global insulin sensitivity) with concomitant subcutaneous adipose tissue microdialysis and biopsy (subcutaneous adipose tissue insulin sensitivity). Investigations were repeated in seven patients with CHC following antiviral therapy with a documented sustained virological response.

RESULTS

Adipose tissue was more insulin resistant in patients with CHC compared to healthy controls, as evidence by elevated glycerol production rate and impaired insulin-mediated suppression of both circulating nonesterified fatty acids (NEFA) and adipose interstitial fluid glycerol release during the hyperinsulinaemic euglycaemic clamp. Hepatic and muscle insulin sensitivity were similar between patients with CHC and controls. Following viral eradication, hepatic insulin sensitivity improved as demonstrated by a reduction in endogenous glucose production rate. In addition, circulating NEFA decreased with sustained virological response (SVR) and insulin was more effective at suppressing adipose tissue interstitial glycerol release with a parallel increase in the expression of insulin signalling cascade genes in adipose tissue consistent with enhanced adipose tissue insulin sensitivity.

CONCLUSION

Chronic hepatitis C patients have profound subcutaneous adipose tissue insulin resistance in comparison with BMI-matched controls. For the first time, we have demonstrated that viral eradication improves global, hepatic and adipose tissue insulin sensitivity.

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.

Multiparametric magnetic resonance imaging for quantitation of liver disease: a two-centre cross-sectional observational study

LiverMultiScan is an emerging diagnostic tool using multiparametric MRI to quantify liver disease. In a two-centre prospective validation study, 161 consecutive adult patients who had clinically-indicated liver biopsies underwent contemporaneous non-contrast multiparametric MRI at 3.0 tesla (proton density fat fraction (PDFF), T1 and T2* mapping), transient elastography (TE) and Enhanced Liver Fibrosis (ELF) test. Non-invasive liver tests were correlated with gold standard histothological measures. Reproducibility of LiverMultiScan was investigated in 22 healthy volunteers. Iron-corrected T1 (cT1), TE, and ELF demonstrated a positive correlation with hepatic collagen proportionate area (all p < 0·001). TE was superior to ELF and cT1 for predicting fibrosis stage. cT1 maintained good predictive accuracy for diagnosing significant fibrosis in cases with indeterminate ELF, but not for cases with indeterminate TE values. PDFF had high predictive accuracy for individual steatosis grades, with AUROCs ranging from 0.90-0.94. T2* mapping diagnosed iron accumulation with AUROC of 0.79 (95% CI: 0.67-0.92) and negative predictive value of 96%. LiverMultiScan showed excellent test/re-test reliability (coefficients of variation ranging from 1.4% to 2.8% for cT1). Overall failure rates for LiverMultiScan, ELF and TE were 4.3%, 1.9% and 15%, respectively. LiverMultiScan is an emerging point-of-care diagnostic tool that is comparable with the established non-invasive tests for assessment of liver fibrosis, whilst at the same time offering a superior technical success rate and contemporaneous measurement of liver steatosis and iron accumulation.

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.

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.

Multiclass imbalance learning: Improving classification of pediatric brain tumors from magnetic resonance spectroscopy

Purpose

Classification of pediatric brain tumors from ¹H‐magnetic resonance spectroscopy (MRS) can aid diagnosis and management of brain tumors. However, varied incidence of the different tumor types leads to imbalanced class sizes and introduces difficulties in classifying rare tumor groups. This study assessed different imbalanced multiclass learning techniques and compared the use of complete spectra and quantified metabolite profiles for classification of three main childhood brain tumor types.

Methods

Single‐voxel, Short echo time MRS data were collected from 90 patients with pilocytic astrocytoma (n = 42), medulloblastoma (n = 38), or ependymoma (n = 10). Both spectra and metabolite profiles were used to develop the learning algorithms. The borderline synthetic minority oversampling technique and AdaboostM1 were used to correct for the skewed distribution. Classifiers were trained using five different pattern recognition algorithms.

Results

Use of imbalanced learning techniques improved the balanced accuracy rate (BAR) of all classification methods (average BAR over all classification methods for spectra: oversampled data = 0.81, original = 0.63, P < 0.001; metabolite concentration: oversampled‐data = 0.91, original = 0.75, P < 0.0001). Performance of all classifiers in discriminating ependymomas increased when oversampled data were used compared with original data for both complete spectra (F‐measure P < 0.01) and metabolite profile (F‐measure P < 0.001).

Conclusion

Imbalanced learning techniques improve the classification accuracy of childhood brain tumors from MRS where group sizes differ and facilitate the inclusion of rarer tumor types into clinical decision support systems. Magn Reson Med 77:2114–2124, 2017. © 2016 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.

Dual-5α-Reductase Inhibition Promotes Hepatic Lipid Accumulation in Man

CONTEXT

5α-Reductase 1 and 2 (SRD5A1, SRD5A2) inactivate cortisol to 5α-dihydrocortisol in addition to their role in the generation of DHT. Dutasteride (dual SRD5A1 and SRD5A2 inhibitor) and finasteride (selective SRD5A2 inhibitor) are commonly prescribed, but their potential metabolic effects have only recently been identified.

OBJECTIVE

Our objective was to provide a detailed assessment of the metabolic effects of SRD5A inhibition and in particular the impact on hepatic lipid metabolism.

DESIGN

We conducted a randomized study in 12 healthy male volunteers with detailed metabolic phenotyping performed before and after a 3-week treatment with finasteride (5 mg od) or dutasteride (0.5 mg od). Hepatic magnetic resonance spectroscopy (MRS) and two-step hyperinsulinemic euglycemic clamps incorporating stable isotopes with concomitant adipose tissue microdialysis were used to evaluate carbohydrate and lipid flux. Analysis of the serum metabolome was performed using ultra-HPLC-mass spectrometry.

SETTING

The study was performed in the Wellcome Trust Clinical Research Facility, Queen Elizabeth Hospital, Birmingham, United Kingdom.

MAIN OUTCOME MEASURE

Incorporation of hepatic lipid was measured with MRS.

RESULTS

Dutasteride, not finasteride, increased hepatic insulin resistance. Intrahepatic lipid increased on MRS after dutasteride treatment and was associated with increased rates of de novo lipogenesis. Adipose tissue lipid mobilization was decreased by dutasteride. Analysis of the serum metabolome demonstrated that in the fasted state, dutasteride had a significant effect on lipid metabolism.

CONCLUSIONS

Dual-SRD5A inhibition with dutasteride is associated with increased intrahepatic lipid accumulation.

MRS thermometry calibration at 3 T: effects of protein, ionic concentration and magnetic field strength

MRS thermometry has been utilized to measure temperature changes in the brain, which may aid in the diagnosis of brain trauma and tumours. However, the temperature calibration of the technique has been shown to be sensitive to non-temperature-based factors, which may provide unique information on the tissue microenvironment if the mechanisms can be further understood. The focus of this study was to investigate the effects of varied protein content on the calibration of MRS thermometry at 3 T, which has not been thoroughly explored in the literature. The effects of ionic concentration and magnetic field strength were also considered. Temperature reference materials were controlled by water circulation and freezing organic fixed-point compounds (diphenyl ether and ethylene carbonate) stable to within 0.2 °C. The temperature was measured throughout the scan time with a fluoro-optic probe, with an uncertainty of 0.16 °C. The probe was calibrated at the National Physical Laboratory (NPL) with traceability to the International Temperature Scale 1990 (ITS-90). MRS thermometry measures were based on single-voxel spectroscopy chemical shift differences between water and N-acetylaspartate (NAA), Δ(H20-NAA), using a Philips Achieva 3 T scanner. Six different phantom solutions with varying protein or ionic concentration, simulating potential tissue differences, were investigated within a temperature range of 21-42 °C. Results were compared with a similar study performed at 1.5 T to observe the effect of field strengths. Temperature calibration curves were plotted to convert Δ(H20-NAA) to apparent temperature. The apparent temperature changed by -0.2 °C/% of bovine serum albumin (BSA) and a trend of 0.5 °C/50 mM ionic concentration was observed. Differences in the calibration coefficients for the 10% BSA solution were seen in this study at 3 T compared with a study at 1.5 T. MRS thermometry may be utilized to measure temperature and the tissue microenvironment, which could provide unique unexplored information for brain abnormalities and other pathologies.

Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra-voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice-water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub-regions. A mixed effect model was used to measure the intra- and inter-scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra- and inter-scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra-scanner CV of 8.4% and inter-scanner CV of 24.8%. No major difference in the inter-scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra-scanner reproducibility, with the inter-scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter-scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi-centre clinical studies and trials.

MRS water resonance frequency in childhood brain tumours: a novel potential biomarker of temperature and tumour environment

(1)H MRS thermometry has been investigated for brain trauma and hypothermia monitoring applications but has not been explored in brain tumours. The proton resonance frequency (PRF) of water is dependent on temperature but is also influenced by microenvironment factors, such as fast proton exchange with macromolecules, ionic concentration and magnetic susceptibility. (1)H MRS has been utilized for brain tumour diagnostic and prognostic purposes in children; however, the water PRF measure may provide complementary information to further improve characterization. Water PRF values were investigated from a repository of MRS data acquired from childhood brain tumours and children with apparently normal brains. The cohort consisted of histologically proven glioma (22), medulloblastoma (19) and control groups (28, MRS in both the basal ganglia and parietal white matter regions). All data were acquired at 1.5 T using a short TE (30 ms) single voxel spectroscopy (PRESS) protocol. Water PRF values were calculated using methyl creatine and total choline. Spectral peak amplitude weighted averaging was used to improve the accuracy of the measurements. Mean PRF values were significantly larger for medulloblastoma compared with glioma, with a difference in the means of 0.0147 ppm (p < 0.05), while the mean PRF for glioma was significantly lower than for the healthy cohort, with a difference in the means of 0.0061 ppm (p < 0.05). This would suggest the apparent temperature of the glioma group was ~1.5 °C higher than the medulloblastomas and ~0.7 °C higher than a healthy brain. However, the PRF shift may not reflect a change in temperature, given that alterations in protein content, microstructure and ionic concentration contribute to PRF shifts. Measurement of these effects could also be used as a supplementary biomarker, and further investigation is required. This study has shown that the water PRF value has the potential to be used for characterizing childhood brain tumours, which has not been reported previously.

Texture analysis of T1 - and T2 -weighted MR images and use of probabilistic neural network to discriminate posterior fossa tumours in children

Brain tumours are the most common solid tumours in children, representing 20% of all cancers. The most frequent posterior fossa tumours are medulloblastomas, pilocytic astrocytomas and ependymomas. Texture analysis (TA) of MR images can be used to support the diagnosis of these tumours by providing additional quantitative information. MaZda software was used to perform TA on T1 - and T2 -weighted images of children with pilocytic astrocytomas, medulloblastomas and ependymomas of the posterior fossa, who had MRI at Birmingham Children's Hospital prior to treatment. The region of interest was selected on three slices per patient in Image J, using thresholding and manual outlining. TA produced 279 features, which were reduced using principal component analysis (PCA). The principal components (PCs) explaining 95% of the variance were used in a linear discriminant analysis (LDA) and a probabilistic neural network (PNN) to classify the cases, using DTREG statistics software. PCA of texture features from both T1 - and T2 -weighted images yielded 13 PCs to explain >95% of the variance. The PNN classifier for T1 -weighted images achieved 100% accuracy on training the data and 90% on leave-one-out cross-validation (LOOCV); for T2 -weighted images, the accuracy was 100% on training the data and 93.3% on LOOCV. A PNN classifier with T1 and T2 PCs achieved 100% accuracy on training the data and 85.8% on LOOCV. LDA classification accuracies were noticeably poorer. The features found to hold the highest discriminating potential were all co-occurrence matrix derived, where adjacent pixels had highly correlated intensities. This study shows that TA can be performed on standard T1 - and T2 -weighted images of childhood posterior fossa tumours using readily available software to provide high diagnostic accuracy. Discriminatory features do not correspond to those used in the clinical interpretation of the images and therefore provide novel tumour information.

Clinical protocols for ³¹P MRS of the brain and their use in evaluating optic pathway gliomas in children

INTRODUCTION

In vivo (31)P Magnetic Resonance Spectroscopy (MRS) measures phosphorus-containing metabolites that play an essential role in many disease processes. An advantage over (1)H MRS is that total choline can be separated into phosphocholine and glycerophosphocholine which have opposite associations with tumour grade. We demonstrate (31)P MRS can provide robust metabolic information on an acceptable timescale to yield information of clinical importance.

METHODS

All MRI examinations were carried out on a 3T whole body scanner with all (31)P MRS scans conducted using a dual-tuned (1)H/(31)P head coil. Once optimised on phantoms, the protocol was tested in six healthy volunteers (four male and two female, mean age: 25±2.7). (31)P MRS was then implemented on three children with optic pathway gliomas.

RESULTS

(31)P MRS on volunteers showed that a number of metabolite ratios varied significantly (p<0.05 ANOVA) across different structures of the brain, whereas PC/GPC did not. Standard imaging showed the optic pathway gliomas were enhancing on T1-weighted imaging after contrast injection and have high tCho on (1)H MRS, both of which are associated with high grade lesions. (31)P MRS showed the phosphocholine/glycerophosphocholine ratio to be low (<0.6) which suggests low grade tumours in keeping with their clinical behaviour and the histology of most biopsied optic pathway gliomas.

CONCLUSION

(31)P MRS can be implemented in the brain as part of a clinical protocol to provide robust measurement of important metabolites, in particular providing a greater understanding of cases where tCho is raised on (1)H MRS.

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.

Classification of single-voxel 1H spectra of childhood cerebellar tumors using LCModel and whole tissue representations

In this study, mean tumor spectra are used as the basis functions in LCModel to create a direct classification tool for short echo time (1)H magnetic resonance spectroscopy of pediatric brain tumors. LCModel is a widely used analysis tool designed to fit a linear combination of individual metabolite spectra to in vivo spectra. Here, we have used LCModel to fit mean spectra and corresponding variability components of childhood cerebellar tumors, as calculated using principal component analysis, and assessed for classification accuracy. Classification was performed according to the highest estimated tumor proportion. This method was tested in a leave-one-out analysis discriminating between pediatric brain tumor spectra of medulloblastoma vs. pilocytic astrocytoma and medulloblastoma vs. pilocytic astrocytoma vs. ependymoma. Additionally, the effect of accepting different Cramér-Rao Lower Bound cut-off criteria on classification accuracy and estimated tissue proportions was investigated. The best classification results differentiating medulloblastoma vs. pilocytic astrocytoma and medulloblastoma vs. pilocytic astrocytoma vs. ependymoma were 100 and 87.7%, respectively. These results are comparable to a specialized pattern recognition analysis of this data set and give easy to interpret results in the form of estimated tissue proportions. The method requires minimal user input and is easily transferable across sites and to other magnetic resonance spectroscopy classification problems.

A hybrid method of application of independent component analysis to in vivo 1H MR spectra of childhood brain tumours

Independent component analysis (ICA) can automatically extract individual metabolite, macromolecular and lipid (MMLip) components from a series of in vivo MR spectra. The traditional feature extraction (FE)-based ICA approach is limited, in that a large sample size is required and a combination of metabolite and MMLip components can appear in the same independent component. The alternative ICA approach, based on blind source separation (BSS), is weak when dealing with overlapping peaks. Combining the advantages of both BSS and FE methods may lead to better results. Thus, we propose an ICA approach involving a hybrid of the BSS and FE techniques for the automated decomposition of a series of MR spectra. Experiments were performed on synthesised and patient in vivo childhood brain tumour MR spectra datasets. The hybrid ICA method showed an improvement in the decomposition ability compared with BSS-ICA or FE-ICA, with an increased correlation between the independent components and simulated metabolite and MMLip signals. Furthermore, we were able to automatically extract metabolites from the patient MR spectra dataset that were not in commonly used basis sets (e.g. guanidinoacetate).

Short echo time single voxel 1H magnetic resonance spectroscopy in the diagnosis and characterisation of pineal tumours in children

BACKGROUND

Magnetic resonance spectroscopy (MRS) has been successful in characterising a range of brain tumours and is a useful aid to non-invasive diagnosis. The pineal region poses considerable surgical challenges and a major surgical resection is not required in the management of all tumours. Improved non-invasive assessment of pineal region tumours would be of considerable benefit.

METHODS

Single voxel MRS (TE 30 ms, TR 1500, 1.5 T) was performed on 15 pineal tumours: 5 germinomas, 1 non-germinomatous secreting germ cell tumour (GCT), 2 teratomas, 5 pineoblastomas, 1 pineal parenchymal tumour (PPT) of intermediate differentiation and 1 pineocytoma. Two germinomas outside the pineal gland were also studied. Metabolite, lipid and macromolecule concentrations were determined with LCModel™.

RESULTS

Germ cell tumours had significantly higher lipid and macromolecule concentrations than other tumours (t-test; P < 0.05). The teratomas had significantly lower total choline and creatine levels than germinomas (z test; P < 0.05). Taurine was convincingly detected in germinomas as well as PPTs.

CONCLUSIONS

Magnetic resonance spectroscopy is useful for characterising pineal region tumours, aiding the non-invasive diagnosis and giving additional biological insight.

MR spectroscopy-based brain metabolite profiling in propionic acidaemia: metabolic changes in the basal ganglia during acute decompensation and effect of liver transplantation

Background

Propionic acidaemia (PA) results from deficiency of Propionyl CoA carboxylase, the commonest form presenting in the neonatal period. Despite best current management, PA is associated with severe neurological sequelae, in particular movement disorders resulting from basal ganglia infarction, although the pathogenesis remains poorly understood. The role of liver transplantation remains controversial but may confer some neuro-protection. The present study utilises quantitative magnetic resonance spectroscopy (MRS) to investigate brain metabolite alterations in propionic acidaemia during metabolic stability and acute encephalopathic episodes.

Methods

Quantitative MRS was used to evaluate brain metabolites in eight children with neonatal onset propionic acidaemia, with six elective studies acquired during metabolic stability and five studies during acute encephalopathic episodes. MRS studies were acquired concurrently with clinically indicated MR imaging studies at 1.5 Tesla. LCModel software was used to provide metabolite quantification. Comparison was made with a dataset of MRS metabolite concentrations from a cohort of children with normal appearing MR imaging.

Results

MRI findings confirm the vulnerability of basal ganglia to infarction during acute encephalopathy. We identified statistically significant decreases in basal ganglia glutamate+glutamine and N-Acetylaspartate, and increase in lactate, during encephalopathic episodes. In white matter lactate was significantly elevated but other metabolites not significantly altered. Metabolite data from two children who had received liver transplantation were not significantly different from the comparator group.

Conclusions

The metabolite alterations seen in propionic acidaemia in the basal ganglia during acute encephalopathy reflect loss of viable neurons, and a switch to anaerobic respiration. The decrease in glutamine + glutamate supports the hypothesis that they are consumed to replenish a compromised Krebs cycle and that this is a marker of compromised aerobic respiration within brain tissue. Thus there is a need for improved brain protective strategies during acute metabolic decompensations. MRS provides a non-invasive tool for which could be employed to evaluate novel treatments aimed at restoring basal ganglia homeostasis. The results from the liver transplantation sub-group supports the hypothesis that liver transplantation provides systemic metabolic stability by providing a hepatic pool of functional propionyl CoA carboxylase, thus preventing further acute decompensations which are associated with the risk of brain infarction.

Magnetic resonance spectroscopy in the diagnostic evaluation of brainstem lesions in Alexander disease

Alexander disease is a progressive neurodegenerative disease, which can present with brainstem lesions with imaging characteristics similar to multifocal low-grade glioma, thus presenting a diagnostic dilemma. The authors report a 6-year-old child presenting with multifocal brainstem lesions subsequently diagnosed to have Alexander disease. In vivo magnetic resonance spectroscopy generated a metabolite profile of the lesion allowing differentiation from low-grade glioma. Magnetic resonance spectroscopy is a powerful tool in the assessment of brainstem lesions and is a useful adjunct to conventional magnetic resonance imaging in the assessment and diagnosis of atypical brain lesions.

A comparison between simulated and experimental basis sets for assessing short-TE in vivo ¹H MRS data at 1.5 T

A number of algorithms designed to determine metabolite concentrations from in vivo (1)H MRS require a collection of single metabolite spectra, known as a basis set, which can be obtained experimentally or by simulation. It has been assumed that basis sets can be used interchangeably, but no systematic study has investigated the effects of small variations in basis functions on the metabolite values obtained. The aim of this study was to compare the results of simulated with experimental basis sets when used to fit short-TE (1)H MRS data of variable quality at 1.5 T. Two hundred and twelve paediatric brain tumour spectra were included in the analysis, and each was analysed twice with LCModel™ using a simulated and experimental basis set. To determine the influence of data quality on quantification, each spectrum was assessed and 152 were classified as being of 'good' quality. Bland-Altman statistics were used to measure the agreement between the two basis sets for all available spectra and only 'good'-quality spectra. Monte-Carlo simulations were performed to investigate the influence of minor shifts in metabolite frequencies on metabolite concentration estimates. All metabolites showed good agreement between the two basis sets, and the average metabolite limits of agreement were approximately ±3.84 mM for all available data and ±0.99 mM for good-quality data. Errors obtained from the Monte-Carlo analysis were found to be more accurate than the Cramer-Rao lower bounds (CRLB) for 12 of 15 metabolites when metabolite frequency shifting was considered. For the majority of purposes, a level of agreement of ±0.99 mM between simulated and experimental basis sets is sufficiently small for them to be used interchangeably. Multiple analyses using slightly modified basis sets may be useful in estimating fitting errors, which are not predicted by CRLBs.

Quantitative in vivo brain magnetic resonance spectroscopic monitoring of neurological involvement in mucopolysaccharidosis type II (Hunter Syndrome)

Neurological involvement in X-linked mucopolysaccharidosis type II (Hunter syndrome) is indicative of more severe disease, but is not attenuated by current enzyme replacement therapy which does not significantly penetrate the blood-brain barrier. Magnetic resonance spectroscopy is an objective method of determining brain metabolites and has the potential to identify disease biomarkers with utility in evaluating current and novel therapies. MRS studies from seven patients with MPSII all receiving enzyme replacement therapy were compared with a large cohort of children with various neurocognitive disorders with normal MR imaging. All studies were completed on 1.5Tesla clinical MR scanners. Brain metabolite concentrations were determined from basal ganglia and parieto-occipital white matter using LCModel quantification. Serial trends in brain metabolites were analysed. Examination of mean spectra and quantitative metabolite concentrations demonstrated significantly decreased white matter N-acetylaspartate (a neuronal marker), total choline and glutamate, and elevated myo-inositol (glial marker) in MPSII patients. Analysis of serial determinations of white matter N-acetylaspartate demonstrated no change in two patients with stable MR imaging features but decreasing N-acetylaspartate in two patients more severely affected or deteriorating. These data demonstrate the utility of MRS to monitor serial alterations in brain metabolites including N-acetylaspartate which could be used as biomarkers of progressive neurological disease in MPSII. Integrated as an adjunct to MRI, such an approach could aid the evaluation of the efficacy of current ERT and also novel CNS-targeted therapies in MPSII.

Non-invasive detection of glycine as a biomarker of malignancy in childhood brain tumours using in-vivo 1H MRS at 1.5 tesla confirmed by ex-vivo high-resolution magic-angle spinning NMR

Management of brain tumours in children would benefit from improved non-invasive diagnosis, characterisation and prognostic biomarkers. Metabolite profiles derived from in-vivo MRS have been shown to provide such information. Studies indicate that using optimum a priori information on metabolite contents in the construction of linear combination (LC) models of MR spectra leads to improved metabolite profile estimation. Glycine (Gly) is usually neglected in such models due to strong overlap with myo-inositol (mI) and a low concentration in normal brain. However, biological studies indicate that Gly is abundant in high-grade brain tumours. This study aimed to investigate the quantitation of Gly in paediatric brain tumours using MRS analysed by LCModel, and its potential as a non-invasive biomarker of malignancy. Single-voxel MRS was performed using PRESS (TR 1500 ms, TE 30 ms/135 ms) on a 1.5 T scanner. Forty-seven cases (18 high grade (HG), 17 low grade (LG), 12 ungraded) were retrospectively selected if both short-TE and long-TE MRS (n = 33) or short-TE MRS and high-resolution magic-angle spinning (HRMAS) of matched surgical samples (n = 15) were available. The inclusion of Gly in LCModel analyses led to significantly reduced fit residues for both short-TE and long-TE MRS (p < 0.05). The Gly concentrations estimated from short-TE MRS were significantly correlated with the long-TE values (R = 0.91, p < 0.001). The Gly concentration estimated by LCModel was significantly higher in HG versus LG tumours for both short-TE (p < 1e-6) and long-TE (p = 0.003) MRS. This was consistent with the HRMAS results, which showed a significantly higher normalised Gly concentration in HG tumours (p < 0.05) and a significant correlation with the normalised Gly concentration measured from short-TE in-vivo MRS (p < 0.05). This study suggests that glycine can be reliably detected in paediatric brain tumours using in-vivo MRS on standard clinical scanners and that it is a promising biomarker of tumour aggressiveness.

In-utero stenting: development of a low-cost high-fidelity task trainer

OBJECTIVE

To develop an in-utero stent placement training model.

METHODS

The in-utero stent task trainer was constructed using a formalin-preserved gravid pig uterus. Altering the size of the uterine segment, changing the fluid level in the uterus and addition of a large Ziploc freezer bag variably filled with differing amounts of ultrasound gel can vary the procedural skill required.

RESULTS

Thoracoamniotic and vesicoamniotic shunts can be simulated using this life-like model. The cost of eight to 10 learning stations is approximately US $ 60. Fetal position, maternal size and amniotic fluid status can be altered rapidly to increase the complexity of the procedure.

CONCLUSIONS

This low-cost and realistic task trainer can provide the opportunity to practice in-utero shunt procedures in a non-clinical environment. This model should enhance learning and reinforce acquired skills.

A comparative study of feature extraction and blind source separation of independent component analysis (ICA) on childhood brain tumour 1H magnetic resonance spectra

Independent component analysis (ICA) has the potential of determining automatically the metabolite signals which make up MR spectra. However, the reliability with which this is accomplished and the optimal approach for investigating in vivo MRS have not been determined. Furthermore, the properties of ICA in brain tumour MRS with respect to dataset size and data quality have not been systematically explored. The two common techniques for applying ICA, blind source separation (BSS) and feature extraction (FE) were examined in this study using simulated data and the findings confirmed on patient data. Short echo time (TE 30 ms), low and high field (1.5 and 3 T) in vivo brain tumour MR spectra of childhood astrocytoma, ependymoma and medulloblastoma were generated by using a quantum mechanical simulator with ten metabolite and lipid components. Patient data (TE 30 ms, 1.5 T) were acquired from children with brain tumours. ICA of simulated data shows that individual metabolite components can be extracted from a set of MRS data. The BSS method generates independent components with a closer correlation to the original metabolite and lipid components than the FE method when the number of spectra in the dataset is small. The experiments also show that stable results are achieved with 300 MRS at an SNR equal to 10. The FE method is relatively insensitive to different ranges of full width at half maximum (FWHM) (from 0 to 3 Hz), whereas the BSS method degrades on increasing the range of FWHM. The peak frequency variations do not affect the results within the range of +/-0.08 ppm for the FE method, and +/-0.05 ppm for the BSS method. When the methods were applied to the patient dataset, results consistent with the synthesized experiments were obtained.

High resolution magic angle spinning 1H NMR of childhood brain and nervous system tumours

Background

Brain and nervous system tumours are the most common solid cancers in children. Molecular characterisation of these tumours is important for providing novel biomarkers of disease and identifying molecular pathways which may provide putative targets for new therapies. 1H magic angle spinning NMR spectroscopy (1H HR-MAS) is a powerful tool for determining metabolite profiles from small pieces of intact tissue and could potentially provide important molecular information.

Methods

Forty tissue samples from 29 children with glial and primitive neuro-ectodermal tumours were analysed using HR-MAS (600 MHz Varian gHX nanoprobe). Tumour spectra were fitted to a library of individual metabolite spectra to provide metabolite values. These values were then used in a two tailed t-test and multi-variate analysis employing a principal component analysis and a linear discriminant analysis. Classification accuracy was estimated using a leave-one-out analysis and B632+ bootstrapping.

Results

Glial tumours had significantly (two tailed t-test p < 0.05) higher creatine and glutamine and lower taurine, phosphoethanolamine, phosphorylcholine and choline compared with primitive neuro-ectodermal tumours. Classification accuracy was 90%. Medulloblastomas (n = 9) had significantly (two tailed t-test p < 0.05) higher creatine, glutamine, phosphorylcholine, glycine and scyllo-inositol than neuroblastomas (n = 7), classification accuracy was 94%. Supratentorial primitive neuro-ectodermal tumours had metabolite profiles in keeping with other primitive neuro-ectodermal tumours whilst ependymomas (n = 2) had metabolite profiles intermediate between pilocytic astrocytomas (n = 10) and primitive neuro-ectodermal tumours.

Conclusion

HR-MAS identified key differences in the metabolite profiles of childhood brain and nervous system improving the molecular characterisation of these tumours. Further investigation of the underlying molecular pathways is required to assess their potential as targets for new agents.

A quantitative comparison of metabolite signals as detected by in vivo MRS with ex vivo 1H HR-MAS for childhood brain tumours

(1)H MRS provides a powerful method for investigating tumour metabolism by allowing the measurement of metabolites in vivo. Recently, the technique of (1)H high-resolution magic angle spinning (HR-MAS) has been shown to produce high-quality data, allowing the accurate measurement of many metabolites present in unprocessed biopsy tissue. The purpose of this study was to evaluate the agreement between the techniques of in vivo MRS and ex vivo HR-MAS for investigating childhood brain tumours. Short-TE (30 ms), single-voxel, in vivo MRS was performed on 16 paediatric patients with brain tumours at 1.5 T. A frozen biopsy sample was available for each patient. HR-MAS was performed on the biopsy samples, and metabolite quantities were determined from the MRS and HR-MAS data using the LCModel and TARQUIN algorithms, respectively. Linear regression was performed on the metabolite quantities to asses the agreement between MRS and HR-MAS. Eight of the 12 metabolite quantities were found to correlate significantly (P < 0.05). The four worst correlating metabolites were aspartate, scyllo-inositol, glycerophosphocholine and N-acetylaspartate, and, except for glycerophosphocholine, this error was reflected in their higher Cramer-Rao lower bounds (CRLBs), suggesting that low signal-to-noise was the greatest source of error for these metabolites. Glycerophosphocholine had a lower CRLB implying that interference with phosphocholine and choline was the most significant source of error. The generally good agreement observed between the two techniques suggests that both MRS and HR-MAS can be used to reliably estimate metabolite quantities in brain tumour tissue and that tumour heterogeneity and metabolite degradation do not have an important effect on the HR-MAS metabolite profile for the tumours investigated. HR-MAS can be used to improve the analysis and understanding of MRS data.

Identification and characterisation of childhood cerebellar tumours by in vivo proton MRS

(1)H MRS has great potential for the clinical investigation of childhood brain tumours, but the low incidence in, and difficulties of performing trials on, children have hampered progress in this area. Most studies have used a long-TE, thus limiting the metabolite information obtained, and multivariate analysis has been largely unexplored. Thirty-five children with untreated cerebellar tumours (18 medulloblastomas, 12 pilocytic astrocytomas and five ependymomas) were investigated using a single-voxel short-TE PRESS sequence on a 1.5 T scanner. Spectra were analysed using LCModel to yield metabolite profiles, and key metabolite assignments were verified by comparison with high-resolution magic-angle-spinning NMR of representative tumour biopsy samples. In addition to univariate metabolite comparisons, the use of multivariate classifiers was investigated. Principal component analysis was used for dimension reduction, and linear discriminant analysis was used for variable selection and classification. A bootstrap cross-validation method suitable for estimating the true performance of classifiers in small datasets was used. The discriminant function coefficients were stable and showed that medulloblastomas were characterised by high taurine, phosphocholine and glutamate and low glutamine, astrocytomas were distinguished by low creatine and high N-acetylaspartate, and ependymomas were differentiated by high myo-inositol and glycerophosphocholine. The same metabolite features were seen in NMR spectra of ex vivo samples. Successful classification was achieved for glial-cell (astrocytoma + ependymoma) versus non-glial-cell (medulloblastoma) tumours, with a bootstrap 0.632 + error, e(B.632+), of 5.3%. For astrocytoma vs medulloblastoma and astrocytoma vs medulloblastoma vs ependymoma classification, the e(B.632+) was 6.9% and 7.1%, respectively. The study showed that (1)H MRS detects key differences in the metabolite profiles for the main types of childhood cerebellar tumours and that discriminant analysis of metabolite profiles is a promising tool for classification. The findings warrant confirmation by larger multi-centre studies.

Characterization and purification of glycosaminoglycans from crude biological samples

Chondroitin sulfate (CS) is a glycosaminoglycan derived from cartilage and commonly used to treat osteoarthritis, psoriasis, and other conditions. The dimethylmethylene blue (DMMB) assay has been used often to measure glycosaminoglycan levels in relatively pure samples. In this study, we verified the accuracy of the DMMB assay in measuring CS levels in unpurified extract from bovine trachea and shark cartilage, despite potential interference from salts, proteins, and DNA. We found that the glycosaminoglycan signal obtained was due to CS and not to other glycosaminoglycan species. This was confirmed using fluorophore-assisted carbohydrate electrophoresis, which also revealed that the majority of the CS was monosulfated at the C4 or C6 position. Finally, we used anion-exchange chromatography to purify the bovine extract and obtained complete recovery of the glycosaminoglycans, with no contaminating protein. The results of this study should be very useful for future purification and analysis of this common supplement.

Magnetic resonance spectroscopy suggests key differences in the metastatic behaviour of medulloblastoma

BACKGROUND

Metastatic medulloblastoma has a poorer prognosis than localised disease in part due to inherent properties of the tumour. 1H magnetic resonance spectroscopy (MRS) provides a powerful method for investigating tumour metabolism in vivo.

METHODS

Magnetic resonance imaging and short echo time (Te 30 ms) single voxel MRS were performed on the primary tumour of 16 children with medulloblastoma prior to surgical resection. Tumour volumes were calculated using a segmentation technique and the MRS was analysed using LCModel.

RESULTS

Patients with metastatic disease had primary tumours which were smaller (p=0.01), had higher levels of total choline (p=0.03) and lower levels of mobile lipids (p=0.04).

CONCLUSION

Metastatic medulloblastomas have metabolite profiles indicative of increased cell growth and decreased cell death compared with localised tumours reflecting intrinsic differences in underlying biology. Localised tumours with an MRS metabolite profile similar to those with metastatic disease may be at increased risk of metastatic relapse.

Age-related changes in the normal sagittal relationship between globe and orbit

PURPOSE

To establish the pattern of change in globe protrusion with advancing age. The findings contribute to our understanding of orbital ageing, and are useful in the longitudinal assessment of patients with orbital disease, craniofacial abnormalities and trauma.

METHODS

Ocular protrusion from the lateral orbital rim to the corneal apex was measured in 653 Caucasians aged 21-80 years. Healthy subjects only were included in the study excluding those with ocular or orbital diseases. Measurements were taken using a single instrument and observer. Data were analysed for both sexes and each eye separately.

RESULTS

The mean exophthalmometry reading in both sexes (318 female and 335 male) was 19+/-2mm. Ninety-eight percent of readings between the two eyes were within 1mm of each other and no subject had greater than 2mm of asymmetry. In all groups there was a negative linear correlation between ocular protrusion and age. This correlation was found to be highly statistically significant in all groups (r=0.56-0.65, p<0.0001). There was no statistically significant difference between change in ocular protrusion with age between the left and right eye for females or males. This study demonstrates a strong association between ocular protrusion and age in a Caucasian population. This association is an almost linear reduction in ocular protrusion with increasing age between the ages of 31 and 80. Asymmetry in ocular protrusion between the two eyes does not develop with increasing age.

Andersen-Tawil syndrome: New potassium channel mutations and possible phenotypic variation

OBJECTIVE

To evaluate clinical, genetic, and electrophysiologic features of patients with Andersen-Tawil syndrome (ATS) in the United Kingdom.

METHODS

Clinical and neurophysiologic evaluation was conducted of 11 families suspected to have ATS. Molecular genetic analysis of each proband was performed by direct DNA sequencing of the entire coding region of KCNJ2. Control samples were screened by direct DNA sequencing. The electrophysiologic consequences of several new mutations were studied in an oocyte expression system.

RESULTS

All 11 ATS families harbored pathogenic mutations in KCNJ2 with six mutations not previously reported. Some unusual clinical features including renal tubular defect, CNS involvement, and dental and phonation abnormalities were observed. Five mutations (T75M, D78G, R82Q, L217P, and G300D) were expressed, all of which resulted in nonfunctional channels when expressed alone, and co-expression with wild-type (WT) KCNJ2 demonstrated a dominant negative effect.

CONCLUSION

Six new disease-causing mutations in KCNJ2 were identified, one of which was in a PIP2 binding site. Molecular expression studies indicated that five of the mutations exerted a dominant negative effect on the wild-type allele. KCNJ2 mutations are an important cause of ATS in the UK.

Calibration of gradient propagation delays for accurate two-dimensional radiofrequency pulses

Hardware-related delays between the requested and actual start times of the gradient waveforms on each physical axis are of particular importance for multidimensional selective excitation in which the synchronization of gradient and radiofrequency (RF) waveforms is critical. A method is proposed for the accurate calibration of gradient propagation delays to optimize the spatial accuracy of 2D RF pulses, although the results may also be used to reduce artifacts in other MR techniques. The sensitivity of 2D RF pulses to uncorrected time shifts between the gradient and RF waveforms was exploited to calibrate accurately the propagation delays on each physical gradient axis. This was achieved using a technique that relates the effect of gradient delays in the component waveforms of a constant-angular rate spiral k-space trajectory 2D RF pulse to the spatial location of the subsequent excitation profile. Comparison was also made with a procedure based on a previously described k-space plotting method, showing broad agreement, but with some discrepancies that illustrate the value of a self-referenced correction method for multidimensional RF pulses.

Corroboration of in utero MRI using post-mortem MRI and autopsy in foetuses with CNS abnormalities

AIMS

To corroborate the findings of in utero magnetic resonance imaging (MRI) with autopsy and post-mortem MRI in cases of known or suspected central nervous system (CNS) abnormalities on ultrasound and to compare the diagnostic accuracy of ante-natal ultrasound and in utero MRI.

METHODS

Twelve pregnant women, whose foetuses had suspected central nervous system abnormalities underwent in utero MRI. The foetuses were imaged using MRi before autopsy. The data were used to evaluate the diagnostic accuracy of in utero MRI when compared with a reference standard of autopsy and post-mortem MRI in 10 cases and post-mortem MRI alone in two cases.

RESULTS

The diagnostic accuracy of antenatal ultrasound and in utero MRI in correctly characterizing brain and spine abnormalities were 42 and 100%, respectively.

CONCLUSION

In utero MRI provides a useful adjuvant to antenatal ultrasound when assessing CNS abnormalities by providing more accurate anatomical information. Post-mortem MRI assists the diagnosis of macroscopic structural abnormalities.

Macular pigments: their characteristics and putative role

The macular pigments (MP) absorb light in the blue-green region of the visible spectrum and comprise two carotenoids, lutein and zeaxanthin. In humans the concentration of MP varies widely across the normal population. There are two (not mutually exclusive) proposed roles for MP: to improve visual function and to act as an antioxidant and protect the macula from damage by oxidative stress. In this article we review the origin, spectral characteristics and ocular distribution of MP and also discuss the effect MP has on central visual function and the techniques available for measurement of MP optical density in vivo. Finally, we review the evidence for both proposed physiological roles of MP. Considering the first of these, we conclude that although MP might improve visual function in theory, to date there is no firm evidence that higher levels of MP are correlated with enhanced measures of visual performance. There is a growing body of evidence that has highlighted associations between macular disease and low levels of MP, most particularly with age-related macular degeneration (AMD) and with risk factors for AMD. However, all findings to date are associative only and there is no direct evidence for high MP levels conferring a protective effect. Increased dietary intake of MP gives rise to increased levels of serum and retinal MP. This, taken together with the associative evidence of low MP levels in disease, indicates that a potential, and perhaps serendipitous, therapeutic strategy for macular disease exists. We conclude, however, that the potential protective properties of MP will only be fully evaluated by undertaking longitudinal studies that follow initially healthy participants through to the development of macular disease.

Comparison of ultrasound and magnetic resonance imaging in 100 singleton pregnancies with suspected brain abnormalities

OBJECTIVE

To compare the diagnostic accuracy of the current reference standard-ultrasound with in utero magnetic resonance imaging, in a selected group of patients.

DESIGN

Prospective study.

SETTING

Five fetal maternal tertiary referral centres and an academic radiology unit.

SAMPLE

One hundred cases of fetuses with central nervous system abnormalities where there has been diagnostic difficulties on ultrasound. In 48 cases the women were less than 24 weeks of gestation and in 52 cases later in pregnancy.

METHODS

All women were imaged on a 1.5 T clinical system using a single shot fast spin echo technique. The results of antenatal ultrasound and in utero magnetic resonance were compared.

MAIN OUTCOME MEASURES

The definitive diagnosis was made either at autopsy or by postmortem magnetic resonance imaging, in cases that went to termination of pregnancy, or a combination of postnatal imaging and clinical follow up in the others.

RESULTS

In 52 of cases, ultrasound and magnetic resonance gave identical results and in a further 12, magnetic resonance provided extra information that was judged not to have had direct effects on management. In 35 of cases, magnetic resonance either changed the diagnosis (29) or gave extra information that could have altered management (6). In 11 of the 30 cases where magnetic resonance changed the diagnosis, the brain was described as normal on magnetic resonance.

CONCLUSIONS

In utero magnetic resonance imaging is a powerful tool in investigating fetal brain abnormalities. Our results suggest that in selected cases of brain abnormalities, detected by ultrasound, antenatal magnetic resonance may provide additional, clinically useful information that may alter management.

Frequency and natural history of subdural haemorrhages in babies and relation to obstetric factors

BACKGROUND

Subdural haematomas are thought to be uncommon in babies born at term. This view is mainly based on findings in symptomatic neonates and babies in whom subdural haemorrhages are detected fortuitously. We aimed to establish the frequency of subdural haemorrhages in asymptomatic term neonates; to study the natural history of such subdural haematomas; and to ascertain which obstetric factors, if any, are associated with presence of subdural haematoma.

METHODS

We did a prospective study in babies who were born in the Jessop wing of the Central Sheffield University Hospitals between March, 2001, and November, 2002. We scanned neonates with a 0.2 T magnetic resonance machine.

FINDINGS

111 babies underwent MRI in this study. 49 were born by normal vertex delivery without instrumentation, 25 by caesarean section, four with forceps, 13 ventouse, 18 failed ventouse leading to forceps, one failed ventouse leading to caesarean section, and one failed forceps leading to caesarean section. Nine babies had subdural haemorrhages: three were normal vaginal deliveries (risk 6.1%), five were delivered by forceps after an attempted ventouse delivery (27.8%), and one had a traumatic ventouse delivery (7.7%). All babies with subdural haemorrhage were assessed clinically but no intervention was needed. All were rescanned at 4 weeks and haematomas had completely resolved.

INTERPRETATION

Presence of unilateral and bilateral subdural haemorrhage is not necessarily indicative of excessive birth trauma.