Short echo time 1 H magnetic resonance spectroscopy of childhood brain tumours

Proton MR Spectroscopy of Pediatric Brain Disorders

In vivo MR spectroscopy is a non -invasive methodology that provides information about the biochemistry of tissues. It is available as a “push-button” application on state-of-the-art clinical MR scanners. MR spectroscopy has been used to study various brain diseases including tumors, stroke, trauma, degenerative disorders, epilepsy/seizures, inborn errors, neuropsychiatric disorders, and others. The purpose of this review is to provide an overview of MR spectroscopy findings in the pediatric population and its clinical use.

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.

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.

Progressive multifocal exophytic pontine glioblastoma: a case report with literature review

Multifocal pontine glioblastoma exhibiting an exophytic growth pattern in the cerebello-pontine angle (CPA) is rare. We present a case of a 5-year-old girl with consecutive neurological imaging and other clinical findings indicating progressive multifocal exophytic pontine glioblastoma. Three lesions were reported, of which two were initially presented, and one was developed 2 months later. One lesion demonstrated a progressing exophytic extension in the cistern of the left side of the CPA. The other two lesions were located and confined within the pons. Initial magnetic resonance imaging and positron emission tomography–computed tomography indicated low-grade glioma or inflammatory disease. However, 2 and 3 months later, subsequent magnetic resonance spectroscopy (MRS) displayed elevated choline and depressed N-acetyl aspartate peaks compared with the peaks on the initial MRS, indicating a high-grade glioma. Subtotal resection was performed for the CPA lesion. Histopathologic examination showed discrepant features of different parts of the CPA lesion. The patient received no further chemotherapy or radiotherapy and died 2 months after surgery. The multifocal and exophytic features of this case and the heterogeneous manifestations on neurological images were rare and confusing for both diagnosis and surgical decision-making. Our case report may contribute knowledge and helpful guidance for other medical doctors.

Advanced MR imaging in hemispheric low-grade gliomas before surgery; the indications and limits in the pediatric age

INTRODUCTION

Advanced magnetic resonance imaging (MRI) techniques is an umbrella term that includes diffusion (DWI) and diffusion tensor (DTI), perfusion (PWI), spectroscopy (MRS), and functional (fMRI) imaging. These advanced modalities have improved the imaging of brain tumors and provided valuable additional information for treatment planning. Despite abundant literature on advanced MRI techniques in adult brain tumors, few reports exist for pediatric brain ones, potentially because of technical challenges.

REVIEW OF THE LITERATURE

The authors review techniques and clinical applications of DWI, PWI, MRS, and fMRI, in the setting of pediatric hemispheric low-grade gliomas.

PERSONAL EXPERIENCE

The authors propose their personal experience to highlight benefits and limits of advanced MR imaging in diagnosis, grading, and presurgical planning of pediatric hemispheric low-grade gliomas.

DISCUSSION

Advanced techniques should be used as complementary tools to conventional MRI, and in theory, the combined use of the three techniques should ensure achieving the best results in the diagnosis of hemispheric low-grade glioma and in presurgical planning to maximize tumor resection and preserve brain function.

FUTURE PERSPECTIVES

In the setting of pediatric neurooncology, these techniques can be used to distinguish low-grade from high-grade tumor. However, these methods have to be applied on a large scale to understand their real potential and clinical relapse, and further technical development is required to reduce the excessive scan times and other technical limitations.

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

AIMS

To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy ((1)H MRS) as a non-invasive diagnostic aid for paediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on (1)H MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy.

METHODS

Seventy-eight patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas (PILOAs) was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.5 T Point-Resolved Spectroscopy (PRESS), Proton Brain Exam (PROBE) or Stimulated Echo Acquisition Mode (STEAM), echo time (TE) 20-32 ms and 135-136 ms). MRS data were processed using two strategies, determination of metabolite concentrations using TARQUIN software and automatic feature extraction with Peak Integration (PI). Linear Discriminant Analysis (LDA) was applied to this data to produce diagnostic classifiers. An evaluation of the diagnostic accuracy was performed based on resampling to measure the Balanced Accuracy Rate (BAR).

RESULTS

The accuracy of the diagnostic classifiers for discriminating the three tumour types was found to be high (BAR 0.98) when a combination of TE was used. The combination of both TEs significantly improved the classification performance (p<0.01, Tukey's test) compared with the use of one TE alone. Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00).

CONCLUSION

(1)H MRS has excellent accuracy for the non-invasive diagnosis of common childhood brain tumours particularly if the metabolite information is maximised and should become part of routine clinical assessment for these children.

Molecular imaging of pediatric brain tumors: comparison of tumor metabolism using ¹⁸F-FDG-PET and MRSI

Magnetic resonance spectroscopic imaging (MRSI) and (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) are non-invasive imaging techniques routinely used to evaluate tumor malignancy in adults with brain tumors. We compared the metabolic activity of pediatric brain tumors using FDG-PET and MRSI. Children (n = 37) diagnosed with a primary brain tumor underwent FDG-PET and MRSI within two weeks of each other. Tumor metabolism was classified as inactive, active or highly active using the maximum choline:N-acetyl-asparate (Cho:NAA) on MRSI and the highest tumor uptake on FDG-PET. A voxel-wise comparison was used to evaluate the area with the greatest abnormal metabolism. Agreement between methods was assessed using the percent agreement and the kappa statistic (κ). Pediatric brain tumors were metabolically heterogeneous on FDG-PET and MRSI studies. Active tumor metabolism was observed more frequently using MRSI compared to FDG-PET, and agreement in tumor classification was weak (κ = 0.16, p = 0.12), with 42 % agreement (95 % CI = 25-61 %). Voxel-wise comparison for identifying the area of greatest metabolic activity showed overlap in the majority (62 %) of studies, though exact agreement between techniques was low (29.4 %, 95 % CI = 15.1-47.5 %). These results indicate that FDG-PET and MRSI detect similar but not always identical regions of tumor activity, and there is little agreement in the degree of tumor metabolic activity between the two techniques.

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.

Proton magnetic resonance spectroscopy predicts survival in children with diffuse intrinsic pontine glioma

Patients with diffuse intrinsic pontine glioma (DIPG) face a grim prognosis with limited treatment options. Many patients will enroll on investigational trials though the role of chemotherapy or immunotherapy is unclear. Radiographic changes on conventional MRI are used to evaluate tumor response and progression, but are not predictive of outcome in these patients. More sensitive measures of tumor biology are needed to improve patient management. We evaluated changes in magnetic resonance spectroscopy (MRS) biomarkers in patients with DIPG. Thirty-eight patients were enrolled prospectively on an IRB-approved protocol, which included standard MRI, single voxel spectroscopy (SVS) and multi-slice multi-voxel spectroscopy (MRSI). Scans were performed at multiple time points during each patient's clinical course, with a total of 142 scans. The prognostic values of Choline:N-acetylaspartate (Cho:NAA), Cho:Creatine (Cho:Cr) and the presence of lactate and lipids (+Lac/Lip) were evaluated. Cho:NAA and variance in Cho:NAA values among different voxels within a tumor were each predictive of shorter survival. This prospective study shows that MRS can be used to identify high-risk patients and monitor changes in tumor metabolism, which may reflect changes in tumor behavior.

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.

Advances in the management of pediatric central nervous system tumors

Central nervous system tumors are the most common pediatric solid tumors and a leading cause of cancer-related mortality and morbidity in this age group. Survival rates have improved significantly over the last decades for most of the tumor types, as a consequence of improvements in neuroimaging, neurosurgery and neuroanesthesia, radiation oncology, and medical oncology. The complexity of the management of these patients requires a multidisciplinary approach and has led to the emergence of a new subspecialty of pediatric neuro-oncologists who are dedicated to the management and follow-up of this population. This review highlights the most critical advances in the diagnostic and treatment modalities of pediatric brain tumors. A specific review of the most common tumor types discusses treatment options, controversies, and ongoing developments, with an emphasis on cooperative trials.

Myo-inositol: a marker of reactive astrogliosis in glial tumors?

In a prospective study, two-dimensional (1)H-MRS with TE of 30 ms was performed before surgery in 56 patients with glial brain tumors. Concentrations of myo-inositol (MI), trimethylamine (TMA) and creatine/phosphocreatine (tCr) were evaluated for the whole tumor and scaled to the normal-appearing contralateral brain tissue. To assign changes in MI to specific tissue pathology, the normalized peak and mean concentrations of MI were correlated with TMA and tCr concentrations. TMA is accepted as a marker of proliferating tumor tissue, and tCr might be a marker of reactive astrogliosis. The mean and peak concentrations of MI and tCr correlated positively (r = 0.7), but not the concentrations of MI and TMA. The absolute concentration of MI was significantly increased in all tumor tissues (5.55 +/- 2.92 mM; mean +/- SD) compared with the normal-appearing white matter (4.33 +/- 1.22 mM, p = 0.005), with the highest concentrations for gliomatoses (n = 10) and grade II oligoastrocytomas (n = 3). Significant differences (P = 0.004) between low- and high-grade astrocytomas were found for TMA (1.67 +/- 0.32 mM and 2.65 +/- 0.86 mM, respectively), but not for MI (5.92 +/- 1.98 mM and 5.49 +/- 3.27 mM, respectively). As increased MI and tCr concentrations were found in gliomatosis and other cerebral diseases associated with marked astrogliosis, this process may also be responsible for the observed changes in MI in other glial tumors.

The use of short-echo-time 1H MRS for childhood cerebellar tumours prior to histopathological diagnosis

BACKGROUND

Proton magnetic resonance spectroscopy (MRS) measures concentrations of metabolites in vivo and provides a powerful method for identifying tumours. MRS has not entered routine clinical use partly due to the difficulty of analysing the spectra.

OBJECTIVE

To create a straightforward method for interpreting short-echo-time MRS of childhood cerebellar tumours.

MATERIALS AND METHODS

Single-voxel MRS (1.5-T Siemens Symphony NUM4, TR/TE 1,500/30 ms) was performed at presentation in 30 children with cerebellar tumours. The MRS results were analysed for comparison with histological diagnosis. Peak heights for N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mIns) were determined and receiver operator characteristic curves used to select ratios that best discriminated between the tumour types. The method was implemented by a group of clinicians and scientists, blinded to the results.

RESULTS

A total of 27 MRS studies met the quality control criteria. NAA/Cr >4.0 distinguished all but one of the astrocytomas from the other tumours. A combination of Cr/Cho <0.75 and mIns/NAA <2.1 separated all the medulloblastomas from the ependymomas.

CONCLUSION

Peak height ratios from short-echo-time MRS can accurately predict the histopathology of childhood cerebellar tumours.

Generating prior probabilities for classifiers of brain tumours using belief networks

Background

Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented.

Methods

The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data.

Results

Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET), germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence.

Conclusion

Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.