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Gill SK, Rose HEL, Wilson M, Rodriguez Gutierrez D, Worthington L, Davies NP, MacPherson L, Hargrave DR, Saunders DE, Clark CA, Payne GS, Leach MO, Howe FA, Auer DP, Jaspan T, Morgan PS, Grundy RG, Avula S, Pizer B, Arvanitis TN, Peet AC. Characterisation of paediatric brain tumours by their MRS metabolite profiles. NMR Biomed 2024; 37:e5101. [PMID: 38303627 DOI: 10.1002/nbm.5101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 11/20/2023] [Accepted: 12/04/2023] [Indexed: 02/03/2024]
Abstract
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.
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Affiliation(s)
- Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Heather E L Rose
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Martin Wilson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
| | | | - Lara Worthington
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
- Department of Imaging and Medical Physics, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
- Department of Imaging and Medical Physics, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | - Darren R Hargrave
- Paediatric Oncology Unit, Great Ormond Street Hospital For Sick Children, London, UK
| | - Dawn E Saunders
- Paediatric Oncology Unit, Great Ormond Street Hospital For Sick Children, London, UK
| | - Christopher A Clark
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Geoffrey S Payne
- CRUK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Martin O Leach
- CRUK Cancer Imaging Centre, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Franklyn A Howe
- Neurosciences Research Section, Molecular and Clinical Sciences Research Institute, St George's, University of London, London, UK
| | - Dorothee P Auer
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Radiological Sciences, Department of Clinical Neuroscience, University of Nottingham, Nottingham, UK
- Neuroradiology, Nottingham University Hospital, Queen's Medical Centre, Nottingham, UK
| | - Tim Jaspan
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Neuroradiology, Nottingham University Hospital, Queen's Medical Centre, Nottingham, UK
| | - Paul S Morgan
- Medical Physics, Nottingham University Hospital, Queen's Medical Centre, Nottingham, UK
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
| | - Richard G Grundy
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
| | - Shivaram Avula
- Department of Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Barry Pizer
- Department of Paediatric Oncology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Theodoros N Arvanitis
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
- Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital NHS Foundation Trust, Birmingham, UK
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2
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Abdul Rashid K, Ibrahim K, Wong JHD, Mohd Ramli N. Lipid Alterations in Glioma: A Systematic Review. Metabolites 2022; 12:metabo12121280. [PMID: 36557318 PMCID: PMC9783089 DOI: 10.3390/metabo12121280] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/08/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.
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Affiliation(s)
- Khairunnisa Abdul Rashid
- Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Kamariah Ibrahim
- Department of Biomedical Science, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Jeannie Hsiu Ding Wong
- Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Norlisah Mohd Ramli
- Department of Biomedical Imaging, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia
- Correspondence: ; Tel.: +60-379673238
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Zhao D, Grist JT, Rose HEL, Davies NP, Wilson M, MacPherson L, Abernethy LJ, Avula S, Pizer B, Gutierrez DR, Jaspan T, Morgan PS, Mitra D, Bailey S, Sawlani V, Arvanitis TN, Sun Y, Peet AC. Metabolite selection for machine learning in childhood brain tumour classification. NMR Biomed 2022; 35:e4673. [PMID: 35088473 DOI: 10.1002/nbm.4673] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 06/14/2023]
Abstract
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.
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Affiliation(s)
- Dadi Zhao
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - James T Grist
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Heather E L Rose
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
- Imaging and Medical Physics, University Hospitals Birmingham, Birmingham, UK
| | - Martin Wilson
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | | | | | | | - Barry Pizer
- Paediatric Oncology, Alder Hey Children's Hospital, Liverpool, UK
| | - Daniel R Gutierrez
- Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Medical Physics, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Tim Jaspan
- Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Neuroradiology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Paul S Morgan
- Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Medical Physics, Nottingham University Hospitals NHS Trust, Nottingham, UK
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Dipayan Mitra
- Neuroradiology, The Newcastle upon Tyne Hospitals, Newcastle upon Tyne, UK
| | - Simon Bailey
- Paediatric Oncology, Great North Children's Hospital, Newcastle upon Tyne, UK
| | - Vijay Sawlani
- Radiology, Queen Elizabeth Hospital Birmingham, Birmingham, UK
- School of Psychology, University of Birmingham, Birmingham, UK
| | - Theodoros N Arvanitis
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
- Institute of Digital Healthcare, WMG, University of Warwick, Coventry, UK
| | - Yu Sun
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
- University of Birmingham and Southeast University Joint Research Centre for Biomedical Engineering, Suzhou, China
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Oncology, Birmingham Children's Hospital, Birmingham, UK
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Lin K, Cidan W, Qi Y, Wang X. Glioma Grading Prediction Using Multiparametric Magnetic Resonance Imaging-based Radiomics Combined with Proton Magnetic Resonance Spectroscopy and Diffusion Tensor Imaging. Med Phys 2022; 49:4419-4429. [PMID: 35366379 DOI: 10.1002/mp.15648] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 11/30/2021] [Accepted: 03/23/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To evaluate the efficacy of three-dimensional (3D) segmentation-based radiomics analysis of multiparametric MRI combined with proton magnetic resonance spectroscopy (1 H-MRS) and diffusion tensor imaging (DTI) in glioma grading. METHOD A total of 100 patients with histologically confirmed gliomas (grade II-IV) were examined using conventional MRI, 1 H-MRS, and DTI. Tumor segmentations of T1-weighted imaging (T1WI), contrast-enhanced T1WI (T1WI+C), T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC) mapping, and fractional anisotropy (FA) mapping were performed. In total, 396 radiomics features were extracted and reduced using basic tests and least absolute shrinkage and selection operator (LASSO) regression. The selected features of each sequence were combined, and logistic regression with ten-fold cross-validation was applied to develop the grading model. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were compared. The model developed from the training set was applied to the test set to measure accuracy. One optimal grading quantitative parameter was selected for each 1 H-MRS and DTI analysis. A radiomics nomogram model including radiomics signature, quantitative parameters, and clinical features was developed. RESULTS T1WI+C exhibited the highest grading efficacy among single sequences (AUC, 0.92; sensitivity, 0.89; specificity, 0.85), but the efficacy of the combined model was higher (AUC, 0.97; sensitivity, 0.94; specificity, 0.91). The AUCs of all models exhibited high accuracy, and no significant differences were observed in AUCs between the training and test sets. The visualized nomogram was developed based on the combined radiomics signature and choline (Cho)/N-acetyl aspartate (NAA) from 1 H-MRS. CONCLUSION Multiparametric MRI can be used to predict the pathological grading of HGG and LGG by combining radiomics features with quantitative parameters. The visualized nomogram may provide an intuitive assessment tool in clinical practice. CLINICAL TRIAL REGISTRATION This trial was not registered, as it was a retrospective study and was approved by the local institutional review board. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Kun Lin
- Department of Radiology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China
| | - Wangjiu Cidan
- Department of Radiology, People's Hospital of Tibet Autonomous Region, 18 Linkuo North Road, Chengguan District, Lhasa, 850000, China
| | - Ying Qi
- Department of Radiology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China
| | - Xiaoming Wang
- Department of Radiology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Heping District, Shenyang, Liaoning, 110004, China
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Davies NP, Rose HEL, Manias KA, Natarajan K, Abernethy LJ, Oates A, Janjua U, Davies P, MacPherson L, Arvanitis TN, Peet AC. Added value of magnetic resonance spectroscopy for diagnosing childhood cerebellar tumours. NMR Biomed 2022; 35:e4630. [PMID: 34647377 DOI: 10.1002/nbm.4630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/20/2021] [Accepted: 09/15/2021] [Indexed: 06/13/2023]
Abstract
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.
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Affiliation(s)
- Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Department of Medical Physics, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Heather E L Rose
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Kal Natarajan
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Department of Medical Physics, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | | | - Adam Oates
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Umair Janjua
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Paul Davies
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Lesley MacPherson
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Theodoros N Arvanitis
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
- Institute of Digital Healthcare, WMG, University of Warwick, Coventry, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
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Sbardella E, Puliani G, Feola T, Pofi R, Pirchio R, Sesti F, Verdecchia F, Gianfrilli D, Moffat D, Isidori AM, Grossman AB. A clinical approach to parasellar lesions in the transition age. J Neuroendocrinol 2021; 33:e12995. [PMID: 34138496 DOI: 10.1111/jne.12995] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 03/23/2021] [Accepted: 05/11/2021] [Indexed: 12/16/2022]
Abstract
Many reviews have summarised the pathology and management of the parasellar region in adult patients, although an analysis of these aspects in the transition years, from puberty onset to the age of peak bone mass, has been lacking. A comprehensive search of English-language original articles, published from 2000 to 2020, was conducted in the MEDLINE database (December 2019 to March 2020). We selected all studies regarding epidemiology, diagnosis and management of the following parasellar lesions: germinoma, craniopharyngioma, Langerhans cell histiocytosis, optic glioma, hypothalamic hamartoma, tuber cinereum hamartoma, cranial chordoma, Rathke cleft cyst, hypophysitis and hypothalamitis during the transition age from childhood to adulthood. In the present review, we provide an overview of the principal parasellar lesions occurring in the transition age. Symptoms are usually a result of the mass effect of the lesions on nearby structures, as well as anterior pituitary deficits. Diabetes insipidus occurs frequently in these patients. In this age group, pubertal developmental disorders may be more evident compared to other stages of life. Parasellar lesions in the transition age mostly include neoplastic lesions such as germinomas, hamartomas, optic gliomas, craniopharyngiomas Langerhans cell histiocytosis and chordomas, and rarely inflammatory lesions (hypophysitis, hypothalamitis). There are limited data on the management of parasellar lesions in the transition age. Endocrine evaluation is crucial for identifying conditions that require hormonal treatment so that they can be treated early to improve the quality of life of the individual patient in this complex age range. The clinical approach to parasellar lesions involves a multidisciplinary effort.
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Affiliation(s)
- Emilia Sbardella
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Giulia Puliani
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
- Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Tiziana Feola
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
- Neuroendocrinology, Neuromed Institute, IRCCS, Pozzilli, Italy
| | - Riccardo Pofi
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Rosa Pirchio
- Dipartimento di Medicina Clinica e Chirurgia, Sezione di Endocrinologia, Università Federico II di Napoli, Naples, Italy
| | - Franz Sesti
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Federica Verdecchia
- Dipartimento Pediatrico Universitario Ospedaliero, Bambino Gesù Children Hospital, Rome, Italy
| | - Daniele Gianfrilli
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Daniel Moffat
- Department of Neurosurgery, Barts and the London NHS Trust, London, UK
| | - Andrea M Isidori
- Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Ashley B Grossman
- Department of Endocrinology, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Oxford, UK
- Centre for Endocrinology, Barts and the London School of Medicine, London, UK
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Grist JT, Miller JJ, Zaccagna F, McLean MA, Riemer F, Matys T, Tyler DJ, Laustsen C, Coles AJ, Gallagher FA. Hyperpolarized 13C MRI: A novel approach for probing cerebral metabolism in health and neurological disease. J Cereb Blood Flow Metab 2020; 40:1137-1147. [PMID: 32153235 PMCID: PMC7238376 DOI: 10.1177/0271678x20909045] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/24/2020] [Accepted: 01/28/2020] [Indexed: 12/13/2022]
Abstract
Cerebral metabolism is tightly regulated and fundamental for healthy neurological function. There is increasing evidence that alterations in this metabolism may be a precursor and early biomarker of later stage disease processes. Proton magnetic resonance spectroscopy (1H-MRS) is a powerful tool to non-invasively assess tissue metabolites and has many applications for studying the normal and diseased brain. However, the technique has limitations including low spatial and temporal resolution, difficulties in discriminating overlapping peaks, and challenges in assessing metabolic flux rather than steady-state concentrations. Hyperpolarized carbon-13 magnetic resonance imaging is an emerging clinical technique that may overcome some of these spatial and temporal limitations, providing novel insights into neurometabolism in both health and in pathological processes such as glioma, stroke and multiple sclerosis. This review will explore the growing body of pre-clinical data that demonstrates a potential role for the technique in assessing metabolism in the central nervous system. There are now a number of clinical studies being undertaken in this area and this review will present the emerging clinical data as well as the potential future applications of hyperpolarized 13C magnetic resonance imaging in the brain, in both clinical and pre-clinical studies.
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Affiliation(s)
- James T Grist
- Institute of Cancer and Genomic Sciences, University of
Birmingham, Birmingham, UK
- Department of Radiology, University of Cambridge, Cambridge,
UK
| | - Jack J Miller
- Department of Physiology, Anatomy, and Genetics, University of
Oxford, Oxford, UK
- Department of Physics, Clarendon Laboratory, University of
Oxford, Oxford, UK
- Oxford Centre for Clinical Magnetic Resonance Research, John
Radcliffe Hospital, Oxford, UK
| | - Fulvio Zaccagna
- Department of Radiology, University of Cambridge, Cambridge,
UK
| | - Mary A McLean
- Department of Radiology, University of Cambridge, Cambridge,
UK
- CRUK Cambridge Institute, Cambridge, UK
| | - Frank Riemer
- Department of Radiology, University of Cambridge, Cambridge,
UK
| | - Tomasz Matys
- Department of Radiology, University of Cambridge, Cambridge,
UK
| | - Damian J Tyler
- Department of Physiology, Anatomy, and Genetics, University of
Oxford, Oxford, UK
- Oxford Centre for Clinical Magnetic Resonance Research, John
Radcliffe Hospital, Oxford, UK
| | | | - Alasdair J Coles
- Department of Clinical Neurosciences, University of Cambridge,
Cambridge, UK
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8
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Grist JT, Withey S, MacPherson L, Oates A, Powell S, Novak J, Abernethy L, Pizer B, Grundy R, Bailey S, Mitra D, Arvanitis TN, Auer DP, Avula S, Peet AC. Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study. Neuroimage Clin 2020; 25:102172. [PMID: 32032817 DOI: 10.1016/j.nicl.2020.102172] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/04/2019] [Accepted: 01/10/2020] [Indexed: 12/12/2022]
Abstract
The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non-invasive diagnosis of children's brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality. The aim of this work was to combine multi-centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types. The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with >80% predictive precision. This work represents a step forward to aid in the non-invasive diagnosis of paediatric brain tumours, using advanced clinical imaging.
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Manias KA, Gill SK, MacPherson L, Oates A, Pinkey B, Davies P, Zarinabad N, Davies NP, Babourina-Brooks B, Wilson M, Peet AC. Diagnostic accuracy and added value of qualitative radiological review of 1H-magnetic resonance spectroscopy in evaluation of childhood brain tumors. Neurooncol Pract 2019; 6:428-437. [PMID: 31832213 DOI: 10.1093/nop/npz010] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
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.
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Affiliation(s)
- Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
| | - Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
| | | | - Adam Oates
- Department of Radiology, Birmingham Children's Hospital, UK
| | | | - Paul Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK
| | | | - Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK.,Department of Imaging and Medical Physics, University Hospitals Birmingham NHS Foundation Trust, UK
| | | | | | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
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10
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Zhu L, Wang J, Shi H, Tao X. Multimodality fMRI with perfusion, diffusion-weighted MRI and 1 H-MRS in the diagnosis of lympho-associated benign and malignant lesions of the parotid gland. J Magn Reson Imaging 2018; 49:423-432. [PMID: 30475438 DOI: 10.1002/jmri.26260] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 06/28/2018] [Accepted: 06/29/2018] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Differential diagnosis of the mucosa-associated lymphoid tissue lymphoma (MALToma) and tumor-like benign lymphoepithelial lesion (BLEL) in the parotid gland is difficult. PURPOSE To distinguish MALToma and BLEL with multimodality MRI including hydrogenproton magnetic resonance spectroscopy (1 H-MRS), diffusion-weighted imaging (DWI-MR), and dynamic contrast-enhanced (DCE-MR), and evaluate each sequence. STUDY TYPE Retrospective. POPULATION Twenty-five patients with parotid tumor-like BLEL and 20 with parotid MALToma. FIELD STRENGTH/SEQUENCE 1.5-T/T1 WI, T2 WI, single-voxel 1 H-MRS, DWI-MR, and DCE-MR. ASSESSMENT All MR images were interpreted and agreed upon by two radiologists who were blinded to clinical information and histopathologic results. The imaging diagnoses were then compared to the histopathologic results. STATISTICAL TESTS Youden index was used to determine the optimized threshold value. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of different functional (f)MRI methods. RESULTS Fisher's exact test indicated a significant difference between the 1 H-MRS images of the two lesions (P < 0.001). The sensitivity, specificity, and accuracy of positive choline (Cho) peak in 1 H-MRS of parotid MALToma were 80%, 76%, and 77.7%, respectively. The mean apparent diffusion coefficient (ADC) was 0.992 × 10-3 mm2 /s in patients with parotid tumor-like BLEL and 0.634 × 10-3 mm2 /s in patients with parotid MALToma, and the difference was statistically significant (t-test, P < 0.001). Choosing the Youden index as 0.669 × 10-3 mm2 /s, the sensitivity, specificity, and accuracy of the assay were 78.9%, 95.8%, and 88.4%, respectively. Assuming that time-intensity curve (TIC) type I indicated parotid MALToma (positive), and type II and type III indicated parotid tumor-like BLEL (negative), the sensitivity, specificity, and accuracy of time-to-peak (TTP) and initial slope of increase (ISI) in diagnosing MALToma were 94.1%, 95.2%, and 94.7%, respectively. Combining methods of TTP, ADC, and Cho peak reached the highest AUC (1.000). DATA CONCLUSION Combined use 1 H-MRS, DWI-MR, and DCE-MR increased the accuracy of the differential diagnosis between these lesions to 100%. Cho peak in 1 H-MRS, ADC less than 0.669 × 10-3 mm2 /s, TIC type I together indicated parotid MALToma. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:423-432.
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Affiliation(s)
- Ling Zhu
- Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Department of Radiology, Shanghai, P.R. China
| | - Jingbo Wang
- Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Department of Radiology, Shanghai, P.R. China
| | - Huimin Shi
- Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Department of Radiology, Shanghai, P.R. China
| | - Xiaofeng Tao
- Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Department of Radiology, Shanghai, P.R. China
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11
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Abstract
Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.
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Affiliation(s)
- Geoffrey S Payne
- University Hospitals Southampton NHS Foundation Trust, Tremona Road, Southampton SO16 6YD, United Kingdom
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12
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Abstract
1H-Magnetic Resonance Spectroscopy (MRS) is a novel advanced imaging technique used as an adjunct to MRI to reveal complementary non-invasive information about the biochemical composition of imaged tissue. Clinical uses in paediatrics include aiding diagnosis of brain tumours, neonatal disorders such as hypoxic-ischaemic encephalopathy, inherited metabolic diseases, traumatic brain injury, demyelinating conditions and infectious brain lesions. MRS has potential to improve diagnosis and treatment monitoring of childhood brain tumours and other CNS diseases, facilitate biopsy and surgical planning, and provide prognostic biomarkers. MRS is employed as a research tool outside the brain in liver disease and disorders of muscle metabolism. The range of clinical uses is likely to increase with growing evidence for added value. Multicentre trials are needed to definitively establish the benefits of MRS in specific clinical scenarios and integrate this promising new technique into routine practice to improve patient care. This article gives a brief overview of MRS and its potential clinical applications, and addresses challenges surrounding translation into practice.
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Affiliation(s)
- Karen Angela Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, West Midlands, UK.,Department of Paediatric Oncology, Birmingham Children's Hospital, Birmingham, West Midlands, UK
| | - Andrew Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, West Midlands, UK.,Department of Paediatric Oncology, Birmingham Children's Hospital, Birmingham, West Midlands, UK
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13
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Ratai EM, Zhang Z, Fink J, Muzi M, Hanna L, Greco E, Richards T, Kim D, Andronesi OC, Mintz A, Kostakoglu L, Prah M, Ellingson B, Schmainda K, Sorensen G, Barboriak D, Mankoff D, Gerstner ER. ACRIN 6684: Multicenter, phase II assessment of tumor hypoxia in newly diagnosed glioblastoma using magnetic resonance spectroscopy. PLoS One 2018; 13:e0198548. [PMID: 29902200 PMCID: PMC6002091 DOI: 10.1371/journal.pone.0198548] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 05/21/2018] [Indexed: 11/18/2022] Open
Abstract
A multi-center imaging trial by the American College of Radiology Imaging Network (ACRIN) "A Multicenter, phase II assessment of tumor hypoxia in glioblastoma using 18F Fluoromisonidazole (FMISO) with PET and MRI (ACRIN 6684)", was conducted to assess hypoxia in patients with glioblastoma (GBM). The aims of this study were to support the role of proton magnetic resonance spectroscopic imaging (1H MRSI) as a prognostic marker for brain tumor patients in multi-center clinical trials. Seventeen participants from four sites had analyzable 3D MRSI datasets acquired on Philips, GE or Siemens scanners at either 1.5T or 3T. MRSI data were analyzed using LCModel to quantify metabolites N-acetylaspartate (NAA), creatine (Cr), choline (Cho), and lactate (Lac). Receiver operating characteristic curves for NAA/Cho, Cho/Cr, lactate/Cr, and lactate/NAA were constructed for overall survival at 1-year (OS-1) and 6-month progression free survival (PFS-6). The OS-1 for the 17 evaluable patients was 59% (10/17). Receiver operating characteristic analyses found the NAA/Cho in tumor (AUC = 0.83, 95% CI: 0.61 to 1.00) and in peritumoral regions (AUC = 0.95, 95% CI 0.85 to 1.00) were predictive for survival at 1 year. PFS-6 was 65% (11/17). Neither NAA/Cho nor Cho/Cr was effective in predicting 6-month progression free survival. Lac/Cr in tumor was a significant negative predictor of PFS-6, indicating that higher lactate/Cr levels are associated with poorer outcome. (AUC = 0.79, 95% CI: 0.54 to 1.00). In conclusion, despite the small sample size in the setting of a multi-center trial comprising different vendors, field strengths, and varying levels of expertise at data acquisition, MRS markers NAA/Cho, Lac/Cr and Lac/NAA predicted overall survival at 1 year and 6-month progression free survival. This study validates that MRSI may be useful in evaluating the prognosis in glioblastoma and should be considered for incorporating into multi-center clinical trials.
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Affiliation(s)
- Eva-Maria Ratai
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, United States
- A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States of America
| | - Zheng Zhang
- Center for Statistical Sciences, Brown University, Providence, RI, United States of America
| | - James Fink
- Department of Radiology, University of Washington, Seattle, WA, United States of America
| | - Mark Muzi
- Department of Radiology, University of Washington, Seattle, WA, United States of America
| | - Lucy Hanna
- Center for Statistical Sciences, Brown University, Providence, RI, United States of America
| | - Erin Greco
- Center for Statistical Sciences, Brown University, Providence, RI, United States of America
| | - Todd Richards
- Department of Radiology, University of Washington, Seattle, WA, United States of America
| | - Daniel Kim
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, United States
- A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States of America
| | - Ovidiu C. Andronesi
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, United States
- A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States of America
| | - Akiva Mintz
- Department of Radiology, Wake Forest University, Winston-Salem, NC, United States of America
| | - Lale Kostakoglu
- Department of Radiology, Mt. Sinai Medical Center, New York, NY, United States of America
| | - Melissa Prah
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States of America
| | - Benjamin Ellingson
- Department of Radiology, UCLA Medical Center, Los Angeles, CA, United States of America
| | - Kathleen Schmainda
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States of America
| | - Gregory Sorensen
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, United States
- A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States of America
| | - Daniel Barboriak
- Department of Radiology, Duke University, Durham, NC, United States of America
| | - David Mankoff
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Elizabeth R. Gerstner
- A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States of America
- Massachusetts General Hospital Cancer Center, Boston, and Harvard Medical School, MA, United States of America
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14
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Manias K, Gill SK, Zarinabad N, Davies P, English M, Ford D, MacPherson L, Nicklaus-Wollenteit I, Oates A, Solanki G, Adamski J, Wilson M, Peet AC. Evaluation of the added value of 1H-magnetic resonance spectroscopy for the diagnosis of pediatric brain lesions in clinical practice. Neurooncol Pract 2017; 5:18-27. [PMID: 29692921 PMCID: PMC5909808 DOI: 10.1093/nop/npx005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background Magnetic resonance spectroscopy (MRS) aids noninvasive diagnosis of pediatric brain tumors, but use in clinical practice is not well documented. We aimed to review clinical use of MRS, establish added value in noninvasive diagnosis, and investigate potential impact on patient care. Methods Sixty-nine children with lesions imaged using MRS and reviewed by the tumor board from 2014 to 2016 met inclusion criteria. Contemporaneous MRI diagnosis, spectroscopy analysis, histopathology, and clinical information were reviewed. Final diagnosis was agreed on by the tumor board at study end. Results Five cases were excluded for lack of documented MRI diagnosis. The principal MRI diagnosis by pediatric radiologists was correct in 59%, increasing to 73% with addition of MRS. Of the 73%, 19.1% (95% CI, 9.1%-33.3%) were incorrectly diagnosed with MRI alone. MRS led to a significant improvement in correct diagnosis over all tumor types (P = .012). Of diagnoses correctly made with MRI, confidence increased by 37% when adding MRS, with no patients incorrectly re-diagnosed. Indolent lesions were diagnosed noninvasively in 85% of cases, with MRS a major contributor to 91% of these diagnoses. Of all patients, 39% were managed without histopathological diagnosis. MRS contributed to diagnosis in 68% of this group, modifying it in 12%. MRS influenced management in 33% of cases, mainly through avoiding and guiding biopsy and aiding tumor characterization. Conclusion MRS can improve accuracy and confidence in noninvasive diagnosis of pediatric brain lesions in clinical practice. There is potential to improve outcomes through avoiding biopsy of indolent lesions, aiding tumor characterization, and facilitating earlier family discussions and treatment planning.
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Affiliation(s)
- Karen Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Niloufar Zarinabad
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Paul Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Martin English
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Daniel Ford
- Department of Clinical Oncology, Queen Elizabeth Hospital, Birmingham, UK
| | - Lesley MacPherson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Radiology, Birmingham Children's Hospital, Birmingham, UK
| | - Ina Nicklaus-Wollenteit
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Histopathology, Birmingham Children's Hospital, Birmingham, UK
| | - Adam Oates
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Radiology, Birmingham Children's Hospital, Birmingham, UK
| | - Guirish Solanki
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Neurosurgery, Birmingham Children's Hospital, Birmingham, UK
| | - Jenny Adamski
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Martin Wilson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,School of Psychology, University of Birmingham, Birmingham, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
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15
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Manias KA, Gill SK, MacPherson L, Foster K, Oates A, Peet AC. Magnetic resonance imaging based functional imaging in paediatric oncology. Eur J Cancer 2016; 72:251-265. [PMID: 28011138 DOI: 10.1016/j.ejca.2016.10.037] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Revised: 09/26/2016] [Accepted: 10/30/2016] [Indexed: 12/16/2022]
Abstract
Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice.
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Affiliation(s)
- Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; Department of Paediatric Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
| | - Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; Department of Paediatric Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
| | - Lesley MacPherson
- Department of Radiology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
| | - Katharine Foster
- Department of Radiology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
| | - Adam Oates
- Department of Radiology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK; Department of Paediatric Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
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16
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Siasios I, Valotassiou V, Kapsalaki E, Tsougos I, Georgoulias P, Fotiadou A, Ioannou M, Koukoulis G, Dimopoulos V, Fountas K. Magnetic Resonance Spectroscopy and Single-Photon Emission Computed Tomography in the Evaluation of Cerebral Tumors: A Case Report. J Clin Med Res 2016; 9:74-78. [PMID: 27924180 PMCID: PMC5127220 DOI: 10.14740/jocmr2775w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2016] [Indexed: 12/16/2022] Open
Abstract
In their daily clinical practice, physicians have to confront diagnostic dilemmas which cannot be resolved by the application of only one imaging technique. In this case report, we present a 66-year-old woman who was admitted to our institution for the surgical resection of a recently diagnosed brain tumor. The patient had a history of epileptic seizures and was hospitalized in the past for anti-phospholipid syndrome related to a non-Hodgkin lymphoma in remission. Magnetic resonance imaging (MRI) examination revealed an enhancing right parasagittal lesion with significant edema suggestive of a high grade glioma. Advanced MRI techniques including proton magnetic resonance spectroscopy (1H-MRS) showed findings compatible of glioma. An additional examination was performed as part of a protocol that we are routinely performing in our institution for all brain tumors including not only the gold standard advanced MRI techniques but also single-photon emission computed tomography (SPECT) with technetium-99m (Tc99m). Brain SPECT indicated the presence of a meningioma which was verified by the histopathology of the resected specimen. In conclusion, a multimodality approach for the pre-surgical assessment of brain tumors has significant advantages not only for the diagnosis but also for the evaluation of intracranial tumors histology.
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Affiliation(s)
- Ioannis Siasios
- Department of Neurosurgery, University Hospital of Larissa, Greece; Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, Buffalo, NY, USA
| | | | - Eftychia Kapsalaki
- Department of Diagnostic Radiology, University Hospital of Larissa, Greece
| | - Ioannis Tsougos
- Department of Medical Physics, University Hospital of Larissa, Greece
| | | | | | - Maria Ioannou
- Department of Pathology, University Hospital of Larissa, Greece
| | | | - Vassilios Dimopoulos
- Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, Buffalo, NY, USA
| | - Kostas Fountas
- Department of Neurosurgery, University Hospital of Larissa, Greece
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17
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Jaspan T, Morgan PS, Warmuth-Metz M, Sanchez Aliaga E, Warren D, Calmon R, Grill J, Hargrave D, Garcia J, Zahlmann G. Response Assessment in Pediatric Neuro-Oncology: Implementation and Expansion of the RANO Criteria in a Randomized Phase II Trial of Pediatric Patients with Newly Diagnosed High-Grade Gliomas. AJNR Am J Neuroradiol 2016; 37:1581-7. [PMID: 27127006 DOI: 10.3174/ajnr.a4782] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Accepted: 02/14/2016] [Indexed: 11/07/2022]
Abstract
Determination of tumor response to treatment in neuro-oncology is challenging, particularly when antiangiogenic agents are considered. Nontumoral factors (eg, blood-brain barrier disruption, edema, and necrosis) can alter contrast enhancement independent of true tumor response/progression. Furthermore, gliomas are often infiltrative, with nonenhancing components. In adults, the Response Assessment in Neuro-Oncology (RANO) criteria attempted to address these issues. No such guidelines exist yet for children. The ongoing randomized phase II trial, A Study of Avastin (bevacizumab) in Combination With Temolozomide (TMZ) and Radiotherapy in Paediatric and Adolescent Patients With High-Grade Glioma (HERBY), will establish the efficacy and safety of the antiangiogenic agent bevacizumab for the first-line treatment of newly diagnosed high-grade glioma in children (n = 121 patients, enrollment complete). The primary end point is event-free survival (tumor progression/recurrence by central review, second primary malignancy, or death). Determination of progression or response is based on predefined clinical and radiographic criteria, modeled on the RANO criteria and supported by expert pseudoprogression review and the use of standardized imaging protocols. The HERBY trial will also compare conventional MR imaging (T1-weighted and T2/fluid-attenuated inversion recovery sequences) with conventional MR imaging plus diffusion/perfusion imaging for response assessment. It is anticipated that HERBY will provide new insights into antiangiogenic-treated pediatric brain tumors. HERBY will also investigate the practicality of obtaining adequate quality diffusion/perfusion scans in a trial setting, and the feasibility of implementing standard imaging protocols across multiple sites. To date, 61/73 (83.6%) patients with available data have completed diffusion-weighted imaging (uptake of other nonconventional techniques has been limited). Harmonization of imaging protocols and techniques may improve the robustness of pediatric neuro-oncology studies and aid future trial comparability.
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Affiliation(s)
- T Jaspan
- From Nottingham University Hospitals National Health Service Trust (T.J., P.S.M.), Nottingham, UK
| | - P S Morgan
- From Nottingham University Hospitals National Health Service Trust (T.J., P.S.M.), Nottingham, UK
| | | | - E Sanchez Aliaga
- VU University Medical Center (E.S.A.), Amsterdam, the Netherlands
| | - D Warren
- Leeds Teaching Hospital National Health Service Trust (D.W.), Leeds, West Yorkshire, UK
| | - R Calmon
- Assistance Publique-Hôpitaux de Paris (R.C.), Paris, France
| | - J Grill
- Gustave Roussy and Paris-Sud University (J.Grill), Villejuif, France
| | - D Hargrave
- Great Ormond Street Hospital (D.H.), London, UK
| | - J Garcia
- F. Hoffmann-La Roche (J.Garcia, G.Z.), Basel, Switzerland
| | - G Zahlmann
- F. Hoffmann-La Roche (J.Garcia, G.Z.), Basel, Switzerland
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18
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Julià-Sapé M, Griffiths JR, Tate AR, Howe FA, Acosta D, Postma G, Underwood J, Majós C, Arús C. Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes. NMR Biomed 2015; 28:1772-1787. [PMID: 26768492 DOI: 10.1002/nbm.3439] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Revised: 07/15/2015] [Accepted: 10/01/2015] [Indexed: 06/05/2023]
Abstract
The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection of MR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra from brain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future.
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Affiliation(s)
- Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | | | - A Rosemary Tate
- School of Informatics, University of Sussex, Falmer, Brighton, UK
| | - Franklyn A Howe
- Cardiovascular and Cell Sciences Research Institute, St George's, University of London, London, UK
| | - Dionisio Acosta
- CHIME, University College London, The Farr Institute of Health Informatics Research, London, UK
| | - Geert Postma
- Radboud University Nijmegen, Institute for Molecules and Materials, Analytical Chemistry, Nijmegen, The Netherlands
| | | | - Carles Majós
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Institut de Diagnòstic per la Imatge (IDI), CSU de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
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Kohe S, Brundler MA, Jenkinson H, Parulekar M, Wilson M, Peet AC, McConville CM. Metabolite profiling in retinoblastoma identifies novel clinicopathological subgroups. Br J Cancer 2015; 113:1216-24. [PMID: 26348444 PMCID: PMC4647873 DOI: 10.1038/bjc.2015.318] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 06/27/2015] [Accepted: 08/11/2015] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Tumour classification, based on histopathology or molecular pathology, is of value to predict tumour behaviour and to select appropriate treatment. In retinoblastoma, pathology information is not available at diagnosis and only exists for enucleated tumours. Alternative methods of tumour classification, using noninvasive techniques such as magnetic resonance spectroscopy, are urgently required to guide treatment decisions at the time of diagnosis. METHODS High-resolution magic-angle spinning magnetic resonance spectroscopy (HR-MAS MRS) was undertaken on enucleated retinoblastomas. Principal component analysis and cluster analysis of the HR-MAS MRS data was used to identify tumour subgroups. Individual metabolite concentrations were determined and were correlated with histopathological risk factors for each group. RESULTS Multivariate analysis identified three metabolic subgroups of retinoblastoma, with the most discriminatory metabolites being taurine, hypotaurine, total-choline and creatine. Metabolite concentrations correlated with specific histopathological features: taurine was correlated with differentiation, total-choline and phosphocholine with retrolaminar optic nerve invasion, and total lipids with necrosis. CONCLUSIONS We have demonstrated that a metabolite-based classification of retinoblastoma can be obtained using ex vivo magnetic resonance spectroscopy, and that the subgroups identified correlate with histopathological features. This result justifies future studies to validate the clinical relevance of these subgroups and highlights the potential of in vivo MRS as a noninvasive diagnostic tool for retinoblastoma patient stratification.
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Affiliation(s)
- Sarah Kohe
- School of Cancer Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK
| | - Marie-Anne Brundler
- Department of Histopathology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Helen Jenkinson
- Department of Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham B4 6NH, UK
| | - Manoj Parulekar
- Department of Ophthalmology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham B4 6NH, UK
| | - Martin Wilson
- School of Cancer Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK
| | - Andrew C Peet
- School of Cancer Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK
- Department of Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham B4 6NH, UK
| | - Carmel M McConville
- School of Cancer Sciences, University of Birmingham, Vincent Drive, Birmingham B15 2TT, UK
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She DJ, Xing Z, Zeng Z, Shang XY, Cao DR. Differentiation of hemangioblastomas from pilocytic astrocytomas using 3-T magnetic resonance perfusion-weighted imaging and MR spectroscopy. Neuroradiology 2015; 57:275-81. [PMID: 25487356 DOI: 10.1007/s00234-014-1475-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2014] [Accepted: 11/27/2014] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Hemangioblastomas and pilocytic astrocytomas (PAs) present similar imaging features on conventional MR imaging, making differential diagnosis a challenge. The purpose of this study was to evaluate the usefulness of dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI) and proton MR spectroscopic imaging in the differentiation of hemangioblastomas and PAs. METHODS A 3.0-T MR imaging unit was used to perform DSC-PWI and conventional MR imaging on 14 patients with hemangioblastomas and 22 patients with PAs. Four patients with hemangioblastomas and 10 PA patients also underwent proton MR spectroscopy. Parameters of relative peak height (rPH) and relative percentage of signal intensity recovery (rPSR) were acquired by DSC-PWI and variables of N-acetylaspasrtate (NAA)/creatine (Cr), choline (Cho)/Cr, and lactate-lipid (Lac-Lip)/Cr by MR spectroscopy. The sensitivity, specificity, and the area under the receiver operating characteristic curve of all analyzed parameters at respective cutoff values were determined. RESULTS Higher rPH but lower rPSR values were detected in hemangioblastomas compared to PAs. The NAA/Cr ratio was significantly lower in hemangioblastomas compared with PAs. The threshold values ≥3.2 for rPH provide sensitivity, specificity, positive predictive values, and negative predictive values of 85.7, 95.5, 92.3, and 91.3%, respectively, for differentiating hemangioblastomas from PAs. The optimal threshold values were ≤0.9 for rPSR and ≤1.5 for NAA/Cr ratios in tumor. CONCLUSION Significantly higher rPH and lower NAA/Cr were seen in patients with hemangioblastomas when compared with PA patients, suggesting that DSC-PWI and proton MR spectroscopy are helpful in the characterization and differentiation of these two types of tumors.
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El Sherbeny AE, El-Shafey MH, Biomy SL, Shakal AA, Hefeda MM, Seiam AHR. Diagnostic yield of combined magnetic resonance spectroscopy and diffusion weighted imaging in intracranial neoplasms. The Egyptian Journal of Radiology and Nuclear Medicine 2014. [DOI: 10.1016/j.ejrnm.2014.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022] Open
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Gill SK, Wilson M, Davies NP, MacPherson L, English M, Arvanitis TN, Peet AC. Diagnosing relapse in children's brain tumors using metabolite profiles. Neuro Oncol 2013; 16:156-64. [PMID: 24305716 DOI: 10.1093/neuonc/not143] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
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.
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Affiliation(s)
- Simrandip K Gill
- Corresponding author: Andrew C. Peet, MRCPCH, PhD, Institute of Child Health, Clinical Research Block, Whittall Street, Birmingham B4 6NH, UK.
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