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

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    Author
    Rodriguez, Gutierrez, D
    Jaspan, Tim
    Morgan, Paul S
    Grundy, Richard G
    Auer, Dorothee P
    Keyword
    Adolescent
    Brain neoplasms
    Child
    Magnetic resonance imaging
    Date
    2018
    
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    Publisher's URL
    https://dx.doi.org/10.1002/mrm.26837
    Abstract
    PURPOSE: 3T magnetic resonance scanners have boosted clinical application of 1 H-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 International Society for Magnetic Resonance in Medicine. Copyright © 2017 International Society for Magnetic Resonance in Medicine.
    Citation
    Zarinabad, N., Abernethy, L.J., Avula, S., Davies, N.P., Rodriguez Gutierrez, D., Jaspan, T., MacPherson, L., Mitra, D., Rose, H.E.L., Wilson, M., Morgan, P.S., Bailey, S., Pizer, B., Arvanitis, T.N., Grundy, R.G., Auer, D.P. and Peet, A. (2018) 'Application of pattern recognition techniques for classification of pediatric brain tumors by in vivo 3T 1 H-MR spectroscopy-A multi-center study', Magnetic resonance in medicine, 79(4), pp. 2359-2366. doi: https://dx.doi.org/10.1002/mrm.26837.
    Publisher
    John Wiley and Sons Ltd
    Type
    Article
    URI
    http://hdl.handle.net/20.500.12904/15885
    Collections
    Medical Physics and Clinical Engineering
    Healthcare Scientists

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