Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours

Martin Wilson, Carole L Cummins, Lesley Macpherson, Yu Sun, Kal Natarajan, Richard G Grundy, Theodoros N Arvanitis, Risto A Kauppinen, Andrew C Peet

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43 Citations (Scopus)
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Abstract

Background Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. 1H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Patients and methods Short echo time (30 ms) single voxel 1H MRS was performed on children attending Birmingham Children’s Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Results Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (p < 0.05). A multivariate model of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p < 5e–5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. Conclusions MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy.
Original languageEnglish
JournalEuropean Journal of Cancer
Volume49
Issue number2
Early online date1 Oct 2012
DOIs
Publication statusPublished - Jan 2013

Keywords

  • MRS
  • Metabolism
  • 1H
  • Proton
  • Lipids
  • Childhood
  • Glutamine
  • LCModel
  • Grade
  • Non-invasive

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