Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra

Anne R. Tate, Joshua Underwood, Dionisio M. Acosta, Margarida Julià-Sapé, Carles Majós, Àngel Moreno-Torres, Franklyn A. Howe, Marinette van der Graaf, Virginie Lefournier, Mary M. Murphy, Alison Loosemore, Christophe Ladroue, Pieter Wesseling, Jean Luc Bosson, Miguel E. Cabañas, Arjan W. Simonetti, Witold Gajewicz, Jorge Calvar, Antoni Capdevilla, Peter R. WilkinsB. Anthony Bell, Chantal Rémy, Arend Heerschap, Des Watson, John R. Griffiths, Carles Arús

Research output: Contribution to journalArticleResearchpeer-review

170 Citations (Scopus)


A computer-based decision support system to assist radiologists in diagnosing and grading brain tumours has been developed by the multi-centre INTERPRET project. Spectra from a database of 1H single-voxel spectra of different types of brain tumours, acquired in vivo from 334 patients at four different centres, are clustered according to their pathology, using automated pattern recognition techniques and the results are presented as a two-dimensional scatterplot using an intuitive graphical user interface (GUI). Formal quality control procedures were performed to standardize the performance of the instruments and check each spectrum, and teams of expert neuroradiologists, neurosurgeons, neurologists and neuropathologists clinically validated each case. The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours - glioblastomas and metastases). It also helps to resolve diagnostic difficulty in borderline cases. When the prototype was tested by radiologists and other clinicians it was favourably received. Results of the preliminary clinical analysis of the added value of using the DSS for brain tumour diagnosis with MRS showed a small but significant improvement over MRI used alone. In the comparison of individual pathologies, PNETs were significantly better diagnosed with the DSS than with MRI alone. Copyright © 2006 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)411-434
JournalNMR in Biomedicine
Publication statusPublished - 1 Jun 2006


  • 1 H
  • Brain
  • Cancer
  • Humans
  • MRS
  • MRS pattern recognition
  • Multivariate analysis

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