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Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra
Author(s) -
Tate Anne R.,
Underwood Joshua,
Acosta Dionisio M.,
JuliàSapé Margarida,
Majós Carles,
MorenoTorres Àngel,
Howe Franklyn A.,
van der Graaf Marinette,
Lefournier Virginie,
Murphy Mary M.,
Loosemore Alison,
Ladroue Christophe,
Wesseling Pieter,
Luc Bosson Jean,
Cabañas Miquel E.,
Simonetti Arjan W.,
Gajewicz Witold,
Calvar Jorge,
Capdevila Antoni,
Wilkins Peter R.,
Bell B. Anthony,
Rémy Chantal,
Heerschap Arend,
Watson Des,
Griffiths John R.,
Arús Carles
Publication year - 2006
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.1016
Subject(s) - grading (engineering) , voxel , magnetic resonance imaging , decision support system , medicine , computer science , medical physics , in vivo , radiology , artificial intelligence , civil engineering , engineering , microbiology and biotechnology , biology
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 1 H 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.