Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra

Elies Fuster-Garcia, Clara Navarro, Javier Vicente, Salvador Tortajada, Juan M. García-Gómez, Carlos Sáez, Jorge Calvar, John Griffiths, Margarida Julià-Sapé, Franklyn A. Howe, Jesús Pujol, Andrew C. Peet, Arend Heerschap, Àngel Moreno-Torres, M. C. Martínez-Bisbal, Beatriz Martínez-Granados, Pieter Wesseling, Wolfhard Semmler, Jaume Capellades, Carles MajósÀngel Alberich-Bayarri, Antoni Capdevila, Daniel Monleón, Luis Martí-Bonmatí, Carles Arús, Bernardo Celda, Montserrat Robles

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


Object: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. Materials and methods: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 155 1.5T and 37 3T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. Results: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 ± 0.03 for 1.5T and 0.88 ± 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. Conclusion: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T 1H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.

Original languageEnglish
Pages (from-to)35-42
Number of pages8
JournalMagnetic Resonance Materials in Physics, Biology and Medicine
Issue number1
Publication statusPublished - Feb 2011
Externally publishedYes


  • Brain tumours
  • Clinical decision support systems
  • Magnetic resonance spectroscopy


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