Literature DB >> 21249420

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-Garcia1, 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, Angel Moreno-Torres, M C Martínez-Bisbal, Beatriz Martínez-Granados, Pieter Wesseling, Wolfhard Semmler, Jaume Capellades, Carles Majós, Angel Alberich-Bayarri, Antoni Capdevila, Daniel Monleón, Luis Martí-Bonmatí, Carles Arús, Bernardo Celda, Montserrat Robles.   

Abstract

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 (1)H 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.

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Year:  2011        PMID: 21249420     DOI: 10.1007/s10334-010-0241-8

Source DB:  PubMed          Journal:  MAGMA        ISSN: 0968-5243            Impact factor:   2.310


  23 in total

1.  Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging.

Authors:  Teresa Laudadio; M Carmen Martínez-Bisbal; Bernardo Celda; Sabine Van Huffel
Journal:  NMR Biomed       Date:  2008-05       Impact factor: 4.044

2.  Linear discriminant analysis of brain tumour (1)H MR spectra: a comparison of classification using whole spectra versus metabolite quantification.

Authors:  K S Opstad; C Ladroue; B A Bell; J R Griffiths; F A Howe
Journal:  NMR Biomed       Date:  2007-12       Impact factor: 4.044

3.  Effect of feature extraction for brain tumor classification based on short echo time 1H MR spectra.

Authors:  Jan Luts; Jean-Baptiste Poullet; Juan M Garcia-Gomez; Arend Heerschap; Montserrat Robles; Johan A K Suykens; Sabine Van Huffel
Journal:  Magn Reson Med       Date:  2008-08       Impact factor: 4.668

4.  Classification of brain tumours using short echo time 1H MR spectra.

Authors:  A Devos; L Lukas; J A K Suykens; L Vanhamme; A R Tate; F A Howe; C Majós; A Moreno-Torres; M van der Graaf; C Arús; S Van Huffel
Journal:  J Magn Reson       Date:  2004-09       Impact factor: 2.229

5.  MRS quality assessment in a multicentre study on MRS-based classification of brain tumours.

Authors:  Marinette van der Graaf; Margarida Julià-Sapé; Franklyn A Howe; Anne Ziegler; Carles Majós; Angel Moreno-Torres; Mark Rijpkema; Dionisio Acosta; Kirstie S Opstad; Yvonne M van der Meulen; Carles Arús; Arend Heerschap
Journal:  NMR Biomed       Date:  2008-02       Impact factor: 4.044

6.  Proton magnetic resonance spectroscopy in the distinction of high-grade cerebral gliomas from single metastatic brain tumors.

Authors:  Andrès Server; Roger Josefsen; Bettina Kulle; Jan Maehlen; Till Schellhorn; Øystein Gadmar; Theresa Kumar; Monika Haakonsen; Carl W Langberg; Per H Nakstad
Journal:  Acta Radiol       Date:  2010-04       Impact factor: 1.990

7.  Brain tumor classification based on long echo proton MRS signals.

Authors:  L Lukas; A Devos; J A K Suykens; L Vanhamme; F A Howe; C Majós; A Moreno-Torres; M Van der Graaf; A R Tate; C Arús; S Van Huffel
Journal:  Artif Intell Med       Date:  2004-05       Impact factor: 5.326

8.  The effect of combining two echo times in automatic brain tumor classification by MRS.

Authors:  Juan M García-Gómez; Salvador Tortajada; César Vidal; Margarida Julià-Sapé; Jan Luts; Angel Moreno-Torres; Sabine Van Huffel; Carles Arús; Montserrat Robles
Journal:  NMR Biomed       Date:  2008-11       Impact factor: 4.044

9.  Automated classification of short echo time in in vivo 1H brain tumor spectra: a multicenter study.

Authors:  A Rosemary Tate; Carles Majós; Angel Moreno; Franklyn A Howe; John R Griffiths; Carles Arús
Journal:  Magn Reson Med       Date:  2003-01       Impact factor: 4.668

10.  Multiproject-multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy.

Authors:  Juan M García-Gómez; Jan Luts; Margarida Julià-Sapé; Patrick Krooshof; Salvador Tortajada; Javier Vicente Robledo; Willem Melssen; Elies Fuster-García; Iván Olier; Geert Postma; Daniel Monleón; Angel Moreno-Torres; Jesús Pujol; Ana-Paula Candiota; M Carmen Martínez-Bisbal; Johan Suykens; Lutgarde Buydens; Bernardo Celda; Sabine Van Huffel; Carles Arús; Montserrat Robles
Journal:  MAGMA       Date:  2008-11-07       Impact factor: 2.310

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  3 in total

1.  Malignancy probability map as a novel imaging biomarker to predict malignancy distribution: employing MRS in GBM patients.

Authors:  Manijeh Beigi; Kevan Ghasemi; Parvin Mirzaghavami; Mohammadreza Khanmohammadi; Hamidreza SalighehRad
Journal:  J Neurooncol       Date:  2018-03-14       Impact factor: 4.130

2.  Evaluation of the INTERPRET decision-support system: can it improve the diagnostic value of magnetic resonance spectroscopy of the brain?

Authors:  J Hellström; R Romanos Zapata; S Libard; J Wikström; F Ortiz-Nieto; I Alafuzoff; R Raininko
Journal:  Neuroradiology       Date:  2018-11-15       Impact factor: 2.804

3.  Strategies for annotation and curation of translational databases: the eTUMOUR project.

Authors:  Margarida Julià-Sapé; Miguel Lurgi; Mariola Mier; Francesc Estanyol; Xavier Rafael; Ana Paula Candiota; Anna Barceló; Alina García; M Carmen Martínez-Bisbal; Rubén Ferrer-Luna; Ángel Moreno-Torres; Bernardo Celda; Carles Arús
Journal:  Database (Oxford)       Date:  2012-11-22       Impact factor: 3.451

  3 in total

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