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

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

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dc.contributor.author Fuster García, Elíes es_ES
dc.contributor.author Navarro., Clara es_ES
dc.contributor.author Vicente Robledo, Javier es_ES
dc.contributor.author Tortajada Velert, Salvador es_ES
dc.contributor.author García Gómez, Juan Miguel es_ES
dc.contributor.author Sáez Silvestre, Carlos es_ES
dc.contributor.author Calvar ., Jorge es_ES
dc.contributor.author Griffiths ., John es_ES
dc.contributor.author Julia Sape, Margarita es_ES
dc.contributor.author Howe ., Franklyn A es_ES
dc.contributor.author Pujol ., Jesús es_ES
dc.contributor.author Peet ., Andrew C es_ES
dc.contributor.author Heerschap ., Arend es_ES
dc.contributor.author Moreno Torres, Àngel es_ES
dc.contributor.author Martínez-Bisbal, M.Carmen es_ES
dc.contributor.author Martinez Granados, Beatriz es_ES
dc.contributor.author Wesseling ., Pieter es_ES
dc.contributor.author Semmler ., Wolfhard es_ES
dc.contributor.author Capellades ., Jaume es_ES
dc.contributor.author Majós ., Carles es_ES
dc.contributor.author Alberich Bayarri, Ángel es_ES
dc.contributor.author Capdevila ., Antoni es_ES
dc.contributor.author Monleón ., Daniel es_ES
dc.contributor.author Marti Bonmati, Luis es_ES
dc.contributor.author Arús ., Carles es_ES
dc.contributor.author Celda ., Bernardo es_ES
dc.contributor.author Robles Viejo, Montserrat es_ES
dc.date.accessioned 2014-09-11T16:04:51Z
dc.date.issued 2011-02
dc.identifier.issn 0968-5243
dc.identifier.uri http://hdl.handle.net/10251/39576
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/s10334-010-0241-8 es_ES
dc.description.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 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. © 2011 ESMRMB. es_ES
dc.description.sponsorship We would like to thank Miriam Camison-Sanchez for help in the quality control of the MRS data and diagnosis validation. This work was partially funded by the European Commission (FP6-2002-LIFESCIHEALTH 503094) and (IST-2004-27214), the I + D support program of the Universitat Politecnica de Valencia and by the Health Institute Carlos III through the RETICS Combiomed, RD07/0067/2001. CIBER-BBN is an initiative funded by the VI National R&D&D&I Plan 2008-2011, CIBER Actions and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund. The authors acknowledge to Programa Torres Quevedo from Ministerio de Educacion y Ciencia, co-founded by the European Social Fund (PTQ05-02-03386, PTQ-08-01-06802, PTQ-08-01-06817). en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Magnetic Resonance Materials in Physics, Biology and Medicine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Brain tumours es_ES
dc.subject Clinical decision support systems es_ES
dc.subject Magnetic resonance spectroscopy es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra es_ES
dc.type Artículo es_ES
dc.embargo.terms forever es_ES
dc.identifier.doi 10.1007/s10334-010-0241-8
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP6/503094/EU/WEB ACCESSIBLE MR DECISION SUPPORT SYSTEM FOR BRAIN TUMOUR DIAGNOSIS AND PROGNOSIS, INCORPORATING IN VIVO AND EX VIVO GENOMIC AND METABOLIMIC DATA/ETUMOUR/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//RD07%2F0067%2F2001/ES/RED TEMÁTICA DE INVESTIGACIÓN COOPERATIVA EN BIOMEDICINA COMPUTACIONAL/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//PTQ05-02-03386/ES/PTQ05-02-03386/ / es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//PTQ-08-01-06802/ES/PTQ-08-01-06802/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//PTQ-08-01-06817/ES/PTQ-08-01-06817/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada es_ES
dc.description.bibliographicCitation Fuster García, E.; Navarro., C.; Vicente Robledo, J.; Tortajada Velert, S.; García Gómez, JM.; Sáez Silvestre, C.; Calvar ., J.... (2011). Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra. Magnetic Resonance Materials in Physics, Biology and Medicine. 24(1):35-42. https://doi.org/10.1007/s10334-010-0241-8 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://link.springer.com/article/10.1007/s10334-010-0241-8 es_ES
dc.description.upvformatpinicio 35 es_ES
dc.description.upvformatpfin 42 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 24 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 217489
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
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