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dc.contributor.author | Vicente Robledo, Javier | es_ES |
dc.contributor.author | Fuster García, Elíes | es_ES |
dc.contributor.author | Tortajada Velert, Salvador | es_ES |
dc.contributor.author | García Gómez, Juan Miguel | es_ES |
dc.contributor.author | Davies, Nigel | es_ES |
dc.contributor.author | Natarajan, Kal | es_ES |
dc.contributor.author | Wilson, Martin | es_ES |
dc.contributor.author | Grundy, Richard G. | es_ES |
dc.contributor.author | Wesseling, Pieter | es_ES |
dc.contributor.author | Monleón, Daniel | es_ES |
dc.contributor.author | Celda, Bernardo | es_ES |
dc.contributor.author | Robles, Montserrat | es_ES |
dc.contributor.author | Peet, Andrew C. | es_ES |
dc.date.accessioned | 2014-03-03T11:30:14Z | |
dc.date.issued | 2013-02 | |
dc.identifier.issn | 0959-8049 | |
dc.identifier.uri | http://hdl.handle.net/10251/36089 | |
dc.description.abstract | Aims: To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy (1H-MRS) as a non-invasive diagnostic aid for pediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on 1H-MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy. Methods: 78 patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.5Tesla PRESS, PROBE or STEAM, TE 20-32 ms, and 135-136 ms). MRS data was processed using two strategies, determination of metabolite concentrations using TARQUIN software and automatic feature extraction with Peak Integration. Linear Discriminant Analysis was applied to this data to produce diagnostic classifiers. An evaluation of the diagnostic accuracy was performed based on resampling to measure the Balanced Accuracy Rate (BAR). Results: The accuracy of the diagnostic classifiers for discriminating the three tumour types was found to be high (BAR 0.98) when a combination of TE was used. The combination of both TE significantly improved the classification performance (p < 0.01, Tukey¿s test) compared with the use of one TE alone. 3 Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00). Conclusions: 1H-MRS has excellent accuracy for the non-invasive diagnosis of common childhood brain tumours particularly if the metabolite information is maximised and should become part of routine clinical assessment for these children. | es_ES |
dc.description.sponsorship | This work was funded by the European Commission (FP6-2002-LIFESCIHEALTH 503094). Additional analysis was made available through the CR UK and EPSRC Cancer Imaging Programme at the Children's cancer and Leukaemia Group in association with the MRC and Department of Health (England) (C7809/A10342). We thank eTUMOUR partners for providing data, in particular J. Capellades (IDI-Badalona), C. Majos (IDI-Bellvitge), A. Moreno (Centre Diagnostic Pedralbes), J. Calvar (FLENI) and A. Capdevila (H. Sant Joan de Deu). | en_EN |
dc.format.extent | 10 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | European Journal of Cancer | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | 1H MRS | es_ES |
dc.subject | Paediatric brain tumours | es_ES |
dc.subject | Classification | es_ES |
dc.subject | Pattern recognition | es_ES |
dc.subject | Feature extraction | es_ES |
dc.subject | Pre-surgery diagnosis assessment | es_ES |
dc.subject | Non-invasive diagnosis | es_ES |
dc.subject | Multi-centre study | es_ES |
dc.subject | Clinical assessment | es_ES |
dc.subject.classification | FISICA APLICADA | es_ES |
dc.title | Accurate classification of childhood brain tumours by in vivo 1H MRS - a multi-centre study | es_ES |
dc.type | Artículo | es_ES |
dc.embargo.lift | 10000-01-01 | |
dc.embargo.terms | forever | es_ES |
dc.identifier.doi | 10.1016/j.ejca.2012.09.003 | |
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.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.description.bibliographicCitation | Vicente Robledo, J.; Fuster Garcia, E.; Tortajada Velert, S.; García Gómez, JM.; Davies, N.; Natarajan, K.; Wilson, M.... (2013). Accurate classification of childhood brain tumours by in vivo 1H MRS - a multi-centre study. European Journal of Cancer. 49(3):658-667. doi:10.1016/j.ejca.2012.09.003 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.ejca.2012.09.003 | es_ES |
dc.description.upvformatpinicio | 658 | es_ES |
dc.description.upvformatpfin | 667 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 49 | es_ES |
dc.description.issue | 3 | es_ES |
dc.relation.senia | 234778 | |
dc.contributor.funder | European Commission | es_ES |