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Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction

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Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction

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dc.contributor.author Larroza, Andrés es_ES
dc.contributor.author López-Lereu, M.P. es_ES
dc.contributor.author Monmeneu, J.V. es_ES
dc.contributor.author Gavara-Doñate, Josep es_ES
dc.contributor.author Chorro, F.J. es_ES
dc.contributor.author Bodi, V. es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2020-07-10T03:31:22Z
dc.date.available 2020-07-10T03:31:22Z
dc.date.issued 2018-04-16 es_ES
dc.identifier.issn 0094-2405 es_ES
dc.identifier.uri http://hdl.handle.net/10251/147734
dc.description.abstract [EN] Purpose: To investigate the ability of texture analysis to differentiate between infarcted nonviable, viable, and remote segments on cardiac cine magnetic resonance imaging (MRI). Methods: This retrospective study included 50 patients suffering chronic myocardial infarction. The data were randomly split into training (30 patients) and testing (20 patients) sets. The left ventricular myocardium was segmented according to the 17-segment model in both cine and late gadolinium enhancement (LGE) MRI. Infarcted myocardium regions were identified on LGE in short-axis views. Nonviable segments were identified as those showing LGE 50%, and viable segments those showing 0 < LGE < 50% transmural extension. Features derived from five texture analysis methods were extracted from the segments on cine images. A support vector machine (SVM) classifier was trained with different combination of texture features to obtain a model that provided optimal classification performance. Results: The best classification on testing set was achieved with local binary patterns features using a 2D + t approach, in which the features are computed by including information of the time dimension available in cine sequences. The best overall area under the receiver operating characteristic curve (AUC) were: 0.849, sensitivity of 92% to detect nonviable segments, 72% to detect viable segments, and 85% to detect remote segments. Conclusion: Nonviable segments can be detected on cine MRI using texture analysis and this may be used as hypothesis for future research aiming to detect the infarcted myocardium by means of a gadolinium-free approach. es_ES
dc.description.sponsorship This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and FEDER funds under grant BFU2015-64380-C2-2-R, by Instituto de Salud Carlos III and FEDER funds under grants FIS PI14/00271 and PIE15/00013 and by the Generalitat Valenciana under grant PROMETEO/2013/007. The first author, Andres Larroza, was supported by grant FPU12/01140 from the Spanish Ministerio de Educacion, Cultura y Deporte (MECD). es_ES
dc.language Inglés es_ES
dc.publisher John Wiley & Sons es_ES
dc.relation.ispartof Medical Physics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Classification es_ES
dc.subject Diagnosis es_ES
dc.subject Heart es_ES
dc.subject Machine learning es_ES
dc.subject Magnetic resonance imaging es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1002/mp.12783 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//BFU2015-64380-C2-2-R/ES/ANALISIS DE TEXTURAS EN IMAGEN CEREBRAL MULTIMODAL POR RESONANCIA MAGNETICA PARA UNA DETECCION TEMPRANA DE ALTERACIONES EN LA RED Y BIOMARCADORES DE ENFERMEDAD/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//PIE15%2F00013/ES/A multidisciplinary project to advance in basic mechanisms, diagnosis, prediction, and prevention of cardiac damage in reperfused acute myocardial infarction/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//PI14%2F00271/ES/Fibrosis miocárdica tras un infarto de miocardio. Estudio traslacional para la innovación diagnóstica con resonancia magnética y para el entendimiento de los mecanismos reguladores/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//PROMETEO%2F2013%2F007/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU12%2F01140/ES/FPU12%2F01140/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Larroza, A.; López-Lereu, M.; Monmeneu, J.; Gavara-Doñate, J.; Chorro, F.; Bodi, V.; Moratal, D. (2018). Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction. Medical Physics. 45(4):1471-1480. https://doi.org/10.1002/mp.12783 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1002/mp.12783 es_ES
dc.description.upvformatpinicio 1471 es_ES
dc.description.upvformatpfin 1480 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 45 es_ES
dc.description.issue 4 es_ES
dc.identifier.pmid 29389013 es_ES
dc.relation.pasarela S\379091 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
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