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Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study

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Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study

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dc.contributor.author Meneses, Alba es_ES
dc.contributor.author Santabárbara, José Manuel es_ES
dc.contributor.author Romero, Juan Antonio es_ES
dc.contributor.author Aliaga, Roberto es_ES
dc.contributor.author Maceira, Alicia María es_ES
dc.contributor.author Moratal, David es_ES
dc.date.accessioned 2022-04-05T06:27:54Z
dc.date.available 2022-04-05T06:27:54Z
dc.date.issued 2021-07 es_ES
dc.identifier.uri http://hdl.handle.net/10251/181732
dc.description.abstract [EN] The reference diagnostic test of fibrosis, steatosis, and hepatic iron overload is liver biopsy, a clear invasive procedure. The main objective of this work was to propose HSA, or human serum albumin, as a biomarker for the assessment of fibrosis and to study non-invasive biomarkers for the assessment of steatosis and hepatic iron overload by means of an MR image acquisition protocol. It was performed on a set of eight subjects to determine fibrosis, steatosis, and hepatic iron overload with four different MRI sequences. We calibrated longitudinal relaxation times (T1 [ms]) with seven human serum albumin (HSA [%]) phantoms, and we studied the relationship between them as this protein is synthesized by the liver, and its concentration decreases in advanced fibrosis. Steatosis was calculated by means of the fat fraction (FF [%]) between fat and water liver signals in "fat-only images" (the subtraction of in-phase [IP] images and out-of-phase [OOP] images) and in "water-only images" (the addition of IP and OOP images). Liver iron concentration (LIC [mu mol/g]) was obtained by the transverse relaxation time (T2* [ms]) using Gandon's method with multiple echo times (TE) in T2-weighted IP and OOP images. The preliminary results showed that there is an inverse relationship (r = -0.9662) between the T1 relaxation times (ms) and HSA concentrations (%). Steatosis was determined with FF > 6.4% and when the liver signal was greater than the paravertebral muscles signal, and thus, the liver appeared hyperintense in fat-only images. Hepatic iron overload was detected with LIC > 36 mu mol/g, and in these cases, the liver signal was smaller than the paravertebral muscles signal, and thus, the liver behaved as hypointense in IP images. es_ES
dc.description.sponsorship This research was funded by "Conselleria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana" (grants AEST/2019/037 and AEST/2020/029), from the "Agencia Valenciana de la Innovacion, Generalitat Valenciana" (ref. INNCAD00/19/085 and INNCAD/2020/84), and from the "Centro para el Desarrollo Tecnologico Industrial" (Programa Eurostars-2, actuacion Interempresas Internacional), Spanish "Ministerio de Ciencia, Innovacion y Universidades" (ref. CIIP-20192020). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Diagnostics es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Biomarker es_ES
dc.subject Magnetic resonance protocol es_ES
dc.subject Fibrosis es_ES
dc.subject Steatosis es_ES
dc.subject Hepatic iron overload es_ES
dc.subject Phantom es_ES
dc.subject Image analysis es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/diagnostics11071178 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MCIU//CIIP-20192020/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AVI//INNCAD%2F2020%2F84/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AVI//INNCAD00%2F19%2F085//Proyecto 4DTools: nuevas técnicas y biomarcadores para diagnóstico-pronóstico de patologías de la aorta ascendente a través de técnicas de imagen médica/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AEST%2F2019%2F037/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/GVA//AEST%2F2020%2F029//Aplicación de técnicas de deep learning (aprendizaje profundo) para un análisis automático de imágenes de Resonancia/ 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 Meneses, A.; Santabárbara, JM.; Romero, JA.; Aliaga, R.; Maceira, AM.; Moratal, D. (2021). Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study. Diagnostics. 11(7):1-12. https://doi.org/10.3390/diagnostics11071178 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/diagnostics11071178 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 12 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 7 es_ES
dc.identifier.eissn 2075-4418 es_ES
dc.identifier.pmid 34209547 es_ES
dc.identifier.pmcid PMC8307019 es_ES
dc.relation.pasarela S\457709 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Agència Valenciana de la Innovació es_ES
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades es_ES


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