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dc.contributor.authorGkontra, Polyxeni 
dc.contributor.authorNorton, Kerri-Ann
dc.contributor.authorZak, Magdalena M. 
dc.contributor.authorClemente, Cristina 
dc.contributor.authorAguero, Jaume 
dc.contributor.authorIbáñez, Borja 
dc.contributor.authorSantos, Andres
dc.contributor.authorPopel, Aleksander S.
dc.contributor.authorArroyo, Alicia G 
dc.date.accessioned2018-11-22T08:10:54Z
dc.date.available2018-11-22T08:10:54Z
dc.date.issued2018
dc.identifierISI:000423508900025
dc.identifier.citationSci Rep. 2018; 8(1):1854
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/20.500.12105/6692
dc.description.abstractThe microvasculature continuously adapts in response to pathophysiological conditions to meet tissue demands. Quantitative assessment of the dynamic changes in the coronary microvasculature is therefore crucial in enhancing our knowledge regarding the impact of cardiovascular diseases in tissue perfusion and in developing efficient angiotherapies. Using confocal microscopy and thick tissue sections, we developed a 3D fully automated pipeline that allows to precisely reconstruct the microvasculature and to extract parameters that quantify all its major features, its relation to smooth muscle actin positive cells and capillary diffusion regions. The novel pipeline was applied in the analysis of the coronary microvasculature from healthy tissue and tissue at various stages after myocardial infarction (MI) in the pig model, whose coronary vasculature closely resembles that of human tissue. We unravelled alterations in the microvasculature, particularly structural changes and angioadaptation in the aftermath of MI. In addition, we evaluated the extracted knowledge's potential for the prediction of pathophysiological conditions in tissue, using different classification schemes. The high accuracy achieved in this respect, demonstrates the ability of our approach not only to quantify and identify pathology-related changes of microvascular beds, but also to predict complex and dynamic microvascular patterns.
dc.description.sponsorshipThe authors would like to thank Angel Colmenar for staining tissues for four of the subjects. The authors would also like to express their gratitude to Carlos Galan Arriola for providing us with the tissue from infarcted pigs at 45 days post MI along with the characteristics of the corresponding subjects and MRI-based estimations of blood flow. The research leading to these results has received funding from the People Programme (Marie Curie Action) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant Agreement 608027. This work was also supported by grants from the Spanish Ministry of Economy and Competitiveness SAF2014-52050-R to A.G.A., TEC2015-66978-R to A.S. and SAF2013-49663-EXP to B.I., from the Institute of Health Carlos III and the European Regional Development Fund (ERDF/FEDER) PI13/01979 to B.I., from La Marato TV3 Foundation to A.G.A., and from NIH grant R01HL101200 to A.P. The CNIC is supported by the Ministry of Economy, Industry and Competitiveness (MINECO) and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505).
dc.language.isoeng
dc.publisherNature Publishing Group 
dc.type.hasVersionVoR
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleDeciphering microvascular changes after myocardial infarction through 3D fully automated image analysis
dc.typejournal article
dc.rights.licenseAtribución 4.0 Internacional*
dc.identifier.pubmedID29382844
dc.format.volume8
dc.identifier.doi10.1038/s41598-018-19758-4
dc.contributor.funderEuropean Commission 
dc.contributor.funderMinisterio de Economía y Competitividad (España) 
dc.contributor.funderInstituto de Salud Carlos III 
dc.contributor.funderUnión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF) 
dc.contributor.funderFundación La Marató TV3 
dc.contributor.funderNational Institutes of Health (Estados Unidos) 
dc.contributor.funderMinisterio de Economía, Industria y Competitividad (España) 
dc.contributor.funderFundación ProCNIC 
dc.description.peerreviewed
dc.relation.publisherversionhttps://doi.org/10.1038/s41598-018-19758-4
dc.identifier.journalScientific Reports
dc.repisalud.orgCNICCNIC::Grupos de investigación::Metaloproteinasas de Matriz en Angiogénesis e Inflamación
dc.repisalud.orgCNICCNIC::Grupos de investigación::Laboratorio Traslacional para la Imagen y Terapia Cardiovascular
dc.repisalud.institucionCNIC
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SAF2014-52050-Res_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/TEC2015-66978-Res_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/SAF2013-49663-EXPes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/PI13/01979es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/608027/EUes_ES
dc.rights.accessRightsopen accesses_ES


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Este Item está sujeto a una licencia Creative Commons: Atribución 4.0 Internacional