Ectopic beats arise from micro-reentries near infarct regions in simulations of a patient-specific heart model View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Rafael Sachetto Oliveira, Sergio Alonso, Fernando Otaviano Campos, Bernardo Martins Rocha, João Filipe Fernandes, Titus Kuehne, Rodrigo Weber dos Santos

ABSTRACT

Ectopic beats are known to be involved in the initiation of a variety of cardiac arrhythmias. Although their location may vary, ectopic excitations have been found to originate from infarct areas, regions of micro-fibrosis and other heterogeneous tissues. However, the underlying mechanisms that link ectopic foci to heterogeneous tissues have yet to be fully understood. In this work, we investigate the mechanism of micro-reentry that leads to the generation of ectopic beats near infarct areas using a patient-specific heart model. The patient-specific geometrical model of the heart, including scar and peri-infarct zones, is obtained through magnetic resonance imaging (MRI). The infarct region is composed of ischemic myocytes and non-conducting cells (fibrosis, for instance). Electrophysiology is captured using an established cardiac myocyte model of the human ventricle modified to describe ischemia. The simulation results clearly reveal that ectopic beats emerge from micro-reentries that are sustained by the heterogeneous structure of the infarct regions. Because microscopic information about the heterogeneous structure of the infarct regions is not available, Monte-Carlo simulations are used to identify the probabilities of an infarct region to behave as an ectopic focus for different levels of ischemia and different percentages of non-conducting cells. From the proposed model, it is observed that ectopic beats are generated when a percentage of non-conducting cells is near a topological metric known as the percolation threshold. Although the mechanism for micro-reentries was proposed half a century ago to be a source of ectopic beats or premature ventricular contractions during myocardial infarction, the present study is the first to reproduce this mechanism in-silico using patient-specific data. More... »

PAGES

16392

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-018-34304-y

DOI

http://dx.doi.org/10.1038/s41598-018-34304-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107954809

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30401912


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Cardiorespiratory Medicine and Haematology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Universidade Federal de Juiz de Fora", 
          "id": "https://www.grid.ac/institutes/grid.411198.4", 
          "name": [
            "Department of Computer Science, Universidade Federal de S\u00e3o Jo\u00e3o del-Rei, S\u00e3o Jo\u00e3o del-Rei, Brazil", 
            "Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Oliveira", 
        "givenName": "Rafael Sachetto", 
        "id": "sg:person.01146251377.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01146251377.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universitat Polit\u00e8cnica de Catalunya", 
          "id": "https://www.grid.ac/institutes/grid.6835.8", 
          "name": [
            "Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil", 
            "Department of Physics, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alonso", 
        "givenName": "Sergio", 
        "id": "sg:person.0610445501.94", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610445501.94"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "King's College London", 
          "id": "https://www.grid.ac/institutes/grid.13097.3c", 
          "name": [
            "Institute for Computational and Imaging Science in Cardiovascular Medicine, Charit\u00e9 \u2013 Universit\u00e4tsmedizin, Berlin, Germany", 
            "School of Biomedical Engineering and Imaging Sciences, King\u2019s College London, London, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Campos", 
        "givenName": "Fernando Otaviano", 
        "id": "sg:person.0645504065.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645504065.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universidade Federal de Juiz de Fora", 
          "id": "https://www.grid.ac/institutes/grid.411198.4", 
          "name": [
            "Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rocha", 
        "givenName": "Bernardo Martins", 
        "id": "sg:person.01071066004.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01071066004.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Charit\u00e9", 
          "id": "https://www.grid.ac/institutes/grid.6363.0", 
          "name": [
            "Institute for Computational and Imaging Science in Cardiovascular Medicine, Charit\u00e9 \u2013 Universit\u00e4tsmedizin, Berlin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fernandes", 
        "givenName": "Jo\u00e3o Filipe", 
        "id": "sg:person.01336511206.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336511206.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Deutsches Herzzentrum Berlin", 
          "id": "https://www.grid.ac/institutes/grid.418209.6", 
          "name": [
            "Institute for Computational and Imaging Science in Cardiovascular Medicine, Charit\u00e9 \u2013 Universit\u00e4tsmedizin, Berlin, Germany", 
            "Department of Congenital Heart Disease, German Heart Centre Berlin (DHZB), Berlin, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kuehne", 
        "givenName": "Titus", 
        "id": "sg:person.01075751376.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075751376.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universidade Federal de Juiz de Fora", 
          "id": "https://www.grid.ac/institutes/grid.411198.4", 
          "name": [
            "Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Santos", 
        "givenName": "Rodrigo Weber dos", 
        "id": "sg:person.010537032075.64", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010537032075.64"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1136/hrt.31.3.273", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001316484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrthm.2007.08.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001478603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.res.44.4.576", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001508842"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/fjc.0b013e318207a35f", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001527156"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/fjc.0b013e318207a35f", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001527156"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.res.62.4.811", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001625511"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.yjmcc.2013.04.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003809056"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2015.10.026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006397279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/ajpheart.00346.2006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006647617"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bpj.2013.05.025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008116761"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/ajpheart.00385.2013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008335850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pcbi.1003891", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008925774"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjmed.2005.02.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011096478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0025-5564(88)90056-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013934109"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/cddis.2011.130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014698385", 
          "https://doi.org/10.1038/cddis.2011.130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10840-009-9443-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015467442", 
          "https://doi.org/10.1007/s10840-009-9443-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10840-009-9443-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015467442", 
          "https://doi.org/10.1007/s10840-009-9443-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2007.04.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017535148"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0033-0620(77)90005-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018642218"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2004.11.058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021830772"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.48.4.702", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022489838"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11517-012-0880-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025792746", 
          "https://doi.org/10.1007/s11517-012-0880-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrthm.2016.03.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027816728"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pbiomolbio.2016.01.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028151190"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep20835", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030661254", 
          "https://doi.org/10.1038/srep20835"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/ajpheart.00794.2003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030842476"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cvr/cvv149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031792598"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrthm.2009.07.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032130126"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2015/713058", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033054854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/europace/eum206", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036889404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fphys.2014.00424", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040026635"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.114.028104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040359770"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.114.028104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040359770"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.yjmcc.2013.10.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041661996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0144979", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042622548"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1540-8167.2006.00389.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044550963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.110.940619", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046111196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hrthm.2009.02.026", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048491336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0735-1097(96)00250-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049165797"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0166972", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051805225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/ajpheart.00010.2008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052189554"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep40985", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053750125", 
          "https://doi.org/10.1038/srep40985"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0008-6363(97)00093-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054579742"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/51/23/014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059026342"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cvr/24.9.741", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059487139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cvr/6.2.135", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059488570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.110.158101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060761431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.110.158101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1060761431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbme.2011.2162841", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061528512"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbme.2013.2256359", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061529231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/ajpheart.00096.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063193478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.116.021955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063344450"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.116.021955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063344450"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ao.51.002713", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065127892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15420/aer.2015.4.1.19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067835213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000456531", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074231122"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pbiomolbio.2017.02.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083854343"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2017.02.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084083693"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fphys.2017.00195", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084434186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cnm.2913", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086115643"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.4999612", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091332057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.15420/aer.2017.20.1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091460957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/s41598-017-15735-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092558634", 
          "https://doi.org/10.1038/s41598-017-15735-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11886-018-0963-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101387585", 
          "https://doi.org/10.1007/s11886-018-0963-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11886-018-0963-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101387585", 
          "https://doi.org/10.1007/s11886-018-0963-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11886-018-0963-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101387585", 
          "https://doi.org/10.1007/s11886-018-0963-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11886-018-0963-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101387585", 
          "https://doi.org/10.1007/s11886-018-0963-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbme.2018.2815504", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101538225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tbme.2018.2815504", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101538225"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3389/fphy.2018.00057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1104421359"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "Ectopic beats are known to be involved in the initiation of a variety of cardiac arrhythmias. Although their location may vary, ectopic excitations have been found to originate from infarct areas, regions of micro-fibrosis and other heterogeneous tissues. However, the underlying mechanisms that link ectopic foci to heterogeneous tissues have yet to be fully understood. In this work, we investigate the mechanism of micro-reentry that leads to the generation of ectopic beats near infarct areas using a patient-specific heart model. The patient-specific geometrical model of the heart, including scar and peri-infarct zones, is obtained through magnetic resonance imaging (MRI). The infarct region is composed of ischemic myocytes and non-conducting cells (fibrosis, for instance). Electrophysiology is captured using an established cardiac myocyte model of the human ventricle modified to describe ischemia. The simulation results clearly reveal that ectopic beats emerge from micro-reentries that are sustained by the heterogeneous structure of the infarct regions. Because microscopic information about the heterogeneous structure of the infarct regions is not available, Monte-Carlo simulations are used to identify the probabilities of an infarct region to behave as an ectopic focus for different levels of ischemia and different percentages of non-conducting cells. From the proposed model, it is observed that ectopic beats are generated when a percentage of non-conducting cells is near a topological metric known as the percolation threshold. Although the mechanism for micro-reentries was proposed half a century ago to be a source of ectopic beats or premature ventricular contractions during myocardial infarction, the present study is the first to reproduce this mechanism in-silico using patient-specific data.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/s41598-018-34304-y", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045337", 
        "issn": [
          "2045-2322"
        ], 
        "name": "Scientific Reports", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "8"
      }
    ], 
    "name": "Ectopic beats arise from micro-reentries near infarct regions in simulations of a patient-specific heart model", 
    "pagination": "16392", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8200ff8172e732515eba21c7b17e38c2bbedbccaa5567391c5621f6de515a680"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30401912"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101563288"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41598-018-34304-y"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107954809"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41598-018-34304-y", 
      "https://app.dimensions.ai/details/publication/pub.1107954809"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T18:33", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8675_00000610.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/s41598-018-34304-y"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-34304-y'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-34304-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-34304-y'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-018-34304-y'


 

This table displays all metadata directly associated to this object as RDF triples.

316 TRIPLES      21 PREDICATES      90 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41598-018-34304-y schema:about anzsrc-for:11
2 anzsrc-for:1102
3 schema:author Nd45b6fbf7dd4435e8f7638ec9b13b18d
4 schema:citation sg:pub.10.1007/s10840-009-9443-2
5 sg:pub.10.1007/s11517-012-0880-1
6 sg:pub.10.1007/s11886-018-0963-1
7 sg:pub.10.1038/cddis.2011.130
8 sg:pub.10.1038/s41598-017-15735-5
9 sg:pub.10.1038/srep20835
10 sg:pub.10.1038/srep40985
11 https://doi.org/10.1002/cnm.2913
12 https://doi.org/10.1016/0025-5564(88)90056-9
13 https://doi.org/10.1016/0033-0620(77)90005-6
14 https://doi.org/10.1016/j.amjcard.2007.04.029
15 https://doi.org/10.1016/j.amjmed.2005.02.010
16 https://doi.org/10.1016/j.bpj.2013.05.025
17 https://doi.org/10.1016/j.hrthm.2007.08.017
18 https://doi.org/10.1016/j.hrthm.2009.02.026
19 https://doi.org/10.1016/j.hrthm.2009.07.012
20 https://doi.org/10.1016/j.hrthm.2016.03.019
21 https://doi.org/10.1016/j.jacc.2004.11.058
22 https://doi.org/10.1016/j.jacc.2015.10.026
23 https://doi.org/10.1016/j.jacc.2017.02.001
24 https://doi.org/10.1016/j.pbiomolbio.2016.01.008
25 https://doi.org/10.1016/j.pbiomolbio.2017.02.007
26 https://doi.org/10.1016/j.yjmcc.2013.04.018
27 https://doi.org/10.1016/j.yjmcc.2013.10.018
28 https://doi.org/10.1016/s0008-6363(97)00093-x
29 https://doi.org/10.1016/s0735-1097(96)00250-1
30 https://doi.org/10.1063/1.4999612
31 https://doi.org/10.1088/0031-9155/51/23/014
32 https://doi.org/10.1093/cvr/24.9.741
33 https://doi.org/10.1093/cvr/6.2.135
34 https://doi.org/10.1093/cvr/cvv149
35 https://doi.org/10.1093/europace/eum206
36 https://doi.org/10.1097/fjc.0b013e318207a35f
37 https://doi.org/10.1103/physrevlett.110.158101
38 https://doi.org/10.1103/physrevlett.114.028104
39 https://doi.org/10.1109/tbme.2011.2162841
40 https://doi.org/10.1109/tbme.2013.2256359
41 https://doi.org/10.1109/tbme.2018.2815504
42 https://doi.org/10.1111/j.1540-8167.2006.00389.x
43 https://doi.org/10.1136/hrt.31.3.273
44 https://doi.org/10.1152/ajpheart.00010.2008
45 https://doi.org/10.1152/ajpheart.00096.2002
46 https://doi.org/10.1152/ajpheart.00346.2006
47 https://doi.org/10.1152/ajpheart.00385.2013
48 https://doi.org/10.1152/ajpheart.00794.2003
49 https://doi.org/10.1155/2015/713058
50 https://doi.org/10.1159/000456531
51 https://doi.org/10.1161/01.cir.48.4.702
52 https://doi.org/10.1161/01.res.44.4.576
53 https://doi.org/10.1161/01.res.62.4.811
54 https://doi.org/10.1161/circulationaha.110.940619
55 https://doi.org/10.1161/circulationaha.116.021955
56 https://doi.org/10.1364/ao.51.002713
57 https://doi.org/10.1371/journal.pcbi.1003891
58 https://doi.org/10.1371/journal.pone.0144979
59 https://doi.org/10.1371/journal.pone.0166972
60 https://doi.org/10.15420/aer.2015.4.1.19
61 https://doi.org/10.15420/aer.2017.20.1
62 https://doi.org/10.3389/fphy.2018.00057
63 https://doi.org/10.3389/fphys.2014.00424
64 https://doi.org/10.3389/fphys.2017.00195
65 schema:datePublished 2018-12
66 schema:datePublishedReg 2018-12-01
67 schema:description Ectopic beats are known to be involved in the initiation of a variety of cardiac arrhythmias. Although their location may vary, ectopic excitations have been found to originate from infarct areas, regions of micro-fibrosis and other heterogeneous tissues. However, the underlying mechanisms that link ectopic foci to heterogeneous tissues have yet to be fully understood. In this work, we investigate the mechanism of micro-reentry that leads to the generation of ectopic beats near infarct areas using a patient-specific heart model. The patient-specific geometrical model of the heart, including scar and peri-infarct zones, is obtained through magnetic resonance imaging (MRI). The infarct region is composed of ischemic myocytes and non-conducting cells (fibrosis, for instance). Electrophysiology is captured using an established cardiac myocyte model of the human ventricle modified to describe ischemia. The simulation results clearly reveal that ectopic beats emerge from micro-reentries that are sustained by the heterogeneous structure of the infarct regions. Because microscopic information about the heterogeneous structure of the infarct regions is not available, Monte-Carlo simulations are used to identify the probabilities of an infarct region to behave as an ectopic focus for different levels of ischemia and different percentages of non-conducting cells. From the proposed model, it is observed that ectopic beats are generated when a percentage of non-conducting cells is near a topological metric known as the percolation threshold. Although the mechanism for micro-reentries was proposed half a century ago to be a source of ectopic beats or premature ventricular contractions during myocardial infarction, the present study is the first to reproduce this mechanism in-silico using patient-specific data.
68 schema:genre research_article
69 schema:inLanguage en
70 schema:isAccessibleForFree true
71 schema:isPartOf N0167c4ec6ca9488f910b529e90773d38
72 Ne5054613cc8940d1aeca7460e03ebfc7
73 sg:journal.1045337
74 schema:name Ectopic beats arise from micro-reentries near infarct regions in simulations of a patient-specific heart model
75 schema:pagination 16392
76 schema:productId N4a5171a532e74d76a0e38dbdd23706db
77 N55f4d9d634284d6d93ab66ce60167b23
78 N6368fd1deb694f42b4d759979e520ebb
79 N6e7b0c4832924dfd90369e3ae76e1c42
80 Nc97e19b20f3c4421a42b789e1af686cb
81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107954809
82 https://doi.org/10.1038/s41598-018-34304-y
83 schema:sdDatePublished 2019-04-10T18:33
84 schema:sdLicense https://scigraph.springernature.com/explorer/license/
85 schema:sdPublisher N75a7d371cbdd4d8c976e75f97986f445
86 schema:url https://www.nature.com/articles/s41598-018-34304-y
87 sgo:license sg:explorer/license/
88 sgo:sdDataset articles
89 rdf:type schema:ScholarlyArticle
90 N0167c4ec6ca9488f910b529e90773d38 schema:issueNumber 1
91 rdf:type schema:PublicationIssue
92 N08a8c5e28d3e437085cc8cc0f7e19932 rdf:first sg:person.0645504065.79
93 rdf:rest Nc83f84af368f453195b21925f3eceb93
94 N1196c669be744ae6b2c43294df3d6f8a rdf:first sg:person.01336511206.45
95 rdf:rest N2e9e8147ae8946608e03b112713e4db9
96 N2e9e8147ae8946608e03b112713e4db9 rdf:first sg:person.01075751376.37
97 rdf:rest N613b93abc8384f1eb568a36d0e9fcaff
98 N4a5171a532e74d76a0e38dbdd23706db schema:name pubmed_id
99 schema:value 30401912
100 rdf:type schema:PropertyValue
101 N55f4d9d634284d6d93ab66ce60167b23 schema:name doi
102 schema:value 10.1038/s41598-018-34304-y
103 rdf:type schema:PropertyValue
104 N613b93abc8384f1eb568a36d0e9fcaff rdf:first sg:person.010537032075.64
105 rdf:rest rdf:nil
106 N6368fd1deb694f42b4d759979e520ebb schema:name nlm_unique_id
107 schema:value 101563288
108 rdf:type schema:PropertyValue
109 N6e7b0c4832924dfd90369e3ae76e1c42 schema:name readcube_id
110 schema:value 8200ff8172e732515eba21c7b17e38c2bbedbccaa5567391c5621f6de515a680
111 rdf:type schema:PropertyValue
112 N75a7d371cbdd4d8c976e75f97986f445 schema:name Springer Nature - SN SciGraph project
113 rdf:type schema:Organization
114 Nc83f84af368f453195b21925f3eceb93 rdf:first sg:person.01071066004.71
115 rdf:rest N1196c669be744ae6b2c43294df3d6f8a
116 Nc97e19b20f3c4421a42b789e1af686cb schema:name dimensions_id
117 schema:value pub.1107954809
118 rdf:type schema:PropertyValue
119 Nd45b6fbf7dd4435e8f7638ec9b13b18d rdf:first sg:person.01146251377.25
120 rdf:rest Nf1996df069604ae6b8043dd6960d22c7
121 Ne5054613cc8940d1aeca7460e03ebfc7 schema:volumeNumber 8
122 rdf:type schema:PublicationVolume
123 Nf1996df069604ae6b8043dd6960d22c7 rdf:first sg:person.0610445501.94
124 rdf:rest N08a8c5e28d3e437085cc8cc0f7e19932
125 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
126 schema:name Medical and Health Sciences
127 rdf:type schema:DefinedTerm
128 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
129 schema:name Cardiorespiratory Medicine and Haematology
130 rdf:type schema:DefinedTerm
131 sg:journal.1045337 schema:issn 2045-2322
132 schema:name Scientific Reports
133 rdf:type schema:Periodical
134 sg:person.010537032075.64 schema:affiliation https://www.grid.ac/institutes/grid.411198.4
135 schema:familyName Santos
136 schema:givenName Rodrigo Weber dos
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010537032075.64
138 rdf:type schema:Person
139 sg:person.01071066004.71 schema:affiliation https://www.grid.ac/institutes/grid.411198.4
140 schema:familyName Rocha
141 schema:givenName Bernardo Martins
142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01071066004.71
143 rdf:type schema:Person
144 sg:person.01075751376.37 schema:affiliation https://www.grid.ac/institutes/grid.418209.6
145 schema:familyName Kuehne
146 schema:givenName Titus
147 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01075751376.37
148 rdf:type schema:Person
149 sg:person.01146251377.25 schema:affiliation https://www.grid.ac/institutes/grid.411198.4
150 schema:familyName Oliveira
151 schema:givenName Rafael Sachetto
152 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01146251377.25
153 rdf:type schema:Person
154 sg:person.01336511206.45 schema:affiliation https://www.grid.ac/institutes/grid.6363.0
155 schema:familyName Fernandes
156 schema:givenName João Filipe
157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01336511206.45
158 rdf:type schema:Person
159 sg:person.0610445501.94 schema:affiliation https://www.grid.ac/institutes/grid.6835.8
160 schema:familyName Alonso
161 schema:givenName Sergio
162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0610445501.94
163 rdf:type schema:Person
164 sg:person.0645504065.79 schema:affiliation https://www.grid.ac/institutes/grid.13097.3c
165 schema:familyName Campos
166 schema:givenName Fernando Otaviano
167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645504065.79
168 rdf:type schema:Person
169 sg:pub.10.1007/s10840-009-9443-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015467442
170 https://doi.org/10.1007/s10840-009-9443-2
171 rdf:type schema:CreativeWork
172 sg:pub.10.1007/s11517-012-0880-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025792746
173 https://doi.org/10.1007/s11517-012-0880-1
174 rdf:type schema:CreativeWork
175 sg:pub.10.1007/s11886-018-0963-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101387585
176 https://doi.org/10.1007/s11886-018-0963-1
177 rdf:type schema:CreativeWork
178 sg:pub.10.1038/cddis.2011.130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014698385
179 https://doi.org/10.1038/cddis.2011.130
180 rdf:type schema:CreativeWork
181 sg:pub.10.1038/s41598-017-15735-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092558634
182 https://doi.org/10.1038/s41598-017-15735-5
183 rdf:type schema:CreativeWork
184 sg:pub.10.1038/srep20835 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030661254
185 https://doi.org/10.1038/srep20835
186 rdf:type schema:CreativeWork
187 sg:pub.10.1038/srep40985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053750125
188 https://doi.org/10.1038/srep40985
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1002/cnm.2913 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086115643
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1016/0025-5564(88)90056-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013934109
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1016/0033-0620(77)90005-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018642218
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1016/j.amjcard.2007.04.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017535148
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1016/j.amjmed.2005.02.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011096478
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1016/j.bpj.2013.05.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008116761
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1016/j.hrthm.2007.08.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001478603
203 rdf:type schema:CreativeWork
204 https://doi.org/10.1016/j.hrthm.2009.02.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048491336
205 rdf:type schema:CreativeWork
206 https://doi.org/10.1016/j.hrthm.2009.07.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032130126
207 rdf:type schema:CreativeWork
208 https://doi.org/10.1016/j.hrthm.2016.03.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027816728
209 rdf:type schema:CreativeWork
210 https://doi.org/10.1016/j.jacc.2004.11.058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021830772
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1016/j.jacc.2015.10.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006397279
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1016/j.jacc.2017.02.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084083693
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1016/j.pbiomolbio.2016.01.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028151190
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1016/j.pbiomolbio.2017.02.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083854343
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1016/j.yjmcc.2013.04.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003809056
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1016/j.yjmcc.2013.10.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041661996
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1016/s0008-6363(97)00093-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1054579742
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1016/s0735-1097(96)00250-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049165797
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1063/1.4999612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091332057
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1088/0031-9155/51/23/014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059026342
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1093/cvr/24.9.741 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059487139
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1093/cvr/6.2.135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059488570
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1093/cvr/cvv149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031792598
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1093/europace/eum206 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036889404
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1097/fjc.0b013e318207a35f schema:sameAs https://app.dimensions.ai/details/publication/pub.1001527156
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1103/physrevlett.110.158101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060761431
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1103/physrevlett.114.028104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040359770
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1109/tbme.2011.2162841 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061528512
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1109/tbme.2013.2256359 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061529231
249 rdf:type schema:CreativeWork
250 https://doi.org/10.1109/tbme.2018.2815504 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101538225
251 rdf:type schema:CreativeWork
252 https://doi.org/10.1111/j.1540-8167.2006.00389.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1044550963
253 rdf:type schema:CreativeWork
254 https://doi.org/10.1136/hrt.31.3.273 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001316484
255 rdf:type schema:CreativeWork
256 https://doi.org/10.1152/ajpheart.00010.2008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052189554
257 rdf:type schema:CreativeWork
258 https://doi.org/10.1152/ajpheart.00096.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063193478
259 rdf:type schema:CreativeWork
260 https://doi.org/10.1152/ajpheart.00346.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006647617
261 rdf:type schema:CreativeWork
262 https://doi.org/10.1152/ajpheart.00385.2013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008335850
263 rdf:type schema:CreativeWork
264 https://doi.org/10.1152/ajpheart.00794.2003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030842476
265 rdf:type schema:CreativeWork
266 https://doi.org/10.1155/2015/713058 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033054854
267 rdf:type schema:CreativeWork
268 https://doi.org/10.1159/000456531 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074231122
269 rdf:type schema:CreativeWork
270 https://doi.org/10.1161/01.cir.48.4.702 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022489838
271 rdf:type schema:CreativeWork
272 https://doi.org/10.1161/01.res.44.4.576 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001508842
273 rdf:type schema:CreativeWork
274 https://doi.org/10.1161/01.res.62.4.811 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001625511
275 rdf:type schema:CreativeWork
276 https://doi.org/10.1161/circulationaha.110.940619 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046111196
277 rdf:type schema:CreativeWork
278 https://doi.org/10.1161/circulationaha.116.021955 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063344450
279 rdf:type schema:CreativeWork
280 https://doi.org/10.1364/ao.51.002713 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065127892
281 rdf:type schema:CreativeWork
282 https://doi.org/10.1371/journal.pcbi.1003891 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008925774
283 rdf:type schema:CreativeWork
284 https://doi.org/10.1371/journal.pone.0144979 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042622548
285 rdf:type schema:CreativeWork
286 https://doi.org/10.1371/journal.pone.0166972 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051805225
287 rdf:type schema:CreativeWork
288 https://doi.org/10.15420/aer.2015.4.1.19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067835213
289 rdf:type schema:CreativeWork
290 https://doi.org/10.15420/aer.2017.20.1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091460957
291 rdf:type schema:CreativeWork
292 https://doi.org/10.3389/fphy.2018.00057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104421359
293 rdf:type schema:CreativeWork
294 https://doi.org/10.3389/fphys.2014.00424 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040026635
295 rdf:type schema:CreativeWork
296 https://doi.org/10.3389/fphys.2017.00195 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084434186
297 rdf:type schema:CreativeWork
298 https://www.grid.ac/institutes/grid.13097.3c schema:alternateName King's College London
299 schema:name Institute for Computational and Imaging Science in Cardiovascular Medicine, Charité – Universitätsmedizin, Berlin, Germany
300 School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
301 rdf:type schema:Organization
302 https://www.grid.ac/institutes/grid.411198.4 schema:alternateName Universidade Federal de Juiz de Fora
303 schema:name Department of Computer Science, Universidade Federal de São João del-Rei, São João del-Rei, Brazil
304 Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
305 rdf:type schema:Organization
306 https://www.grid.ac/institutes/grid.418209.6 schema:alternateName Deutsches Herzzentrum Berlin
307 schema:name Department of Congenital Heart Disease, German Heart Centre Berlin (DHZB), Berlin, Germany
308 Institute for Computational and Imaging Science in Cardiovascular Medicine, Charité – Universitätsmedizin, Berlin, Germany
309 rdf:type schema:Organization
310 https://www.grid.ac/institutes/grid.6363.0 schema:alternateName Charité
311 schema:name Institute for Computational and Imaging Science in Cardiovascular Medicine, Charité – Universitätsmedizin, Berlin, Germany
312 rdf:type schema:Organization
313 https://www.grid.ac/institutes/grid.6835.8 schema:alternateName Universitat Politècnica de Catalunya
314 schema:name Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain
315 Graduate Program in Computational Modeling, Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil
316 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...