Strain analysis is superior to wall thickening in discriminating between infarcted myocardium with and without microvascular obstruction View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Henk Everaars, Lourens F. H. J. Robbers, Marco Götte, Pierre Croisille, Alexander Hirsch, Paul F. A. Teunissen, Peter M. van de Ven, Niels van Royen, Felix Zijlstra, Jan J. Piek, Albert C. van Rossum, Robin Nijveldt

ABSTRACT

OBJECTIVES: The aim of the present study was to evaluate the diagnostic performances of strain and wall thickening analysis in discriminating among three types of myocardium after acute myocardial infarction: non-infarcted myocardium, infarcted myocardium without microvascular obstruction (MVO) and infarcted myocardium with MVO. METHODS: Seventy-one patients with a successfully treated ST-segment elevation myocardial infarction underwent cardiovascular magnetic resonance imaging at 2-6 days after reperfusion. The imaging protocol included conventional cine imaging, myocardial tissue tagging and late gadolinium enhancement. Regional circumferential and radial strain and associated strain rates were analyzed in a 16-segment model as were the absolute and relative wall thickening. RESULTS: Hyperenhancement was detected in 418 (38%) of 1096 segments and was accompanied by MVO in 145 (35%) of hyperenhanced segments. Wall thickening, circumferential and radial strain were all significantly diminished in segments with hyperenhancement and decreased even further if MVO was also present (all p < 0.001). Peak circumferential strain (CS) surpassed all other strain and wall thickening parameters in its ability to discriminate between hyperenhanced and non-enhanced myocardium (all p < 0.05). Furthermore, CS was superior to both absolute and relative wall thickening in differentiating infarcted segments with MVO from infarcted segments without MVO (p = 0.02 and p = 0.001, respectively). CONCLUSIONS: Strain analysis is superior to wall thickening in differentiating between non-infarcted myocardium, infarcted myocardium without MVO and infarcted myocardium with MVO. Peak circumferential strain is the most accurate marker of regional function. KEY POINTS: • CMR can quantify regional myocardial function by analysis of wall thickening on cine images and strain analysis of tissue tagged images. • Strain analysis is superior to wall thickening in differentiating between different degrees of myocardial injury after acute myocardial infarction. • Peak circumferential strain is the most accurate marker of regional function. More... »

PAGES

5171-5181

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-018-5493-0

DOI

http://dx.doi.org/10.1007/s00330-018-5493-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104476100

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29948065


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "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": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Everaars", 
        "givenName": "Henk", 
        "id": "sg:person.016521430657.64", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016521430657.64"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Netherlands Heart Institute", 
          "id": "https://www.grid.ac/institutes/grid.411737.7", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands", 
            "Netherlands Heart Institute (NHI), Utrecht, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Robbers", 
        "givenName": "Lourens F. H. J.", 
        "id": "sg:person.0664376714.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0664376714.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "G\u00f6tte", 
        "givenName": "Marco", 
        "id": "sg:person.0752211750.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752211750.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Creatis Medical Imaging Research Center, Lyon, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Croisille", 
        "givenName": "Pierre", 
        "id": "sg:person.0732302170.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0732302170.63"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Erasmus University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.5645.2", 
          "name": [
            "Department of Cardiology, Thoraxcenter, Erasmus Medical Center, Rotterdam, The Netherlands", 
            "Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hirsch", 
        "givenName": "Alexander", 
        "id": "sg:person.01152360347.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152360347.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Teunissen", 
        "givenName": "Paul F. A.", 
        "id": "sg:person.0765170357.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765170357.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "van de Ven", 
        "givenName": "Peter M.", 
        "id": "sg:person.0647042767.19", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0647042767.19"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "van Royen", 
        "givenName": "Niels", 
        "id": "sg:person.01162161746.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162161746.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Erasmus University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.5645.2", 
          "name": [
            "Department of Cardiology, Thoraxcenter, Erasmus Medical Center, Rotterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zijlstra", 
        "givenName": "Felix", 
        "id": "sg:person.0777347333.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0777347333.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Academic Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.5650.6", 
          "name": [
            "Department of Cardiology, Amsterdam Medical Center, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Piek", 
        "givenName": "Jan J.", 
        "id": "sg:person.01226650670.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01226650670.60"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Netherlands Heart Institute", 
          "id": "https://www.grid.ac/institutes/grid.411737.7", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands", 
            "Netherlands Heart Institute (NHI), Utrecht, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "van Rossum", 
        "givenName": "Albert C.", 
        "id": "sg:person.0724665415.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724665415.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "VU University Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.16872.3a", 
          "name": [
            "Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nijveldt", 
        "givenName": "Robin", 
        "id": "sg:person.0677433001.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677433001.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/1476-7120-7-53", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001231534", 
          "https://doi.org/10.1186/1476-7120-7-53"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0735-1097(00)01186-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001762979"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.66.6.1146", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002422388"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/hrt.45.3.248", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003198301"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiol.2502080739", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003868980"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/eht100", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006090689"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehq449", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006205922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm198308113090602", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007394257"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.1910340206", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008204199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.63.4.739", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008751119"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehs289", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011642153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcmg.2010.11.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011769114"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiology.214.2.r00fe17453", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011869836"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.56.5.786", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012958129"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.90.1.127", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013296661"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/mrm.10422", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013697679"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0735-1097(95)00599-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018439559"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1532-429x-15-58", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019953644", 
          "https://doi.org/10.1186/1532-429x-15-58"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jmri.24623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020317526"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.97.8.765", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022594707"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcmg.2011.08.016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023325464"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.115.004148", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025324892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.115.004148", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025324892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2015.06.034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025573703"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/eurheartj/ehs215", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030848257"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiol.2353040601", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032217873"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1532-429x-16-10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033752490", 
          "https://doi.org/10.1186/1532-429x-16-10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jacc.2008.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033899951"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.echo.2013.09.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037606414"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/hc0402.102975", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039853393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01797678", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045543697", 
          "https://doi.org/10.1007/bf01797678"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01797678", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045543697", 
          "https://doi.org/10.1007/bf01797678"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcmg.2009.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046323379"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circinterventions.114.001786", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047071245"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circinterventions.114.001786", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047071245"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1532-429x-14-46", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050301570", 
          "https://doi.org/10.1186/1532-429x-14-46"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.res.57.1.152", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050413557"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10554-009-9499-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051617355", 
          "https://doi.org/10.1007/s10554-009-9499-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10554-009-9499-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051617355", 
          "https://doi.org/10.1007/s10554-009-9499-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cvr/6.5.516", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059488619"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmi.2009.2037955", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061695505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.93.2.223", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063336919"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.95.4.924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1063337854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2531595", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069977037"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1148/radiology.171.3.2717762", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079270177"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "OBJECTIVES: The aim of the present study was to evaluate the diagnostic performances of strain and wall thickening analysis in discriminating among three types of myocardium after acute myocardial infarction: non-infarcted myocardium, infarcted myocardium without microvascular obstruction (MVO) and infarcted myocardium with MVO.\nMETHODS: Seventy-one patients with a successfully treated ST-segment elevation myocardial infarction underwent cardiovascular magnetic resonance imaging at 2-6 days after reperfusion. The imaging protocol included conventional cine imaging, myocardial tissue tagging and late gadolinium enhancement. Regional circumferential and radial strain and associated strain rates were analyzed in a 16-segment model as were the absolute and relative wall thickening.\nRESULTS: Hyperenhancement was detected in 418 (38%) of 1096 segments and was accompanied by MVO in 145 (35%) of hyperenhanced segments. Wall thickening, circumferential and radial strain were all significantly diminished in segments with hyperenhancement and decreased even further if MVO was also present (all p < 0.001). Peak circumferential strain (CS) surpassed all other strain and wall thickening parameters in its ability to discriminate between hyperenhanced and non-enhanced myocardium (all p < 0.05). Furthermore, CS was superior to both absolute and relative wall thickening in differentiating infarcted segments with MVO from infarcted segments without MVO (p = 0.02 and p = 0.001, respectively).\nCONCLUSIONS: Strain analysis is superior to wall thickening in differentiating between non-infarcted myocardium, infarcted myocardium without MVO and infarcted myocardium with MVO. Peak circumferential strain is the most accurate marker of regional function.\nKEY POINTS: \u2022 CMR can quantify regional myocardial function by analysis of wall thickening on cine images and strain analysis of tissue tagged images. \u2022 Strain analysis is superior to wall thickening in differentiating between different degrees of myocardial injury after acute myocardial infarction. \u2022 Peak circumferential strain is the most accurate marker of regional function.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00330-018-5493-0", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1289120", 
        "issn": [
          "0938-7994", 
          "1432-1084"
        ], 
        "name": "European Radiology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "12", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "28"
      }
    ], 
    "name": "Strain analysis is superior to wall thickening in discriminating between infarcted myocardium with and without microvascular obstruction", 
    "pagination": "5171-5181", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "53790aee59b902d1a2caa01cf7d58de33b4a9dd2f526f7fdd51c258545f08ce0"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29948065"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9114774"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00330-018-5493-0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1104476100"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00330-018-5493-0", 
      "https://app.dimensions.ai/details/publication/pub.1104476100"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:09", 
    "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/v90/0000000267_0000000267/records_56131_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs00330-018-5493-0"
  }
]
 

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.10.1007/s00330-018-5493-0'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5493-0'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5493-0'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-018-5493-0'


 

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

289 TRIPLES      21 PREDICATES      70 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00330-018-5493-0 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author N320518e6848441a2b730365a8aa9e268
4 schema:citation sg:pub.10.1007/bf01797678
5 sg:pub.10.1007/s10554-009-9499-1
6 sg:pub.10.1186/1476-7120-7-53
7 sg:pub.10.1186/1532-429x-14-46
8 sg:pub.10.1186/1532-429x-15-58
9 sg:pub.10.1186/1532-429x-16-10
10 https://doi.org/10.1002/jmri.24623
11 https://doi.org/10.1002/mrm.10422
12 https://doi.org/10.1002/mrm.1910340206
13 https://doi.org/10.1016/0735-1097(95)00599-4
14 https://doi.org/10.1016/j.amjcard.2015.06.034
15 https://doi.org/10.1016/j.echo.2013.09.011
16 https://doi.org/10.1016/j.jacc.2008.04.006
17 https://doi.org/10.1016/j.jcmg.2009.11.006
18 https://doi.org/10.1016/j.jcmg.2010.11.015
19 https://doi.org/10.1016/j.jcmg.2011.08.016
20 https://doi.org/10.1016/s0735-1097(00)01186-4
21 https://doi.org/10.1056/nejm198308113090602
22 https://doi.org/10.1093/cvr/6.5.516
23 https://doi.org/10.1093/eurheartj/ehq449
24 https://doi.org/10.1093/eurheartj/ehs215
25 https://doi.org/10.1093/eurheartj/ehs289
26 https://doi.org/10.1093/eurheartj/eht100
27 https://doi.org/10.1109/tmi.2009.2037955
28 https://doi.org/10.1136/hrt.45.3.248
29 https://doi.org/10.1148/radiol.2353040601
30 https://doi.org/10.1148/radiol.2502080739
31 https://doi.org/10.1148/radiology.171.3.2717762
32 https://doi.org/10.1148/radiology.214.2.r00fe17453
33 https://doi.org/10.1161/01.cir.56.5.786
34 https://doi.org/10.1161/01.cir.63.4.739
35 https://doi.org/10.1161/01.cir.66.6.1146
36 https://doi.org/10.1161/01.cir.90.1.127
37 https://doi.org/10.1161/01.cir.93.2.223
38 https://doi.org/10.1161/01.cir.95.4.924
39 https://doi.org/10.1161/01.cir.97.8.765
40 https://doi.org/10.1161/01.res.57.1.152
41 https://doi.org/10.1161/circimaging.115.004148
42 https://doi.org/10.1161/circinterventions.114.001786
43 https://doi.org/10.1161/hc0402.102975
44 https://doi.org/10.2307/2531595
45 schema:datePublished 2018-12
46 schema:datePublishedReg 2018-12-01
47 schema:description OBJECTIVES: The aim of the present study was to evaluate the diagnostic performances of strain and wall thickening analysis in discriminating among three types of myocardium after acute myocardial infarction: non-infarcted myocardium, infarcted myocardium without microvascular obstruction (MVO) and infarcted myocardium with MVO. METHODS: Seventy-one patients with a successfully treated ST-segment elevation myocardial infarction underwent cardiovascular magnetic resonance imaging at 2-6 days after reperfusion. The imaging protocol included conventional cine imaging, myocardial tissue tagging and late gadolinium enhancement. Regional circumferential and radial strain and associated strain rates were analyzed in a 16-segment model as were the absolute and relative wall thickening. RESULTS: Hyperenhancement was detected in 418 (38%) of 1096 segments and was accompanied by MVO in 145 (35%) of hyperenhanced segments. Wall thickening, circumferential and radial strain were all significantly diminished in segments with hyperenhancement and decreased even further if MVO was also present (all p < 0.001). Peak circumferential strain (CS) surpassed all other strain and wall thickening parameters in its ability to discriminate between hyperenhanced and non-enhanced myocardium (all p < 0.05). Furthermore, CS was superior to both absolute and relative wall thickening in differentiating infarcted segments with MVO from infarcted segments without MVO (p = 0.02 and p = 0.001, respectively). CONCLUSIONS: Strain analysis is superior to wall thickening in differentiating between non-infarcted myocardium, infarcted myocardium without MVO and infarcted myocardium with MVO. Peak circumferential strain is the most accurate marker of regional function. KEY POINTS: • CMR can quantify regional myocardial function by analysis of wall thickening on cine images and strain analysis of tissue tagged images. • Strain analysis is superior to wall thickening in differentiating between different degrees of myocardial injury after acute myocardial infarction. • Peak circumferential strain is the most accurate marker of regional function.
48 schema:genre research_article
49 schema:inLanguage en
50 schema:isAccessibleForFree true
51 schema:isPartOf N81b9cf99a0c04ad0b57b7d43238e754b
52 Nb74970168d674722ab3103973c2b0405
53 sg:journal.1289120
54 schema:name Strain analysis is superior to wall thickening in discriminating between infarcted myocardium with and without microvascular obstruction
55 schema:pagination 5171-5181
56 schema:productId N213359902f45405988f03485c0d33248
57 N6001818ec08b42bf9edfd43f3ba62736
58 N75d1df6901d84c4ab2c90711dba016ff
59 Nb0f76c51136f4139948a0abfde3a0d7a
60 Ncfa866df4e0e41bd9a23d2b73345ad48
61 schema:sameAs https://app.dimensions.ai/details/publication/pub.1104476100
62 https://doi.org/10.1007/s00330-018-5493-0
63 schema:sdDatePublished 2019-04-11T08:09
64 schema:sdLicense https://scigraph.springernature.com/explorer/license/
65 schema:sdPublisher Nff2f96146f084b259c2ebb3941e4d3ff
66 schema:url https://link.springer.com/10.1007%2Fs00330-018-5493-0
67 sgo:license sg:explorer/license/
68 sgo:sdDataset articles
69 rdf:type schema:ScholarlyArticle
70 N0c1f90b774754ddda8eacf93ea2e9c77 rdf:first sg:person.01162161746.93
71 rdf:rest N88ade4759a4b475195ca8ed3d4e5ab24
72 N213359902f45405988f03485c0d33248 schema:name readcube_id
73 schema:value 53790aee59b902d1a2caa01cf7d58de33b4a9dd2f526f7fdd51c258545f08ce0
74 rdf:type schema:PropertyValue
75 N24522e4561424b0c8012b225049678eb rdf:first sg:person.0765170357.54
76 rdf:rest N3b2779b633864ec8b314525bd3664450
77 N320518e6848441a2b730365a8aa9e268 rdf:first sg:person.016521430657.64
78 rdf:rest Nc69a042719b747eba035d7b41c3a95e3
79 N3b2779b633864ec8b314525bd3664450 rdf:first sg:person.0647042767.19
80 rdf:rest N0c1f90b774754ddda8eacf93ea2e9c77
81 N3dddd276799045dd9630f463a65549da rdf:first sg:person.0732302170.63
82 rdf:rest N73d208d0a8e649c3ab8eff3f22220b02
83 N45e2903b79c54a788f09dd575189d6db rdf:first sg:person.0724665415.02
84 rdf:rest Nea3fa60956844ab1bf09bce6704a9faa
85 N6001818ec08b42bf9edfd43f3ba62736 schema:name doi
86 schema:value 10.1007/s00330-018-5493-0
87 rdf:type schema:PropertyValue
88 N73d208d0a8e649c3ab8eff3f22220b02 rdf:first sg:person.01152360347.30
89 rdf:rest N24522e4561424b0c8012b225049678eb
90 N75d1df6901d84c4ab2c90711dba016ff schema:name nlm_unique_id
91 schema:value 9114774
92 rdf:type schema:PropertyValue
93 N761378e497a14fe8aa865fbf4a7a5c1a rdf:first sg:person.01226650670.60
94 rdf:rest N45e2903b79c54a788f09dd575189d6db
95 N7cc13db4e0564aa5baac3cbf303f00d5 rdf:first sg:person.0752211750.05
96 rdf:rest N3dddd276799045dd9630f463a65549da
97 N81b9cf99a0c04ad0b57b7d43238e754b schema:volumeNumber 28
98 rdf:type schema:PublicationVolume
99 N88ade4759a4b475195ca8ed3d4e5ab24 rdf:first sg:person.0777347333.46
100 rdf:rest N761378e497a14fe8aa865fbf4a7a5c1a
101 Na4783c50f2e743808dffb07c010f1a22 schema:name Creatis Medical Imaging Research Center, Lyon, France
102 rdf:type schema:Organization
103 Nb0f76c51136f4139948a0abfde3a0d7a schema:name dimensions_id
104 schema:value pub.1104476100
105 rdf:type schema:PropertyValue
106 Nb74970168d674722ab3103973c2b0405 schema:issueNumber 12
107 rdf:type schema:PublicationIssue
108 Nc69a042719b747eba035d7b41c3a95e3 rdf:first sg:person.0664376714.27
109 rdf:rest N7cc13db4e0564aa5baac3cbf303f00d5
110 Ncfa866df4e0e41bd9a23d2b73345ad48 schema:name pubmed_id
111 schema:value 29948065
112 rdf:type schema:PropertyValue
113 Nea3fa60956844ab1bf09bce6704a9faa rdf:first sg:person.0677433001.48
114 rdf:rest rdf:nil
115 Nff2f96146f084b259c2ebb3941e4d3ff schema:name Springer Nature - SN SciGraph project
116 rdf:type schema:Organization
117 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
118 schema:name Medical and Health Sciences
119 rdf:type schema:DefinedTerm
120 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
121 schema:name Clinical Sciences
122 rdf:type schema:DefinedTerm
123 sg:journal.1289120 schema:issn 0938-7994
124 1432-1084
125 schema:name European Radiology
126 rdf:type schema:Periodical
127 sg:person.01152360347.30 schema:affiliation https://www.grid.ac/institutes/grid.5645.2
128 schema:familyName Hirsch
129 schema:givenName Alexander
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152360347.30
131 rdf:type schema:Person
132 sg:person.01162161746.93 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
133 schema:familyName van Royen
134 schema:givenName Niels
135 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01162161746.93
136 rdf:type schema:Person
137 sg:person.01226650670.60 schema:affiliation https://www.grid.ac/institutes/grid.5650.6
138 schema:familyName Piek
139 schema:givenName Jan J.
140 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01226650670.60
141 rdf:type schema:Person
142 sg:person.016521430657.64 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
143 schema:familyName Everaars
144 schema:givenName Henk
145 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016521430657.64
146 rdf:type schema:Person
147 sg:person.0647042767.19 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
148 schema:familyName van de Ven
149 schema:givenName Peter M.
150 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0647042767.19
151 rdf:type schema:Person
152 sg:person.0664376714.27 schema:affiliation https://www.grid.ac/institutes/grid.411737.7
153 schema:familyName Robbers
154 schema:givenName Lourens F. H. J.
155 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0664376714.27
156 rdf:type schema:Person
157 sg:person.0677433001.48 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
158 schema:familyName Nijveldt
159 schema:givenName Robin
160 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0677433001.48
161 rdf:type schema:Person
162 sg:person.0724665415.02 schema:affiliation https://www.grid.ac/institutes/grid.411737.7
163 schema:familyName van Rossum
164 schema:givenName Albert C.
165 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724665415.02
166 rdf:type schema:Person
167 sg:person.0732302170.63 schema:affiliation Na4783c50f2e743808dffb07c010f1a22
168 schema:familyName Croisille
169 schema:givenName Pierre
170 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0732302170.63
171 rdf:type schema:Person
172 sg:person.0752211750.05 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
173 schema:familyName Götte
174 schema:givenName Marco
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752211750.05
176 rdf:type schema:Person
177 sg:person.0765170357.54 schema:affiliation https://www.grid.ac/institutes/grid.16872.3a
178 schema:familyName Teunissen
179 schema:givenName Paul F. A.
180 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765170357.54
181 rdf:type schema:Person
182 sg:person.0777347333.46 schema:affiliation https://www.grid.ac/institutes/grid.5645.2
183 schema:familyName Zijlstra
184 schema:givenName Felix
185 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0777347333.46
186 rdf:type schema:Person
187 sg:pub.10.1007/bf01797678 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045543697
188 https://doi.org/10.1007/bf01797678
189 rdf:type schema:CreativeWork
190 sg:pub.10.1007/s10554-009-9499-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051617355
191 https://doi.org/10.1007/s10554-009-9499-1
192 rdf:type schema:CreativeWork
193 sg:pub.10.1186/1476-7120-7-53 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001231534
194 https://doi.org/10.1186/1476-7120-7-53
195 rdf:type schema:CreativeWork
196 sg:pub.10.1186/1532-429x-14-46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050301570
197 https://doi.org/10.1186/1532-429x-14-46
198 rdf:type schema:CreativeWork
199 sg:pub.10.1186/1532-429x-15-58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019953644
200 https://doi.org/10.1186/1532-429x-15-58
201 rdf:type schema:CreativeWork
202 sg:pub.10.1186/1532-429x-16-10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033752490
203 https://doi.org/10.1186/1532-429x-16-10
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1002/jmri.24623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020317526
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1002/mrm.10422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013697679
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1002/mrm.1910340206 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008204199
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1016/0735-1097(95)00599-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018439559
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1016/j.amjcard.2015.06.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025573703
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1016/j.echo.2013.09.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037606414
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1016/j.jacc.2008.04.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033899951
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1016/j.jcmg.2009.11.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046323379
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1016/j.jcmg.2010.11.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011769114
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1016/j.jcmg.2011.08.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023325464
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1016/s0735-1097(00)01186-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001762979
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1056/nejm198308113090602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007394257
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1093/cvr/6.5.516 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059488619
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1093/eurheartj/ehq449 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006205922
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1093/eurheartj/ehs215 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030848257
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1093/eurheartj/ehs289 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011642153
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1093/eurheartj/eht100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006090689
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1109/tmi.2009.2037955 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061695505
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1136/hrt.45.3.248 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003198301
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1148/radiol.2353040601 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032217873
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1148/radiol.2502080739 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003868980
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1148/radiology.171.3.2717762 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079270177
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1148/radiology.214.2.r00fe17453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011869836
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1161/01.cir.56.5.786 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012958129
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1161/01.cir.63.4.739 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008751119
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1161/01.cir.66.6.1146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002422388
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1161/01.cir.90.1.127 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013296661
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1161/01.cir.93.2.223 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063336919
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1161/01.cir.95.4.924 schema:sameAs https://app.dimensions.ai/details/publication/pub.1063337854
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1161/01.cir.97.8.765 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022594707
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1161/01.res.57.1.152 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050413557
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1161/circimaging.115.004148 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025324892
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1161/circinterventions.114.001786 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047071245
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1161/hc0402.102975 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039853393
272 rdf:type schema:CreativeWork
273 https://doi.org/10.2307/2531595 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069977037
274 rdf:type schema:CreativeWork
275 https://www.grid.ac/institutes/grid.16872.3a schema:alternateName VU University Medical Center
276 schema:name Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
277 Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
278 rdf:type schema:Organization
279 https://www.grid.ac/institutes/grid.411737.7 schema:alternateName Netherlands Heart Institute
280 schema:name Department of Cardiology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
281 Netherlands Heart Institute (NHI), Utrecht, The Netherlands
282 rdf:type schema:Organization
283 https://www.grid.ac/institutes/grid.5645.2 schema:alternateName Erasmus University Medical Center
284 schema:name Department of Cardiology, Thoraxcenter, Erasmus Medical Center, Rotterdam, The Netherlands
285 Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands
286 rdf:type schema:Organization
287 https://www.grid.ac/institutes/grid.5650.6 schema:alternateName Academic Medical Center
288 schema:name Department of Cardiology, Amsterdam Medical Center, Amsterdam, The Netherlands
289 rdf:type schema:Organization
 




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


...