Relationship between coronary hyper-intensive plaques identified by cardiovascular magnetic resonance and clinical severity of acute coronary syndrome View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-02-25

AUTHORS

Wen Liu, Sijing Wu, Zhenjia Wang, Yanni Du, Zhaoyang Fan, Li Dong, Yonghe Guo, Yi Liu, Xiaoming Bi, Jing An, Yujie Zhou, Wei Liu, Debiao Li, Wei Yu, Yibin Xie

ABSTRACT

BackgroundCoronary hyper-intense plaque (CHIP) detected on T1-weighted cardiovascular magnetic resonance (CMR) has been shown to associate with vulnerable plaque features and worse outcomes in low- and intermediate-risk populations. However, the prevalence of CHIP and its clinical significance in the higher-risk acute coronary syndrome (ACS) population have not been systematically studied. This study aims to assess the relationship between CHIP and ACS clinical severity using intracoronary optical coherence tomography (OCT) as the reference.MethodsA total of 62 patients with known or suspected coronary artery disease were prospectively enrolled including a clinically diagnosed ACS group (n = 50) and a control group with stable angina pectoris (n = 12). The ACS group consisted of consecutive patients including unstable angina pectoris (n = 27), non-ST-segment-elevation myocardial infarction (non-STEMI) (n = 8), and ST-segment-elevation myocardial infarction (STEMI) (n = 15), respectively. All patients underwent non-contrast coronary CMR to determine the plaque-to-myocardium signal intensity ratio (PMR).ResultsAmong the four groups of patients, a progressive increase in the prevalence of CHIPs (stable angina, 8%; unstable angina, 26%; non-STEMI, 38%; STEMI, 67%; p = 0.009), and PMR values (stable angina, 1.1; unstable angina, 1.2; non-STEMI, 1.3; STEMI, 1.6; median values, P = 0.004) were observed. Thrombus (7/8, 88% vs. 4/22, 18%, p = 0.001) and plaque rupture (5/8, 63% vs. 2/22, 9%, p = 0.007) were significantly more prevalent in CHIPs than in plaques without hyper-intensity. Elevated PMR was associated with high-risk plaque features including plaque rupture, thrombus, and intimal vasculature. A positive correlation was observed between PMR and the number of high-risk plaque features identified by OCT (r = 0.44, p = 0.015).ConclusionsThe prevalence of CHIPs and PMR are positively associated with the disease severity and high-risk plaque morphology in ACS. More... »

PAGES

12

Journal

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12968-021-00706-7

DOI

http://dx.doi.org/10.1186/s12968-021-00706-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1135713606

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33627144


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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Acute Coronary Syndrome", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Case-Control Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Coronary Artery Disease", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Coronary Vessels", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Plaque, Atherosclerotic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Predictive Value of Tests", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Prospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Assessment", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Risk Factors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Rupture, Spontaneous", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Severity of Illness Index", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tomography, Optical Coherence", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.412474.0", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
            "Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Wen", 
        "id": "sg:person.012016701452.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012016701452.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wu", 
        "givenName": "Sijing", 
        "id": "sg:person.012323454521.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012323454521.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Zhenjia", 
        "id": "sg:person.015602164052.93", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015602164052.93"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Du", 
        "givenName": "Yanni", 
        "id": "sg:person.016310523671.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016310523671.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.50956.3f", 
          "name": [
            "Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fan", 
        "givenName": "Zhaoyang", 
        "id": "sg:person.01136172260.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136172260.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dong", 
        "givenName": "Li", 
        "id": "sg:person.01161036206.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161036206.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guo", 
        "givenName": "Yonghe", 
        "id": "sg:person.01345134522.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01345134522.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Yi", 
        "id": "sg:person.010472053652.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010472053652.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "MR R&D, Siemens Healthineers, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.415886.6", 
          "name": [
            "MR R&D, Siemens Healthineers, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bi", 
        "givenName": "Xiaoming", 
        "id": "sg:person.01066244563.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066244563.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "MR Collaborations NE Asia, Siemens Healthineers, Beijing, China", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "MR Collaborations NE Asia, Siemens Healthineers, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "An", 
        "givenName": "Jing", 
        "id": "sg:person.01066175422.29", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066175422.29"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhou", 
        "givenName": "Yujie", 
        "id": "sg:person.011572621637.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011572621637.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Wei", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.50956.3f", 
          "name": [
            "Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Li", 
        "givenName": "Debiao", 
        "id": "sg:person.01152021525.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152021525.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.24696.3f", 
          "name": [
            "Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yu", 
        "givenName": "Wei", 
        "id": "sg:person.01143631075.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143631075.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.50956.3f", 
          "name": [
            "Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xie", 
        "givenName": "Yibin", 
        "id": "sg:person.01320556462.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320556462.83"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/s12968-018-0447-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1103553668", 
          "https://doi.org/10.1186/s12968-018-0447-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1532-429x-13-76", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027925514", 
          "https://doi.org/10.1186/1532-429x-13-76"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s12968-020-00620-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1127162840", 
          "https://doi.org/10.1186/s12968-020-00620-4"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2021-02-25", 
    "datePublishedReg": "2021-02-25", 
    "description": "BackgroundCoronary hyper-intense plaque (CHIP) detected on T1-weighted cardiovascular magnetic resonance (CMR) has been shown to associate with vulnerable plaque features and worse outcomes in low- and intermediate-risk populations. However, the prevalence of CHIP and its clinical significance in the higher-risk acute coronary syndrome (ACS) population have not been systematically studied. This study aims to assess the relationship between CHIP and ACS clinical severity using intracoronary optical coherence tomography (OCT) as the reference.MethodsA total of 62 patients with known or suspected coronary artery disease were prospectively enrolled including a clinically diagnosed ACS group (n\u2009=\u200950) and a control group with stable angina pectoris (n\u2009=\u200912). The ACS group consisted of consecutive patients including unstable angina pectoris (n\u2009=\u200927), non-ST-segment-elevation myocardial infarction (non-STEMI) (n\u2009=\u20098), and ST-segment-elevation myocardial infarction (STEMI) (n\u2009=\u200915), respectively. All patients underwent non-contrast coronary CMR to determine the plaque-to-myocardium signal intensity ratio (PMR).ResultsAmong the four groups of patients, a progressive increase in the prevalence of CHIPs (stable angina, 8%; unstable angina, 26%; non-STEMI, 38%; STEMI, 67%; p\u2009=\u20090.009), and PMR values (stable angina, 1.1; unstable angina, 1.2; non-STEMI, 1.3; STEMI, 1.6; median values, P\u2009=\u20090.004) were observed. Thrombus (7/8, 88% vs. 4/22, 18%, p\u2009=\u20090.001) and plaque rupture (5/8, 63% vs. 2/22, 9%, p\u2009=\u20090.007) were significantly more prevalent in CHIPs than in plaques without hyper-intensity. Elevated PMR was associated with high-risk plaque features including plaque rupture, thrombus, and intimal vasculature. A positive correlation was observed between PMR and the number of high-risk plaque features identified by OCT (r\u2009=\u20090.44, p\u2009=\u20090.015).ConclusionsThe prevalence of CHIPs and PMR are positively associated with the disease severity and high-risk plaque morphology in ACS.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s12968-021-00706-7", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.8347877", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1030439", 
        "issn": [
          "1548-7679", 
          "1879-2855"
        ], 
        "name": "Journal of Cardiovascular Magnetic Resonance", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "23"
      }
    ], 
    "keywords": [
      "cardiovascular magnetic resonance", 
      "ST-segment elevation myocardial infarction", 
      "high-risk plaque features", 
      "prevalence of CHIP", 
      "plaque features", 
      "optical coherence tomography", 
      "angina pectoris", 
      "ACS group", 
      "myocardial infarction", 
      "clinical severity", 
      "plaque rupture", 
      "T1-weighted cardiovascular magnetic resonance", 
      "acute coronary syndrome population", 
      "myocardium signal intensity ratio", 
      "segment elevation myocardial infarction", 
      "high-risk plaque morphology", 
      "intermediate-risk population", 
      "stable angina pectoris", 
      "acute coronary syndrome", 
      "coronary artery disease", 
      "unstable angina pectoris", 
      "group of patients", 
      "vulnerable plaque features", 
      "intracoronary optical coherence tomography", 
      "intimal vasculature", 
      "ConclusionsThe prevalence", 
      "coronary syndrome", 
      "artery disease", 
      "consecutive patients", 
      "worse outcomes", 
      "clinical significance", 
      "syndrome population", 
      "signal intensity ratio", 
      "magnetic resonance", 
      "control group", 
      "elevated PMR", 
      "patients", 
      "disease severity", 
      "plaque morphology", 
      "coherence tomography", 
      "plaques", 
      "prevalence", 
      "severity", 
      "pectoris", 
      "progressive increase", 
      "infarction", 
      "PMR values", 
      "thrombus", 
      "positive correlation", 
      "group", 
      "rupture", 
      "syndrome", 
      "population", 
      "disease", 
      "vasculature", 
      "tomography", 
      "outcomes", 
      "total", 
      "ACS", 
      "PMR", 
      "significance", 
      "relationship", 
      "study", 
      "features", 
      "increase", 
      "correlation", 
      "number", 
      "ratio", 
      "resonance", 
      "values", 
      "reference", 
      "morphology", 
      "intensity ratio", 
      "chip"
    ], 
    "name": "Relationship between coronary hyper-intensive plaques identified by cardiovascular magnetic resonance and clinical severity of acute coronary syndrome", 
    "pagination": "12", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1135713606"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12968-021-00706-7"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33627144"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12968-021-00706-7", 
      "https://app.dimensions.ai/details/publication/pub.1135713606"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:48", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_899.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s12968-021-00706-7"
  }
]
 

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.10.1186/s12968-021-00706-7'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12968-021-00706-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12968-021-00706-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12968-021-00706-7'


 

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

335 TRIPLES      21 PREDICATES      120 URIs      109 LITERALS      25 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12968-021-00706-7 schema:about N0a183d0aceaf47c59c94226371bb4c02
2 N2d77844cd66e4f839c18ef2b8f72abef
3 N4ac69c10b6bf4f44a31d56ef1fdb0b0c
4 N4b96702454bd47c3b37f5897306a96d6
5 N4d78c47a104748b2bcb87f0a56c42cd8
6 N511455775543471093844cbe2e6f3dbf
7 N5cf01c62be174887a0a2456732799459
8 N83ba3ad3ffd9427c8c3acca3bc387754
9 N911e364d42bf478bb07caaaf5c8de038
10 Na06f71e8ac79465c9ea6d6a3d47f80a8
11 Nb31b5f906c334cb5b3860161958cb2d2
12 Nb71e0194933d454791c66ab0e948b73b
13 Nb9e81f45315642bd9e80410a745994ca
14 Ndaca32faf0014640bd026dc072ed5259
15 Neae6a5d9686f483ea6009651cd8ea6be
16 Nf1a8dbe943bf404db07128ffe18175d3
17 Nf8d4b3c6257148148bae35d9d9714c75
18 Nfc9678d7d0d44477be53f1af9f90fbac
19 anzsrc-for:11
20 anzsrc-for:1102
21 schema:author N29cc3cabb9fb4aa292fc1c7d88bf623f
22 schema:citation sg:pub.10.1186/1532-429x-13-76
23 sg:pub.10.1186/s12968-018-0447-x
24 sg:pub.10.1186/s12968-020-00620-4
25 schema:datePublished 2021-02-25
26 schema:datePublishedReg 2021-02-25
27 schema:description BackgroundCoronary hyper-intense plaque (CHIP) detected on T1-weighted cardiovascular magnetic resonance (CMR) has been shown to associate with vulnerable plaque features and worse outcomes in low- and intermediate-risk populations. However, the prevalence of CHIP and its clinical significance in the higher-risk acute coronary syndrome (ACS) population have not been systematically studied. This study aims to assess the relationship between CHIP and ACS clinical severity using intracoronary optical coherence tomography (OCT) as the reference.MethodsA total of 62 patients with known or suspected coronary artery disease were prospectively enrolled including a clinically diagnosed ACS group (n = 50) and a control group with stable angina pectoris (n = 12). The ACS group consisted of consecutive patients including unstable angina pectoris (n = 27), non-ST-segment-elevation myocardial infarction (non-STEMI) (n = 8), and ST-segment-elevation myocardial infarction (STEMI) (n = 15), respectively. All patients underwent non-contrast coronary CMR to determine the plaque-to-myocardium signal intensity ratio (PMR).ResultsAmong the four groups of patients, a progressive increase in the prevalence of CHIPs (stable angina, 8%; unstable angina, 26%; non-STEMI, 38%; STEMI, 67%; p = 0.009), and PMR values (stable angina, 1.1; unstable angina, 1.2; non-STEMI, 1.3; STEMI, 1.6; median values, P = 0.004) were observed. Thrombus (7/8, 88% vs. 4/22, 18%, p = 0.001) and plaque rupture (5/8, 63% vs. 2/22, 9%, p = 0.007) were significantly more prevalent in CHIPs than in plaques without hyper-intensity. Elevated PMR was associated with high-risk plaque features including plaque rupture, thrombus, and intimal vasculature. A positive correlation was observed between PMR and the number of high-risk plaque features identified by OCT (r = 0.44, p = 0.015).ConclusionsThe prevalence of CHIPs and PMR are positively associated with the disease severity and high-risk plaque morphology in ACS.
28 schema:genre article
29 schema:isAccessibleForFree true
30 schema:isPartOf N7baf107286c14e30992f9c8f1e41d408
31 Nb77d6e8e4b704faf9645928ff4e95bab
32 sg:journal.1030439
33 schema:keywords ACS
34 ACS group
35 ConclusionsThe prevalence
36 PMR
37 PMR values
38 ST-segment elevation myocardial infarction
39 T1-weighted cardiovascular magnetic resonance
40 acute coronary syndrome
41 acute coronary syndrome population
42 angina pectoris
43 artery disease
44 cardiovascular magnetic resonance
45 chip
46 clinical severity
47 clinical significance
48 coherence tomography
49 consecutive patients
50 control group
51 coronary artery disease
52 coronary syndrome
53 correlation
54 disease
55 disease severity
56 elevated PMR
57 features
58 group
59 group of patients
60 high-risk plaque features
61 high-risk plaque morphology
62 increase
63 infarction
64 intensity ratio
65 intermediate-risk population
66 intimal vasculature
67 intracoronary optical coherence tomography
68 magnetic resonance
69 morphology
70 myocardial infarction
71 myocardium signal intensity ratio
72 number
73 optical coherence tomography
74 outcomes
75 patients
76 pectoris
77 plaque features
78 plaque morphology
79 plaque rupture
80 plaques
81 population
82 positive correlation
83 prevalence
84 prevalence of CHIP
85 progressive increase
86 ratio
87 reference
88 relationship
89 resonance
90 rupture
91 segment elevation myocardial infarction
92 severity
93 signal intensity ratio
94 significance
95 stable angina pectoris
96 study
97 syndrome
98 syndrome population
99 thrombus
100 tomography
101 total
102 unstable angina pectoris
103 values
104 vasculature
105 vulnerable plaque features
106 worse outcomes
107 schema:name Relationship between coronary hyper-intensive plaques identified by cardiovascular magnetic resonance and clinical severity of acute coronary syndrome
108 schema:pagination 12
109 schema:productId N056d306c5dda4b06bdb7d81a69a9dbe9
110 N134dc2cea952461f98382cd27a59ae44
111 Nbe9343ef83b74b7e9c74555ab795b0ee
112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1135713606
113 https://doi.org/10.1186/s12968-021-00706-7
114 schema:sdDatePublished 2022-10-01T06:48
115 schema:sdLicense https://scigraph.springernature.com/explorer/license/
116 schema:sdPublisher N5b02fb8ae7d24a9b9a828a77da0a0b6d
117 schema:url https://doi.org/10.1186/s12968-021-00706-7
118 sgo:license sg:explorer/license/
119 sgo:sdDataset articles
120 rdf:type schema:ScholarlyArticle
121 N056d306c5dda4b06bdb7d81a69a9dbe9 schema:name pubmed_id
122 schema:value 33627144
123 rdf:type schema:PropertyValue
124 N068c9e66140a427fa203a61ef7ef17b7 rdf:first sg:person.010472053652.04
125 rdf:rest N0f4f44f275f04a8d87e9f87f0a47b4e0
126 N07ea9cd9edac4feebcc85e58412f761c rdf:first sg:person.01066175422.29
127 rdf:rest Ndc6ba8d936b04d9e9ce9b38816e6f8ac
128 N0a183d0aceaf47c59c94226371bb4c02 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Coronary Artery Disease
130 rdf:type schema:DefinedTerm
131 N0f4f44f275f04a8d87e9f87f0a47b4e0 rdf:first sg:person.01066244563.44
132 rdf:rest N07ea9cd9edac4feebcc85e58412f761c
133 N134dc2cea952461f98382cd27a59ae44 schema:name dimensions_id
134 schema:value pub.1135713606
135 rdf:type schema:PropertyValue
136 N1e2b8edacd1b4e5188a7022e8d10e629 rdf:first sg:person.015602164052.93
137 rdf:rest N7b290d616b6c4894be2856367920d277
138 N29cc3cabb9fb4aa292fc1c7d88bf623f rdf:first sg:person.012016701452.48
139 rdf:rest N633502812acc4d87a98865505c93e3a8
140 N2d77844cd66e4f839c18ef2b8f72abef schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
141 schema:name Tomography, Optical Coherence
142 rdf:type schema:DefinedTerm
143 N4ac69c10b6bf4f44a31d56ef1fdb0b0c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name Prospective Studies
145 rdf:type schema:DefinedTerm
146 N4b96702454bd47c3b37f5897306a96d6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Case-Control Studies
148 rdf:type schema:DefinedTerm
149 N4d78c47a104748b2bcb87f0a56c42cd8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Severity of Illness Index
151 rdf:type schema:DefinedTerm
152 N4e67fb3a620842959c3b462614b42f0d rdf:first sg:person.01152021525.33
153 rdf:rest Nc05d02883fd94d9899d4eae489692233
154 N511455775543471093844cbe2e6f3dbf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Male
156 rdf:type schema:DefinedTerm
157 N5b02fb8ae7d24a9b9a828a77da0a0b6d schema:name Springer Nature - SN SciGraph project
158 rdf:type schema:Organization
159 N5cf01c62be174887a0a2456732799459 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
160 schema:name Magnetic Resonance Imaging
161 rdf:type schema:DefinedTerm
162 N633502812acc4d87a98865505c93e3a8 rdf:first sg:person.012323454521.07
163 rdf:rest N1e2b8edacd1b4e5188a7022e8d10e629
164 N68c86c794d8f46438f6090e5ede25cb0 rdf:first sg:person.01345134522.37
165 rdf:rest N068c9e66140a427fa203a61ef7ef17b7
166 N784ae30df348475bad19241173c2628d rdf:first sg:person.01161036206.83
167 rdf:rest N68c86c794d8f46438f6090e5ede25cb0
168 N7b290d616b6c4894be2856367920d277 rdf:first sg:person.016310523671.44
169 rdf:rest Na77a13d2ddc24ccbbf9b7ed948ddc02d
170 N7b2a534c5bf94c25ae73671a09e906d4 schema:affiliation grid-institutes:grid.24696.3f
171 schema:familyName Liu
172 schema:givenName Wei
173 rdf:type schema:Person
174 N7baf107286c14e30992f9c8f1e41d408 schema:issueNumber 1
175 rdf:type schema:PublicationIssue
176 N83ba3ad3ffd9427c8c3acca3bc387754 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
177 schema:name Rupture, Spontaneous
178 rdf:type schema:DefinedTerm
179 N911e364d42bf478bb07caaaf5c8de038 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
180 schema:name Predictive Value of Tests
181 rdf:type schema:DefinedTerm
182 Na06f71e8ac79465c9ea6d6a3d47f80a8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
183 schema:name Acute Coronary Syndrome
184 rdf:type schema:DefinedTerm
185 Na77a13d2ddc24ccbbf9b7ed948ddc02d rdf:first sg:person.01136172260.58
186 rdf:rest N784ae30df348475bad19241173c2628d
187 Nb31b5f906c334cb5b3860161958cb2d2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
188 schema:name Middle Aged
189 rdf:type schema:DefinedTerm
190 Nb71e0194933d454791c66ab0e948b73b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
191 schema:name Risk Assessment
192 rdf:type schema:DefinedTerm
193 Nb77d6e8e4b704faf9645928ff4e95bab schema:volumeNumber 23
194 rdf:type schema:PublicationVolume
195 Nb9e81f45315642bd9e80410a745994ca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
196 schema:name Female
197 rdf:type schema:DefinedTerm
198 Nbe9343ef83b74b7e9c74555ab795b0ee schema:name doi
199 schema:value 10.1186/s12968-021-00706-7
200 rdf:type schema:PropertyValue
201 Nc05d02883fd94d9899d4eae489692233 rdf:first sg:person.01143631075.45
202 rdf:rest Ndeb6e6c883a84f91965f0211f262264f
203 Ndaca32faf0014640bd026dc072ed5259 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
204 schema:name Plaque, Atherosclerotic
205 rdf:type schema:DefinedTerm
206 Ndc6ba8d936b04d9e9ce9b38816e6f8ac rdf:first sg:person.011572621637.24
207 rdf:rest Nf734ba74930840e9bb38c8746778ab12
208 Ndeb6e6c883a84f91965f0211f262264f rdf:first sg:person.01320556462.83
209 rdf:rest rdf:nil
210 Neae6a5d9686f483ea6009651cd8ea6be schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
211 schema:name Humans
212 rdf:type schema:DefinedTerm
213 Nf1a8dbe943bf404db07128ffe18175d3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
214 schema:name Risk Factors
215 rdf:type schema:DefinedTerm
216 Nf734ba74930840e9bb38c8746778ab12 rdf:first N7b2a534c5bf94c25ae73671a09e906d4
217 rdf:rest N4e67fb3a620842959c3b462614b42f0d
218 Nf8d4b3c6257148148bae35d9d9714c75 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
219 schema:name Aged
220 rdf:type schema:DefinedTerm
221 Nfc9678d7d0d44477be53f1af9f90fbac schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
222 schema:name Coronary Vessels
223 rdf:type schema:DefinedTerm
224 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
225 schema:name Medical and Health Sciences
226 rdf:type schema:DefinedTerm
227 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
228 schema:name Cardiorespiratory Medicine and Haematology
229 rdf:type schema:DefinedTerm
230 sg:grant.8347877 http://pending.schema.org/fundedItem sg:pub.10.1186/s12968-021-00706-7
231 rdf:type schema:MonetaryGrant
232 sg:journal.1030439 schema:issn 1548-7679
233 1879-2855
234 schema:name Journal of Cardiovascular Magnetic Resonance
235 schema:publisher Springer Nature
236 rdf:type schema:Periodical
237 sg:person.010472053652.04 schema:affiliation grid-institutes:grid.24696.3f
238 schema:familyName Liu
239 schema:givenName Yi
240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010472053652.04
241 rdf:type schema:Person
242 sg:person.01066175422.29 schema:affiliation grid-institutes:None
243 schema:familyName An
244 schema:givenName Jing
245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066175422.29
246 rdf:type schema:Person
247 sg:person.01066244563.44 schema:affiliation grid-institutes:grid.415886.6
248 schema:familyName Bi
249 schema:givenName Xiaoming
250 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01066244563.44
251 rdf:type schema:Person
252 sg:person.01136172260.58 schema:affiliation grid-institutes:grid.50956.3f
253 schema:familyName Fan
254 schema:givenName Zhaoyang
255 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136172260.58
256 rdf:type schema:Person
257 sg:person.01143631075.45 schema:affiliation grid-institutes:grid.24696.3f
258 schema:familyName Yu
259 schema:givenName Wei
260 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143631075.45
261 rdf:type schema:Person
262 sg:person.01152021525.33 schema:affiliation grid-institutes:grid.50956.3f
263 schema:familyName Li
264 schema:givenName Debiao
265 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152021525.33
266 rdf:type schema:Person
267 sg:person.011572621637.24 schema:affiliation grid-institutes:grid.24696.3f
268 schema:familyName Zhou
269 schema:givenName Yujie
270 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011572621637.24
271 rdf:type schema:Person
272 sg:person.01161036206.83 schema:affiliation grid-institutes:grid.24696.3f
273 schema:familyName Dong
274 schema:givenName Li
275 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161036206.83
276 rdf:type schema:Person
277 sg:person.012016701452.48 schema:affiliation grid-institutes:grid.412474.0
278 schema:familyName Liu
279 schema:givenName Wen
280 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012016701452.48
281 rdf:type schema:Person
282 sg:person.012323454521.07 schema:affiliation grid-institutes:grid.24696.3f
283 schema:familyName Wu
284 schema:givenName Sijing
285 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012323454521.07
286 rdf:type schema:Person
287 sg:person.01320556462.83 schema:affiliation grid-institutes:grid.50956.3f
288 schema:familyName Xie
289 schema:givenName Yibin
290 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320556462.83
291 rdf:type schema:Person
292 sg:person.01345134522.37 schema:affiliation grid-institutes:grid.24696.3f
293 schema:familyName Guo
294 schema:givenName Yonghe
295 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01345134522.37
296 rdf:type schema:Person
297 sg:person.015602164052.93 schema:affiliation grid-institutes:grid.24696.3f
298 schema:familyName Wang
299 schema:givenName Zhenjia
300 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015602164052.93
301 rdf:type schema:Person
302 sg:person.016310523671.44 schema:affiliation grid-institutes:grid.24696.3f
303 schema:familyName Du
304 schema:givenName Yanni
305 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016310523671.44
306 rdf:type schema:Person
307 sg:pub.10.1186/1532-429x-13-76 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027925514
308 https://doi.org/10.1186/1532-429x-13-76
309 rdf:type schema:CreativeWork
310 sg:pub.10.1186/s12968-018-0447-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1103553668
311 https://doi.org/10.1186/s12968-018-0447-x
312 rdf:type schema:CreativeWork
313 sg:pub.10.1186/s12968-020-00620-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127162840
314 https://doi.org/10.1186/s12968-020-00620-4
315 rdf:type schema:CreativeWork
316 grid-institutes:None schema:alternateName MR Collaborations NE Asia, Siemens Healthineers, Beijing, China
317 schema:name MR Collaborations NE Asia, Siemens Healthineers, Beijing, China
318 rdf:type schema:Organization
319 grid-institutes:grid.24696.3f schema:alternateName Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China
320 Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
321 schema:name Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China
322 Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
323 rdf:type schema:Organization
324 grid-institutes:grid.412474.0 schema:alternateName Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China
325 schema:name Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
326 Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China
327 rdf:type schema:Organization
328 grid-institutes:grid.415886.6 schema:alternateName MR R&D, Siemens Healthineers, Los Angeles, CA, USA
329 schema:name MR R&D, Siemens Healthineers, Los Angeles, CA, USA
330 rdf:type schema:Organization
331 grid-institutes:grid.50956.3f schema:alternateName Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
332 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
333 schema:name Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
334 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
335 rdf:type schema:Organization
 




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


...