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.411606.4", 
          "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.411606.4", 
          "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.411606.4", 
          "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.411606.4", 
          "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/s12968-020-00620-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1127162840", 
          "https://doi.org/10.1186/s12968-020-00620-4"
        ], 
        "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"
      }
    ], 
    "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": "2022-12-01T06:42", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221201/entities/gbq_results/article/article_875.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.

336 TRIPLES      21 PREDICATES      120 URIs      109 LITERALS      25 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12968-021-00706-7 schema:about N1e17bda2f5894d78a7b8d6706155328f
2 N26f0179901d04b219fd43620cbf298c6
3 N33487b81813e4df7a31e6a7730126c71
4 N341b3652f0864bdcb5eb7098a802e353
5 N46e1391951c84c6fbbee4cf91f6b73a9
6 N4798a8c1006a418eaf093e8665fd6180
7 N5bb15bafc80e418fb4b932cea2cd104e
8 N5bb8667bba4247ecbd946b841338ca95
9 N648546edb2b64a02944e8305aa9c44d6
10 N7182df90f8064f9bb88025feaf205970
11 N740315fa8a2046bdba201c311f26d84e
12 Nad8d01bf961842e897d10588904e828e
13 Nb696234744b847c7994cda17253da2a8
14 Nb7ab60884492475c90cab34508e9761c
15 Ncb70335420994b109d45f1b16d6ae076
16 Neac38057170749cb8ac5cb30c85e542f
17 Neb6c6286f54049458167ff92c0c4fcc4
18 Nebedcfd5f57f43b9bc632e834d95fbad
19 anzsrc-for:11
20 anzsrc-for:1102
21 schema:author N09122fc9c180432bbe1eacfcefe7e249
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 Ne853af97104d4ac28b2beee073cc6bb3
31 Nfa465579df34499d92e91ed25db4fca6
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 N51c4c4fb1b74475bbdc6d6bb4fb3302b
110 N6f3cbfb97526499882826b2f47f74714
111 Ne181c8f34ec24ab08faadd6a7ca802a5
112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1135713606
113 https://doi.org/10.1186/s12968-021-00706-7
114 schema:sdDatePublished 2022-12-01T06:42
115 schema:sdLicense https://scigraph.springernature.com/explorer/license/
116 schema:sdPublisher N83389b26980c478b9843614084fc2c98
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 N09122fc9c180432bbe1eacfcefe7e249 rdf:first sg:person.012016701452.48
122 rdf:rest N4e7e64c5a09b4858b522efcce0ddc3ec
123 N092f58082f9845c5a69cd5c44a0db801 rdf:first sg:person.01066175422.29
124 rdf:rest Na0257f32ba714286b84510ddc8840932
125 N19fa4157dc534a80a1ba192558a5ff87 rdf:first sg:person.01066244563.44
126 rdf:rest N092f58082f9845c5a69cd5c44a0db801
127 N1e17bda2f5894d78a7b8d6706155328f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Magnetic Resonance Imaging
129 rdf:type schema:DefinedTerm
130 N26f0179901d04b219fd43620cbf298c6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Severity of Illness Index
132 rdf:type schema:DefinedTerm
133 N2a8900cc89b544ccbdb4215d6ff4d45c rdf:first sg:person.01161036206.83
134 rdf:rest N580db9d91bff4227874f15dcd7c10175
135 N33487b81813e4df7a31e6a7730126c71 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
136 schema:name Case-Control Studies
137 rdf:type schema:DefinedTerm
138 N341b3652f0864bdcb5eb7098a802e353 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Predictive Value of Tests
140 rdf:type schema:DefinedTerm
141 N39cef882d1db4a60ae3fa69db433b10d rdf:first N41ef30258db244d7ab4df26745829d64
142 rdf:rest N6ced0b6ee64741c6a2f53041fbf522c1
143 N3c90057708334a04941364304a95bd78 rdf:first sg:person.01136172260.58
144 rdf:rest N2a8900cc89b544ccbdb4215d6ff4d45c
145 N41ef30258db244d7ab4df26745829d64 schema:affiliation grid-institutes:grid.411606.4
146 schema:familyName Liu
147 schema:givenName Wei
148 rdf:type schema:Person
149 N46e1391951c84c6fbbee4cf91f6b73a9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Coronary Vessels
151 rdf:type schema:DefinedTerm
152 N4798a8c1006a418eaf093e8665fd6180 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
153 schema:name Risk Factors
154 rdf:type schema:DefinedTerm
155 N4e7e64c5a09b4858b522efcce0ddc3ec rdf:first sg:person.012323454521.07
156 rdf:rest N74b4f7f5959e43c29bd3f1159f84c5bb
157 N51c4c4fb1b74475bbdc6d6bb4fb3302b schema:name pubmed_id
158 schema:value 33627144
159 rdf:type schema:PropertyValue
160 N580db9d91bff4227874f15dcd7c10175 rdf:first sg:person.01345134522.37
161 rdf:rest N7503903d8ec54528b6524c023dba050f
162 N5bb15bafc80e418fb4b932cea2cd104e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
163 schema:name Humans
164 rdf:type schema:DefinedTerm
165 N5bb8667bba4247ecbd946b841338ca95 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
166 schema:name Female
167 rdf:type schema:DefinedTerm
168 N5e1099dfd37343698f23139eee59903b rdf:first sg:person.01320556462.83
169 rdf:rest rdf:nil
170 N648546edb2b64a02944e8305aa9c44d6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
171 schema:name Coronary Artery Disease
172 rdf:type schema:DefinedTerm
173 N6ced0b6ee64741c6a2f53041fbf522c1 rdf:first sg:person.01152021525.33
174 rdf:rest Nd4c0fede638f42f8b12909a1e469cf10
175 N6f3cbfb97526499882826b2f47f74714 schema:name dimensions_id
176 schema:value pub.1135713606
177 rdf:type schema:PropertyValue
178 N7182df90f8064f9bb88025feaf205970 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
179 schema:name Aged
180 rdf:type schema:DefinedTerm
181 N740315fa8a2046bdba201c311f26d84e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
182 schema:name Middle Aged
183 rdf:type schema:DefinedTerm
184 N74b4f7f5959e43c29bd3f1159f84c5bb rdf:first sg:person.015602164052.93
185 rdf:rest N833cd870d1ee47b19369d077b522af4f
186 N7503903d8ec54528b6524c023dba050f rdf:first sg:person.010472053652.04
187 rdf:rest N19fa4157dc534a80a1ba192558a5ff87
188 N83389b26980c478b9843614084fc2c98 schema:name Springer Nature - SN SciGraph project
189 rdf:type schema:Organization
190 N833cd870d1ee47b19369d077b522af4f rdf:first sg:person.016310523671.44
191 rdf:rest N3c90057708334a04941364304a95bd78
192 Na0257f32ba714286b84510ddc8840932 rdf:first sg:person.011572621637.24
193 rdf:rest N39cef882d1db4a60ae3fa69db433b10d
194 Nad8d01bf961842e897d10588904e828e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
195 schema:name Plaque, Atherosclerotic
196 rdf:type schema:DefinedTerm
197 Nb696234744b847c7994cda17253da2a8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
198 schema:name Risk Assessment
199 rdf:type schema:DefinedTerm
200 Nb7ab60884492475c90cab34508e9761c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
201 schema:name Rupture, Spontaneous
202 rdf:type schema:DefinedTerm
203 Ncb70335420994b109d45f1b16d6ae076 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
204 schema:name Prospective Studies
205 rdf:type schema:DefinedTerm
206 Nd4c0fede638f42f8b12909a1e469cf10 rdf:first sg:person.01143631075.45
207 rdf:rest N5e1099dfd37343698f23139eee59903b
208 Ne181c8f34ec24ab08faadd6a7ca802a5 schema:name doi
209 schema:value 10.1186/s12968-021-00706-7
210 rdf:type schema:PropertyValue
211 Ne853af97104d4ac28b2beee073cc6bb3 schema:volumeNumber 23
212 rdf:type schema:PublicationVolume
213 Neac38057170749cb8ac5cb30c85e542f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
214 schema:name Acute Coronary Syndrome
215 rdf:type schema:DefinedTerm
216 Neb6c6286f54049458167ff92c0c4fcc4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
217 schema:name Tomography, Optical Coherence
218 rdf:type schema:DefinedTerm
219 Nebedcfd5f57f43b9bc632e834d95fbad schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
220 schema:name Male
221 rdf:type schema:DefinedTerm
222 Nfa465579df34499d92e91ed25db4fca6 schema:issueNumber 1
223 rdf:type schema:PublicationIssue
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.411606.4
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.411606.4
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.411606.4
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 Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
320 schema:name Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
321 rdf:type schema:Organization
322 grid-institutes:grid.411606.4 schema:alternateName Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China
323 schema:name Department of Cardiology, Beijing AnZhen Hospital, Affiliated to Capital Medical University, Anzhen Road, ChaoYang District, 100029, Beijing, China
324 rdf:type schema:Organization
325 grid-institutes:grid.412474.0 schema:alternateName Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China
326 schema:name Department of Radiology, Anzhen Hospital, Affiliated to Capital Medical University, 2 Anzhen Road, ChaoYang District, 100029, Beijing, China
327 Department of Radiology, Peking University Cancer Hospital & Institute, 52 Fucheng Road, Hai Dian District, 100142, Beijing, China
328 rdf:type schema:Organization
329 grid-institutes:grid.415886.6 schema:alternateName MR R&D, Siemens Healthineers, Los Angeles, CA, USA
330 schema:name MR R&D, Siemens Healthineers, Los Angeles, CA, USA
331 rdf:type schema:Organization
332 grid-institutes:grid.50956.3f schema:alternateName Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
333 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
334 schema:name Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
335 Department of Biomedical Sciences, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA, USA
336 rdf:type schema:Organization
 




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


...