Accuracy of myocardial perfusion imaging in detecting multivessel coronary artery disease: A cardiac CZT study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-04

AUTHORS

Alessia Gimelli, Riccardo Liga, Valerio Duce, Annette Kusch, Alberto Clemente, Paolo Marzullo

ABSTRACT

BACKGROUND: Myocardial perfusion imaging (MPI) performed on traditional single-photon emission computed-tomography cameras has been shown to have a sub-optimal accuracy in detecting multivessel coronary artery disease (CAD). METHODS: Six-hundred and ninety-five patients were submitted to MPI on a novel cadmium-zinc-telluride (CZT) camera and coronary angiography. A coronary stenosis >70% was considered obstructive. In every patient, the summed stress score (SSS) was computed. Moreover, the regional stress scores were also calculated for every coronary territory. RESULTS: Four-hundred and forty-one patients had obstructive CAD in one (28%), two (19%), or three (17%) vessels. At per-patient analysis, the SSS showed a significant accuracy in detecting obstructive CAD (AUC 0.87, P < .001). Specifically, its accuracy was maintained also in patients with double (AUC 0.83; P < .001) or triple-vessels disease (AUC 0.79, P < .001), where CZT was able to correctly identify CAD extent in 64% of patients. On a per-vessel basis, CZT confirmed its high accuracy in detecting obstructive CAD (AUC 0.88, P < .001), independently from the involved coronary vessel. CONCLUSIONS: MPI performed on a CZT camera is highly accurate in detecting obstructive CAD, independently from the coronary artery involved and the overall disease burden. More... »

PAGES

687-695

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12350-015-0360-8

DOI

http://dx.doi.org/10.1007/s12350-015-0360-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043235675

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26846367


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

JSON-LD is the canonical representation for SciGraph data.

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

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Cardiorespiratory Medicine and Haematology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cadmium", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Coronary Artery Disease", 
        "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": "Image Enhancement", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Image Interpretation, Computer-Assisted", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Myocardial Perfusion Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Radionuclide Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sensitivity and Specificity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tellurium", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tomography, Emission-Computed, Single-Photon", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Zinc", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Fondazione Toscana Gabriele Monasterio", 
          "id": "https://www.grid.ac/institutes/grid.452599.6", 
          "name": [
            "Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gimelli", 
        "givenName": "Alessia", 
        "id": "sg:person.01143542411.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143542411.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Azienda Ospedaliera Universitaria Pisana", 
          "id": "https://www.grid.ac/institutes/grid.144189.1", 
          "name": [
            "Cardio-thoracic and Vascular Department, University Hospital of Pisa, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liga", 
        "givenName": "Riccardo", 
        "id": "sg:person.01214120740.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01214120740.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Azienda Ospedaliera Universitaria Pisana", 
          "id": "https://www.grid.ac/institutes/grid.144189.1", 
          "name": [
            "Cardio-thoracic and Vascular Department, University Hospital of Pisa, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Duce", 
        "givenName": "Valerio", 
        "id": "sg:person.01042427044.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042427044.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fondazione Toscana Gabriele Monasterio", 
          "id": "https://www.grid.ac/institutes/grid.452599.6", 
          "name": [
            "Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kusch", 
        "givenName": "Annette", 
        "id": "sg:person.0717433724.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717433724.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fondazione Toscana Gabriele Monasterio", 
          "id": "https://www.grid.ac/institutes/grid.452599.6", 
          "name": [
            "Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Clemente", 
        "givenName": "Alberto", 
        "id": "sg:person.01147512527.73", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01147512527.73"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Istituto di Fisiologia Clinica", 
          "id": "https://www.grid.ac/institutes/grid.418529.3", 
          "name": [
            "Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy", 
            "CNR, Institute of Clinical Physiology, Pisa, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marzullo", 
        "givenName": "Paolo", 
        "id": "sg:person.01067622763.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01067622763.33"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/eurheartj/eht296", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003024186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1016/s1071-3581(00)70009-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003812148", 
          "https://doi.org/10.1016/s1071-3581(00)70009-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejm199406233302503", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003836878"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0735-1097(00)00825-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011349887"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0735-1097(96)00052-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015188814"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-015-3129-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016623768", 
          "https://doi.org/10.1007/s00259-015-3129-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12350-009-9172-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018389515", 
          "https://doi.org/10.1007/s12350-009-9172-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12350-009-9172-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018389515", 
          "https://doi.org/10.1007/s12350-009-9172-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-005-1779-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018411656", 
          "https://doi.org/10.1007/s00259-005-1779-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-005-1779-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018411656", 
          "https://doi.org/10.1007/s00259-005-1779-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.957399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020586362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.957399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020586362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.110.957399", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020586362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/hrt.2010.217281", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020592941"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1067/mnc.2000.107426", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021399646", 
          "https://doi.org/10.1067/mnc.2000.107426"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12350-015-0101-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022453088", 
          "https://doi.org/10.1007/s12350-015-0101-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ehjci/jeu037", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023228325"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jcmg.2009.06.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025705408"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0002-8703(00)90230-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026190211"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.112.107417", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026861627"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.114.002179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033786724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circimaging.114.002179", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033786724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-013-2505-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034412711", 
          "https://doi.org/10.1007/s00259-013-2505-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-015-3008-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034514206", 
          "https://doi.org/10.1007/s00259-015-3008-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-011-1855-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034542479", 
          "https://doi.org/10.1007/s00259-011-1855-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-011-1918-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034700602", 
          "https://doi.org/10.1007/s00259-011-1918-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.111.091009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035173871"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmra061889", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036222524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/ehjci/jeu166", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039618115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/hc0402.102975", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039853393"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.108.055954", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047287141"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-009-1375-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051507500", 
          "https://doi.org/10.1007/s00259-009-1375-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-009-1375-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051507500", 
          "https://doi.org/10.1007/s00259-009-1375-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1076593580", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-04", 
    "datePublishedReg": "2017-04-01", 
    "description": "BACKGROUND: Myocardial perfusion imaging (MPI) performed on traditional single-photon emission computed-tomography cameras has been shown to have a sub-optimal accuracy in detecting multivessel coronary artery disease (CAD).\nMETHODS: Six-hundred and ninety-five patients were submitted to MPI on a novel cadmium-zinc-telluride (CZT) camera and coronary angiography. A coronary stenosis >70% was considered obstructive. In every patient, the summed stress score (SSS) was computed. Moreover, the regional stress scores were also calculated for every coronary territory.\nRESULTS: Four-hundred and forty-one patients had obstructive CAD in one (28%), two (19%), or three (17%) vessels. At per-patient analysis, the SSS showed a significant accuracy in detecting obstructive CAD (AUC 0.87, P\u00a0<\u00a0.001). Specifically, its accuracy was maintained also in patients with double (AUC 0.83; P\u00a0<\u00a0.001) or triple-vessels disease (AUC 0.79, P\u00a0<\u00a0.001), where CZT was able to correctly identify CAD extent in 64% of patients. On a per-vessel basis, CZT confirmed its high accuracy in detecting obstructive CAD (AUC 0.88, P\u00a0<\u00a0.001), independently from the involved coronary vessel.\nCONCLUSIONS: MPI performed on a CZT camera is highly accurate in detecting obstructive CAD, independently from the coronary artery involved and the overall disease burden.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12350-015-0360-8", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1106202", 
        "issn": [
          "1071-3581", 
          "1532-6551"
        ], 
        "name": "Journal of Nuclear Cardiology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "24"
      }
    ], 
    "name": "Accuracy of myocardial perfusion imaging in detecting multivessel coronary artery disease: A cardiac CZT study", 
    "pagination": "687-695", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "cdf252af873d16c05188e951bc5f026001f2462df2c16b3381e613e10ec017ef"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26846367"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9423534"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12350-015-0360-8"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1043235675"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12350-015-0360-8", 
      "https://app.dimensions.ai/details/publication/pub.1043235675"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T14:19", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8660_00000566.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs12350-015-0360-8"
  }
]
 

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/s12350-015-0360-8'

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/s12350-015-0360-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12350-015-0360-8'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12350-015-0360-8'


 

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

265 TRIPLES      21 PREDICATES      72 URIs      36 LITERALS      24 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12350-015-0360-8 schema:about N1102289ab2064d699d0a8f94b78755fb
2 N1f3b4f228f524378a5ff2d8681edaf0d
3 N226b74833f034232b63a608530dc7bd7
4 N25f616995f764d8da11dd77e8ac99aa7
5 N3f27d81a0f48484f986c884501d3c87a
6 N5f43c276ba9b483e9308621b14fcded6
7 N8ead63783c26410fb45432ee11658347
8 N908f807b241941db992c7e282ac5c75d
9 N974cdcd66a6147189bbbf0f648c0d625
10 Na4871d1ef58643c8a6f49bbdbffd0150
11 Naed2c853c6c44d60851e283f99655d44
12 Nc095826efea44410ba2690423a6798b2
13 Nc5e017fe34584a8da05f9eeffd741326
14 Nc9abfcf0fee146b4bd4757c1ad1f4246
15 Ndde0f605677e49bebdbb92c12d0bfc00
16 anzsrc-for:11
17 anzsrc-for:1102
18 schema:author N890cf9b68a8b47c6b6de5b2c74b73c86
19 schema:citation sg:pub.10.1007/s00259-005-1779-y
20 sg:pub.10.1007/s00259-009-1375-7
21 sg:pub.10.1007/s00259-011-1855-4
22 sg:pub.10.1007/s00259-011-1918-6
23 sg:pub.10.1007/s00259-013-2505-9
24 sg:pub.10.1007/s00259-015-3008-7
25 sg:pub.10.1007/s00259-015-3129-z
26 sg:pub.10.1007/s12350-009-9172-z
27 sg:pub.10.1007/s12350-015-0101-z
28 sg:pub.10.1016/s1071-3581(00)70009-2
29 sg:pub.10.1067/mnc.2000.107426
30 https://app.dimensions.ai/details/publication/pub.1076593580
31 https://doi.org/10.1016/0735-1097(96)00052-6
32 https://doi.org/10.1016/j.jcmg.2009.06.004
33 https://doi.org/10.1016/s0002-8703(00)90230-8
34 https://doi.org/10.1016/s0735-1097(00)00825-1
35 https://doi.org/10.1056/nejm199406233302503
36 https://doi.org/10.1056/nejmra061889
37 https://doi.org/10.1093/ehjci/jeu037
38 https://doi.org/10.1093/ehjci/jeu166
39 https://doi.org/10.1093/eurheartj/eht296
40 https://doi.org/10.1136/hrt.2010.217281
41 https://doi.org/10.1161/circimaging.110.957399
42 https://doi.org/10.1161/circimaging.114.002179
43 https://doi.org/10.1161/hc0402.102975
44 https://doi.org/10.2967/jnumed.108.055954
45 https://doi.org/10.2967/jnumed.111.091009
46 https://doi.org/10.2967/jnumed.112.107417
47 schema:datePublished 2017-04
48 schema:datePublishedReg 2017-04-01
49 schema:description BACKGROUND: Myocardial perfusion imaging (MPI) performed on traditional single-photon emission computed-tomography cameras has been shown to have a sub-optimal accuracy in detecting multivessel coronary artery disease (CAD). METHODS: Six-hundred and ninety-five patients were submitted to MPI on a novel cadmium-zinc-telluride (CZT) camera and coronary angiography. A coronary stenosis >70% was considered obstructive. In every patient, the summed stress score (SSS) was computed. Moreover, the regional stress scores were also calculated for every coronary territory. RESULTS: Four-hundred and forty-one patients had obstructive CAD in one (28%), two (19%), or three (17%) vessels. At per-patient analysis, the SSS showed a significant accuracy in detecting obstructive CAD (AUC 0.87, P < .001). Specifically, its accuracy was maintained also in patients with double (AUC 0.83; P < .001) or triple-vessels disease (AUC 0.79, P < .001), where CZT was able to correctly identify CAD extent in 64% of patients. On a per-vessel basis, CZT confirmed its high accuracy in detecting obstructive CAD (AUC 0.88, P < .001), independently from the involved coronary vessel. CONCLUSIONS: MPI performed on a CZT camera is highly accurate in detecting obstructive CAD, independently from the coronary artery involved and the overall disease burden.
50 schema:genre research_article
51 schema:inLanguage en
52 schema:isAccessibleForFree false
53 schema:isPartOf Nad2b491359f74595a97f1788f4d71042
54 Nd15b0c7578a447e2a046264cf407ffb4
55 sg:journal.1106202
56 schema:name Accuracy of myocardial perfusion imaging in detecting multivessel coronary artery disease: A cardiac CZT study
57 schema:pagination 687-695
58 schema:productId N1e726726145f4eec8ba3e13179e7887a
59 N8d2448e1f9a249bda422f879bd98bbad
60 Nbbb37fc28e0c4246b2de2a0e5f8fc5dd
61 Nc0126638069f4234b22ee9a6f0cb83e9
62 Ne0016d0d37d1445285162e3fc930a25b
63 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043235675
64 https://doi.org/10.1007/s12350-015-0360-8
65 schema:sdDatePublished 2019-04-10T14:19
66 schema:sdLicense https://scigraph.springernature.com/explorer/license/
67 schema:sdPublisher N97b5eeae7590407f9afbb8566bb4d16b
68 schema:url http://link.springer.com/10.1007%2Fs12350-015-0360-8
69 sgo:license sg:explorer/license/
70 sgo:sdDataset articles
71 rdf:type schema:ScholarlyArticle
72 N1102289ab2064d699d0a8f94b78755fb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
73 schema:name Reproducibility of Results
74 rdf:type schema:DefinedTerm
75 N1e726726145f4eec8ba3e13179e7887a schema:name doi
76 schema:value 10.1007/s12350-015-0360-8
77 rdf:type schema:PropertyValue
78 N1f3b4f228f524378a5ff2d8681edaf0d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Cadmium
80 rdf:type schema:DefinedTerm
81 N226b74833f034232b63a608530dc7bd7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Image Enhancement
83 rdf:type schema:DefinedTerm
84 N25f616995f764d8da11dd77e8ac99aa7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
85 schema:name Radionuclide Imaging
86 rdf:type schema:DefinedTerm
87 N3f27d81a0f48484f986c884501d3c87a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
88 schema:name Image Interpretation, Computer-Assisted
89 rdf:type schema:DefinedTerm
90 N5f43c276ba9b483e9308621b14fcded6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
91 schema:name Female
92 rdf:type schema:DefinedTerm
93 N7675a888a3394003a53e1aa2c9761851 rdf:first sg:person.01214120740.79
94 rdf:rest Nf82482bbe6c246e7a081aa8d27254c3d
95 N890cf9b68a8b47c6b6de5b2c74b73c86 rdf:first sg:person.01143542411.58
96 rdf:rest N7675a888a3394003a53e1aa2c9761851
97 N8d2448e1f9a249bda422f879bd98bbad schema:name pubmed_id
98 schema:value 26846367
99 rdf:type schema:PropertyValue
100 N8ead63783c26410fb45432ee11658347 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Coronary Artery Disease
102 rdf:type schema:DefinedTerm
103 N908f807b241941db992c7e282ac5c75d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Tellurium
105 rdf:type schema:DefinedTerm
106 N974cdcd66a6147189bbbf0f648c0d625 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Humans
108 rdf:type schema:DefinedTerm
109 N97b5eeae7590407f9afbb8566bb4d16b schema:name Springer Nature - SN SciGraph project
110 rdf:type schema:Organization
111 Na4871d1ef58643c8a6f49bbdbffd0150 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Aged
113 rdf:type schema:DefinedTerm
114 Nabb23f2af98943e6af6d2d93e1d1426d rdf:first sg:person.01067622763.33
115 rdf:rest rdf:nil
116 Nad2b491359f74595a97f1788f4d71042 schema:volumeNumber 24
117 rdf:type schema:PublicationVolume
118 Naed2c853c6c44d60851e283f99655d44 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
119 schema:name Zinc
120 rdf:type schema:DefinedTerm
121 Nbbb37fc28e0c4246b2de2a0e5f8fc5dd schema:name dimensions_id
122 schema:value pub.1043235675
123 rdf:type schema:PropertyValue
124 Nc0126638069f4234b22ee9a6f0cb83e9 schema:name readcube_id
125 schema:value cdf252af873d16c05188e951bc5f026001f2462df2c16b3381e613e10ec017ef
126 rdf:type schema:PropertyValue
127 Nc095826efea44410ba2690423a6798b2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Myocardial Perfusion Imaging
129 rdf:type schema:DefinedTerm
130 Nc5e017fe34584a8da05f9eeffd741326 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Tomography, Emission-Computed, Single-Photon
132 rdf:type schema:DefinedTerm
133 Nc9abfcf0fee146b4bd4757c1ad1f4246 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Sensitivity and Specificity
135 rdf:type schema:DefinedTerm
136 Nd15b0c7578a447e2a046264cf407ffb4 schema:issueNumber 2
137 rdf:type schema:PublicationIssue
138 Ndde0f605677e49bebdbb92c12d0bfc00 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Male
140 rdf:type schema:DefinedTerm
141 Ne0016d0d37d1445285162e3fc930a25b schema:name nlm_unique_id
142 schema:value 9423534
143 rdf:type schema:PropertyValue
144 Ne0a60d533c4f454e933ceea85a1fea92 rdf:first sg:person.01147512527.73
145 rdf:rest Nabb23f2af98943e6af6d2d93e1d1426d
146 Nf5db697b90874cfcb12c0b7c3c685475 rdf:first sg:person.0717433724.50
147 rdf:rest Ne0a60d533c4f454e933ceea85a1fea92
148 Nf82482bbe6c246e7a081aa8d27254c3d rdf:first sg:person.01042427044.36
149 rdf:rest Nf5db697b90874cfcb12c0b7c3c685475
150 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
151 schema:name Medical and Health Sciences
152 rdf:type schema:DefinedTerm
153 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
154 schema:name Cardiorespiratory Medicine and Haematology
155 rdf:type schema:DefinedTerm
156 sg:journal.1106202 schema:issn 1071-3581
157 1532-6551
158 schema:name Journal of Nuclear Cardiology
159 rdf:type schema:Periodical
160 sg:person.01042427044.36 schema:affiliation https://www.grid.ac/institutes/grid.144189.1
161 schema:familyName Duce
162 schema:givenName Valerio
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01042427044.36
164 rdf:type schema:Person
165 sg:person.01067622763.33 schema:affiliation https://www.grid.ac/institutes/grid.418529.3
166 schema:familyName Marzullo
167 schema:givenName Paolo
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01067622763.33
169 rdf:type schema:Person
170 sg:person.01143542411.58 schema:affiliation https://www.grid.ac/institutes/grid.452599.6
171 schema:familyName Gimelli
172 schema:givenName Alessia
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143542411.58
174 rdf:type schema:Person
175 sg:person.01147512527.73 schema:affiliation https://www.grid.ac/institutes/grid.452599.6
176 schema:familyName Clemente
177 schema:givenName Alberto
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01147512527.73
179 rdf:type schema:Person
180 sg:person.01214120740.79 schema:affiliation https://www.grid.ac/institutes/grid.144189.1
181 schema:familyName Liga
182 schema:givenName Riccardo
183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01214120740.79
184 rdf:type schema:Person
185 sg:person.0717433724.50 schema:affiliation https://www.grid.ac/institutes/grid.452599.6
186 schema:familyName Kusch
187 schema:givenName Annette
188 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0717433724.50
189 rdf:type schema:Person
190 sg:pub.10.1007/s00259-005-1779-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1018411656
191 https://doi.org/10.1007/s00259-005-1779-y
192 rdf:type schema:CreativeWork
193 sg:pub.10.1007/s00259-009-1375-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051507500
194 https://doi.org/10.1007/s00259-009-1375-7
195 rdf:type schema:CreativeWork
196 sg:pub.10.1007/s00259-011-1855-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034542479
197 https://doi.org/10.1007/s00259-011-1855-4
198 rdf:type schema:CreativeWork
199 sg:pub.10.1007/s00259-011-1918-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034700602
200 https://doi.org/10.1007/s00259-011-1918-6
201 rdf:type schema:CreativeWork
202 sg:pub.10.1007/s00259-013-2505-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034412711
203 https://doi.org/10.1007/s00259-013-2505-9
204 rdf:type schema:CreativeWork
205 sg:pub.10.1007/s00259-015-3008-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034514206
206 https://doi.org/10.1007/s00259-015-3008-7
207 rdf:type schema:CreativeWork
208 sg:pub.10.1007/s00259-015-3129-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1016623768
209 https://doi.org/10.1007/s00259-015-3129-z
210 rdf:type schema:CreativeWork
211 sg:pub.10.1007/s12350-009-9172-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1018389515
212 https://doi.org/10.1007/s12350-009-9172-z
213 rdf:type schema:CreativeWork
214 sg:pub.10.1007/s12350-015-0101-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1022453088
215 https://doi.org/10.1007/s12350-015-0101-z
216 rdf:type schema:CreativeWork
217 sg:pub.10.1016/s1071-3581(00)70009-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003812148
218 https://doi.org/10.1016/s1071-3581(00)70009-2
219 rdf:type schema:CreativeWork
220 sg:pub.10.1067/mnc.2000.107426 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021399646
221 https://doi.org/10.1067/mnc.2000.107426
222 rdf:type schema:CreativeWork
223 https://app.dimensions.ai/details/publication/pub.1076593580 schema:CreativeWork
224 https://doi.org/10.1016/0735-1097(96)00052-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015188814
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1016/j.jcmg.2009.06.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025705408
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1016/s0002-8703(00)90230-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026190211
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1016/s0735-1097(00)00825-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011349887
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1056/nejm199406233302503 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003836878
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1056/nejmra061889 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036222524
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1093/ehjci/jeu037 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023228325
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1093/ehjci/jeu166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039618115
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1093/eurheartj/eht296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003024186
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1136/hrt.2010.217281 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020592941
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1161/circimaging.110.957399 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020586362
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1161/circimaging.114.002179 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033786724
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1161/hc0402.102975 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039853393
249 rdf:type schema:CreativeWork
250 https://doi.org/10.2967/jnumed.108.055954 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047287141
251 rdf:type schema:CreativeWork
252 https://doi.org/10.2967/jnumed.111.091009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035173871
253 rdf:type schema:CreativeWork
254 https://doi.org/10.2967/jnumed.112.107417 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026861627
255 rdf:type schema:CreativeWork
256 https://www.grid.ac/institutes/grid.144189.1 schema:alternateName Azienda Ospedaliera Universitaria Pisana
257 schema:name Cardio-thoracic and Vascular Department, University Hospital of Pisa, Pisa, Italy
258 rdf:type schema:Organization
259 https://www.grid.ac/institutes/grid.418529.3 schema:alternateName Istituto di Fisiologia Clinica
260 schema:name CNR, Institute of Clinical Physiology, Pisa, Italy
261 Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy
262 rdf:type schema:Organization
263 https://www.grid.ac/institutes/grid.452599.6 schema:alternateName Fondazione Toscana Gabriele Monasterio
264 schema:name Fondazione Toscana Gabriele Monasterio, Via Moruzzi, 1, 56124, Pisa, Italy
265 rdf:type schema:Organization
 




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


...