Absolute myocardial flow quantification with 82Rb PET/CT: comparison of different software packages and methods View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-01

AUTHORS

Abdel K. Tahari, Andy Lee, Mahadevan Rajaram, Kenji Fukushima, Martin A Lodge, Benjamin C. Lee, Edward P. Ficaro, Stephan Nekolla, Ran Klein, Robert A. deKemp, Richard L. Wahl, Frank M. Bengel, Paco E. Bravo

ABSTRACT

PURPOSE: In clinical cardiac (82)Rb PET, globally impaired coronary flow reserve (CFR) is a relevant marker for predicting short-term cardiovascular events. However, there are limited data on the impact of different software and methods for estimation of myocardial blood flow (MBF) and CFR. Our objective was to compare quantitative results obtained from previously validated software tools. METHODS: We retrospectively analyzed cardiac (82)Rb PET/CT data from 25 subjects (group 1, 62 ± 11 years) with low-to-intermediate probability of coronary artery disease (CAD) and 26 patients (group 2, 57 ± 10 years; P=0.07) with known CAD. Resting and vasodilator-stress MBF and CFR were derived using three software applications: (1) Corridor4DM (4DM) based on factor analysis (FA) and kinetic modeling, (2) 4DM based on region-of-interest (ROI) and kinetic modeling, (3) MunichHeart (MH), which uses a simplified ROI-based retention model approach, and (4) FlowQuant (FQ) based on ROI and compartmental modeling with constant distribution volume. RESULTS: Resting and stress MBF values (in milliliters per minute per gram) derived using the different methods were significantly different: using 4DM-FA, 4DM-ROI, FQ, and MH resting MBF values were 1.47 ± 0.59, 1.16 ± 0.51, 0.91 ± 0.39, and 0.90 ± 0.44, respectively (P<0.001), and stress MBF values were 3.05 ± 1.66, 2.26 ± 1.01, 1.90 ± 0.82, and 1.83 ± 0.81, respectively (P<0.001). However, there were no statistically significant differences among the CFR values (2.15 ± 1.08, 2.05 ± 0.83, 2.23 ± 0.89, and 2.21 ± 0.90, respectively; P=0.17). Regional MBF and CFR according to vascular territories showed similar results. Linear correlation coefficient for global CFR varied between 0.71 (MH vs. 4DM-ROI) and 0.90 (FQ vs. 4DM-ROI). Using a cut-off value of 2.0 for abnormal CFR, the agreement among the software programs ranged between 76 % (MH vs. FQ) and 90 % (FQ vs. 4DM-ROI). Interobserver agreement was in general excellent with all software packages. CONCLUSION: Quantitative assessment of resting and stress MBF with (82)Rb PET is dependent on the software and methods used, whereas CFR appears to be more comparable. Follow-up and treatment assessment should be done with the same software and method. More... »

PAGES

126-135

References to SciGraph publications

  • 2010-10. Single photon-emission computed tomography in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2010-08. Quantification of myocardial blood flow and flow reserve: Technical aspects in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2012-08. 82Rb PET myocardial perfusion imaging is superior to 99mTc-labelled agent SPECT in patients with known or suspected coronary artery disease in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2007-11. Quantification of myocardial blood flow with 82Rb dynamic PET imaging in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2010-08. Intra- and inter-operator repeatability of myocardial blood flow and myocardial flow reserve measurements using rubidium-82 pet and a highly automated analysis program in JOURNAL OF NUCLEAR CARDIOLOGY
  • 1998-09. Reproducibility of polar map generation and assessment of defect severity and extent assessment in myocardial perfusion imaging using positron emission tomography in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2009-04. Rubidium-82 PET-CT for quantitative assessment of myocardial blood flow: validation in a canine model of coronary artery stenosis in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2008-11. Independent and incremental prognostic value of left ventricular ejection fraction determined by stress gated rubidium 82 PET imaging in patients with known or suspected coronary artery disease in JOURNAL OF NUCLEAR CARDIOLOGY
  • 2006-01. Diagnostic accuracy of rest/stress ECG-gated Rb-82 myocardial perfusion PET: Comparison with ECG-gated Tc-99m sestamibi SPECT in JOURNAL OF NUCLEAR CARDIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00259-013-2537-1

    DOI

    http://dx.doi.org/10.1007/s00259-013-2537-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1019325978

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23982454


    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": "Coronary Circulation", 
            "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 Processing, Computer-Assisted", 
            "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": "Multimodal Imaging", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Myocardial Perfusion Imaging", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Positron-Emission Tomography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Retrospective Studies", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Rubidium Radioisotopes", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Software", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Tomography, X-Ray Computed", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tahari", 
            "givenName": "Abdel K.", 
            "id": "sg:person.0704501612.49", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0704501612.49"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Andy", 
            "id": "sg:person.0752615012.05", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752615012.05"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rajaram", 
            "givenName": "Mahadevan", 
            "id": "sg:person.01223721440.78", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223721440.78"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fukushima", 
            "givenName": "Kenji", 
            "id": "sg:person.01022150250.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01022150250.39"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lodge", 
            "givenName": "Martin A", 
            "id": "sg:person.01026461773.16", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026461773.16"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "INVIA Medical Imaging Solutions, Ann Arbor, MI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lee", 
            "givenName": "Benjamin C.", 
            "id": "sg:person.01061006633.19", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061006633.19"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Michigan Medicine", 
              "id": "https://www.grid.ac/institutes/grid.412590.b", 
              "name": [
                "University of Michigan Health Systems, Ann Arbor, MI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ficaro", 
            "givenName": "Edward P.", 
            "id": "sg:person.0657342120.37", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657342120.37"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Technical University Munich", 
              "id": "https://www.grid.ac/institutes/grid.6936.a", 
              "name": [
                "Technical University of Munich, Munich, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Nekolla", 
            "givenName": "Stephan", 
            "id": "sg:person.013000403137.02", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013000403137.02"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Ottawa", 
              "id": "https://www.grid.ac/institutes/grid.28046.38", 
              "name": [
                "University of Ottawa Heart Institute, Ottawa, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Klein", 
            "givenName": "Ran", 
            "id": "sg:person.01126527574.37", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01126527574.37"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Ottawa", 
              "id": "https://www.grid.ac/institutes/grid.28046.38", 
              "name": [
                "University of Ottawa Heart Institute, Ottawa, Canada"
              ], 
              "type": "Organization"
            }, 
            "familyName": "deKemp", 
            "givenName": "Robert A.", 
            "id": "sg:person.0757534712.07", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757534712.07"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wahl", 
            "givenName": "Richard L.", 
            "id": "sg:person.011037736512.45", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011037736512.45"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hannover Medical School", 
              "id": "https://www.grid.ac/institutes/grid.10423.34", 
              "name": [
                "Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bengel", 
            "givenName": "Frank M.", 
            "id": "sg:person.01225020511.95", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225020511.95"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Johns Hopkins University", 
              "id": "https://www.grid.ac/institutes/grid.21107.35", 
              "name": [
                "Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bravo", 
            "givenName": "Paco E.", 
            "id": "sg:person.01326535277.42", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01326535277.42"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.2967/jnumed.110.081828", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001520969"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1118/1.3438474", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002410326"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.111.095398", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004858876"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-008-0972-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005274145", 
              "https://doi.org/10.1007/s00259-008-0972-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-008-0972-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005274145", 
              "https://doi.org/10.1007/s00259-008-0972-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2006.12.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007430749"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijcard.2012.03.076", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007891388"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1161/circulationaha.111.050427", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011963131"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1161/01.res.70.3.496", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012060884"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.112.108183", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014369216"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1161/circulationaha.106.629808", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014870616"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-007-0478-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018573299", 
              "https://doi.org/10.1007/s00259-007-0478-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-007-0478-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018573299", 
              "https://doi.org/10.1007/s00259-007-0478-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9246-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018751663", 
              "https://doi.org/10.1007/s12350-010-9246-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9246-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018751663", 
              "https://doi.org/10.1007/s12350-010-9246-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1053/j.semnuclmed.2004.09.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022883749"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2011.01.065", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027739308"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s002590050301", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027870105", 
              "https://doi.org/10.1007/s002590050301"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9256-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031907500", 
              "https://doi.org/10.1007/s12350-010-9256-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9256-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031907500", 
              "https://doi.org/10.1007/s12350-010-9256-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2006.06.025", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032478234"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.108.054395", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035639750"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf03007355", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037394649", 
              "https://doi.org/10.1007/bf03007355"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf03007355", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037394649", 
              "https://doi.org/10.1007/bf03007355"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2009.02.069", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037628406"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2009.02.065", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037812548"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.104.007831", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043551310"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9225-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047284350", 
              "https://doi.org/10.1007/s12350-010-9225-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12350-010-9225-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047284350", 
              "https://doi.org/10.1007/s12350-010-9225-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-012-2140-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047309064", 
              "https://doi.org/10.1007/s00259-012-2140-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1016/j.nuclcard.2005.12.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049290178", 
              "https://doi.org/10.1016/j.nuclcard.2005.12.004"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jacc.2011.02.068", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049351487"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/42.996340", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061171178"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077094730", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1082979514", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2014-01", 
        "datePublishedReg": "2014-01-01", 
        "description": "PURPOSE: In clinical cardiac (82)Rb PET, globally impaired coronary flow reserve (CFR) is a relevant marker for predicting short-term cardiovascular events. However, there are limited data on the impact of different software and methods for estimation of myocardial blood flow (MBF) and CFR. Our objective was to compare quantitative results obtained from previously validated software tools.\nMETHODS: We retrospectively analyzed cardiac (82)Rb PET/CT data from 25 subjects (group 1, 62 \u00b1 11 years) with low-to-intermediate probability of coronary artery disease (CAD) and 26 patients (group 2, 57 \u00b1 10 years; P=0.07) with known CAD. Resting and vasodilator-stress MBF and CFR were derived using three software applications: (1) Corridor4DM (4DM) based on factor analysis (FA) and kinetic modeling, (2) 4DM based on region-of-interest (ROI) and kinetic modeling, (3) MunichHeart (MH), which uses a simplified ROI-based retention model approach, and (4) FlowQuant (FQ) based on ROI and compartmental modeling with constant distribution volume.\nRESULTS: Resting and stress MBF values (in milliliters per minute per gram) derived using the different methods were significantly different: using 4DM-FA, 4DM-ROI, FQ, and MH resting MBF values were 1.47 \u00b1 0.59, 1.16 \u00b1 0.51, 0.91 \u00b1 0.39, and 0.90 \u00b1 0.44, respectively (P<0.001), and stress MBF values were 3.05 \u00b1 1.66, 2.26 \u00b1 1.01, 1.90 \u00b1 0.82, and 1.83 \u00b1 0.81, respectively (P<0.001). However, there were no statistically significant differences among the CFR values (2.15 \u00b1 1.08, 2.05 \u00b1 0.83, 2.23 \u00b1 0.89, and 2.21 \u00b1 0.90, respectively; P=0.17). Regional MBF and CFR according to vascular territories showed similar results. Linear correlation coefficient for global CFR varied between 0.71 (MH vs. 4DM-ROI) and 0.90 (FQ vs. 4DM-ROI). Using a cut-off value of 2.0 for abnormal CFR, the agreement among the software programs ranged between 76 % (MH vs. FQ) and 90 % (FQ vs. 4DM-ROI). Interobserver agreement was in general excellent with all software packages.\nCONCLUSION: Quantitative assessment of resting and stress MBF with (82)Rb PET is dependent on the software and methods used, whereas CFR appears to be more comparable. Follow-up and treatment assessment should be done with the same software and method.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s00259-013-2537-1", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2683453", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1297401", 
            "issn": [
              "1619-7070", 
              "1619-7089"
            ], 
            "name": "European Journal of Nuclear Medicine and Molecular Imaging", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "41"
          }
        ], 
        "name": "Absolute myocardial flow quantification with 82Rb PET/CT: comparison of different software packages and methods", 
        "pagination": "126-135", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "5c14c4df0cee284ab96b8d9aff0ffb72452f8a1cc265b27400dd10088a2fde7e"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "23982454"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101140988"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00259-013-2537-1"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1019325978"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00259-013-2537-1", 
          "https://app.dimensions.ai/details/publication/pub.1019325978"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T01:07", 
        "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_8697_00000512.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs00259-013-2537-1"
      }
    ]
     

    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/s00259-013-2537-1'

    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/s00259-013-2537-1'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-013-2537-1'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-013-2537-1'


     

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

    315 TRIPLES      21 PREDICATES      71 URIs      34 LITERALS      22 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00259-013-2537-1 schema:about N00ed0f4e726342d1811b9af8d602a197
    2 N0cc9c67d7b844343aca20198150a63e8
    3 N0d55e314078d43629133a57081ee6e53
    4 N2562d80166dc4e2f873c0e94923d3fdd
    5 N25b87b631c3d43d1ac6e96c2d1d2c8a8
    6 N3ac23435003b42e7aa634882f82d5084
    7 N3cb4fcae81a742558c1adc3b19724eb6
    8 N4ba7aff094b048898fa69618001ececc
    9 N4cbdbab609ad490486f625ea126aeae6
    10 N7a2b2847322d4bef8401051f939621bc
    11 N81903a6f8d1c4c0d9f6ecb8783cd929c
    12 Nb65e8eed36c34cf7bc8d054b91b8f90a
    13 Ndaad5b0bfd114e9fbc5d93e8700e0ff4
    14 anzsrc-for:11
    15 anzsrc-for:1102
    16 schema:author N3f8a00b39db3458fa8b8c418d086612d
    17 schema:citation sg:pub.10.1007/bf03007355
    18 sg:pub.10.1007/s00259-007-0478-2
    19 sg:pub.10.1007/s00259-008-0972-1
    20 sg:pub.10.1007/s00259-012-2140-x
    21 sg:pub.10.1007/s002590050301
    22 sg:pub.10.1007/s12350-010-9225-3
    23 sg:pub.10.1007/s12350-010-9246-y
    24 sg:pub.10.1007/s12350-010-9256-9
    25 sg:pub.10.1016/j.nuclcard.2005.12.004
    26 https://app.dimensions.ai/details/publication/pub.1077094730
    27 https://app.dimensions.ai/details/publication/pub.1082979514
    28 https://doi.org/10.1016/j.ijcard.2012.03.076
    29 https://doi.org/10.1016/j.jacc.2006.06.025
    30 https://doi.org/10.1016/j.jacc.2006.12.015
    31 https://doi.org/10.1016/j.jacc.2009.02.065
    32 https://doi.org/10.1016/j.jacc.2009.02.069
    33 https://doi.org/10.1016/j.jacc.2011.01.065
    34 https://doi.org/10.1016/j.jacc.2011.02.068
    35 https://doi.org/10.1053/j.semnuclmed.2004.09.002
    36 https://doi.org/10.1109/42.996340
    37 https://doi.org/10.1118/1.3438474
    38 https://doi.org/10.1161/01.res.70.3.496
    39 https://doi.org/10.1161/circulationaha.106.629808
    40 https://doi.org/10.1161/circulationaha.111.050427
    41 https://doi.org/10.2967/jnumed.104.007831
    42 https://doi.org/10.2967/jnumed.108.054395
    43 https://doi.org/10.2967/jnumed.110.081828
    44 https://doi.org/10.2967/jnumed.111.095398
    45 https://doi.org/10.2967/jnumed.112.108183
    46 schema:datePublished 2014-01
    47 schema:datePublishedReg 2014-01-01
    48 schema:description PURPOSE: In clinical cardiac (82)Rb PET, globally impaired coronary flow reserve (CFR) is a relevant marker for predicting short-term cardiovascular events. However, there are limited data on the impact of different software and methods for estimation of myocardial blood flow (MBF) and CFR. Our objective was to compare quantitative results obtained from previously validated software tools. METHODS: We retrospectively analyzed cardiac (82)Rb PET/CT data from 25 subjects (group 1, 62 ± 11 years) with low-to-intermediate probability of coronary artery disease (CAD) and 26 patients (group 2, 57 ± 10 years; P=0.07) with known CAD. Resting and vasodilator-stress MBF and CFR were derived using three software applications: (1) Corridor4DM (4DM) based on factor analysis (FA) and kinetic modeling, (2) 4DM based on region-of-interest (ROI) and kinetic modeling, (3) MunichHeart (MH), which uses a simplified ROI-based retention model approach, and (4) FlowQuant (FQ) based on ROI and compartmental modeling with constant distribution volume. RESULTS: Resting and stress MBF values (in milliliters per minute per gram) derived using the different methods were significantly different: using 4DM-FA, 4DM-ROI, FQ, and MH resting MBF values were 1.47 ± 0.59, 1.16 ± 0.51, 0.91 ± 0.39, and 0.90 ± 0.44, respectively (P<0.001), and stress MBF values were 3.05 ± 1.66, 2.26 ± 1.01, 1.90 ± 0.82, and 1.83 ± 0.81, respectively (P<0.001). However, there were no statistically significant differences among the CFR values (2.15 ± 1.08, 2.05 ± 0.83, 2.23 ± 0.89, and 2.21 ± 0.90, respectively; P=0.17). Regional MBF and CFR according to vascular territories showed similar results. Linear correlation coefficient for global CFR varied between 0.71 (MH vs. 4DM-ROI) and 0.90 (FQ vs. 4DM-ROI). Using a cut-off value of 2.0 for abnormal CFR, the agreement among the software programs ranged between 76 % (MH vs. FQ) and 90 % (FQ vs. 4DM-ROI). Interobserver agreement was in general excellent with all software packages. CONCLUSION: Quantitative assessment of resting and stress MBF with (82)Rb PET is dependent on the software and methods used, whereas CFR appears to be more comparable. Follow-up and treatment assessment should be done with the same software and method.
    49 schema:genre research_article
    50 schema:inLanguage en
    51 schema:isAccessibleForFree true
    52 schema:isPartOf Nd0417b1c47c14502a82ecc9c54c1d8c8
    53 Ne295c80d6e314e2784f8f331e4e47799
    54 sg:journal.1297401
    55 schema:name Absolute myocardial flow quantification with 82Rb PET/CT: comparison of different software packages and methods
    56 schema:pagination 126-135
    57 schema:productId N0d094259c66246089dbad28d97130448
    58 N23f4cd3f3aee4e4fb53109642d37a451
    59 N2b95ec72404b41678d266deee6bfd95c
    60 N3cb938917fd34d5193af70745546835e
    61 Nee60f37696ae44fabc58bebe5ccbbc21
    62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019325978
    63 https://doi.org/10.1007/s00259-013-2537-1
    64 schema:sdDatePublished 2019-04-11T01:07
    65 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    66 schema:sdPublisher Ne87ce8e567b146fbb75408e21e818d11
    67 schema:url http://link.springer.com/10.1007%2Fs00259-013-2537-1
    68 sgo:license sg:explorer/license/
    69 sgo:sdDataset articles
    70 rdf:type schema:ScholarlyArticle
    71 N00ed0f4e726342d1811b9af8d602a197 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    72 schema:name Coronary Circulation
    73 rdf:type schema:DefinedTerm
    74 N08fb1662cee14dbbb5797c98fbae5a81 rdf:first sg:person.01225020511.95
    75 rdf:rest Neadffe90f3bc42d78ea092cdddf2fdca
    76 N096e8264898f4d6aa2f94533c0f45b9a rdf:first sg:person.011037736512.45
    77 rdf:rest N08fb1662cee14dbbb5797c98fbae5a81
    78 N0cc9c67d7b844343aca20198150a63e8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    79 schema:name Middle Aged
    80 rdf:type schema:DefinedTerm
    81 N0d094259c66246089dbad28d97130448 schema:name dimensions_id
    82 schema:value pub.1019325978
    83 rdf:type schema:PropertyValue
    84 N0d55e314078d43629133a57081ee6e53 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    85 schema:name Myocardial Perfusion Imaging
    86 rdf:type schema:DefinedTerm
    87 N174ff196479d40508d65e8bfc16eb246 rdf:first sg:person.0757534712.07
    88 rdf:rest N096e8264898f4d6aa2f94533c0f45b9a
    89 N23f4cd3f3aee4e4fb53109642d37a451 schema:name doi
    90 schema:value 10.1007/s00259-013-2537-1
    91 rdf:type schema:PropertyValue
    92 N2562d80166dc4e2f873c0e94923d3fdd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    93 schema:name Multimodal Imaging
    94 rdf:type schema:DefinedTerm
    95 N25b87b631c3d43d1ac6e96c2d1d2c8a8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    96 schema:name Humans
    97 rdf:type schema:DefinedTerm
    98 N2b95ec72404b41678d266deee6bfd95c schema:name readcube_id
    99 schema:value 5c14c4df0cee284ab96b8d9aff0ffb72452f8a1cc265b27400dd10088a2fde7e
    100 rdf:type schema:PropertyValue
    101 N38ab4b80a1a94edfb50ba0cd284f5f43 rdf:first sg:person.0752615012.05
    102 rdf:rest Ncb624953260e4745bf01e5cadf476d3f
    103 N3ac23435003b42e7aa634882f82d5084 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    104 schema:name Tomography, X-Ray Computed
    105 rdf:type schema:DefinedTerm
    106 N3cb4fcae81a742558c1adc3b19724eb6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    107 schema:name Rubidium Radioisotopes
    108 rdf:type schema:DefinedTerm
    109 N3cb938917fd34d5193af70745546835e schema:name nlm_unique_id
    110 schema:value 101140988
    111 rdf:type schema:PropertyValue
    112 N3f8a00b39db3458fa8b8c418d086612d rdf:first sg:person.0704501612.49
    113 rdf:rest N38ab4b80a1a94edfb50ba0cd284f5f43
    114 N4ba7aff094b048898fa69618001ececc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    115 schema:name Image Processing, Computer-Assisted
    116 rdf:type schema:DefinedTerm
    117 N4cbdbab609ad490486f625ea126aeae6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    118 schema:name Female
    119 rdf:type schema:DefinedTerm
    120 N5c84c23dd4504478afb48103cb9eef21 rdf:first sg:person.0657342120.37
    121 rdf:rest N93dbfcf6426f42ee88c3132d6a56fa88
    122 N7a2b2847322d4bef8401051f939621bc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    123 schema:name Retrospective Studies
    124 rdf:type schema:DefinedTerm
    125 N7bad353418374497b4ce4e5f8cbfb608 rdf:first sg:person.01126527574.37
    126 rdf:rest N174ff196479d40508d65e8bfc16eb246
    127 N81903a6f8d1c4c0d9f6ecb8783cd929c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    128 schema:name Positron-Emission Tomography
    129 rdf:type schema:DefinedTerm
    130 N93dbfcf6426f42ee88c3132d6a56fa88 rdf:first sg:person.013000403137.02
    131 rdf:rest N7bad353418374497b4ce4e5f8cbfb608
    132 Nad757ddf3b894a9296b5a4c48436e6e4 schema:name INVIA Medical Imaging Solutions, Ann Arbor, MI, USA
    133 rdf:type schema:Organization
    134 Nb65e8eed36c34cf7bc8d054b91b8f90a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    135 schema:name Software
    136 rdf:type schema:DefinedTerm
    137 Ncb624953260e4745bf01e5cadf476d3f rdf:first sg:person.01223721440.78
    138 rdf:rest Nd5aa5224df924922996941ea6f04df88
    139 Nd0417b1c47c14502a82ecc9c54c1d8c8 schema:issueNumber 1
    140 rdf:type schema:PublicationIssue
    141 Nd585a6ff5db7439fb0732cf967a9090b rdf:first sg:person.01026461773.16
    142 rdf:rest Nfcef0494b2b946f6beeb3fc50ed644d7
    143 Nd5aa5224df924922996941ea6f04df88 rdf:first sg:person.01022150250.39
    144 rdf:rest Nd585a6ff5db7439fb0732cf967a9090b
    145 Ndaad5b0bfd114e9fbc5d93e8700e0ff4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    146 schema:name Male
    147 rdf:type schema:DefinedTerm
    148 Ne295c80d6e314e2784f8f331e4e47799 schema:volumeNumber 41
    149 rdf:type schema:PublicationVolume
    150 Ne87ce8e567b146fbb75408e21e818d11 schema:name Springer Nature - SN SciGraph project
    151 rdf:type schema:Organization
    152 Neadffe90f3bc42d78ea092cdddf2fdca rdf:first sg:person.01326535277.42
    153 rdf:rest rdf:nil
    154 Nee60f37696ae44fabc58bebe5ccbbc21 schema:name pubmed_id
    155 schema:value 23982454
    156 rdf:type schema:PropertyValue
    157 Nfcef0494b2b946f6beeb3fc50ed644d7 rdf:first sg:person.01061006633.19
    158 rdf:rest N5c84c23dd4504478afb48103cb9eef21
    159 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    160 schema:name Medical and Health Sciences
    161 rdf:type schema:DefinedTerm
    162 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
    163 schema:name Cardiorespiratory Medicine and Haematology
    164 rdf:type schema:DefinedTerm
    165 sg:grant.2683453 http://pending.schema.org/fundedItem sg:pub.10.1007/s00259-013-2537-1
    166 rdf:type schema:MonetaryGrant
    167 sg:journal.1297401 schema:issn 1619-7070
    168 1619-7089
    169 schema:name European Journal of Nuclear Medicine and Molecular Imaging
    170 rdf:type schema:Periodical
    171 sg:person.01022150250.39 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    172 schema:familyName Fukushima
    173 schema:givenName Kenji
    174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01022150250.39
    175 rdf:type schema:Person
    176 sg:person.01026461773.16 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    177 schema:familyName Lodge
    178 schema:givenName Martin A
    179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01026461773.16
    180 rdf:type schema:Person
    181 sg:person.01061006633.19 schema:affiliation Nad757ddf3b894a9296b5a4c48436e6e4
    182 schema:familyName Lee
    183 schema:givenName Benjamin C.
    184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061006633.19
    185 rdf:type schema:Person
    186 sg:person.011037736512.45 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    187 schema:familyName Wahl
    188 schema:givenName Richard L.
    189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011037736512.45
    190 rdf:type schema:Person
    191 sg:person.01126527574.37 schema:affiliation https://www.grid.ac/institutes/grid.28046.38
    192 schema:familyName Klein
    193 schema:givenName Ran
    194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01126527574.37
    195 rdf:type schema:Person
    196 sg:person.01223721440.78 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    197 schema:familyName Rajaram
    198 schema:givenName Mahadevan
    199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223721440.78
    200 rdf:type schema:Person
    201 sg:person.01225020511.95 schema:affiliation https://www.grid.ac/institutes/grid.10423.34
    202 schema:familyName Bengel
    203 schema:givenName Frank M.
    204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225020511.95
    205 rdf:type schema:Person
    206 sg:person.013000403137.02 schema:affiliation https://www.grid.ac/institutes/grid.6936.a
    207 schema:familyName Nekolla
    208 schema:givenName Stephan
    209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013000403137.02
    210 rdf:type schema:Person
    211 sg:person.01326535277.42 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    212 schema:familyName Bravo
    213 schema:givenName Paco E.
    214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01326535277.42
    215 rdf:type schema:Person
    216 sg:person.0657342120.37 schema:affiliation https://www.grid.ac/institutes/grid.412590.b
    217 schema:familyName Ficaro
    218 schema:givenName Edward P.
    219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657342120.37
    220 rdf:type schema:Person
    221 sg:person.0704501612.49 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    222 schema:familyName Tahari
    223 schema:givenName Abdel K.
    224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0704501612.49
    225 rdf:type schema:Person
    226 sg:person.0752615012.05 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
    227 schema:familyName Lee
    228 schema:givenName Andy
    229 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752615012.05
    230 rdf:type schema:Person
    231 sg:person.0757534712.07 schema:affiliation https://www.grid.ac/institutes/grid.28046.38
    232 schema:familyName deKemp
    233 schema:givenName Robert A.
    234 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0757534712.07
    235 rdf:type schema:Person
    236 sg:pub.10.1007/bf03007355 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037394649
    237 https://doi.org/10.1007/bf03007355
    238 rdf:type schema:CreativeWork
    239 sg:pub.10.1007/s00259-007-0478-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018573299
    240 https://doi.org/10.1007/s00259-007-0478-2
    241 rdf:type schema:CreativeWork
    242 sg:pub.10.1007/s00259-008-0972-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005274145
    243 https://doi.org/10.1007/s00259-008-0972-1
    244 rdf:type schema:CreativeWork
    245 sg:pub.10.1007/s00259-012-2140-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1047309064
    246 https://doi.org/10.1007/s00259-012-2140-x
    247 rdf:type schema:CreativeWork
    248 sg:pub.10.1007/s002590050301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027870105
    249 https://doi.org/10.1007/s002590050301
    250 rdf:type schema:CreativeWork
    251 sg:pub.10.1007/s12350-010-9225-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047284350
    252 https://doi.org/10.1007/s12350-010-9225-3
    253 rdf:type schema:CreativeWork
    254 sg:pub.10.1007/s12350-010-9246-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1018751663
    255 https://doi.org/10.1007/s12350-010-9246-y
    256 rdf:type schema:CreativeWork
    257 sg:pub.10.1007/s12350-010-9256-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031907500
    258 https://doi.org/10.1007/s12350-010-9256-9
    259 rdf:type schema:CreativeWork
    260 sg:pub.10.1016/j.nuclcard.2005.12.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049290178
    261 https://doi.org/10.1016/j.nuclcard.2005.12.004
    262 rdf:type schema:CreativeWork
    263 https://app.dimensions.ai/details/publication/pub.1077094730 schema:CreativeWork
    264 https://app.dimensions.ai/details/publication/pub.1082979514 schema:CreativeWork
    265 https://doi.org/10.1016/j.ijcard.2012.03.076 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007891388
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1016/j.jacc.2006.06.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032478234
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1016/j.jacc.2006.12.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007430749
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1016/j.jacc.2009.02.065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037812548
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1016/j.jacc.2009.02.069 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037628406
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.1016/j.jacc.2011.01.065 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027739308
    276 rdf:type schema:CreativeWork
    277 https://doi.org/10.1016/j.jacc.2011.02.068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049351487
    278 rdf:type schema:CreativeWork
    279 https://doi.org/10.1053/j.semnuclmed.2004.09.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022883749
    280 rdf:type schema:CreativeWork
    281 https://doi.org/10.1109/42.996340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061171178
    282 rdf:type schema:CreativeWork
    283 https://doi.org/10.1118/1.3438474 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002410326
    284 rdf:type schema:CreativeWork
    285 https://doi.org/10.1161/01.res.70.3.496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012060884
    286 rdf:type schema:CreativeWork
    287 https://doi.org/10.1161/circulationaha.106.629808 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014870616
    288 rdf:type schema:CreativeWork
    289 https://doi.org/10.1161/circulationaha.111.050427 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011963131
    290 rdf:type schema:CreativeWork
    291 https://doi.org/10.2967/jnumed.104.007831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043551310
    292 rdf:type schema:CreativeWork
    293 https://doi.org/10.2967/jnumed.108.054395 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035639750
    294 rdf:type schema:CreativeWork
    295 https://doi.org/10.2967/jnumed.110.081828 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001520969
    296 rdf:type schema:CreativeWork
    297 https://doi.org/10.2967/jnumed.111.095398 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004858876
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.2967/jnumed.112.108183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014369216
    300 rdf:type schema:CreativeWork
    301 https://www.grid.ac/institutes/grid.10423.34 schema:alternateName Hannover Medical School
    302 schema:name Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
    303 rdf:type schema:Organization
    304 https://www.grid.ac/institutes/grid.21107.35 schema:alternateName Johns Hopkins University
    305 schema:name Divisions of Nuclear Medicine, Johns Hopkins Medical Institutions, Department of Radiology, 601 N. Caroline Street, Suite 3223, 21287, Baltimore, MD, USA
    306 rdf:type schema:Organization
    307 https://www.grid.ac/institutes/grid.28046.38 schema:alternateName University of Ottawa
    308 schema:name University of Ottawa Heart Institute, Ottawa, Canada
    309 rdf:type schema:Organization
    310 https://www.grid.ac/institutes/grid.412590.b schema:alternateName Michigan Medicine
    311 schema:name University of Michigan Health Systems, Ann Arbor, MI, USA
    312 rdf:type schema:Organization
    313 https://www.grid.ac/institutes/grid.6936.a schema:alternateName Technical University Munich
    314 schema:name Technical University of Munich, Munich, Germany
    315 rdf:type schema:Organization
     




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


    ...