Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Elske Quak, Pierre-Yves Le Roux, Michael S. Hofman, Philippe Robin, David Bourhis, Jason Callahan, David Binns, Cédric Desmonts, Pierre-Yves Salaun, Rodney J. Hicks, Nicolas Aide

ABSTRACT

PURPOSE: Point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used. METHODS: NEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines. RESULTS: For the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95%CI: 0.86-2.06) and 1.23 (95%CI: 0.95-1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95%CI: 0.88-1.16) and 1.04 (95%CI: 0.92-1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient's BMI) was less than 5%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good. CONCLUSION: These data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems. More... »

PAGES

2072-2082

References to SciGraph publications

  • 2007-03. Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2011-12. SUVref: reducing reconstruction-dependent variation in PET SUV in EJNMMI RESEARCH
  • 2013-07. Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2014-05. Performance measurement of PSF modeling reconstruction (True X) on Siemens Biograph TruePoint TrueV PET/CT in ANNALS OF NUCLEAR MEDICINE
  • 2010-01. FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0 in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2014-07. qPET – a quantitative extension of the Deauville scale to assess response in interim FDG-PET scans in lymphoma in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2013-10. Evaluation of strategies towards harmonization of FDG PET/CT studies in multicentre trials: comparison of scanner validation phantoms and data analysis procedures in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2014-06. Staging the axilla in breast cancer patients with 18F-FDG PET: how small are the metastases that we can detect with new generation clinical PET systems? in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2015-02. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0

    DOI

    http://dx.doi.org/10.1007/s00259-015-3128-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037717808

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26219870


    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/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Carcinoma, Non-Small-Cell Lung", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Fluorodeoxyglucose F18", 
            "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": "Liver Neoplasms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Lymphoma, Non-Hodgkin", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Melanoma", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Middle Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Positron-Emission Tomography", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Radiopharmaceuticals", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "name": [
                "Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Quak", 
            "givenName": "Elske", 
            "id": "sg:person.01233564514.37", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01233564514.37"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Le Roux", 
            "givenName": "Pierre-Yves", 
            "id": "sg:person.01156373352.82", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156373352.82"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Peter MacCallum Cancer Centre", 
              "id": "https://www.grid.ac/institutes/grid.1055.1", 
              "name": [
                "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hofman", 
            "givenName": "Michael S.", 
            "id": "sg:person.01012460764.55", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012460764.55"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Robin", 
            "givenName": "Philippe", 
            "id": "sg:person.01307140060.86", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307140060.86"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bourhis", 
            "givenName": "David", 
            "id": "sg:person.0636567456.08", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636567456.08"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Peter MacCallum Cancer Centre", 
              "id": "https://www.grid.ac/institutes/grid.1055.1", 
              "name": [
                "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Callahan", 
            "givenName": "Jason", 
            "id": "sg:person.0616621550.24", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616621550.24"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Peter MacCallum Cancer Centre", 
              "id": "https://www.grid.ac/institutes/grid.1055.1", 
              "name": [
                "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Binns", 
            "givenName": "David", 
            "id": "sg:person.01213140513.69", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213140513.69"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Centre Hospitalier Universitaire de Caen", 
              "id": "https://www.grid.ac/institutes/grid.411149.8", 
              "name": [
                "Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Desmonts", 
            "givenName": "C\u00e9dric", 
            "id": "sg:person.0715336115.22", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715336115.22"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Salaun", 
            "givenName": "Pierre-Yves", 
            "id": "sg:person.01021766527.49", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021766527.49"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Peter MacCallum Cancer Centre", 
              "id": "https://www.grid.ac/institutes/grid.1055.1", 
              "name": [
                "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hicks", 
            "givenName": "Rodney J.", 
            "id": "sg:person.01121233254.97", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01121233254.97"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universit\u00e9 de Caen Basse-Normandie", 
              "id": "https://www.grid.ac/institutes/grid.412043.0", 
              "name": [
                "Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France", 
                "Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France", 
                "INSERM 1199, Fran\u00e7ois Baclesse Cancer Centre, Caen, France", 
                "Normandie University, Caen, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Aide", 
            "givenName": "Nicolas", 
            "id": "sg:person.01152406451.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152406451.51"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.ejrad.2014.10.018", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000011438"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnmt.110.086439", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002267161"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-014-2715-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002676223", 
              "https://doi.org/10.1007/s00259-014-2715-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.110.085662", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003909781"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-014-2961-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008918527", 
              "https://doi.org/10.1007/s00259-014-2961-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-014-2961-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008918527", 
              "https://doi.org/10.1007/s00259-014-2961-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.108.057307", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009233958"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1200/jco.2013.53.5229", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011190890"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.111.101733", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014167272"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ejrad.2013.09.030", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015207517"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-006-0224-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015743919", 
              "https://doi.org/10.1007/s00259-006-0224-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-013-2391-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016046039", 
              "https://doi.org/10.1007/s00259-013-2391-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-013-2391-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016046039", 
              "https://doi.org/10.1007/s00259-013-2391-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-013-2465-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016939976", 
              "https://doi.org/10.1007/s00259-013-2465-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-009-1297-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021250910", 
              "https://doi.org/10.1007/s00259-009-1297-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-009-1297-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021250910", 
              "https://doi.org/10.1007/s00259-009-1297-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-009-1297-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021250910", 
              "https://doi.org/10.1007/s00259-009-1297-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12149-014-0815-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021417424", 
              "https://doi.org/10.1007/s12149-014-0815-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.114.148056", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023215819"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-014-2689-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024627703", 
              "https://doi.org/10.1007/s00259-014-2689-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00259-014-2689-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024627703", 
              "https://doi.org/10.1007/s00259-014-2689-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2191-219x-1-16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025107920", 
              "https://doi.org/10.1186/2191-219x-1-16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1118/1.4800806", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025345986"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/rlu.0b013e318251e3d1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039409497"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0140-6736(86)90837-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040287180"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0140-6736(86)90837-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040287180"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0959-8049(99)00229-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049505783"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2967/jnumed.115.158402", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051396191"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3324/haematol.2014.104125", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053332356"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1088/0031-9155/56/8/004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059029129"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tmi.2010.2040188", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061695524"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3413/nukmed-0665-14-05", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1071311701"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077229509", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015-12", 
        "datePublishedReg": "2015-12-01", 
        "description": "PURPOSE: Point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used.\nMETHODS: NEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines.\nRESULTS: For the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95%CI: 0.86-2.06) and 1.23 (95%CI: 0.95-1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95%CI: 0.88-1.16) and 1.04 (95%CI: 0.92-1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient's BMI) was less than 5%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good.\nCONCLUSION: These data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s00259-015-3128-0", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1297401", 
            "issn": [
              "1619-7070", 
              "1619-7089"
            ], 
            "name": "European Journal of Nuclear Medicine and Molecular Imaging", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "13", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "42"
          }
        ], 
        "name": "Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients", 
        "pagination": "2072-2082", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "b3acc48401729b9490ce695add198be318282e1b50868977fa23c8357cd1e684"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "26219870"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "101140988"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00259-015-3128-0"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1037717808"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00259-015-3128-0", 
          "https://app.dimensions.ai/details/publication/pub.1037717808"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T09:54", 
        "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/v90/0000000347_0000000347/records_89798_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs00259-015-3128-0"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-015-3128-0'


     

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

    299 TRIPLES      21 PREDICATES      69 URIs      34 LITERALS      22 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00259-015-3128-0 schema:about N00c6610b303d4666a854609e91ae5a38
    2 N01f115aede9f45e0bee830ecca4e5a93
    3 N16be222f49de4e8890a634a42332f656
    4 N25abab1622974227909fa7cf9b82f2b5
    5 N2a8da95d70d5422c8f1843153df3e897
    6 N4573d8909c2a47b5babe78e4c601d0ec
    7 N478e7761200f4fbabf7f5cdae63e0c1e
    8 N6b56761ff07c403c9fc6d191fb75bf05
    9 N89ce6cf60a2240b7858abaca3d54520e
    10 Nba060ab5699c4cdfba49d1a801c7979e
    11 Nd1e07abf15e44fa094076c0c9552ad3b
    12 Ndd50bd7edbb4424c96d2017ab3f0d032
    13 Ne307abef245d436e9c98ababa356f0ad
    14 anzsrc-for:08
    15 anzsrc-for:0801
    16 schema:author Nb7f87555b9d34716a0655cdc3758c540
    17 schema:citation sg:pub.10.1007/s00259-006-0224-1
    18 sg:pub.10.1007/s00259-009-1297-4
    19 sg:pub.10.1007/s00259-013-2391-1
    20 sg:pub.10.1007/s00259-013-2465-0
    21 sg:pub.10.1007/s00259-014-2689-7
    22 sg:pub.10.1007/s00259-014-2715-9
    23 sg:pub.10.1007/s00259-014-2961-x
    24 sg:pub.10.1007/s12149-014-0815-z
    25 sg:pub.10.1186/2191-219x-1-16
    26 https://app.dimensions.ai/details/publication/pub.1077229509
    27 https://doi.org/10.1016/j.ejrad.2013.09.030
    28 https://doi.org/10.1016/j.ejrad.2014.10.018
    29 https://doi.org/10.1016/s0140-6736(86)90837-8
    30 https://doi.org/10.1016/s0959-8049(99)00229-4
    31 https://doi.org/10.1088/0031-9155/56/8/004
    32 https://doi.org/10.1097/rlu.0b013e318251e3d1
    33 https://doi.org/10.1109/tmi.2010.2040188
    34 https://doi.org/10.1118/1.4800806
    35 https://doi.org/10.1200/jco.2013.53.5229
    36 https://doi.org/10.2967/jnmt.110.086439
    37 https://doi.org/10.2967/jnumed.108.057307
    38 https://doi.org/10.2967/jnumed.110.085662
    39 https://doi.org/10.2967/jnumed.111.101733
    40 https://doi.org/10.2967/jnumed.114.148056
    41 https://doi.org/10.2967/jnumed.115.158402
    42 https://doi.org/10.3324/haematol.2014.104125
    43 https://doi.org/10.3413/nukmed-0665-14-05
    44 schema:datePublished 2015-12
    45 schema:datePublishedReg 2015-12-01
    46 schema:description PURPOSE: Point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used. METHODS: NEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines. RESULTS: For the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95%CI: 0.86-2.06) and 1.23 (95%CI: 0.95-1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95%CI: 0.88-1.16) and 1.04 (95%CI: 0.92-1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient's BMI) was less than 5%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good. CONCLUSION: These data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems.
    47 schema:genre research_article
    48 schema:inLanguage en
    49 schema:isAccessibleForFree true
    50 schema:isPartOf N75870c83fb0f4bd1878cc85e63044c8a
    51 Nab26489574644fc79965c6c06383b6cb
    52 sg:journal.1297401
    53 schema:name Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients
    54 schema:pagination 2072-2082
    55 schema:productId N0702a6a7a6f94b2a85a3f00dc429f1a3
    56 N0761046a8522419ab9efb2cb507bbaad
    57 N08f28959d70443d39baa67a969cba27c
    58 Nb0944d0dc72e45e4b7306539a2ea8848
    59 Nd690654b1a934c0ab71e16710824d1be
    60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037717808
    61 https://doi.org/10.1007/s00259-015-3128-0
    62 schema:sdDatePublished 2019-04-11T09:54
    63 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    64 schema:sdPublisher N52e39ff8e0ec4c3980192374d235a87c
    65 schema:url http://link.springer.com/10.1007%2Fs00259-015-3128-0
    66 sgo:license sg:explorer/license/
    67 sgo:sdDataset articles
    68 rdf:type schema:ScholarlyArticle
    69 N00c6610b303d4666a854609e91ae5a38 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    70 schema:name Aged
    71 rdf:type schema:DefinedTerm
    72 N01f115aede9f45e0bee830ecca4e5a93 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    73 schema:name Image Processing, Computer-Assisted
    74 rdf:type schema:DefinedTerm
    75 N04da951aa69640ce980b32c3236cc57c schema:name Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    76 rdf:type schema:Organization
    77 N06b693c75df94b288812322e7f849215 rdf:first sg:person.01307140060.86
    78 rdf:rest Nbdc273eb30ff470290e3388da93059ff
    79 N0702a6a7a6f94b2a85a3f00dc429f1a3 schema:name doi
    80 schema:value 10.1007/s00259-015-3128-0
    81 rdf:type schema:PropertyValue
    82 N0761046a8522419ab9efb2cb507bbaad schema:name pubmed_id
    83 schema:value 26219870
    84 rdf:type schema:PropertyValue
    85 N08f28959d70443d39baa67a969cba27c schema:name dimensions_id
    86 schema:value pub.1037717808
    87 rdf:type schema:PropertyValue
    88 N16be222f49de4e8890a634a42332f656 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    89 schema:name Middle Aged
    90 rdf:type schema:DefinedTerm
    91 N1ad0726e76f6423e9a4100fcdaf6fba9 schema:name Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    92 rdf:type schema:Organization
    93 N1d1339e739b04fa688e3ca2d9337abef rdf:first sg:person.01021766527.49
    94 rdf:rest Nefc0b0aa1e6a43cca821aab147489928
    95 N25abab1622974227909fa7cf9b82f2b5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    96 schema:name Male
    97 rdf:type schema:DefinedTerm
    98 N2a8da95d70d5422c8f1843153df3e897 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    99 schema:name Radiopharmaceuticals
    100 rdf:type schema:DefinedTerm
    101 N2b660bf230104528a25d61eb54263b73 rdf:first sg:person.01012460764.55
    102 rdf:rest N06b693c75df94b288812322e7f849215
    103 N310befcca9b7402bb349004b3c4fba05 rdf:first sg:person.0616621550.24
    104 rdf:rest Nda31909eeebf4b3a81b0f1548c04f110
    105 N3cf4325fd9ac4ed996a05efff7a6b21d rdf:first sg:person.0715336115.22
    106 rdf:rest N1d1339e739b04fa688e3ca2d9337abef
    107 N4573d8909c2a47b5babe78e4c601d0ec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    108 schema:name Humans
    109 rdf:type schema:DefinedTerm
    110 N478e7761200f4fbabf7f5cdae63e0c1e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    111 schema:name Lymphoma, Non-Hodgkin
    112 rdf:type schema:DefinedTerm
    113 N5156f33da1a8499abccef292e08a55d3 schema:name Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France
    114 rdf:type schema:Organization
    115 N52e39ff8e0ec4c3980192374d235a87c schema:name Springer Nature - SN SciGraph project
    116 rdf:type schema:Organization
    117 N6a33e7a66d1c44ce9f015e0d87abbbda schema:name Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    118 rdf:type schema:Organization
    119 N6b56761ff07c403c9fc6d191fb75bf05 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    120 schema:name Fluorodeoxyglucose F18
    121 rdf:type schema:DefinedTerm
    122 N75870c83fb0f4bd1878cc85e63044c8a schema:issueNumber 13
    123 rdf:type schema:PublicationIssue
    124 N89ce6cf60a2240b7858abaca3d54520e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Melanoma
    126 rdf:type schema:DefinedTerm
    127 Na4468be5941347268808c5a5a559caef schema:name Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    128 rdf:type schema:Organization
    129 Nab26489574644fc79965c6c06383b6cb schema:volumeNumber 42
    130 rdf:type schema:PublicationVolume
    131 Nb0944d0dc72e45e4b7306539a2ea8848 schema:name readcube_id
    132 schema:value b3acc48401729b9490ce695add198be318282e1b50868977fa23c8357cd1e684
    133 rdf:type schema:PropertyValue
    134 Nb7f87555b9d34716a0655cdc3758c540 rdf:first sg:person.01233564514.37
    135 rdf:rest Nc5bafb6db1314bfeaa0e6c84ecd5ee06
    136 Nba060ab5699c4cdfba49d1a801c7979e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Positron-Emission Tomography
    138 rdf:type schema:DefinedTerm
    139 Nbdc273eb30ff470290e3388da93059ff rdf:first sg:person.0636567456.08
    140 rdf:rest N310befcca9b7402bb349004b3c4fba05
    141 Nc5bafb6db1314bfeaa0e6c84ecd5ee06 rdf:first sg:person.01156373352.82
    142 rdf:rest N2b660bf230104528a25d61eb54263b73
    143 Nd1e07abf15e44fa094076c0c9552ad3b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    144 schema:name Female
    145 rdf:type schema:DefinedTerm
    146 Nd690654b1a934c0ab71e16710824d1be schema:name nlm_unique_id
    147 schema:value 101140988
    148 rdf:type schema:PropertyValue
    149 Nda31909eeebf4b3a81b0f1548c04f110 rdf:first sg:person.01213140513.69
    150 rdf:rest N3cf4325fd9ac4ed996a05efff7a6b21d
    151 Nda7f0596902a480f972d7312631ae52c rdf:first sg:person.01152406451.51
    152 rdf:rest rdf:nil
    153 Ndd50bd7edbb4424c96d2017ab3f0d032 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Liver Neoplasms
    155 rdf:type schema:DefinedTerm
    156 Ne307abef245d436e9c98ababa356f0ad schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Carcinoma, Non-Small-Cell Lung
    158 rdf:type schema:DefinedTerm
    159 Nefc0b0aa1e6a43cca821aab147489928 rdf:first sg:person.01121233254.97
    160 rdf:rest Nda7f0596902a480f972d7312631ae52c
    161 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    162 schema:name Information and Computing Sciences
    163 rdf:type schema:DefinedTerm
    164 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    165 schema:name Artificial Intelligence and Image Processing
    166 rdf:type schema:DefinedTerm
    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.01012460764.55 schema:affiliation https://www.grid.ac/institutes/grid.1055.1
    172 schema:familyName Hofman
    173 schema:givenName Michael S.
    174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012460764.55
    175 rdf:type schema:Person
    176 sg:person.01021766527.49 schema:affiliation N1ad0726e76f6423e9a4100fcdaf6fba9
    177 schema:familyName Salaun
    178 schema:givenName Pierre-Yves
    179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021766527.49
    180 rdf:type schema:Person
    181 sg:person.01121233254.97 schema:affiliation https://www.grid.ac/institutes/grid.1055.1
    182 schema:familyName Hicks
    183 schema:givenName Rodney J.
    184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01121233254.97
    185 rdf:type schema:Person
    186 sg:person.01152406451.51 schema:affiliation https://www.grid.ac/institutes/grid.412043.0
    187 schema:familyName Aide
    188 schema:givenName Nicolas
    189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152406451.51
    190 rdf:type schema:Person
    191 sg:person.01156373352.82 schema:affiliation N04da951aa69640ce980b32c3236cc57c
    192 schema:familyName Le Roux
    193 schema:givenName Pierre-Yves
    194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156373352.82
    195 rdf:type schema:Person
    196 sg:person.01213140513.69 schema:affiliation https://www.grid.ac/institutes/grid.1055.1
    197 schema:familyName Binns
    198 schema:givenName David
    199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213140513.69
    200 rdf:type schema:Person
    201 sg:person.01233564514.37 schema:affiliation N5156f33da1a8499abccef292e08a55d3
    202 schema:familyName Quak
    203 schema:givenName Elske
    204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01233564514.37
    205 rdf:type schema:Person
    206 sg:person.01307140060.86 schema:affiliation N6a33e7a66d1c44ce9f015e0d87abbbda
    207 schema:familyName Robin
    208 schema:givenName Philippe
    209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307140060.86
    210 rdf:type schema:Person
    211 sg:person.0616621550.24 schema:affiliation https://www.grid.ac/institutes/grid.1055.1
    212 schema:familyName Callahan
    213 schema:givenName Jason
    214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616621550.24
    215 rdf:type schema:Person
    216 sg:person.0636567456.08 schema:affiliation Na4468be5941347268808c5a5a559caef
    217 schema:familyName Bourhis
    218 schema:givenName David
    219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636567456.08
    220 rdf:type schema:Person
    221 sg:person.0715336115.22 schema:affiliation https://www.grid.ac/institutes/grid.411149.8
    222 schema:familyName Desmonts
    223 schema:givenName Cédric
    224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715336115.22
    225 rdf:type schema:Person
    226 sg:pub.10.1007/s00259-006-0224-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015743919
    227 https://doi.org/10.1007/s00259-006-0224-1
    228 rdf:type schema:CreativeWork
    229 sg:pub.10.1007/s00259-009-1297-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021250910
    230 https://doi.org/10.1007/s00259-009-1297-4
    231 rdf:type schema:CreativeWork
    232 sg:pub.10.1007/s00259-013-2391-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016046039
    233 https://doi.org/10.1007/s00259-013-2391-1
    234 rdf:type schema:CreativeWork
    235 sg:pub.10.1007/s00259-013-2465-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016939976
    236 https://doi.org/10.1007/s00259-013-2465-0
    237 rdf:type schema:CreativeWork
    238 sg:pub.10.1007/s00259-014-2689-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024627703
    239 https://doi.org/10.1007/s00259-014-2689-7
    240 rdf:type schema:CreativeWork
    241 sg:pub.10.1007/s00259-014-2715-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002676223
    242 https://doi.org/10.1007/s00259-014-2715-9
    243 rdf:type schema:CreativeWork
    244 sg:pub.10.1007/s00259-014-2961-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1008918527
    245 https://doi.org/10.1007/s00259-014-2961-x
    246 rdf:type schema:CreativeWork
    247 sg:pub.10.1007/s12149-014-0815-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1021417424
    248 https://doi.org/10.1007/s12149-014-0815-z
    249 rdf:type schema:CreativeWork
    250 sg:pub.10.1186/2191-219x-1-16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025107920
    251 https://doi.org/10.1186/2191-219x-1-16
    252 rdf:type schema:CreativeWork
    253 https://app.dimensions.ai/details/publication/pub.1077229509 schema:CreativeWork
    254 https://doi.org/10.1016/j.ejrad.2013.09.030 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015207517
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1016/j.ejrad.2014.10.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000011438
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1016/s0140-6736(86)90837-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040287180
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1016/s0959-8049(99)00229-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049505783
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1088/0031-9155/56/8/004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059029129
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1097/rlu.0b013e318251e3d1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039409497
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1109/tmi.2010.2040188 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061695524
    267 rdf:type schema:CreativeWork
    268 https://doi.org/10.1118/1.4800806 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025345986
    269 rdf:type schema:CreativeWork
    270 https://doi.org/10.1200/jco.2013.53.5229 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011190890
    271 rdf:type schema:CreativeWork
    272 https://doi.org/10.2967/jnmt.110.086439 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002267161
    273 rdf:type schema:CreativeWork
    274 https://doi.org/10.2967/jnumed.108.057307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009233958
    275 rdf:type schema:CreativeWork
    276 https://doi.org/10.2967/jnumed.110.085662 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003909781
    277 rdf:type schema:CreativeWork
    278 https://doi.org/10.2967/jnumed.111.101733 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014167272
    279 rdf:type schema:CreativeWork
    280 https://doi.org/10.2967/jnumed.114.148056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023215819
    281 rdf:type schema:CreativeWork
    282 https://doi.org/10.2967/jnumed.115.158402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051396191
    283 rdf:type schema:CreativeWork
    284 https://doi.org/10.3324/haematol.2014.104125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053332356
    285 rdf:type schema:CreativeWork
    286 https://doi.org/10.3413/nukmed-0665-14-05 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071311701
    287 rdf:type schema:CreativeWork
    288 https://www.grid.ac/institutes/grid.1055.1 schema:alternateName Peter MacCallum Cancer Centre
    289 schema:name Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia
    290 rdf:type schema:Organization
    291 https://www.grid.ac/institutes/grid.411149.8 schema:alternateName Centre Hospitalier Universitaire de Caen
    292 schema:name Nuclear Medicine Department, University Hospital, Avenue Côte de Nacre, 14000, Caen, France
    293 rdf:type schema:Organization
    294 https://www.grid.ac/institutes/grid.412043.0 schema:alternateName Université de Caen Basse-Normandie
    295 schema:name INSERM 1199, François Baclesse Cancer Centre, Caen, France
    296 Normandie University, Caen, France
    297 Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France
    298 Nuclear Medicine Department, University Hospital, Avenue Côte de Nacre, 14000, Caen, France
    299 rdf:type schema:Organization
     




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


    ...