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

2015-07-30

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

PurposePoint-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.MethodsNEMA 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.ResultsFor 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.ConclusionThese 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

  • 2006-10-11. 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
  • 2011-08-18. SUVref: reducing reconstruction-dependent variation in PET SUV in EJNMMI RESEARCH
  • 2013-04-06. 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
  • 2014-02-07. Performance measurement of PSF modeling reconstruction (True X) on Siemens Biograph TruePoint TrueV PET/CT in ANNALS OF NUCLEAR MEDICINE
  • 2009-11-14. FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0 in EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
  • 2014-03-07. 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
  • 2013-06-11. 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
  • 2014-02-22. 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
  • 2014-12-02. 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/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Clinical 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": {
              "alternateName": "Nuclear Medicine Department, Fran\u00e7ois Baclesse Cancer Centre, Caen, France", 
              "id": "http://www.grid.ac/institutes/None", 
              "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": {
              "alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France", 
              "id": "http://www.grid.ac/institutes/None", 
              "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": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia", 
              "id": "http://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": {
              "alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France", 
              "id": "http://www.grid.ac/institutes/None", 
              "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": {
              "alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France", 
              "id": "http://www.grid.ac/institutes/None", 
              "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": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia", 
              "id": "http://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": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia", 
              "id": "http://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": "Nuclear Medicine Department, University Hospital, Avenue C\u00f4te de Nacre, 14000, Caen, France", 
              "id": "http://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": {
              "alternateName": "Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France", 
              "id": "http://www.grid.ac/institutes/None", 
              "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": "Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia", 
              "id": "http://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": "Normandie University, Caen, France", 
              "id": "http://www.grid.ac/institutes/grid.460771.3", 
              "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": "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": "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/s00259-013-2465-0", 
            "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/s00259-014-2715-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002676223", 
              "https://doi.org/10.1007/s00259-014-2715-9"
            ], 
            "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.10.1186/2191-219x-1-16", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025107920", 
              "https://doi.org/10.1186/2191-219x-1-16"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "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/s00259-013-2391-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016046039", 
              "https://doi.org/10.1007/s00259-013-2391-1"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2015-07-30", 
        "datePublishedReg": "2015-07-30", 
        "description": "PurposePoint-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.MethodsNEMA 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.ResultsFor the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95\u00a0%CI: 0.86\u20132.06) and 1.23 (95\u00a0%CI: 0.95\u20131.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95\u00a0%CI: 0.88\u20131.16) and 1.04 (95\u00a0%CI: 0.92\u20131.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient\u2019s BMI) was less than 5\u00a0%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good.ConclusionThese 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": "article", 
        "id": "sg:pub.10.1007/s00259-015-3128-0", 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1297401", 
            "issn": [
              "1619-7070", 
              "1619-7089"
            ], 
            "name": "European Journal of Nuclear Medicine and Molecular Imaging", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "13", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "42"
          }
        ], 
        "keywords": [
          "standardized uptake value", 
          "oncology patients", 
          "different PET systems", 
          "optimal tumour detection", 
          "optimal lesion detection", 
          "lesion detection", 
          "Nuclear Medicine (EANM) guidelines", 
          "different confounding factors", 
          "superior lesion detection", 
          "patient characteristics", 
          "Medicine guidelines", 
          "potential confounders", 
          "FDG-PET quantification", 
          "Bland-Altman analysis", 
          "ConclusionThese data", 
          "tumor lesions", 
          "uptake value", 
          "confounding factors", 
          "EANM guidelines", 
          "multicentre validation", 
          "European Association", 
          "mean ratio", 
          "patients", 
          "SUVmax", 
          "lesions", 
          "oncologic PET", 
          "SUVpeak", 
          "PET methodology", 
          "tumor imaging", 
          "adherence", 
          "tumor detection", 
          "subsets expectation maximization (OSEM) reconstruction", 
          "guidelines", 
          "PET quantification", 
          "PET data", 
          "new reconstruction technique", 
          "confounders", 
          "ResultsFor", 
          "association", 
          "reconstruction technique", 
          "flight reconstruction", 
          "reconstruction", 
          "imaging", 
          "PET", 
          "data", 
          "detection", 
          "image quality", 
          "factors", 
          "quantitative comparability", 
          "study", 
          "quantitation", 
          "ratio", 
          "expectation maximization reconstruction", 
          "comparability", 
          "function", 
          "quality", 
          "PET system", 
          "quantification", 
          "time", 
          "phantom data", 
          "impact", 
          "analysis", 
          "validation", 
          "system", 
          "characteristics", 
          "tool", 
          "values", 
          "appropriate filters", 
          "proprietary software tools", 
          "technique", 
          "influence", 
          "software tools", 
          "recovery coefficient", 
          "reconstruction algorithm", 
          "order", 
          "quest", 
          "algorithm", 
          "coefficient", 
          "eq", 
          "filter", 
          "methodology", 
          "applications", 
          "OSEM3D"
        ], 
        "name": "Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients", 
        "pagination": "2072-2082", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1037717808"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s00259-015-3128-0"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "26219870"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s00259-015-3128-0", 
          "https://app.dimensions.ai/details/publication/pub.1037717808"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-09-02T15:58", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_660.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1007/s00259-015-3128-0"
      }
    ]
     

    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.

    316 TRIPLES      21 PREDICATES      130 URIs      113 LITERALS      20 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s00259-015-3128-0 schema:about N012935cfc9c64537bc06acf437510542
    2 N47b66bb18b9b4bc9b38ad996ce045008
    3 N4d2d421fb42b49a19236ea55bb325181
    4 N4eb0432d81844d4fabbc602b1e725bbb
    5 N544e277287c4431bb02ca6f81f6b28c8
    6 N6358dcb2b73547548aee82ee8cffe6e3
    7 N67654949505d4699b4815ad2c4f71138
    8 N8a3deac194694e34bbb2b0b05a3a8f1d
    9 N9242c398bf804478aede66c350bb30d1
    10 N988326b2fc4643a69d6103e2cc810ac6
    11 Ne25272b34faf48f4b891cccccbbbfc5f
    12 Nebacc6426f194e358d8fae8c2a2e9e7f
    13 Nf6257acd79ce4034acf53ea68202776c
    14 anzsrc-for:11
    15 anzsrc-for:1103
    16 schema:author N7765fb1e79324bc8b14a784ea1d86598
    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 schema:datePublished 2015-07-30
    27 schema:datePublishedReg 2015-07-30
    28 schema:description PurposePoint-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.MethodsNEMA 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.ResultsFor 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.ConclusionThese 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.
    29 schema:genre article
    30 schema:isAccessibleForFree true
    31 schema:isPartOf N9d6304563bbb46649e0b016946918a5d
    32 Nf83430b8ab954513b13813e842c710e7
    33 sg:journal.1297401
    34 schema:keywords Bland-Altman analysis
    35 ConclusionThese data
    36 EANM guidelines
    37 European Association
    38 FDG-PET quantification
    39 Medicine guidelines
    40 Nuclear Medicine (EANM) guidelines
    41 OSEM3D
    42 PET
    43 PET data
    44 PET methodology
    45 PET quantification
    46 PET system
    47 ResultsFor
    48 SUVmax
    49 SUVpeak
    50 adherence
    51 algorithm
    52 analysis
    53 applications
    54 appropriate filters
    55 association
    56 characteristics
    57 coefficient
    58 comparability
    59 confounders
    60 confounding factors
    61 data
    62 detection
    63 different PET systems
    64 different confounding factors
    65 eq
    66 expectation maximization reconstruction
    67 factors
    68 filter
    69 flight reconstruction
    70 function
    71 guidelines
    72 image quality
    73 imaging
    74 impact
    75 influence
    76 lesion detection
    77 lesions
    78 mean ratio
    79 methodology
    80 multicentre validation
    81 new reconstruction technique
    82 oncologic PET
    83 oncology patients
    84 optimal lesion detection
    85 optimal tumour detection
    86 order
    87 patient characteristics
    88 patients
    89 phantom data
    90 potential confounders
    91 proprietary software tools
    92 quality
    93 quantification
    94 quantitation
    95 quantitative comparability
    96 quest
    97 ratio
    98 reconstruction
    99 reconstruction algorithm
    100 reconstruction technique
    101 recovery coefficient
    102 software tools
    103 standardized uptake value
    104 study
    105 subsets expectation maximization (OSEM) reconstruction
    106 superior lesion detection
    107 system
    108 technique
    109 time
    110 tool
    111 tumor detection
    112 tumor imaging
    113 tumor lesions
    114 uptake value
    115 validation
    116 values
    117 schema:name Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients
    118 schema:pagination 2072-2082
    119 schema:productId N07662bb9ce884f7cadb6d9b207106031
    120 N1a4f12ce42cc4230abad0c616882fe52
    121 N39832ad26f2141e4b72facc471d34241
    122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037717808
    123 https://doi.org/10.1007/s00259-015-3128-0
    124 schema:sdDatePublished 2022-09-02T15:58
    125 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    126 schema:sdPublisher Nebd80c564cb84f0f8b19789066e6d62e
    127 schema:url https://doi.org/10.1007/s00259-015-3128-0
    128 sgo:license sg:explorer/license/
    129 sgo:sdDataset articles
    130 rdf:type schema:ScholarlyArticle
    131 N012935cfc9c64537bc06acf437510542 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    132 schema:name Carcinoma, Non-Small-Cell Lung
    133 rdf:type schema:DefinedTerm
    134 N07662bb9ce884f7cadb6d9b207106031 schema:name pubmed_id
    135 schema:value 26219870
    136 rdf:type schema:PropertyValue
    137 N14f037dc2e5346bbb4cd208608ff3db5 rdf:first sg:person.01121233254.97
    138 rdf:rest Ne63521ae1abd4b9598abe6c93f9e4e97
    139 N1a4f12ce42cc4230abad0c616882fe52 schema:name doi
    140 schema:value 10.1007/s00259-015-3128-0
    141 rdf:type schema:PropertyValue
    142 N39832ad26f2141e4b72facc471d34241 schema:name dimensions_id
    143 schema:value pub.1037717808
    144 rdf:type schema:PropertyValue
    145 N3b6488a4fa6f4fa8b3f0ba3a13b28792 rdf:first sg:person.0636567456.08
    146 rdf:rest N83b20f0105204c4491f3e1def7ab7a01
    147 N47b66bb18b9b4bc9b38ad996ce045008 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    148 schema:name Lymphoma, Non-Hodgkin
    149 rdf:type schema:DefinedTerm
    150 N4d2d421fb42b49a19236ea55bb325181 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    151 schema:name Image Processing, Computer-Assisted
    152 rdf:type schema:DefinedTerm
    153 N4eb0432d81844d4fabbc602b1e725bbb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Male
    155 rdf:type schema:DefinedTerm
    156 N544e277287c4431bb02ca6f81f6b28c8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Middle Aged
    158 rdf:type schema:DefinedTerm
    159 N6358dcb2b73547548aee82ee8cffe6e3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    160 schema:name Positron-Emission Tomography
    161 rdf:type schema:DefinedTerm
    162 N639dedaa919d457aaebeb180d9e760e8 rdf:first sg:person.01213140513.69
    163 rdf:rest Ncc01b1c05ecd4ddda98e775a05cc2fef
    164 N666fc6d7248f418e92208aa62f9c86ab rdf:first sg:person.01307140060.86
    165 rdf:rest N3b6488a4fa6f4fa8b3f0ba3a13b28792
    166 N67654949505d4699b4815ad2c4f71138 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    167 schema:name Female
    168 rdf:type schema:DefinedTerm
    169 N7765fb1e79324bc8b14a784ea1d86598 rdf:first sg:person.01233564514.37
    170 rdf:rest Ncc3a1edff6a04a149415fe9f336be9a2
    171 N83b20f0105204c4491f3e1def7ab7a01 rdf:first sg:person.0616621550.24
    172 rdf:rest N639dedaa919d457aaebeb180d9e760e8
    173 N8a3deac194694e34bbb2b0b05a3a8f1d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    174 schema:name Aged
    175 rdf:type schema:DefinedTerm
    176 N9242c398bf804478aede66c350bb30d1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    177 schema:name Radiopharmaceuticals
    178 rdf:type schema:DefinedTerm
    179 N988326b2fc4643a69d6103e2cc810ac6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    180 schema:name Liver Neoplasms
    181 rdf:type schema:DefinedTerm
    182 N9d6304563bbb46649e0b016946918a5d schema:volumeNumber 42
    183 rdf:type schema:PublicationVolume
    184 Na4952280a01347b1bbc5e2f10736d4e5 rdf:first sg:person.01021766527.49
    185 rdf:rest N14f037dc2e5346bbb4cd208608ff3db5
    186 Ncc01b1c05ecd4ddda98e775a05cc2fef rdf:first sg:person.0715336115.22
    187 rdf:rest Na4952280a01347b1bbc5e2f10736d4e5
    188 Ncc3a1edff6a04a149415fe9f336be9a2 rdf:first sg:person.01156373352.82
    189 rdf:rest Ndbcb8290fff7474faf1b693e94c6e02c
    190 Ndbcb8290fff7474faf1b693e94c6e02c rdf:first sg:person.01012460764.55
    191 rdf:rest N666fc6d7248f418e92208aa62f9c86ab
    192 Ne25272b34faf48f4b891cccccbbbfc5f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    193 schema:name Humans
    194 rdf:type schema:DefinedTerm
    195 Ne63521ae1abd4b9598abe6c93f9e4e97 rdf:first sg:person.01152406451.51
    196 rdf:rest rdf:nil
    197 Nebacc6426f194e358d8fae8c2a2e9e7f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    198 schema:name Melanoma
    199 rdf:type schema:DefinedTerm
    200 Nebd80c564cb84f0f8b19789066e6d62e schema:name Springer Nature - SN SciGraph project
    201 rdf:type schema:Organization
    202 Nf6257acd79ce4034acf53ea68202776c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    203 schema:name Fluorodeoxyglucose F18
    204 rdf:type schema:DefinedTerm
    205 Nf83430b8ab954513b13813e842c710e7 schema:issueNumber 13
    206 rdf:type schema:PublicationIssue
    207 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    208 schema:name Medical and Health Sciences
    209 rdf:type schema:DefinedTerm
    210 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
    211 schema:name Clinical Sciences
    212 rdf:type schema:DefinedTerm
    213 sg:journal.1297401 schema:issn 1619-7070
    214 1619-7089
    215 schema:name European Journal of Nuclear Medicine and Molecular Imaging
    216 schema:publisher Springer Nature
    217 rdf:type schema:Periodical
    218 sg:person.01012460764.55 schema:affiliation grid-institutes:grid.1055.1
    219 schema:familyName Hofman
    220 schema:givenName Michael S.
    221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01012460764.55
    222 rdf:type schema:Person
    223 sg:person.01021766527.49 schema:affiliation grid-institutes:None
    224 schema:familyName Salaun
    225 schema:givenName Pierre-Yves
    226 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01021766527.49
    227 rdf:type schema:Person
    228 sg:person.01121233254.97 schema:affiliation grid-institutes:grid.1055.1
    229 schema:familyName Hicks
    230 schema:givenName Rodney J.
    231 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01121233254.97
    232 rdf:type schema:Person
    233 sg:person.01152406451.51 schema:affiliation grid-institutes:grid.460771.3
    234 schema:familyName Aide
    235 schema:givenName Nicolas
    236 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01152406451.51
    237 rdf:type schema:Person
    238 sg:person.01156373352.82 schema:affiliation grid-institutes:None
    239 schema:familyName Le Roux
    240 schema:givenName Pierre-Yves
    241 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01156373352.82
    242 rdf:type schema:Person
    243 sg:person.01213140513.69 schema:affiliation grid-institutes:grid.1055.1
    244 schema:familyName Binns
    245 schema:givenName David
    246 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213140513.69
    247 rdf:type schema:Person
    248 sg:person.01233564514.37 schema:affiliation grid-institutes:None
    249 schema:familyName Quak
    250 schema:givenName Elske
    251 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01233564514.37
    252 rdf:type schema:Person
    253 sg:person.01307140060.86 schema:affiliation grid-institutes:None
    254 schema:familyName Robin
    255 schema:givenName Philippe
    256 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307140060.86
    257 rdf:type schema:Person
    258 sg:person.0616621550.24 schema:affiliation grid-institutes:grid.1055.1
    259 schema:familyName Callahan
    260 schema:givenName Jason
    261 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616621550.24
    262 rdf:type schema:Person
    263 sg:person.0636567456.08 schema:affiliation grid-institutes:None
    264 schema:familyName Bourhis
    265 schema:givenName David
    266 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0636567456.08
    267 rdf:type schema:Person
    268 sg:person.0715336115.22 schema:affiliation grid-institutes:grid.411149.8
    269 schema:familyName Desmonts
    270 schema:givenName Cédric
    271 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715336115.22
    272 rdf:type schema:Person
    273 sg:pub.10.1007/s00259-006-0224-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015743919
    274 https://doi.org/10.1007/s00259-006-0224-1
    275 rdf:type schema:CreativeWork
    276 sg:pub.10.1007/s00259-009-1297-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021250910
    277 https://doi.org/10.1007/s00259-009-1297-4
    278 rdf:type schema:CreativeWork
    279 sg:pub.10.1007/s00259-013-2391-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016046039
    280 https://doi.org/10.1007/s00259-013-2391-1
    281 rdf:type schema:CreativeWork
    282 sg:pub.10.1007/s00259-013-2465-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016939976
    283 https://doi.org/10.1007/s00259-013-2465-0
    284 rdf:type schema:CreativeWork
    285 sg:pub.10.1007/s00259-014-2689-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024627703
    286 https://doi.org/10.1007/s00259-014-2689-7
    287 rdf:type schema:CreativeWork
    288 sg:pub.10.1007/s00259-014-2715-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002676223
    289 https://doi.org/10.1007/s00259-014-2715-9
    290 rdf:type schema:CreativeWork
    291 sg:pub.10.1007/s00259-014-2961-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1008918527
    292 https://doi.org/10.1007/s00259-014-2961-x
    293 rdf:type schema:CreativeWork
    294 sg:pub.10.1007/s12149-014-0815-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1021417424
    295 https://doi.org/10.1007/s12149-014-0815-z
    296 rdf:type schema:CreativeWork
    297 sg:pub.10.1186/2191-219x-1-16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025107920
    298 https://doi.org/10.1186/2191-219x-1-16
    299 rdf:type schema:CreativeWork
    300 grid-institutes:None schema:alternateName Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France
    301 Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    302 schema:name Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France
    303 Nuclear Medicine Department, University Hospital and EA3878 (GETBO) IFR 148, Brest, France
    304 rdf:type schema:Organization
    305 grid-institutes:grid.1055.1 schema:alternateName Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia
    306 schema:name Centre for Molecular Imaging, Peter MacCallum Cancer Centre, East Melbourne and University of Melbourne, Melbourne, Australia
    307 rdf:type schema:Organization
    308 grid-institutes:grid.411149.8 schema:alternateName Nuclear Medicine Department, University Hospital, Avenue Côte de Nacre, 14000, Caen, France
    309 schema:name Nuclear Medicine Department, University Hospital, Avenue Côte de Nacre, 14000, Caen, France
    310 rdf:type schema:Organization
    311 grid-institutes:grid.460771.3 schema:alternateName Normandie University, Caen, France
    312 schema:name INSERM 1199, François Baclesse Cancer Centre, Caen, France
    313 Normandie University, Caen, France
    314 Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France
    315 Nuclear Medicine Department, University Hospital, Avenue Côte de Nacre, 14000, Caen, France
    316 rdf:type schema:Organization
     




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


    ...