Evaluation of image quality with four positron emitters and three preclinical PET/CT systems View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-12-10

AUTHORS

Jarmo Teuho, Leon Riehakainen, Aake Honkaniemi, Olli Moisio, Chunlei Han, Marko Tirri, Shihao Liu, Tove J. Grönroos, Jie Liu, Lin Wan, Xiao Liang, Yiqing Ling, Yuexuan Hua, Anne Roivainen, Juhani Knuuti, Qingguo Xie, Mika Teräs, Nicola D’Ascenzo, Riku Klén

ABSTRACT

BackgroundWe investigated the image quality of 11C, 68Ga, 18F and 89Zr, which have different positron fractions, physical half-lifes and positron ranges. Three small animal positron emission tomography/computed tomography (PET/CT) systems were used in the evaluation, including the Siemens Inveon, RAYCAN X5 and Molecubes β-cube. The evaluation was performed on a single scanner level using the national electrical manufacturers association (NEMA) image quality phantom and analysis protocol. Acquisitions were performed with the standard NEMA protocol for 18F and using a radionuclide-specific acquisition time for 11C, 68Ga and 89Zr. Images were assessed using percent recovery coefficient (%RC), percentage standard deviation (%STD), image uniformity (%SD), spill-over ratio (SOR) and evaluation of image quantification. Results68Ga had the lowest %RC (< 62%) across all systems. 18F had the highest maximum %RC (> 85%) and lowest %STD for the 5 mm rod across all systems. For 11C and 89Zr, the maximum %RC was close (> 76%) to the %RC with 18F. A larger SOR were measured in water with 11C and 68Ga compared to 18F on all systems. SOR in air reflected image reconstruction and data correction performance. Large variation in image quantification was observed, with maximal errors of 22.73% (89Zr, Inveon), 17.54% (89Zr, RAYCAN) and − 14.87% (68Ga, Molecubes).ConclusionsThe systems performed most optimal in terms of NEMA image quality parameters when using 18F, where 11C and 89Zr performed slightly worse than 18F. The performance was least optimal when using 68Ga, due to large positron range. The large quantification differences prompt optimization not only by terms of image quality but also quantification. Further investigation should be performed to find an appropriate calibration and harmonization protocol and the evaluation should be conducted on a multi-scanner and multi-center level. More... »

PAGES

155

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13550-020-00724-z

DOI

http://dx.doi.org/10.1186/s13550-020-00724-z

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1133379538

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/33301074


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/2008/1101", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical Biochemistry and Metabolomics", 
        "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"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, Turku University Hospital, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland", 
            "Turku PET Centre, Turku University Hospital, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Teuho", 
        "givenName": "Jarmo", 
        "id": "sg:person.01300017613.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01300017613.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Riehakainen", 
        "givenName": "Leon", 
        "id": "sg:person.016373224145.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016373224145.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, Turku University Hospital, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, Turku University Hospital, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Honkaniemi", 
        "givenName": "Aake", 
        "id": "sg:person.07670152745.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07670152745.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Moisio", 
        "givenName": "Olli", 
        "id": "sg:person.016045676667.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016045676667.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, Turku University Hospital, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, Turku University Hospital, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Han", 
        "givenName": "Chunlei", 
        "id": "sg:person.01002717204.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01002717204.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biomedicine, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.1374.1", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland", 
            "Department of Biomedicine, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tirri", 
        "givenName": "Marko", 
        "id": "sg:person.01216532724.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01216532724.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "RaySolution Digital Medical Imaging Co., Ltd, Ezhou, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "RaySolution Digital Medical Imaging Co., Ltd, Ezhou, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Shihao", 
        "id": "sg:person.012343733421.60", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012343733421.60"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "MediCity Research Laboratory, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.1374.1", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland", 
            "MediCity Research Laboratory, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gr\u00f6nroos", 
        "givenName": "Tove J.", 
        "id": "sg:person.01102756462.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01102756462.43"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Jie", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Software Engineering, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Software Engineering, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wan", 
        "givenName": "Lin", 
        "id": "sg:person.011770630533.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011770630533.97"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liang", 
        "givenName": "Xiao", 
        "id": "sg:person.011641245025.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011641245025.59"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ling", 
        "givenName": "Yiqing", 
        "id": "sg:person.010243072715.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010243072715.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hua", 
        "givenName": "Yuexuan", 
        "id": "sg:person.014375144433.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014375144433.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku Center for Disease Modeling, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.1374.1", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland", 
            "Turku PET Centre, Turku University Hospital, Turku, Finland", 
            "Turku Center for Disease Modeling, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Roivainen", 
        "givenName": "Anne", 
        "id": "sg:person.01031503426.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01031503426.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, Turku University Hospital, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland", 
            "Turku PET Centre, Turku University Hospital, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Knuuti", 
        "givenName": "Juhani", 
        "id": "sg:person.01163336756.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163336756.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China", 
          "id": "http://www.grid.ac/institutes/grid.33199.31", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
            "Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy", 
            "Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xie", 
        "givenName": "Qingguo", 
        "id": "sg:person.01035755713.92", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035755713.92"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medical Physics, Turku University Hospital, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.410552.7", 
          "name": [
            "Department of Biomedicine, University of Turku, Turku, Finland", 
            "Department of Medical Physics, Turku University Hospital, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ter\u00e4s", 
        "givenName": "Mika", 
        "id": "sg:person.01101061462.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01101061462.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy", 
          "id": "http://www.grid.ac/institutes/grid.419543.e", 
          "name": [
            "School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People\u2019s Republic of China", 
            "Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "D\u2019Ascenzo", 
        "givenName": "Nicola", 
        "id": "sg:person.011656550073.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011656550073.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Turku PET Centre, University of Turku, Turku, Finland", 
          "id": "http://www.grid.ac/institutes/grid.470895.7", 
          "name": [
            "Turku PET Centre, University of Turku, Turku, Finland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kl\u00e9n", 
        "givenName": "Riku", 
        "id": "sg:person.014042715235.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014042715235.25"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11307-018-1161-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100479553", 
          "https://doi.org/10.1007/s11307-018-1161-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11307-017-1074-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084031017", 
          "https://doi.org/10.1007/s11307-017-1074-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40658-020-0279-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1125115007", 
          "https://doi.org/10.1186/s40658-020-0279-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11307-016-1035-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051007320", 
          "https://doi.org/10.1007/s11307-016-1035-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11307-017-1126-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092066418", 
          "https://doi.org/10.1007/s11307-017-1126-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s40658-016-0144-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036370547", 
          "https://doi.org/10.1186/s40658-016-0144-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11307-016-1012-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031574709", 
          "https://doi.org/10.1007/s11307-016-1012-3"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2020-12-10", 
    "datePublishedReg": "2020-12-10", 
    "description": "BackgroundWe investigated the image quality of 11C, 68Ga, 18F and 89Zr, which have different positron fractions, physical half-lifes and positron ranges. Three small animal positron emission tomography/computed tomography (PET/CT) systems were used in the evaluation, including the Siemens Inveon, RAYCAN X5 and Molecubes \u03b2-cube. The evaluation was performed on a single scanner level using the national electrical manufacturers association (NEMA) image quality phantom and analysis protocol. Acquisitions were performed with the standard NEMA protocol for 18F and using a radionuclide-specific acquisition time for 11C, 68Ga and 89Zr. Images were assessed using percent recovery coefficient (%RC), percentage standard deviation (%STD), image uniformity (%SD), spill-over ratio (SOR) and evaluation of image quantification.\nResults68Ga had the lowest %RC (<\u200962%) across all systems. 18F had the highest maximum %RC (>\u200985%) and lowest %STD for the 5\u00a0mm rod across all systems. For 11C and 89Zr, the maximum %RC was close (>\u200976%) to the %RC with 18F. A larger SOR were measured in water with 11C and 68Ga compared to 18F on all systems. SOR in air reflected image reconstruction and data correction performance. Large variation in image quantification was observed, with maximal errors of 22.73% (89Zr, Inveon), 17.54% (89Zr, RAYCAN) and \u2212\u200914.87% (68Ga, Molecubes).ConclusionsThe systems performed most optimal in terms of NEMA image quality parameters when using 18F, where 11C and 89Zr performed slightly worse than 18F. The performance was least optimal when using 68Ga, due to large positron range. The large quantification differences prompt optimization not only by terms of image quality but also quantification. Further investigation should be performed to find an appropriate calibration and harmonization protocol and the evaluation should be conducted on a multi-scanner and multi-center level.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s13550-020-00724-z", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1045165", 
        "issn": [
          "2191-219X"
        ], 
        "name": "EJNMMI Research", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "10"
      }
    ], 
    "keywords": [
      "image quality", 
      "tomography system", 
      "recovery coefficient", 
      "image uniformity", 
      "ConclusionsThe system", 
      "appropriate calibration", 
      "maximal error", 
      "image reconstruction", 
      "image quality phantom", 
      "RC", 
      "performance", 
      "quality parameters", 
      "acquisition time", 
      "system", 
      "correction performance", 
      "image quality parameters", 
      "National Electrical Manufacturers Association image-quality phantom", 
      "air", 
      "uniformity", 
      "percentage standard deviation", 
      "large positron range", 
      "emitters", 
      "NEMA protocol", 
      "standard deviation", 
      "optimization", 
      "calibration", 
      "rods", 
      "water", 
      "large variation", 
      "coefficient", 
      "image quantification", 
      "phantom", 
      "CT system", 
      "parameters", 
      "spill", 
      "SOR", 
      "error", 
      "quantification", 
      "quality", 
      "range", 
      "ratio", 
      "terms", 
      "evaluation", 
      "investigation", 
      "deviation", 
      "analysis protocol", 
      "fraction", 
      "images", 
      "variation", 
      "time", 
      "reconstruction", 
      "positron range", 
      "harmonization protocol", 
      "PET/CT system", 
      "acquisition", 
      "protocol", 
      "further investigation", 
      "levels", 
      "Inveon", 
      "STDs", 
      "positron emitters", 
      "X5", 
      "positrons", 
      "positron fraction", 
      "Siemens Inveon", 
      "positron emission tomography/", 
      "small-animal positron emission tomography/", 
      "emission tomography/", 
      "prompt optimization", 
      "multi-center level", 
      "tomography/", 
      "BackgroundWe"
    ], 
    "name": "Evaluation of image quality with four positron emitters and three preclinical PET/CT systems", 
    "pagination": "155", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1133379538"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13550-020-00724-z"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "33301074"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13550-020-00724-z", 
      "https://app.dimensions.ai/details/publication/pub.1133379538"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-10T10:28", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/article/article_869.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s13550-020-00724-z"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13550-020-00724-z'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13550-020-00724-z'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13550-020-00724-z'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13550-020-00724-z'


 

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

324 TRIPLES      22 PREDICATES      107 URIs      90 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13550-020-00724-z schema:about anzsrc-for:11
2 anzsrc-for:1101
3 anzsrc-for:1103
4 anzsrc-for:1112
5 schema:author Nc482468f306049a3b7ccc9fe6c65c130
6 schema:citation sg:pub.10.1007/s11307-016-1012-3
7 sg:pub.10.1007/s11307-016-1035-9
8 sg:pub.10.1007/s11307-017-1074-x
9 sg:pub.10.1007/s11307-017-1126-2
10 sg:pub.10.1007/s11307-018-1161-7
11 sg:pub.10.1186/s40658-016-0144-5
12 sg:pub.10.1186/s40658-020-0279-2
13 schema:datePublished 2020-12-10
14 schema:datePublishedReg 2020-12-10
15 schema:description BackgroundWe investigated the image quality of 11C, 68Ga, 18F and 89Zr, which have different positron fractions, physical half-lifes and positron ranges. Three small animal positron emission tomography/computed tomography (PET/CT) systems were used in the evaluation, including the Siemens Inveon, RAYCAN X5 and Molecubes β-cube. The evaluation was performed on a single scanner level using the national electrical manufacturers association (NEMA) image quality phantom and analysis protocol. Acquisitions were performed with the standard NEMA protocol for 18F and using a radionuclide-specific acquisition time for 11C, 68Ga and 89Zr. Images were assessed using percent recovery coefficient (%RC), percentage standard deviation (%STD), image uniformity (%SD), spill-over ratio (SOR) and evaluation of image quantification. Results68Ga had the lowest %RC (< 62%) across all systems. 18F had the highest maximum %RC (> 85%) and lowest %STD for the 5 mm rod across all systems. For 11C and 89Zr, the maximum %RC was close (> 76%) to the %RC with 18F. A larger SOR were measured in water with 11C and 68Ga compared to 18F on all systems. SOR in air reflected image reconstruction and data correction performance. Large variation in image quantification was observed, with maximal errors of 22.73% (89Zr, Inveon), 17.54% (89Zr, RAYCAN) and − 14.87% (68Ga, Molecubes).ConclusionsThe systems performed most optimal in terms of NEMA image quality parameters when using 18F, where 11C and 89Zr performed slightly worse than 18F. The performance was least optimal when using 68Ga, due to large positron range. The large quantification differences prompt optimization not only by terms of image quality but also quantification. Further investigation should be performed to find an appropriate calibration and harmonization protocol and the evaluation should be conducted on a multi-scanner and multi-center level.
16 schema:genre article
17 schema:inLanguage en
18 schema:isAccessibleForFree true
19 schema:isPartOf N4b189f7fc818452a85c61f05313ddf80
20 Nd081b437c7404228aca6147dbc3eb906
21 sg:journal.1045165
22 schema:keywords BackgroundWe
23 CT system
24 ConclusionsThe system
25 Inveon
26 NEMA protocol
27 National Electrical Manufacturers Association image-quality phantom
28 PET/CT system
29 RC
30 SOR
31 STDs
32 Siemens Inveon
33 X5
34 acquisition
35 acquisition time
36 air
37 analysis protocol
38 appropriate calibration
39 calibration
40 coefficient
41 correction performance
42 deviation
43 emission tomography/
44 emitters
45 error
46 evaluation
47 fraction
48 further investigation
49 harmonization protocol
50 image quality
51 image quality parameters
52 image quality phantom
53 image quantification
54 image reconstruction
55 image uniformity
56 images
57 investigation
58 large positron range
59 large variation
60 levels
61 maximal error
62 multi-center level
63 optimization
64 parameters
65 percentage standard deviation
66 performance
67 phantom
68 positron emission tomography/
69 positron emitters
70 positron fraction
71 positron range
72 positrons
73 prompt optimization
74 protocol
75 quality
76 quality parameters
77 quantification
78 range
79 ratio
80 reconstruction
81 recovery coefficient
82 rods
83 small-animal positron emission tomography/
84 spill
85 standard deviation
86 system
87 terms
88 time
89 tomography system
90 tomography/
91 uniformity
92 variation
93 water
94 schema:name Evaluation of image quality with four positron emitters and three preclinical PET/CT systems
95 schema:pagination 155
96 schema:productId N59e2722b10e74b7798f95b7883877807
97 N5c50f1459ee04e6582b5c1542d075a9f
98 Na8479f4c33ed47fb8b06bbe745a102a6
99 schema:sameAs https://app.dimensions.ai/details/publication/pub.1133379538
100 https://doi.org/10.1186/s13550-020-00724-z
101 schema:sdDatePublished 2022-05-10T10:28
102 schema:sdLicense https://scigraph.springernature.com/explorer/license/
103 schema:sdPublisher N98e5a07aa716499b904923a6851eec54
104 schema:url https://doi.org/10.1186/s13550-020-00724-z
105 sgo:license sg:explorer/license/
106 sgo:sdDataset articles
107 rdf:type schema:ScholarlyArticle
108 N13fcf0b680f347b8893708738feadf09 rdf:first sg:person.010243072715.25
109 rdf:rest Nbd8294c8e9d04a058173ebf6be5f6fea
110 N18c94e46e2f34afca1e6611d1c8832c0 rdf:first sg:person.012343733421.60
111 rdf:rest N669b0c9f5b9845b49ba460521429d4a4
112 N27f48bc4acbb4ff293f07390a27a4a77 rdf:first sg:person.01031503426.04
113 rdf:rest Na6c8ca3aaf1c4e7fb19058476a46277f
114 N28a3feb43bcc4e02939b0fb2553c0b70 rdf:first sg:person.016045676667.81
115 rdf:rest N8cda1f2b2a11476984e9e1a32241ebf4
116 N4b189f7fc818452a85c61f05313ddf80 schema:volumeNumber 10
117 rdf:type schema:PublicationVolume
118 N59e2722b10e74b7798f95b7883877807 schema:name pubmed_id
119 schema:value 33301074
120 rdf:type schema:PropertyValue
121 N5c50f1459ee04e6582b5c1542d075a9f schema:name doi
122 schema:value 10.1186/s13550-020-00724-z
123 rdf:type schema:PropertyValue
124 N669b0c9f5b9845b49ba460521429d4a4 rdf:first sg:person.01102756462.43
125 rdf:rest Nb5c9a845fe244f548b4defb881c5b412
126 N66cfb5f2a36e40e9a1a91bfe3ea685a2 rdf:first sg:person.01035755713.92
127 rdf:rest Nb1204019ef9f49b1b3ad69963672359c
128 N7784f1f4e627472cb1b19968559a7e7e rdf:first sg:person.014042715235.25
129 rdf:rest rdf:nil
130 N8cda1f2b2a11476984e9e1a32241ebf4 rdf:first sg:person.01002717204.50
131 rdf:rest Na74251a4e9f04aeeb768e269c2b231a0
132 N98e5a07aa716499b904923a6851eec54 schema:name Springer Nature - SN SciGraph project
133 rdf:type schema:Organization
134 Na07616851112425da175640cbd380652 rdf:first sg:person.011641245025.59
135 rdf:rest N13fcf0b680f347b8893708738feadf09
136 Na6c8ca3aaf1c4e7fb19058476a46277f rdf:first sg:person.01163336756.79
137 rdf:rest N66cfb5f2a36e40e9a1a91bfe3ea685a2
138 Na74251a4e9f04aeeb768e269c2b231a0 rdf:first sg:person.01216532724.70
139 rdf:rest N18c94e46e2f34afca1e6611d1c8832c0
140 Na8479f4c33ed47fb8b06bbe745a102a6 schema:name dimensions_id
141 schema:value pub.1133379538
142 rdf:type schema:PropertyValue
143 Naa88af5a60594b14aba7c804db7d6996 rdf:first sg:person.011656550073.46
144 rdf:rest N7784f1f4e627472cb1b19968559a7e7e
145 Nab1d18f0f27141479130e58ddc689a58 rdf:first sg:person.016373224145.58
146 rdf:rest Nb947040d21e54a8480e915724d348560
147 Nb1204019ef9f49b1b3ad69963672359c rdf:first sg:person.01101061462.02
148 rdf:rest Naa88af5a60594b14aba7c804db7d6996
149 Nb5c9a845fe244f548b4defb881c5b412 rdf:first Ncdcf5781849b451794a75eb98be1d633
150 rdf:rest Nb904ce3fd2fe4edfabf0d873e7a0c528
151 Nb904ce3fd2fe4edfabf0d873e7a0c528 rdf:first sg:person.011770630533.97
152 rdf:rest Na07616851112425da175640cbd380652
153 Nb947040d21e54a8480e915724d348560 rdf:first sg:person.07670152745.46
154 rdf:rest N28a3feb43bcc4e02939b0fb2553c0b70
155 Nbd8294c8e9d04a058173ebf6be5f6fea rdf:first sg:person.014375144433.24
156 rdf:rest N27f48bc4acbb4ff293f07390a27a4a77
157 Nc482468f306049a3b7ccc9fe6c65c130 rdf:first sg:person.01300017613.20
158 rdf:rest Nab1d18f0f27141479130e58ddc689a58
159 Ncdcf5781849b451794a75eb98be1d633 schema:affiliation grid-institutes:grid.33199.31
160 schema:familyName Liu
161 schema:givenName Jie
162 rdf:type schema:Person
163 Nd081b437c7404228aca6147dbc3eb906 schema:issueNumber 1
164 rdf:type schema:PublicationIssue
165 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
166 schema:name Medical and Health Sciences
167 rdf:type schema:DefinedTerm
168 anzsrc-for:1101 schema:inDefinedTermSet anzsrc-for:
169 schema:name Medical Biochemistry and Metabolomics
170 rdf:type schema:DefinedTerm
171 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
172 schema:name Clinical Sciences
173 rdf:type schema:DefinedTerm
174 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
175 schema:name Oncology and Carcinogenesis
176 rdf:type schema:DefinedTerm
177 sg:journal.1045165 schema:issn 2191-219X
178 schema:name EJNMMI Research
179 schema:publisher Springer Nature
180 rdf:type schema:Periodical
181 sg:person.01002717204.50 schema:affiliation grid-institutes:grid.470895.7
182 schema:familyName Han
183 schema:givenName Chunlei
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01002717204.50
185 rdf:type schema:Person
186 sg:person.010243072715.25 schema:affiliation grid-institutes:grid.33199.31
187 schema:familyName Ling
188 schema:givenName Yiqing
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010243072715.25
190 rdf:type schema:Person
191 sg:person.01031503426.04 schema:affiliation grid-institutes:grid.1374.1
192 schema:familyName Roivainen
193 schema:givenName Anne
194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01031503426.04
195 rdf:type schema:Person
196 sg:person.01035755713.92 schema:affiliation grid-institutes:grid.33199.31
197 schema:familyName Xie
198 schema:givenName Qingguo
199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035755713.92
200 rdf:type schema:Person
201 sg:person.01101061462.02 schema:affiliation grid-institutes:grid.410552.7
202 schema:familyName Teräs
203 schema:givenName Mika
204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01101061462.02
205 rdf:type schema:Person
206 sg:person.01102756462.43 schema:affiliation grid-institutes:grid.1374.1
207 schema:familyName Grönroos
208 schema:givenName Tove J.
209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01102756462.43
210 rdf:type schema:Person
211 sg:person.01163336756.79 schema:affiliation grid-institutes:grid.470895.7
212 schema:familyName Knuuti
213 schema:givenName Juhani
214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163336756.79
215 rdf:type schema:Person
216 sg:person.011641245025.59 schema:affiliation grid-institutes:grid.33199.31
217 schema:familyName Liang
218 schema:givenName Xiao
219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011641245025.59
220 rdf:type schema:Person
221 sg:person.011656550073.46 schema:affiliation grid-institutes:grid.419543.e
222 schema:familyName D’Ascenzo
223 schema:givenName Nicola
224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011656550073.46
225 rdf:type schema:Person
226 sg:person.011770630533.97 schema:affiliation grid-institutes:grid.33199.31
227 schema:familyName Wan
228 schema:givenName Lin
229 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011770630533.97
230 rdf:type schema:Person
231 sg:person.01216532724.70 schema:affiliation grid-institutes:grid.1374.1
232 schema:familyName Tirri
233 schema:givenName Marko
234 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01216532724.70
235 rdf:type schema:Person
236 sg:person.012343733421.60 schema:affiliation grid-institutes:None
237 schema:familyName Liu
238 schema:givenName Shihao
239 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012343733421.60
240 rdf:type schema:Person
241 sg:person.01300017613.20 schema:affiliation grid-institutes:grid.470895.7
242 schema:familyName Teuho
243 schema:givenName Jarmo
244 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01300017613.20
245 rdf:type schema:Person
246 sg:person.014042715235.25 schema:affiliation grid-institutes:grid.470895.7
247 schema:familyName Klén
248 schema:givenName Riku
249 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014042715235.25
250 rdf:type schema:Person
251 sg:person.014375144433.24 schema:affiliation grid-institutes:grid.33199.31
252 schema:familyName Hua
253 schema:givenName Yuexuan
254 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014375144433.24
255 rdf:type schema:Person
256 sg:person.016045676667.81 schema:affiliation grid-institutes:grid.470895.7
257 schema:familyName Moisio
258 schema:givenName Olli
259 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016045676667.81
260 rdf:type schema:Person
261 sg:person.016373224145.58 schema:affiliation grid-institutes:grid.470895.7
262 schema:familyName Riehakainen
263 schema:givenName Leon
264 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016373224145.58
265 rdf:type schema:Person
266 sg:person.07670152745.46 schema:affiliation grid-institutes:grid.470895.7
267 schema:familyName Honkaniemi
268 schema:givenName Aake
269 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07670152745.46
270 rdf:type schema:Person
271 sg:pub.10.1007/s11307-016-1012-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031574709
272 https://doi.org/10.1007/s11307-016-1012-3
273 rdf:type schema:CreativeWork
274 sg:pub.10.1007/s11307-016-1035-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051007320
275 https://doi.org/10.1007/s11307-016-1035-9
276 rdf:type schema:CreativeWork
277 sg:pub.10.1007/s11307-017-1074-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1084031017
278 https://doi.org/10.1007/s11307-017-1074-x
279 rdf:type schema:CreativeWork
280 sg:pub.10.1007/s11307-017-1126-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092066418
281 https://doi.org/10.1007/s11307-017-1126-2
282 rdf:type schema:CreativeWork
283 sg:pub.10.1007/s11307-018-1161-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100479553
284 https://doi.org/10.1007/s11307-018-1161-7
285 rdf:type schema:CreativeWork
286 sg:pub.10.1186/s40658-016-0144-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036370547
287 https://doi.org/10.1186/s40658-016-0144-5
288 rdf:type schema:CreativeWork
289 sg:pub.10.1186/s40658-020-0279-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1125115007
290 https://doi.org/10.1186/s40658-020-0279-2
291 rdf:type schema:CreativeWork
292 grid-institutes:None schema:alternateName RaySolution Digital Medical Imaging Co., Ltd, Ezhou, People’s Republic of China
293 schema:name RaySolution Digital Medical Imaging Co., Ltd, Ezhou, People’s Republic of China
294 rdf:type schema:Organization
295 grid-institutes:grid.1374.1 schema:alternateName Department of Biomedicine, University of Turku, Turku, Finland
296 MediCity Research Laboratory, University of Turku, Turku, Finland
297 Turku Center for Disease Modeling, University of Turku, Turku, Finland
298 schema:name Department of Biomedicine, University of Turku, Turku, Finland
299 MediCity Research Laboratory, University of Turku, Turku, Finland
300 Turku Center for Disease Modeling, University of Turku, Turku, Finland
301 Turku PET Centre, Turku University Hospital, Turku, Finland
302 Turku PET Centre, University of Turku, Turku, Finland
303 rdf:type schema:Organization
304 grid-institutes:grid.33199.31 schema:alternateName School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
305 School of Software Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
306 Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
307 schema:name Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy
308 School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
309 School of Software Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
310 Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China
311 rdf:type schema:Organization
312 grid-institutes:grid.410552.7 schema:alternateName Department of Medical Physics, Turku University Hospital, Turku, Finland
313 schema:name Department of Biomedicine, University of Turku, Turku, Finland
314 Department of Medical Physics, Turku University Hospital, Turku, Finland
315 rdf:type schema:Organization
316 grid-institutes:grid.419543.e schema:alternateName Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy
317 schema:name Department of Medical Physics and Engineering, Istituto Neurologico Mediterraneo NEUROMED I.R.C.C.S., Pozzilli, Italy
318 School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, People’s Republic of China
319 rdf:type schema:Organization
320 grid-institutes:grid.470895.7 schema:alternateName Turku PET Centre, Turku University Hospital, Turku, Finland
321 Turku PET Centre, University of Turku, Turku, Finland
322 schema:name Turku PET Centre, Turku University Hospital, Turku, Finland
323 Turku PET Centre, University of Turku, Turku, Finland
324 rdf:type schema:Organization
 




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


...