Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-01-18

AUTHORS

V. Camus, P. Payoux, L. Barré, B. Desgranges, T. Voisin, C. Tauber, R. La Joie, M. Tafani, C. Hommet, G. Chételat, K. Mondon, V. de La Sayette, J. P. Cottier, E. Beaufils, M. J. Ribeiro, V. Gissot, E. Vierron, J. Vercouillie, B. Vellas, F. Eustache, D. Guilloteau

ABSTRACT

PURPOSE: Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer's disease (AD). The aim of this study was to test the feasibility of using PET imaging with (18)F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC). METHODS: In this study, 46 subjects (20 men and 26 women, mean age of 69.0 ± 7.6 years), including 13 with AD, 12 with MCI and 21 HC subjects, were enrolled from three academic memory clinics. PET images were acquired over a 10-min period 50 min after injection of florbetapir (mean ± SD of radioactivity injected, 259 ± 57 MBq). PET images were assessed visually by two individuals blinded to any clinical information and quantitatively via the standard uptake value ratio (SUVr) in the specific regions of interest, which were defined in relation to the cerebellum as the reference region. RESULTS: The mean values of SUVr were higher in AD patients (median 1.20, Q1-Q3 1.16-1.30) than in HC subjects (median 1.05, Q1-Q3 1.04-1.08; p = 0.0001) in the overall cortex and all cortical regions (precuneus, anterior and posterior cingulate, and frontal median, temporal, parietal and occipital cortex). The MCI subjects also showed a higher uptake of florbetapir in the posterior cingulate cortex (median 1.06, Q1-Q3 0.97-1.28) compared with HC subjects (median 0.95, Q1-Q3 0.82-1.02; p = 0.03). Qualitative visual assessment of the PET scans showed a sensitivity of 84.6% (95% CI 0.55-0.98) and a specificity of 38.1% (95% CI 0.18-0.62) for discriminating AD patients from HC subjects; however, the quantitative assessment of the global cortex SUVr showed a sensitivity of 92.3% and specificity of 90.5% with a cut-off value of 1.122 (area under the curve 0.894). CONCLUSION: These preliminary results suggest that PET with florbetapir is a safe and suitable biomarker for AD that can be used routinely in a clinical environment. However, the low specificity of the visual PET scan assessment could be improved by the use of specific training and automatic or semiautomatic quantification tools. More... »

PAGES

621-631

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00259-011-2021-8

DOI

http://dx.doi.org/10.1007/s00259-011-2021-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028393977

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22252372


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"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1109", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Neurosciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Alzheimer Disease", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Amyloid", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aniline Compounds", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Brain", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cognitive Dysfunction", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ethylene Glycols", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Follow-Up Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Positron-Emission Tomography", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Camus", 
        "givenName": "V.", 
        "id": "sg:person.0646041431.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646041431.26"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Toulouse, Toulouse, France", 
          "id": "http://www.grid.ac/institutes/grid.411175.7", 
          "name": [
            "INSERM U825, Toulouse, France", 
            "Universit\u00e9 Paul Sabatier de Toulouse, Toulouse, France", 
            "CHRU de Toulouse, Toulouse, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Payoux", 
        "givenName": "P.", 
        "id": "sg:person.01232301242.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01232301242.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 de Caen Basse Normandie, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.412043.0", 
          "name": [
            "Groupe de D\u00e9veloppements M\u00e9thodologiques en Tomographie par \u00c9mission de Positons, CEA/DSV/I2BM/CI-NAPS UMR6232, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Barr\u00e9", 
        "givenName": "L.", 
        "id": "sg:person.01163622361.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163622361.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.424469.9", 
          "name": [
            "INSERM U1077, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie - UMR-S1077, Caen, France", 
            "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Desgranges", 
        "givenName": "B.", 
        "id": "sg:person.0612107402.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0612107402.12"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Toulouse, Toulouse, France", 
          "id": "http://www.grid.ac/institutes/grid.411175.7", 
          "name": [
            "Universit\u00e9 Paul Sabatier de Toulouse, Toulouse, France", 
            "INSERM U1027, Toulouse, France", 
            "CHRU de Toulouse, Toulouse, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Voisin", 
        "givenName": "T.", 
        "id": "sg:person.0732206121.71", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0732206121.71"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tauber", 
        "givenName": "C.", 
        "id": "sg:person.01137731214.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01137731214.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.424469.9", 
          "name": [
            "INSERM U1077, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie - UMR-S1077, Caen, France", 
            "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "La Joie", 
        "givenName": "R.", 
        "id": "sg:person.0763705171.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0763705171.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Toulouse, Toulouse, France", 
          "id": "http://www.grid.ac/institutes/grid.411175.7", 
          "name": [
            "INSERM U825, Toulouse, France", 
            "Universit\u00e9 Paul Sabatier de Toulouse, Toulouse, France", 
            "CHRU de Toulouse, Toulouse, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tafani", 
        "givenName": "M.", 
        "id": "sg:person.0764654235.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764654235.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hommet", 
        "givenName": "C.", 
        "id": "sg:person.0747242265.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0747242265.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.424469.9", 
          "name": [
            "INSERM U1077, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie - UMR-S1077, Caen, France", 
            "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ch\u00e9telat", 
        "givenName": "G.", 
        "id": "sg:person.0752327220.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752327220.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mondon", 
        "givenName": "K.", 
        "id": "sg:person.01131235164.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131235164.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.424469.9", 
          "name": [
            "INSERM U1077, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie - UMR-S1077, Caen, France", 
            "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "de La Sayette", 
        "givenName": "V.", 
        "id": "sg:person.01006042373.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006042373.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cottier", 
        "givenName": "J. P.", 
        "id": "sg:person.013003554244.49", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013003554244.49"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Beaufils", 
        "givenName": "E.", 
        "id": "sg:person.01310304565.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01310304565.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ribeiro", 
        "givenName": "M. J.", 
        "id": "sg:person.07430111442.39", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07430111442.39"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "CIC-IT /CIC INSERM 202, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gissot", 
        "givenName": "V.", 
        "id": "sg:person.01102531312.74", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01102531312.74"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.12366.30", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vierron", 
        "givenName": "E.", 
        "id": "sg:person.01262066651.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262066651.41"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vercouillie", 
        "givenName": "J.", 
        "id": "sg:person.01177240627.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01177240627.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Toulouse, Toulouse, France", 
          "id": "http://www.grid.ac/institutes/grid.411175.7", 
          "name": [
            "Universit\u00e9 Paul Sabatier de Toulouse, Toulouse, France", 
            "INSERM U1027, Toulouse, France", 
            "CHRU de Toulouse, Toulouse, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Vellas", 
        "givenName": "B.", 
        "id": "sg:person.0772176346.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0772176346.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France", 
          "id": "http://www.grid.ac/institutes/grid.424469.9", 
          "name": [
            "INSERM U1077, Caen, France", 
            "Universit\u00e9 de Caen Basse Normandie - UMR-S1077, Caen, France", 
            "Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Eustache", 
        "givenName": "F.", 
        "id": "sg:person.01317232620.94", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317232620.94"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "CHRU de Tours, Tours, France", 
          "id": "http://www.grid.ac/institutes/grid.411167.4", 
          "name": [
            "UMR INSERM U930-CNRS ERL 3106, Tours, France", 
            "Universit\u00e9 Fran\u00e7ois Rabelais de Tours, Tours, France", 
            "CIC-IT /CIC INSERM 202, Tours, France", 
            "CHRU de Tours, Tours, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guilloteau", 
        "givenName": "D.", 
        "id": "sg:person.0622454377.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0622454377.26"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00415-009-5396-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017021844", 
          "https://doi.org/10.1007/s00415-009-5396-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00702-011-0641-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002397631", 
          "https://doi.org/10.1007/s00702-011-0641-6"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012-01-18", 
    "datePublishedReg": "2012-01-18", 
    "description": "PURPOSE: Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer's disease (AD). The aim of this study was to test the feasibility of using PET imaging with (18)F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC).\nMETHODS: In this study, 46 subjects (20 men and 26 women, mean age of 69.0 \u00b1 7.6 years), including 13 with AD, 12 with MCI and 21 HC subjects, were enrolled from three academic memory clinics. PET images were acquired over a 10-min period 50 min after injection of florbetapir (mean \u00b1 SD of radioactivity injected, 259 \u00b1 57 MBq). PET images were assessed visually by two individuals blinded to any clinical information and quantitatively via the standard uptake value ratio (SUVr) in the specific regions of interest, which were defined in relation to the cerebellum as the reference region.\nRESULTS: The mean values of SUVr were higher in AD patients (median 1.20, Q1-Q3 1.16-1.30) than in HC subjects (median 1.05, Q1-Q3 1.04-1.08; p = 0.0001) in the overall cortex and all cortical regions (precuneus, anterior and posterior cingulate, and frontal median, temporal, parietal and occipital cortex). The MCI subjects also showed a higher uptake of florbetapir in the posterior cingulate cortex (median 1.06, Q1-Q3 0.97-1.28) compared with HC subjects (median 0.95, Q1-Q3 0.82-1.02; p = 0.03). Qualitative visual assessment of the PET scans showed a sensitivity of 84.6% (95% CI 0.55-0.98) and a specificity of 38.1% (95% CI 0.18-0.62) for discriminating AD patients from HC subjects; however, the quantitative assessment of the global cortex SUVr showed a sensitivity of 92.3% and specificity of 90.5% with a cut-off value of 1.122 (area under the curve 0.894).\nCONCLUSION: These preliminary results suggest that PET with florbetapir is a safe and suitable biomarker for AD that can be used routinely in a clinical environment. However, the low specificity of the visual PET scan assessment could be improved by the use of specific training and automatic or semiautomatic quantification tools.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00259-011-2021-8", 
    "inLanguage": "en", 
    "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": "4", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "39"
      }
    ], 
    "keywords": [
      "standard uptake value ratio", 
      "brain amyloid load", 
      "mild cognitive impairment", 
      "HC subjects", 
      "Alzheimer's disease", 
      "amyloid load", 
      "healthy controls", 
      "AD patients", 
      "academic memory clinic", 
      "normal healthy controls", 
      "uptake value ratio", 
      "clinical environment", 
      "positron emission tomography (PET) imaging", 
      "Emission Tomography Imaging", 
      "posterior cingulate cortex", 
      "overall cortex", 
      "scan assessment", 
      "memory clinic", 
      "core biomarkers", 
      "clinical information", 
      "PET scans", 
      "AV-45", 
      "cognitive impairment", 
      "PET images", 
      "MCI subjects", 
      "cingulate cortex", 
      "routine clinical environment", 
      "cortical regions", 
      "patients", 
      "suitable biomarkers", 
      "tomography imaging", 
      "florbetapir", 
      "low specificity", 
      "high uptake", 
      "cortex", 
      "disease", 
      "reference region", 
      "subjects", 
      "biomarkers", 
      "specific training", 
      "visual assessment", 
      "PET", 
      "specificity", 
      "value ratio", 
      "assessment", 
      "mean value", 
      "clinic", 
      "quantitative assessment", 
      "cerebellum", 
      "impairment", 
      "scans", 
      "injection", 
      "study", 
      "sensitivity", 
      "imaging", 
      "preliminary results", 
      "specific regions", 
      "aim", 
      "min", 
      "uptake", 
      "individuals", 
      "control", 
      "training", 
      "quantification tool", 
      "use", 
      "region", 
      "values", 
      "feasibility", 
      "ratio", 
      "results", 
      "information", 
      "tool", 
      "load", 
      "relation", 
      "images", 
      "interest", 
      "environment", 
      "period 50 min", 
      "injection of florbetapir", 
      "global cortex SUVr", 
      "cortex SUVr", 
      "visual PET scan assessment", 
      "PET scan assessment", 
      "semiautomatic quantification tools"
    ], 
    "name": "Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment", 
    "pagination": "621-631", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1028393977"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00259-011-2021-8"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22252372"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00259-011-2021-8", 
      "https://app.dimensions.ai/details/publication/pub.1028393977"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-12-01T19:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/article/article_564.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00259-011-2021-8"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-2021-8'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-2021-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-2021-8'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00259-011-2021-8'


 

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

368 TRIPLES      22 PREDICATES      125 URIs      114 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00259-011-2021-8 schema:about N13a499cab7e74057821ae6cfd630d125
2 N19abdd9e34cf4f32a9dc71aa03ee4588
3 N2257f229d95741819a36d61460f61805
4 N228ae5d517ad451bb62fe7229465782b
5 N2880785faaaf44dd9728b309c05f0248
6 N29b958ac5a284a698f17f5bfb14371d3
7 N5925ed710831488c985b3291e05d9989
8 N7c3eeca0b7dc4099ad99fe8490b7eabb
9 N7fe799e5feb6418facd82216893e926c
10 N88769aa00bae4604af87494f6b75d7c8
11 Nad8f1dc7654e480ca3567cb419295356
12 Nd2c6456b1e7a478dac6317a026c61830
13 anzsrc-for:11
14 anzsrc-for:1103
15 anzsrc-for:1109
16 schema:author N94b209c4b185414981921808414a308b
17 schema:citation sg:pub.10.1007/s00415-009-5396-8
18 sg:pub.10.1007/s00702-011-0641-6
19 schema:datePublished 2012-01-18
20 schema:datePublishedReg 2012-01-18
21 schema:description PURPOSE: Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer's disease (AD). The aim of this study was to test the feasibility of using PET imaging with (18)F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC). METHODS: In this study, 46 subjects (20 men and 26 women, mean age of 69.0 ± 7.6 years), including 13 with AD, 12 with MCI and 21 HC subjects, were enrolled from three academic memory clinics. PET images were acquired over a 10-min period 50 min after injection of florbetapir (mean ± SD of radioactivity injected, 259 ± 57 MBq). PET images were assessed visually by two individuals blinded to any clinical information and quantitatively via the standard uptake value ratio (SUVr) in the specific regions of interest, which were defined in relation to the cerebellum as the reference region. RESULTS: The mean values of SUVr were higher in AD patients (median 1.20, Q1-Q3 1.16-1.30) than in HC subjects (median 1.05, Q1-Q3 1.04-1.08; p = 0.0001) in the overall cortex and all cortical regions (precuneus, anterior and posterior cingulate, and frontal median, temporal, parietal and occipital cortex). The MCI subjects also showed a higher uptake of florbetapir in the posterior cingulate cortex (median 1.06, Q1-Q3 0.97-1.28) compared with HC subjects (median 0.95, Q1-Q3 0.82-1.02; p = 0.03). Qualitative visual assessment of the PET scans showed a sensitivity of 84.6% (95% CI 0.55-0.98) and a specificity of 38.1% (95% CI 0.18-0.62) for discriminating AD patients from HC subjects; however, the quantitative assessment of the global cortex SUVr showed a sensitivity of 92.3% and specificity of 90.5% with a cut-off value of 1.122 (area under the curve 0.894). CONCLUSION: These preliminary results suggest that PET with florbetapir is a safe and suitable biomarker for AD that can be used routinely in a clinical environment. However, the low specificity of the visual PET scan assessment could be improved by the use of specific training and automatic or semiautomatic quantification tools.
22 schema:genre article
23 schema:inLanguage en
24 schema:isAccessibleForFree true
25 schema:isPartOf N03b46f5822064caca792e2b9df1c5b0d
26 Nc041d9e043374bbc84c173dd055a337c
27 sg:journal.1297401
28 schema:keywords AD patients
29 AV-45
30 Alzheimer's disease
31 Emission Tomography Imaging
32 HC subjects
33 MCI subjects
34 PET
35 PET images
36 PET scan assessment
37 PET scans
38 academic memory clinic
39 aim
40 amyloid load
41 assessment
42 biomarkers
43 brain amyloid load
44 cerebellum
45 cingulate cortex
46 clinic
47 clinical environment
48 clinical information
49 cognitive impairment
50 control
51 core biomarkers
52 cortex
53 cortex SUVr
54 cortical regions
55 disease
56 environment
57 feasibility
58 florbetapir
59 global cortex SUVr
60 healthy controls
61 high uptake
62 images
63 imaging
64 impairment
65 individuals
66 information
67 injection
68 injection of florbetapir
69 interest
70 load
71 low specificity
72 mean value
73 memory clinic
74 mild cognitive impairment
75 min
76 normal healthy controls
77 overall cortex
78 patients
79 period 50 min
80 positron emission tomography (PET) imaging
81 posterior cingulate cortex
82 preliminary results
83 quantification tool
84 quantitative assessment
85 ratio
86 reference region
87 region
88 relation
89 results
90 routine clinical environment
91 scan assessment
92 scans
93 semiautomatic quantification tools
94 sensitivity
95 specific regions
96 specific training
97 specificity
98 standard uptake value ratio
99 study
100 subjects
101 suitable biomarkers
102 tomography imaging
103 tool
104 training
105 uptake
106 uptake value ratio
107 use
108 value ratio
109 values
110 visual PET scan assessment
111 visual assessment
112 schema:name Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment
113 schema:pagination 621-631
114 schema:productId N4a488954056741d48c4b8b19853976e0
115 N624cf20334e24c8381c5de1c5ba6ae58
116 Nd727370a13fa42f0b9f97341f9e20b4d
117 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028393977
118 https://doi.org/10.1007/s00259-011-2021-8
119 schema:sdDatePublished 2021-12-01T19:27
120 schema:sdLicense https://scigraph.springernature.com/explorer/license/
121 schema:sdPublisher Nb800de24e74f41bc893902fdc24e993d
122 schema:url https://doi.org/10.1007/s00259-011-2021-8
123 sgo:license sg:explorer/license/
124 sgo:sdDataset articles
125 rdf:type schema:ScholarlyArticle
126 N03b46f5822064caca792e2b9df1c5b0d schema:volumeNumber 39
127 rdf:type schema:PublicationVolume
128 N13a499cab7e74057821ae6cfd630d125 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name Ethylene Glycols
130 rdf:type schema:DefinedTerm
131 N161091e3512d424ba82b22aaafd403c0 rdf:first sg:person.0772176346.25
132 rdf:rest N661ebe3b47714feaa3735f01a3b4f9b9
133 N19abdd9e34cf4f32a9dc71aa03ee4588 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Positron-Emission Tomography
135 rdf:type schema:DefinedTerm
136 N220f9f2e502f4885b452136335a9f100 rdf:first sg:person.07430111442.39
137 rdf:rest Naf19e3226e6c46be90c2c48f800a8a93
138 N2257f229d95741819a36d61460f61805 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Follow-Up Studies
140 rdf:type schema:DefinedTerm
141 N228ae5d517ad451bb62fe7229465782b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Female
143 rdf:type schema:DefinedTerm
144 N2880785faaaf44dd9728b309c05f0248 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Aged
146 rdf:type schema:DefinedTerm
147 N29b958ac5a284a698f17f5bfb14371d3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Humans
149 rdf:type schema:DefinedTerm
150 N4a488954056741d48c4b8b19853976e0 schema:name pubmed_id
151 schema:value 22252372
152 rdf:type schema:PropertyValue
153 N4ad5b183c4ed41349b3e415cb36677de rdf:first sg:person.0612107402.12
154 rdf:rest N90a3b7aaf2864882b17d4b39b269eaeb
155 N4bb0b1cbbc8d44249fc00c99961413d0 rdf:first sg:person.01163622361.57
156 rdf:rest N4ad5b183c4ed41349b3e415cb36677de
157 N5925ed710831488c985b3291e05d9989 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Aniline Compounds
159 rdf:type schema:DefinedTerm
160 N624cf20334e24c8381c5de1c5ba6ae58 schema:name dimensions_id
161 schema:value pub.1028393977
162 rdf:type schema:PropertyValue
163 N661ebe3b47714feaa3735f01a3b4f9b9 rdf:first sg:person.01317232620.94
164 rdf:rest Nc2d29d3c1f2f43c398eedbffc1fddcef
165 N695b5fe7f54545f0ac68bf40346818e2 rdf:first sg:person.0764654235.57
166 rdf:rest Nb7c1f366045148e29d2e688e9596873b
167 N6cbf9750f7f2433e86a9dc7cc6d8526b rdf:first sg:person.01177240627.46
168 rdf:rest N161091e3512d424ba82b22aaafd403c0
169 N79107a6edf504ec597df59b741f5dda1 rdf:first sg:person.0763705171.27
170 rdf:rest N695b5fe7f54545f0ac68bf40346818e2
171 N7c3eeca0b7dc4099ad99fe8490b7eabb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
172 schema:name Cognitive Dysfunction
173 rdf:type schema:DefinedTerm
174 N7fe799e5feb6418facd82216893e926c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
175 schema:name Alzheimer Disease
176 rdf:type schema:DefinedTerm
177 N88769aa00bae4604af87494f6b75d7c8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
178 schema:name Brain
179 rdf:type schema:DefinedTerm
180 N8bffeb68b02b47649b97b3c6f0d04eef rdf:first sg:person.01137731214.01
181 rdf:rest N79107a6edf504ec597df59b741f5dda1
182 N90a3b7aaf2864882b17d4b39b269eaeb rdf:first sg:person.0732206121.71
183 rdf:rest N8bffeb68b02b47649b97b3c6f0d04eef
184 N94b209c4b185414981921808414a308b rdf:first sg:person.0646041431.26
185 rdf:rest Nfe07e0f3883a47d688fb1576d95cd25b
186 N9f6e4a66d13647ada467237056b451b1 rdf:first sg:person.01310304565.47
187 rdf:rest N220f9f2e502f4885b452136335a9f100
188 Nad8f1dc7654e480ca3567cb419295356 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
189 schema:name Male
190 rdf:type schema:DefinedTerm
191 Naf19e3226e6c46be90c2c48f800a8a93 rdf:first sg:person.01102531312.74
192 rdf:rest Nf72bcad96a8e4c90a578b61c3592dee3
193 Nb6b68f00186648daa4c6cec59b8c8997 rdf:first sg:person.01131235164.27
194 rdf:rest Nc186f370ef4f4f119dc72faba557fcb6
195 Nb7c1f366045148e29d2e688e9596873b rdf:first sg:person.0747242265.47
196 rdf:rest Nfe202564d3f74cd6a030e23e7ad810a1
197 Nb800de24e74f41bc893902fdc24e993d schema:name Springer Nature - SN SciGraph project
198 rdf:type schema:Organization
199 Nbcea37dede214df588061ebd414db5bd rdf:first sg:person.013003554244.49
200 rdf:rest N9f6e4a66d13647ada467237056b451b1
201 Nc041d9e043374bbc84c173dd055a337c schema:issueNumber 4
202 rdf:type schema:PublicationIssue
203 Nc186f370ef4f4f119dc72faba557fcb6 rdf:first sg:person.01006042373.50
204 rdf:rest Nbcea37dede214df588061ebd414db5bd
205 Nc2d29d3c1f2f43c398eedbffc1fddcef rdf:first sg:person.0622454377.26
206 rdf:rest rdf:nil
207 Nd2c6456b1e7a478dac6317a026c61830 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
208 schema:name Amyloid
209 rdf:type schema:DefinedTerm
210 Nd727370a13fa42f0b9f97341f9e20b4d schema:name doi
211 schema:value 10.1007/s00259-011-2021-8
212 rdf:type schema:PropertyValue
213 Nf72bcad96a8e4c90a578b61c3592dee3 rdf:first sg:person.01262066651.41
214 rdf:rest N6cbf9750f7f2433e86a9dc7cc6d8526b
215 Nfe07e0f3883a47d688fb1576d95cd25b rdf:first sg:person.01232301242.56
216 rdf:rest N4bb0b1cbbc8d44249fc00c99961413d0
217 Nfe202564d3f74cd6a030e23e7ad810a1 rdf:first sg:person.0752327220.15
218 rdf:rest Nb6b68f00186648daa4c6cec59b8c8997
219 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
220 schema:name Medical and Health Sciences
221 rdf:type schema:DefinedTerm
222 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
223 schema:name Clinical Sciences
224 rdf:type schema:DefinedTerm
225 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
226 schema:name Neurosciences
227 rdf:type schema:DefinedTerm
228 sg:journal.1297401 schema:issn 1619-7070
229 1619-7089
230 schema:name European Journal of Nuclear Medicine and Molecular Imaging
231 schema:publisher Springer Nature
232 rdf:type schema:Periodical
233 sg:person.01006042373.50 schema:affiliation grid-institutes:grid.424469.9
234 schema:familyName de La Sayette
235 schema:givenName V.
236 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006042373.50
237 rdf:type schema:Person
238 sg:person.01102531312.74 schema:affiliation grid-institutes:grid.411167.4
239 schema:familyName Gissot
240 schema:givenName V.
241 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01102531312.74
242 rdf:type schema:Person
243 sg:person.01131235164.27 schema:affiliation grid-institutes:grid.411167.4
244 schema:familyName Mondon
245 schema:givenName K.
246 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01131235164.27
247 rdf:type schema:Person
248 sg:person.01137731214.01 schema:affiliation grid-institutes:grid.411167.4
249 schema:familyName Tauber
250 schema:givenName C.
251 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01137731214.01
252 rdf:type schema:Person
253 sg:person.01163622361.57 schema:affiliation grid-institutes:grid.412043.0
254 schema:familyName Barré
255 schema:givenName L.
256 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163622361.57
257 rdf:type schema:Person
258 sg:person.01177240627.46 schema:affiliation grid-institutes:grid.411167.4
259 schema:familyName Vercouillie
260 schema:givenName J.
261 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01177240627.46
262 rdf:type schema:Person
263 sg:person.01232301242.56 schema:affiliation grid-institutes:grid.411175.7
264 schema:familyName Payoux
265 schema:givenName P.
266 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01232301242.56
267 rdf:type schema:Person
268 sg:person.01262066651.41 schema:affiliation grid-institutes:grid.12366.30
269 schema:familyName Vierron
270 schema:givenName E.
271 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01262066651.41
272 rdf:type schema:Person
273 sg:person.013003554244.49 schema:affiliation grid-institutes:grid.411167.4
274 schema:familyName Cottier
275 schema:givenName J. P.
276 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013003554244.49
277 rdf:type schema:Person
278 sg:person.01310304565.47 schema:affiliation grid-institutes:grid.411167.4
279 schema:familyName Beaufils
280 schema:givenName E.
281 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01310304565.47
282 rdf:type schema:Person
283 sg:person.01317232620.94 schema:affiliation grid-institutes:grid.424469.9
284 schema:familyName Eustache
285 schema:givenName F.
286 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01317232620.94
287 rdf:type schema:Person
288 sg:person.0612107402.12 schema:affiliation grid-institutes:grid.424469.9
289 schema:familyName Desgranges
290 schema:givenName B.
291 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0612107402.12
292 rdf:type schema:Person
293 sg:person.0622454377.26 schema:affiliation grid-institutes:grid.411167.4
294 schema:familyName Guilloteau
295 schema:givenName D.
296 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0622454377.26
297 rdf:type schema:Person
298 sg:person.0646041431.26 schema:affiliation grid-institutes:grid.411167.4
299 schema:familyName Camus
300 schema:givenName V.
301 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0646041431.26
302 rdf:type schema:Person
303 sg:person.0732206121.71 schema:affiliation grid-institutes:grid.411175.7
304 schema:familyName Voisin
305 schema:givenName T.
306 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0732206121.71
307 rdf:type schema:Person
308 sg:person.07430111442.39 schema:affiliation grid-institutes:grid.411167.4
309 schema:familyName Ribeiro
310 schema:givenName M. J.
311 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07430111442.39
312 rdf:type schema:Person
313 sg:person.0747242265.47 schema:affiliation grid-institutes:grid.411167.4
314 schema:familyName Hommet
315 schema:givenName C.
316 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0747242265.47
317 rdf:type schema:Person
318 sg:person.0752327220.15 schema:affiliation grid-institutes:grid.424469.9
319 schema:familyName Chételat
320 schema:givenName G.
321 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752327220.15
322 rdf:type schema:Person
323 sg:person.0763705171.27 schema:affiliation grid-institutes:grid.424469.9
324 schema:familyName La Joie
325 schema:givenName R.
326 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0763705171.27
327 rdf:type schema:Person
328 sg:person.0764654235.57 schema:affiliation grid-institutes:grid.411175.7
329 schema:familyName Tafani
330 schema:givenName M.
331 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0764654235.57
332 rdf:type schema:Person
333 sg:person.0772176346.25 schema:affiliation grid-institutes:grid.411175.7
334 schema:familyName Vellas
335 schema:givenName B.
336 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0772176346.25
337 rdf:type schema:Person
338 sg:pub.10.1007/s00415-009-5396-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017021844
339 https://doi.org/10.1007/s00415-009-5396-8
340 rdf:type schema:CreativeWork
341 sg:pub.10.1007/s00702-011-0641-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002397631
342 https://doi.org/10.1007/s00702-011-0641-6
343 rdf:type schema:CreativeWork
344 grid-institutes:grid.12366.30 schema:alternateName Université François Rabelais de Tours, Tours, France
345 schema:name UMR INSERM U930-CNRS ERL 3106, Tours, France
346 Université François Rabelais de Tours, Tours, France
347 rdf:type schema:Organization
348 grid-institutes:grid.411167.4 schema:alternateName CHRU de Tours, Tours, France
349 schema:name CHRU de Tours, Tours, France
350 CIC-IT /CIC INSERM 202, Tours, France
351 UMR INSERM U930-CNRS ERL 3106, Tours, France
352 Université François Rabelais de Tours, Tours, France
353 rdf:type schema:Organization
354 grid-institutes:grid.411175.7 schema:alternateName CHRU de Toulouse, Toulouse, France
355 schema:name CHRU de Toulouse, Toulouse, France
356 INSERM U1027, Toulouse, France
357 INSERM U825, Toulouse, France
358 Université Paul Sabatier de Toulouse, Toulouse, France
359 rdf:type schema:Organization
360 grid-institutes:grid.412043.0 schema:alternateName Université de Caen Basse Normandie, Caen, France
361 schema:name Groupe de Développements Méthodologiques en Tomographie par Émission de Positons, CEA/DSV/I2BM/CI-NAPS UMR6232, Caen, France
362 Université de Caen Basse Normandie, Caen, France
363 rdf:type schema:Organization
364 grid-institutes:grid.424469.9 schema:alternateName Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France
365 schema:name Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France
366 INSERM U1077, Caen, France
367 Université de Caen Basse Normandie - UMR-S1077, Caen, France
368 rdf:type schema:Organization
 




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


...