Quantitation of Regional Cerebral Blood Flow Corrected for Partial Volume Effect Using O-15 Water and PET: II. Normal Values and ... View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2000-08

AUTHORS

Ian Law, Hidehiro Iida, Søren Holm, Sam Nour, Egill Rostrup, Claus Svarer, Olaf B. Paulson

ABSTRACT

One of the most limiting factors for the accurate quantification of physiologic parameters with positron emission tomography (PET) is the partial volume effect (PVE). To assess the magnitude of this contribution to the measurement of regional cerebral blood flow (rCBF), the authors have formulated four kinetic models each including a parameter defining the perfusable tissue fraction (PTF). The four kinetic models used were 2 one-tissue compartment models with (Model A) and without (Model B) a vascular term and 2 two-tissue compartment models with fixed (Model C) or variable (Model D) white matter flow. Furthermore, rCBF based on the autoradiographic method was measured. The goals of the study were to determine the following in normal humans: (1) the optimal model, (2) the optimal length of fit, (3) the model parameters and their reproducibility, and (4) the effects of data acquisition (2D or 3D). Furthermore, the authors wanted to measure the activation response in the occipital gray matter compartment, and in doing so test the stability of the PTF, during perturbations of rCBF induced by visual stimulation. Eight dynamic PET scans were acquired per subject (n = 8), each for a duration of 6 minutes after IV bolus injection of H2(15)O. Four of these scans were performed using 2D and four using 3D acquisition. Visual stimulation was presented in four scans, and four scans were during rest. Model C was found optimal based on Akaike's Information Criteria (AIC) and had the smallest coefficient of variance after a 6-minute length of fit. Using this model the average PVE corrected rCBF during rest in gray matter was 1.07 mL x min(-1) x g(-1) (0.11 SD), with an average coefficient of variance of 6%. Acquisition mode did not affect the estimated parameters, with the exception of a significant increase in the white matter rCBF using the autoradiographic method (2D: 0.17 mL x min(-1) x g(-1) (0.02 SD); 3D: 0.21 mL x min(-1) x g(-1) (0.02 SD)). At a 6-minute fit the average gray matter CBF using Models C and D were increased by 100% to 150% compared with Models A and B and the autoradiographic method. There were no significant changes in the perfusable tissue fraction by the activation induced rCBF increases. The largest activation response was found using Model C (median = 39.1%). The current study clearly demonstrates the importance of PVE correction in the quantitation of rCBF in normal humans. The potential use of this method is to cost-effectively deliver PVE corrected measures of rCBF and tissue volumes without reference to imaging modalities other than PET. More... »

PAGES

1252-1263

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1097/00004647-200008000-00010

DOI

http://dx.doi.org/10.1097/00004647-200008000-00010

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034367769

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/10950384


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Blood Volume", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Brain", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cerebrovascular Circulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Cardiovascular", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Neurological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Oxygen Radioisotopes", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Periaqueductal Gray", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Photic Stimulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reference Values", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tomography, Emission-Computed", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Visual Perception", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Water", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Law", 
        "givenName": "Ian", 
        "id": "sg:person.0721611050.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0721611050.41"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Research Institute for Brain and Blood Vessels Akita", 
          "id": "https://www.grid.ac/institutes/grid.419094.1", 
          "name": [
            "Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark", 
            "Research Institute for Brain and Blood Vessels, Akita, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Iida", 
        "givenName": "Hidehiro", 
        "id": "sg:person.01225435647.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225435647.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "PET & Cyclotron Unit, Department of Clinical Physiology & Nuclear Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Holm", 
        "givenName": "S\u00f8ren", 
        "id": "sg:person.0740340304.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740340304.66"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nour", 
        "givenName": "Sam", 
        "id": "sg:person.01124214765.32", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01124214765.32"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hvidovre Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411905.8", 
          "name": [
            "Danish Research Center of Magnetic Resonance, Hvidovre Hospital, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rostrup", 
        "givenName": "Egill", 
        "id": "sg:person.01024327043.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01024327043.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Svarer", 
        "givenName": "Claus", 
        "id": "sg:person.01023561537.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01023561537.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hvidovre Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411905.8", 
          "name": [
            "Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark", 
            "Danish Research Center of Magnetic Resonance, Hvidovre Hospital, Copenhagen, Denmark"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Paulson", 
        "givenName": "Olaf B.", 
        "id": "sg:person.01244010503.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01244010503.37"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1097/00004728-199207000-00024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002343965"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004728-199207000-00024", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002343965"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1097/00004647-199701000-00010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009741736", 
          "https://doi.org/10.1097/00004647-199701000-00010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199701000-00010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009741736"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199701000-00010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009741736"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.78.1.104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011572434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-012389760-2/50021-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014416807"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1986.99", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016601652"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1986.99", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016601652"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1988.60", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017135161"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1988.60", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017135161"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00181069", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019263064", 
          "https://doi.org/10.1007/bf00181069"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1097/00004647-200008000-00009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019593086", 
          "https://doi.org/10.1097/00004647-200008000-00009"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-200008000-00009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019593086"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1988.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021199643"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1988.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021199643"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1985.9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025144161"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1985.9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025144161"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1986.14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025953912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1986.14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025953912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/jnnp.50.6.779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026568882"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1097/00004647-199903000-00005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030541539", 
          "https://doi.org/10.1097/00004647-199903000-00005"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199903000-00005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030541539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199903000-00005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030541539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1992.81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033466882"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1992.81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033466882"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/ana.410170315", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035701324"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3109/00365518609083685", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036543731"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1987.37", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037347516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1038/jcbfm.1987.37", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037347516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1097/00004647-199609000-00002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040526151", 
          "https://doi.org/10.1097/00004647-199609000-00002"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199609000-00002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040526151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199609000-00002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040526151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.res.18.3.237", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048860814"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1600-0404.1965.tb01956.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049617573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002093-199601030-00005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050602948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00002093-199601030-00005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050602948"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1097/00004647-199607000-00016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051950856", 
          "https://doi.org/10.1097/00004647-199607000-00016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199607000-00016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051950856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004647-199607000-00016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051950856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/23.531882", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061130792"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tac.1974.1100705", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061471419"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1948051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062514578"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077893930", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1081524860", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1081853635", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1984.51.5.1109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1081856885"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082512558", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082609581", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082624961", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1083263153", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2000-08", 
    "datePublishedReg": "2000-08-01", 
    "description": "One of the most limiting factors for the accurate quantification of physiologic parameters with positron emission tomography (PET) is the partial volume effect (PVE). To assess the magnitude of this contribution to the measurement of regional cerebral blood flow (rCBF), the authors have formulated four kinetic models each including a parameter defining the perfusable tissue fraction (PTF). The four kinetic models used were 2 one-tissue compartment models with (Model A) and without (Model B) a vascular term and 2 two-tissue compartment models with fixed (Model C) or variable (Model D) white matter flow. Furthermore, rCBF based on the autoradiographic method was measured. The goals of the study were to determine the following in normal humans: (1) the optimal model, (2) the optimal length of fit, (3) the model parameters and their reproducibility, and (4) the effects of data acquisition (2D or 3D). Furthermore, the authors wanted to measure the activation response in the occipital gray matter compartment, and in doing so test the stability of the PTF, during perturbations of rCBF induced by visual stimulation. Eight dynamic PET scans were acquired per subject (n = 8), each for a duration of 6 minutes after IV bolus injection of H2(15)O. Four of these scans were performed using 2D and four using 3D acquisition. Visual stimulation was presented in four scans, and four scans were during rest. Model C was found optimal based on Akaike's Information Criteria (AIC) and had the smallest coefficient of variance after a 6-minute length of fit. Using this model the average PVE corrected rCBF during rest in gray matter was 1.07 mL x min(-1) x g(-1) (0.11 SD), with an average coefficient of variance of 6%. Acquisition mode did not affect the estimated parameters, with the exception of a significant increase in the white matter rCBF using the autoradiographic method (2D: 0.17 mL x min(-1) x g(-1) (0.02 SD); 3D: 0.21 mL x min(-1) x g(-1) (0.02 SD)). At a 6-minute fit the average gray matter CBF using Models C and D were increased by 100% to 150% compared with Models A and B and the autoradiographic method. There were no significant changes in the perfusable tissue fraction by the activation induced rCBF increases. The largest activation response was found using Model C (median = 39.1%). The current study clearly demonstrates the importance of PVE correction in the quantitation of rCBF in normal humans. The potential use of this method is to cost-effectively deliver PVE corrected measures of rCBF and tissue volumes without reference to imaging modalities other than PET.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1097/00004647-200008000-00010", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1092815", 
        "issn": [
          "0271-678X", 
          "1559-7016"
        ], 
        "name": "Journal of Cerebral Blood Flow & Metabolism", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "8", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "20"
      }
    ], 
    "name": "Quantitation of Regional Cerebral Blood Flow Corrected for Partial Volume Effect Using O-15 Water and PET: II. Normal Values and Gray Matter Blood Flow Response to Visual Activation", 
    "pagination": "1252-1263", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "a3b6b77f9fbb0d906d1af110f7dc050c05aa9becebecfa6da1061375ca13f01c"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "10950384"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "8112566"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1097/00004647-200008000-00010"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1034367769"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1097/00004647-200008000-00010", 
      "https://app.dimensions.ai/details/publication/pub.1034367769"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T21:24", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000425.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://www.nature.com/jcbfm/journal/v20/n8/full/9590977a.html"
  }
]
 

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.10.1097/00004647-200008000-00010'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1097/00004647-200008000-00010'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1097/00004647-200008000-00010'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1097/00004647-200008000-00010'


 

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

309 TRIPLES      21 PREDICATES      85 URIs      39 LITERALS      27 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1097/00004647-200008000-00010 schema:about N03e3b245da304feca3fc8a2f28d93755
2 N055b29b380c74030925321908a97e747
3 N0dfdd4b2c22e473caad619abc4c5fe74
4 N106b84b36b1c44dab91418643b26bb95
5 N11eb5748719242b1a489f4a1704c3d95
6 N1a5457a63f3d401a98566f54b3d0686d
7 N1e7533e2d3974b5189bf40d92fe6f101
8 N45a929d55cb549828f616811abfa1066
9 N4ba66f644ad743309474e27b35ab6aec
10 N4fd28f13411c4b5f89f6559b053409ce
11 N560dd947b2f648dd8199cfdc6d577e36
12 N651fdd56d2c94ec58197670eb3923324
13 N7a5286771992480ab48eb3a78973590d
14 N84d1bccea4764f8091cdfcfc90bc8b26
15 N92613c48e4f64ad48e2fbfcd64a8a1a0
16 Nbd670b66b1aa484dbbf233df774d833b
17 Ne4bbfdbfd09a43aaa581b023cb2eeca8
18 Nf6aac7569fed45808dafabb3019e6be0
19 anzsrc-for:08
20 anzsrc-for:0801
21 schema:author N25a935293a0341beb1684f9e15d2e0be
22 schema:citation sg:pub.10.1007/bf00181069
23 sg:pub.10.1097/00004647-199607000-00016
24 sg:pub.10.1097/00004647-199609000-00002
25 sg:pub.10.1097/00004647-199701000-00010
26 sg:pub.10.1097/00004647-199903000-00005
27 sg:pub.10.1097/00004647-200008000-00009
28 https://app.dimensions.ai/details/publication/pub.1077893930
29 https://app.dimensions.ai/details/publication/pub.1081524860
30 https://app.dimensions.ai/details/publication/pub.1081853635
31 https://app.dimensions.ai/details/publication/pub.1082512558
32 https://app.dimensions.ai/details/publication/pub.1082609581
33 https://app.dimensions.ai/details/publication/pub.1082624961
34 https://app.dimensions.ai/details/publication/pub.1083263153
35 https://doi.org/10.1002/ana.410170315
36 https://doi.org/10.1016/b978-012389760-2/50021-9
37 https://doi.org/10.1038/jcbfm.1985.9
38 https://doi.org/10.1038/jcbfm.1986.14
39 https://doi.org/10.1038/jcbfm.1986.99
40 https://doi.org/10.1038/jcbfm.1987.37
41 https://doi.org/10.1038/jcbfm.1988.113
42 https://doi.org/10.1038/jcbfm.1988.60
43 https://doi.org/10.1038/jcbfm.1992.81
44 https://doi.org/10.1097/00002093-199601030-00005
45 https://doi.org/10.1097/00004647-199607000-00016
46 https://doi.org/10.1097/00004647-199609000-00002
47 https://doi.org/10.1097/00004647-199701000-00010
48 https://doi.org/10.1097/00004647-199903000-00005
49 https://doi.org/10.1097/00004647-200008000-00009
50 https://doi.org/10.1097/00004728-199207000-00024
51 https://doi.org/10.1109/23.531882
52 https://doi.org/10.1109/tac.1974.1100705
53 https://doi.org/10.1111/j.1600-0404.1965.tb01956.x
54 https://doi.org/10.1126/science.1948051
55 https://doi.org/10.1136/jnnp.50.6.779
56 https://doi.org/10.1152/jn.1984.51.5.1109
57 https://doi.org/10.1161/01.cir.78.1.104
58 https://doi.org/10.1161/01.res.18.3.237
59 https://doi.org/10.3109/00365518609083685
60 schema:datePublished 2000-08
61 schema:datePublishedReg 2000-08-01
62 schema:description One of the most limiting factors for the accurate quantification of physiologic parameters with positron emission tomography (PET) is the partial volume effect (PVE). To assess the magnitude of this contribution to the measurement of regional cerebral blood flow (rCBF), the authors have formulated four kinetic models each including a parameter defining the perfusable tissue fraction (PTF). The four kinetic models used were 2 one-tissue compartment models with (Model A) and without (Model B) a vascular term and 2 two-tissue compartment models with fixed (Model C) or variable (Model D) white matter flow. Furthermore, rCBF based on the autoradiographic method was measured. The goals of the study were to determine the following in normal humans: (1) the optimal model, (2) the optimal length of fit, (3) the model parameters and their reproducibility, and (4) the effects of data acquisition (2D or 3D). Furthermore, the authors wanted to measure the activation response in the occipital gray matter compartment, and in doing so test the stability of the PTF, during perturbations of rCBF induced by visual stimulation. Eight dynamic PET scans were acquired per subject (n = 8), each for a duration of 6 minutes after IV bolus injection of H2(15)O. Four of these scans were performed using 2D and four using 3D acquisition. Visual stimulation was presented in four scans, and four scans were during rest. Model C was found optimal based on Akaike's Information Criteria (AIC) and had the smallest coefficient of variance after a 6-minute length of fit. Using this model the average PVE corrected rCBF during rest in gray matter was 1.07 mL x min(-1) x g(-1) (0.11 SD), with an average coefficient of variance of 6%. Acquisition mode did not affect the estimated parameters, with the exception of a significant increase in the white matter rCBF using the autoradiographic method (2D: 0.17 mL x min(-1) x g(-1) (0.02 SD); 3D: 0.21 mL x min(-1) x g(-1) (0.02 SD)). At a 6-minute fit the average gray matter CBF using Models C and D were increased by 100% to 150% compared with Models A and B and the autoradiographic method. There were no significant changes in the perfusable tissue fraction by the activation induced rCBF increases. The largest activation response was found using Model C (median = 39.1%). The current study clearly demonstrates the importance of PVE correction in the quantitation of rCBF in normal humans. The potential use of this method is to cost-effectively deliver PVE corrected measures of rCBF and tissue volumes without reference to imaging modalities other than PET.
63 schema:genre research_article
64 schema:inLanguage en
65 schema:isAccessibleForFree true
66 schema:isPartOf N1dc723158e834be6ab8be2ca3f20d1af
67 N8213a50872b94898ba1d04bb9b950870
68 sg:journal.1092815
69 schema:name Quantitation of Regional Cerebral Blood Flow Corrected for Partial Volume Effect Using O-15 Water and PET: II. Normal Values and Gray Matter Blood Flow Response to Visual Activation
70 schema:pagination 1252-1263
71 schema:productId N0f31e209be694cc983d0970c86fc0f75
72 N144e226f127d4044b27831dea3bae0d1
73 N6c14c011126d455292e564a829ea9220
74 Nc49c16c97e2543c7a5d8faacfc4ef1f4
75 Nd879bea08c334b27a44abc6358a83c6f
76 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034367769
77 https://doi.org/10.1097/00004647-200008000-00010
78 schema:sdDatePublished 2019-04-10T21:24
79 schema:sdLicense https://scigraph.springernature.com/explorer/license/
80 schema:sdPublisher Ne038c162ac0b40b3b064b99a879b7f8c
81 schema:url http://www.nature.com/jcbfm/journal/v20/n8/full/9590977a.html
82 sgo:license sg:explorer/license/
83 sgo:sdDataset articles
84 rdf:type schema:ScholarlyArticle
85 N03e3b245da304feca3fc8a2f28d93755 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
86 schema:name Cerebrovascular Circulation
87 rdf:type schema:DefinedTerm
88 N055b29b380c74030925321908a97e747 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
89 schema:name Visual Perception
90 rdf:type schema:DefinedTerm
91 N0dfdd4b2c22e473caad619abc4c5fe74 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
92 schema:name Tomography, Emission-Computed
93 rdf:type schema:DefinedTerm
94 N0f31e209be694cc983d0970c86fc0f75 schema:name nlm_unique_id
95 schema:value 8112566
96 rdf:type schema:PropertyValue
97 N106b84b36b1c44dab91418643b26bb95 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Adult
99 rdf:type schema:DefinedTerm
100 N11eb5748719242b1a489f4a1704c3d95 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Models, Cardiovascular
102 rdf:type schema:DefinedTerm
103 N1367d104cf1942079106cc53b0ba080f rdf:first sg:person.01244010503.37
104 rdf:rest rdf:nil
105 N144e226f127d4044b27831dea3bae0d1 schema:name pubmed_id
106 schema:value 10950384
107 rdf:type schema:PropertyValue
108 N1a5457a63f3d401a98566f54b3d0686d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Reference Values
110 rdf:type schema:DefinedTerm
111 N1dc723158e834be6ab8be2ca3f20d1af schema:volumeNumber 20
112 rdf:type schema:PublicationVolume
113 N1e7533e2d3974b5189bf40d92fe6f101 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Photic Stimulation
115 rdf:type schema:DefinedTerm
116 N25a935293a0341beb1684f9e15d2e0be rdf:first sg:person.0721611050.41
117 rdf:rest N6b5a1496fde74172af653b52e08fb8b0
118 N2f4d33f1c7b94426a5ca3dde8981688c rdf:first sg:person.01024327043.24
119 rdf:rest N4040f114367c4c31ac4963baff409c0e
120 N3d666cacaa4449dead14977e95c3e66e rdf:first sg:person.0740340304.66
121 rdf:rest Nf4a15d87314a403f9de116a7218bbb9d
122 N4040f114367c4c31ac4963baff409c0e rdf:first sg:person.01023561537.06
123 rdf:rest N1367d104cf1942079106cc53b0ba080f
124 N45a929d55cb549828f616811abfa1066 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Oxygen Radioisotopes
126 rdf:type schema:DefinedTerm
127 N4ba66f644ad743309474e27b35ab6aec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Magnetic Resonance Imaging
129 rdf:type schema:DefinedTerm
130 N4fd28f13411c4b5f89f6559b053409ce schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Female
132 rdf:type schema:DefinedTerm
133 N560dd947b2f648dd8199cfdc6d577e36 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Brain
135 rdf:type schema:DefinedTerm
136 N651fdd56d2c94ec58197670eb3923324 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
137 schema:name Reproducibility of Results
138 rdf:type schema:DefinedTerm
139 N6b5a1496fde74172af653b52e08fb8b0 rdf:first sg:person.01225435647.37
140 rdf:rest N3d666cacaa4449dead14977e95c3e66e
141 N6c14c011126d455292e564a829ea9220 schema:name doi
142 schema:value 10.1097/00004647-200008000-00010
143 rdf:type schema:PropertyValue
144 N7a5286771992480ab48eb3a78973590d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Models, Neurological
146 rdf:type schema:DefinedTerm
147 N81148654c3f549d08b8592fef2eb4ca6 schema:name Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
148 rdf:type schema:Organization
149 N8213a50872b94898ba1d04bb9b950870 schema:issueNumber 8
150 rdf:type schema:PublicationIssue
151 N84d1bccea4764f8091cdfcfc90bc8b26 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name Blood Volume
153 rdf:type schema:DefinedTerm
154 N8e263556645748c391ea1e90b771f9ac schema:name Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
155 rdf:type schema:Organization
156 N92613c48e4f64ad48e2fbfcd64a8a1a0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
157 schema:name Water
158 rdf:type schema:DefinedTerm
159 Nbd670b66b1aa484dbbf233df774d833b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
160 schema:name Male
161 rdf:type schema:DefinedTerm
162 Nbe022ed648604d42a8fd547d265f7e3e schema:name Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
163 rdf:type schema:Organization
164 Nc49c16c97e2543c7a5d8faacfc4ef1f4 schema:name dimensions_id
165 schema:value pub.1034367769
166 rdf:type schema:PropertyValue
167 Nd879bea08c334b27a44abc6358a83c6f schema:name readcube_id
168 schema:value a3b6b77f9fbb0d906d1af110f7dc050c05aa9becebecfa6da1061375ca13f01c
169 rdf:type schema:PropertyValue
170 Ne038c162ac0b40b3b064b99a879b7f8c schema:name Springer Nature - SN SciGraph project
171 rdf:type schema:Organization
172 Ne4bbfdbfd09a43aaa581b023cb2eeca8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
173 schema:name Periaqueductal Gray
174 rdf:type schema:DefinedTerm
175 Nef7bcfa5e1ec451b8235b6dba57c1586 schema:name PET & Cyclotron Unit, Department of Clinical Physiology & Nuclear Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
176 rdf:type schema:Organization
177 Nf4a15d87314a403f9de116a7218bbb9d rdf:first sg:person.01124214765.32
178 rdf:rest N2f4d33f1c7b94426a5ca3dde8981688c
179 Nf6aac7569fed45808dafabb3019e6be0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
180 schema:name Humans
181 rdf:type schema:DefinedTerm
182 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
183 schema:name Information and Computing Sciences
184 rdf:type schema:DefinedTerm
185 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
186 schema:name Artificial Intelligence and Image Processing
187 rdf:type schema:DefinedTerm
188 sg:journal.1092815 schema:issn 0271-678X
189 1559-7016
190 schema:name Journal of Cerebral Blood Flow & Metabolism
191 rdf:type schema:Periodical
192 sg:person.01023561537.06 schema:affiliation N81148654c3f549d08b8592fef2eb4ca6
193 schema:familyName Svarer
194 schema:givenName Claus
195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01023561537.06
196 rdf:type schema:Person
197 sg:person.01024327043.24 schema:affiliation https://www.grid.ac/institutes/grid.411905.8
198 schema:familyName Rostrup
199 schema:givenName Egill
200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01024327043.24
201 rdf:type schema:Person
202 sg:person.01124214765.32 schema:affiliation N8e263556645748c391ea1e90b771f9ac
203 schema:familyName Nour
204 schema:givenName Sam
205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01124214765.32
206 rdf:type schema:Person
207 sg:person.01225435647.37 schema:affiliation https://www.grid.ac/institutes/grid.419094.1
208 schema:familyName Iida
209 schema:givenName Hidehiro
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225435647.37
211 rdf:type schema:Person
212 sg:person.01244010503.37 schema:affiliation https://www.grid.ac/institutes/grid.411905.8
213 schema:familyName Paulson
214 schema:givenName Olaf B.
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01244010503.37
216 rdf:type schema:Person
217 sg:person.0721611050.41 schema:affiliation Nbe022ed648604d42a8fd547d265f7e3e
218 schema:familyName Law
219 schema:givenName Ian
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0721611050.41
221 rdf:type schema:Person
222 sg:person.0740340304.66 schema:affiliation Nef7bcfa5e1ec451b8235b6dba57c1586
223 schema:familyName Holm
224 schema:givenName Søren
225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0740340304.66
226 rdf:type schema:Person
227 sg:pub.10.1007/bf00181069 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019263064
228 https://doi.org/10.1007/bf00181069
229 rdf:type schema:CreativeWork
230 sg:pub.10.1097/00004647-199607000-00016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051950856
231 https://doi.org/10.1097/00004647-199607000-00016
232 rdf:type schema:CreativeWork
233 sg:pub.10.1097/00004647-199609000-00002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040526151
234 https://doi.org/10.1097/00004647-199609000-00002
235 rdf:type schema:CreativeWork
236 sg:pub.10.1097/00004647-199701000-00010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009741736
237 https://doi.org/10.1097/00004647-199701000-00010
238 rdf:type schema:CreativeWork
239 sg:pub.10.1097/00004647-199903000-00005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030541539
240 https://doi.org/10.1097/00004647-199903000-00005
241 rdf:type schema:CreativeWork
242 sg:pub.10.1097/00004647-200008000-00009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019593086
243 https://doi.org/10.1097/00004647-200008000-00009
244 rdf:type schema:CreativeWork
245 https://app.dimensions.ai/details/publication/pub.1077893930 schema:CreativeWork
246 https://app.dimensions.ai/details/publication/pub.1081524860 schema:CreativeWork
247 https://app.dimensions.ai/details/publication/pub.1081853635 schema:CreativeWork
248 https://app.dimensions.ai/details/publication/pub.1082512558 schema:CreativeWork
249 https://app.dimensions.ai/details/publication/pub.1082609581 schema:CreativeWork
250 https://app.dimensions.ai/details/publication/pub.1082624961 schema:CreativeWork
251 https://app.dimensions.ai/details/publication/pub.1083263153 schema:CreativeWork
252 https://doi.org/10.1002/ana.410170315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035701324
253 rdf:type schema:CreativeWork
254 https://doi.org/10.1016/b978-012389760-2/50021-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014416807
255 rdf:type schema:CreativeWork
256 https://doi.org/10.1038/jcbfm.1985.9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025144161
257 rdf:type schema:CreativeWork
258 https://doi.org/10.1038/jcbfm.1986.14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025953912
259 rdf:type schema:CreativeWork
260 https://doi.org/10.1038/jcbfm.1986.99 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016601652
261 rdf:type schema:CreativeWork
262 https://doi.org/10.1038/jcbfm.1987.37 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037347516
263 rdf:type schema:CreativeWork
264 https://doi.org/10.1038/jcbfm.1988.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021199643
265 rdf:type schema:CreativeWork
266 https://doi.org/10.1038/jcbfm.1988.60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017135161
267 rdf:type schema:CreativeWork
268 https://doi.org/10.1038/jcbfm.1992.81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033466882
269 rdf:type schema:CreativeWork
270 https://doi.org/10.1097/00002093-199601030-00005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050602948
271 rdf:type schema:CreativeWork
272 https://doi.org/10.1097/00004647-199607000-00016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051950856
273 rdf:type schema:CreativeWork
274 https://doi.org/10.1097/00004647-199609000-00002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040526151
275 rdf:type schema:CreativeWork
276 https://doi.org/10.1097/00004647-199701000-00010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009741736
277 rdf:type schema:CreativeWork
278 https://doi.org/10.1097/00004647-199903000-00005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030541539
279 rdf:type schema:CreativeWork
280 https://doi.org/10.1097/00004647-200008000-00009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019593086
281 rdf:type schema:CreativeWork
282 https://doi.org/10.1097/00004728-199207000-00024 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002343965
283 rdf:type schema:CreativeWork
284 https://doi.org/10.1109/23.531882 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061130792
285 rdf:type schema:CreativeWork
286 https://doi.org/10.1109/tac.1974.1100705 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061471419
287 rdf:type schema:CreativeWork
288 https://doi.org/10.1111/j.1600-0404.1965.tb01956.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1049617573
289 rdf:type schema:CreativeWork
290 https://doi.org/10.1126/science.1948051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062514578
291 rdf:type schema:CreativeWork
292 https://doi.org/10.1136/jnnp.50.6.779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026568882
293 rdf:type schema:CreativeWork
294 https://doi.org/10.1152/jn.1984.51.5.1109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1081856885
295 rdf:type schema:CreativeWork
296 https://doi.org/10.1161/01.cir.78.1.104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011572434
297 rdf:type schema:CreativeWork
298 https://doi.org/10.1161/01.res.18.3.237 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048860814
299 rdf:type schema:CreativeWork
300 https://doi.org/10.3109/00365518609083685 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036543731
301 rdf:type schema:CreativeWork
302 https://www.grid.ac/institutes/grid.411905.8 schema:alternateName Hvidovre Hospital
303 schema:name Danish Research Center of Magnetic Resonance, Hvidovre Hospital, Copenhagen, Denmark
304 Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
305 rdf:type schema:Organization
306 https://www.grid.ac/institutes/grid.419094.1 schema:alternateName Research Institute for Brain and Blood Vessels Akita
307 schema:name Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
308 Research Institute for Brain and Blood Vessels, Akita, Japan
309 rdf:type schema:Organization
 




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


...