Tumor heterogeneity measurement using [18F] FDG PET/CT shows prognostic value in patients with non-small cell lung cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

N. M. Hughes, T. Mou, K. N. O’Regan, P. Murphy, J. N. O’Sullivan, E. Wolsztynski, J. Huang, M. P. Kennedy, J. F. Eary, F. O’Sullivan

ABSTRACT

The aim of this study was to evaluate primary tumor heterogeneity in patients with FDG-avid non-small cell lung cancer on PET/CT, with a view to optimising prognostic information from the metabolic signature of the primary tumor. A retrospective analysis of 94 [18F] FDG PET/CTs (56 M:38F) in patients with a diagnosis of primary lung malignancy was performed. Data collected included patient demographics, tumor size, maximum standardized uptake value (SUVmax), clinical stage and tumor histology. Clinical follow up and survival data were obtained from the available medical records. Tumor FDG spatial uptake heterogeneity was evaluated by the lack of conformity of the FDG pattern within the tumor region of interest to a simple 3-dimensional ellipsoidal form. A multivariate Cox regression analysis was used to assess the added prognostic benefit of heterogeneity information beyond radiological staging and other factors. Ninety four patients (mean age 67 years, range 36–85; 59.6% male) were available for analysis. The clinical staging distribution had 25 Stage I, 14 Stage II, 38 Stage III and 17 Stage IV. Mean tumor FDG spatial uptake heterogeneity was 25.87% with a range 2.78%–83.52%. Multivariate analysis found that heterogeneity, clinical stage, SUVmax and gender were associated with survival. Greater FDG spatial uptake heterogeneity is associated with significantly shorter survival (p = 0.0152). An increase of 19.5% (1 standard deviation) in FDG spatial uptake heterogeneity, is associated with a 43% increase in the risk of death. Quantification of the FDG spatial uptake heterogeneity of lung tumors has potential to add prognostic information to lung cancer staging beyond SUVmax and clinical stage information. More... »

PAGES

25

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s41824-018-0043-1

DOI

http://dx.doi.org/10.1186/s41824-018-0043-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107133872


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/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Cork University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411916.a", 
          "name": [
            "Department of Radiology, Cork University Hospital, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hughes", 
        "givenName": "N. M.", 
        "id": "sg:person.014301064670.82", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014301064670.82"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University College Cork", 
          "id": "https://www.grid.ac/institutes/grid.7872.a", 
          "name": [
            "Department of Statistics, University College Cork, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mou", 
        "givenName": "T.", 
        "id": "sg:person.013266220414.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013266220414.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cork University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411916.a", 
          "name": [
            "Department of Radiology, Cork University Hospital, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "O\u2019Regan", 
        "givenName": "K. N.", 
        "id": "sg:person.0761416505.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761416505.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cork University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411916.a", 
          "name": [
            "PET/CT Unit (Alliance Medical), Cork University Hospital, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Murphy", 
        "givenName": "P.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University College Cork", 
          "id": "https://www.grid.ac/institutes/grid.7872.a", 
          "name": [
            "Department of Statistics, University College Cork, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "O\u2019Sullivan", 
        "givenName": "J. N.", 
        "id": "sg:person.01020503411.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01020503411.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University College Cork", 
          "id": "https://www.grid.ac/institutes/grid.7872.a", 
          "name": [
            "Department of Statistics, University College Cork, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wolsztynski", 
        "givenName": "E.", 
        "id": "sg:person.0633450056.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633450056.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University College Cork", 
          "id": "https://www.grid.ac/institutes/grid.7872.a", 
          "name": [
            "Department of Statistics, University College Cork, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Huang", 
        "givenName": "J.", 
        "id": "sg:person.01257127234.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257127234.99"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Cork University Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411916.a", 
          "name": [
            "Department of Respiratory Medicine, Cork University Hospital, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kennedy", 
        "givenName": "M. P.", 
        "id": "sg:person.012471512617.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012471512617.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Cancer Institute", 
          "id": "https://www.grid.ac/institutes/grid.48336.3a", 
          "name": [
            "Cancer Imaging Program, National Cancer Institute, Rockville, MD, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Eary", 
        "givenName": "J. F.", 
        "id": "sg:person.01363213554.24", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01363213554.24"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University College Cork", 
          "id": "https://www.grid.ac/institutes/grid.7872.a", 
          "name": [
            "Department of Statistics, University College Cork, Cork, Ireland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "O\u2019Sullivan", 
        "givenName": "F.", 
        "id": "sg:person.0633130506.32", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633130506.32"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1097/jto.0b013e31815e6d6b", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004936335"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.108.053397", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009036281"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.108.057307", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009233958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa0900043", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010361472"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.112.107375", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012629075"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0094017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016613484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.108.057216", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040838090"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/cco.0b013e328013cd00", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041119924"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/cco.0b013e328013cd00", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041119924"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.113.133389", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042040633"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0145063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047540412"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0145063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047540412"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tmi.2011.2160984", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061695768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10334-017-0610-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084024371", 
          "https://doi.org/10.1007/s10334-017-0610-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10334-017-0610-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1084024371", 
          "https://doi.org/10.1007/s10334-017-0610-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2310/7290.2014.00032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086257117"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2310/7290.2014.00032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086257117"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12", 
    "datePublishedReg": "2018-12-01", 
    "description": "The aim of this study was to evaluate primary tumor heterogeneity in patients with FDG-avid non-small cell lung cancer on PET/CT, with a view to optimising prognostic information from the metabolic signature of the primary tumor. A retrospective analysis of 94 [18F] FDG PET/CTs (56 M:38F) in patients with a diagnosis of primary lung malignancy was performed. Data collected included patient demographics, tumor size, maximum standardized uptake value (SUVmax), clinical stage and tumor histology. Clinical follow up and survival data were obtained from the available medical records. Tumor FDG spatial uptake heterogeneity was evaluated by the lack of conformity of the FDG pattern within the tumor region of interest to a simple 3-dimensional ellipsoidal form. A multivariate Cox regression analysis was used to assess the added prognostic benefit of heterogeneity information beyond radiological staging and other factors. Ninety four patients (mean age 67 years, range 36\u201385; 59.6% male) were available for analysis. The clinical staging distribution had 25 Stage I, 14 Stage II, 38 Stage III and 17 Stage IV. Mean tumor FDG spatial uptake heterogeneity was 25.87% with a range 2.78%\u201383.52%. Multivariate analysis found that heterogeneity, clinical stage, SUVmax and gender were associated with survival. Greater FDG spatial uptake heterogeneity is associated with significantly shorter survival (p = 0.0152). An increase of 19.5% (1 standard deviation) in FDG spatial uptake heterogeneity, is associated with a 43% increase in the risk of death. Quantification of the FDG spatial uptake heterogeneity of lung tumors has potential to add prognostic information to lung cancer staging beyond SUVmax and clinical stage information.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s41824-018-0043-1", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3984001", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1300093", 
        "issn": [
          "2510-3636"
        ], 
        "name": "European Journal of Hybrid Imaging", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2"
      }
    ], 
    "name": "Tumor heterogeneity measurement using [18F] FDG PET/CT shows prognostic value in patients with non-small cell lung cancer", 
    "pagination": "25", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bbc7d72ceab4de83976b725d621eb9b7ec90e2640a6bc732d80f7d31d16034d4"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s41824-018-0043-1"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1107133872"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s41824-018-0043-1", 
      "https://app.dimensions.ai/details/publication/pub.1107133872"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:25", 
    "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/v90/0000000298_0000000298/records_26497_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs41824-018-0043-1"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s41824-018-0043-1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s41824-018-0043-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s41824-018-0043-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s41824-018-0043-1'


 

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

172 TRIPLES      21 PREDICATES      40 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s41824-018-0043-1 schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author N53dd6225cba844ebbc15c93b7724cd0d
4 schema:citation sg:pub.10.1007/s10334-017-0610-7
5 https://doi.org/10.1056/nejmoa0900043
6 https://doi.org/10.1097/cco.0b013e328013cd00
7 https://doi.org/10.1097/jto.0b013e31815e6d6b
8 https://doi.org/10.1109/tmi.2011.2160984
9 https://doi.org/10.1371/journal.pone.0094017
10 https://doi.org/10.1371/journal.pone.0145063
11 https://doi.org/10.2310/7290.2014.00032
12 https://doi.org/10.2967/jnumed.108.053397
13 https://doi.org/10.2967/jnumed.108.057216
14 https://doi.org/10.2967/jnumed.108.057307
15 https://doi.org/10.2967/jnumed.112.107375
16 https://doi.org/10.2967/jnumed.113.133389
17 schema:datePublished 2018-12
18 schema:datePublishedReg 2018-12-01
19 schema:description The aim of this study was to evaluate primary tumor heterogeneity in patients with FDG-avid non-small cell lung cancer on PET/CT, with a view to optimising prognostic information from the metabolic signature of the primary tumor. A retrospective analysis of 94 [18F] FDG PET/CTs (56 M:38F) in patients with a diagnosis of primary lung malignancy was performed. Data collected included patient demographics, tumor size, maximum standardized uptake value (SUVmax), clinical stage and tumor histology. Clinical follow up and survival data were obtained from the available medical records. Tumor FDG spatial uptake heterogeneity was evaluated by the lack of conformity of the FDG pattern within the tumor region of interest to a simple 3-dimensional ellipsoidal form. A multivariate Cox regression analysis was used to assess the added prognostic benefit of heterogeneity information beyond radiological staging and other factors. Ninety four patients (mean age 67 years, range 36–85; 59.6% male) were available for analysis. The clinical staging distribution had 25 Stage I, 14 Stage II, 38 Stage III and 17 Stage IV. Mean tumor FDG spatial uptake heterogeneity was 25.87% with a range 2.78%–83.52%. Multivariate analysis found that heterogeneity, clinical stage, SUVmax and gender were associated with survival. Greater FDG spatial uptake heterogeneity is associated with significantly shorter survival (p = 0.0152). An increase of 19.5% (1 standard deviation) in FDG spatial uptake heterogeneity, is associated with a 43% increase in the risk of death. Quantification of the FDG spatial uptake heterogeneity of lung tumors has potential to add prognostic information to lung cancer staging beyond SUVmax and clinical stage information.
20 schema:genre research_article
21 schema:inLanguage en
22 schema:isAccessibleForFree false
23 schema:isPartOf N87d1e78b106542c28371997d24cab1d8
24 Nd6f48a0c24a5408d956e7652679695a5
25 sg:journal.1300093
26 schema:name Tumor heterogeneity measurement using [18F] FDG PET/CT shows prognostic value in patients with non-small cell lung cancer
27 schema:pagination 25
28 schema:productId N2c7ccf1605414c638570e86ee77d31c3
29 Nf49fe5aac0d344b7b41e8e16ddc485a1
30 Nfef929644e8443adb07debd73dea38e6
31 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107133872
32 https://doi.org/10.1186/s41824-018-0043-1
33 schema:sdDatePublished 2019-04-11T08:25
34 schema:sdLicense https://scigraph.springernature.com/explorer/license/
35 schema:sdPublisher Nc1caea7a72e94759aea55d8c2a1630af
36 schema:url https://link.springer.com/10.1186%2Fs41824-018-0043-1
37 sgo:license sg:explorer/license/
38 sgo:sdDataset articles
39 rdf:type schema:ScholarlyArticle
40 N0ad0049dc4ce47188651eb1523e750c5 rdf:first sg:person.0633130506.32
41 rdf:rest rdf:nil
42 N2c7ccf1605414c638570e86ee77d31c3 schema:name readcube_id
43 schema:value bbc7d72ceab4de83976b725d621eb9b7ec90e2640a6bc732d80f7d31d16034d4
44 rdf:type schema:PropertyValue
45 N53dd6225cba844ebbc15c93b7724cd0d rdf:first sg:person.014301064670.82
46 rdf:rest Nbe67302b92a044a19026d0e470a3966c
47 N5a24f631d3ff4b809d7cb8a19f0a018b rdf:first sg:person.012471512617.69
48 rdf:rest N7338d91dfcb2455f8c2423ee0b6bf392
49 N7338d91dfcb2455f8c2423ee0b6bf392 rdf:first sg:person.01363213554.24
50 rdf:rest N0ad0049dc4ce47188651eb1523e750c5
51 N7873ea7ff8e14d8c9a6b0debdd00e70b rdf:first sg:person.01020503411.54
52 rdf:rest Nc972ca3bce234b9294db0b81434a7877
53 N87d1e78b106542c28371997d24cab1d8 schema:issueNumber 1
54 rdf:type schema:PublicationIssue
55 N88f11c6b573a42db86c848d116993596 rdf:first N9ca78678f0da4ec993daaae10a43788a
56 rdf:rest N7873ea7ff8e14d8c9a6b0debdd00e70b
57 N9ca78678f0da4ec993daaae10a43788a schema:affiliation https://www.grid.ac/institutes/grid.411916.a
58 schema:familyName Murphy
59 schema:givenName P.
60 rdf:type schema:Person
61 Nbe67302b92a044a19026d0e470a3966c rdf:first sg:person.013266220414.06
62 rdf:rest Ncdf5951515a841d89fceb8e62c574381
63 Nc1caea7a72e94759aea55d8c2a1630af schema:name Springer Nature - SN SciGraph project
64 rdf:type schema:Organization
65 Nc972ca3bce234b9294db0b81434a7877 rdf:first sg:person.0633450056.42
66 rdf:rest Ndaeb38ce9f0b4986873972ab9804c737
67 Ncdf5951515a841d89fceb8e62c574381 rdf:first sg:person.0761416505.48
68 rdf:rest N88f11c6b573a42db86c848d116993596
69 Nd6f48a0c24a5408d956e7652679695a5 schema:volumeNumber 2
70 rdf:type schema:PublicationVolume
71 Ndaeb38ce9f0b4986873972ab9804c737 rdf:first sg:person.01257127234.99
72 rdf:rest N5a24f631d3ff4b809d7cb8a19f0a018b
73 Nf49fe5aac0d344b7b41e8e16ddc485a1 schema:name doi
74 schema:value 10.1186/s41824-018-0043-1
75 rdf:type schema:PropertyValue
76 Nfef929644e8443adb07debd73dea38e6 schema:name dimensions_id
77 schema:value pub.1107133872
78 rdf:type schema:PropertyValue
79 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
80 schema:name Medical and Health Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
83 schema:name Oncology and Carcinogenesis
84 rdf:type schema:DefinedTerm
85 sg:grant.3984001 http://pending.schema.org/fundedItem sg:pub.10.1186/s41824-018-0043-1
86 rdf:type schema:MonetaryGrant
87 sg:journal.1300093 schema:issn 2510-3636
88 schema:name European Journal of Hybrid Imaging
89 rdf:type schema:Periodical
90 sg:person.01020503411.54 schema:affiliation https://www.grid.ac/institutes/grid.7872.a
91 schema:familyName O’Sullivan
92 schema:givenName J. N.
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01020503411.54
94 rdf:type schema:Person
95 sg:person.012471512617.69 schema:affiliation https://www.grid.ac/institutes/grid.411916.a
96 schema:familyName Kennedy
97 schema:givenName M. P.
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012471512617.69
99 rdf:type schema:Person
100 sg:person.01257127234.99 schema:affiliation https://www.grid.ac/institutes/grid.7872.a
101 schema:familyName Huang
102 schema:givenName J.
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257127234.99
104 rdf:type schema:Person
105 sg:person.013266220414.06 schema:affiliation https://www.grid.ac/institutes/grid.7872.a
106 schema:familyName Mou
107 schema:givenName T.
108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013266220414.06
109 rdf:type schema:Person
110 sg:person.01363213554.24 schema:affiliation https://www.grid.ac/institutes/grid.48336.3a
111 schema:familyName Eary
112 schema:givenName J. F.
113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01363213554.24
114 rdf:type schema:Person
115 sg:person.014301064670.82 schema:affiliation https://www.grid.ac/institutes/grid.411916.a
116 schema:familyName Hughes
117 schema:givenName N. M.
118 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014301064670.82
119 rdf:type schema:Person
120 sg:person.0633130506.32 schema:affiliation https://www.grid.ac/institutes/grid.7872.a
121 schema:familyName O’Sullivan
122 schema:givenName F.
123 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633130506.32
124 rdf:type schema:Person
125 sg:person.0633450056.42 schema:affiliation https://www.grid.ac/institutes/grid.7872.a
126 schema:familyName Wolsztynski
127 schema:givenName E.
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0633450056.42
129 rdf:type schema:Person
130 sg:person.0761416505.48 schema:affiliation https://www.grid.ac/institutes/grid.411916.a
131 schema:familyName O’Regan
132 schema:givenName K. N.
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0761416505.48
134 rdf:type schema:Person
135 sg:pub.10.1007/s10334-017-0610-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084024371
136 https://doi.org/10.1007/s10334-017-0610-7
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1056/nejmoa0900043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010361472
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1097/cco.0b013e328013cd00 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041119924
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1097/jto.0b013e31815e6d6b schema:sameAs https://app.dimensions.ai/details/publication/pub.1004936335
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1109/tmi.2011.2160984 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061695768
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1371/journal.pone.0094017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016613484
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1371/journal.pone.0145063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047540412
149 rdf:type schema:CreativeWork
150 https://doi.org/10.2310/7290.2014.00032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086257117
151 rdf:type schema:CreativeWork
152 https://doi.org/10.2967/jnumed.108.053397 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009036281
153 rdf:type schema:CreativeWork
154 https://doi.org/10.2967/jnumed.108.057216 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040838090
155 rdf:type schema:CreativeWork
156 https://doi.org/10.2967/jnumed.108.057307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009233958
157 rdf:type schema:CreativeWork
158 https://doi.org/10.2967/jnumed.112.107375 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012629075
159 rdf:type schema:CreativeWork
160 https://doi.org/10.2967/jnumed.113.133389 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042040633
161 rdf:type schema:CreativeWork
162 https://www.grid.ac/institutes/grid.411916.a schema:alternateName Cork University Hospital
163 schema:name Department of Radiology, Cork University Hospital, Cork, Ireland
164 Department of Respiratory Medicine, Cork University Hospital, Cork, Ireland
165 PET/CT Unit (Alliance Medical), Cork University Hospital, Cork, Ireland
166 rdf:type schema:Organization
167 https://www.grid.ac/institutes/grid.48336.3a schema:alternateName National Cancer Institute
168 schema:name Cancer Imaging Program, National Cancer Institute, Rockville, MD, USA
169 rdf:type schema:Organization
170 https://www.grid.ac/institutes/grid.7872.a schema:alternateName University College Cork
171 schema:name Department of Statistics, University College Cork, Cork, Ireland
172 rdf:type schema:Organization
 




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


...