18F-FDG and 11C-4DST PET/CT for evaluating response to platinum-based doublet chemotherapy in advanced non-small cell lung cancer: a prospective study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-12

AUTHORS

Ryogo Minamimoto, Yuichiro Takeda, Masatoshi Hotta, Jun Toyohara, Kazuhiko Nakajima, Go Naka, Haruhito Sugiyama

ABSTRACT

BACKGROUND: 4'-[Methyl-11C] thiothymidine (4DST) PET/CT provides DNA synthesis imaging, which represented a higher correlation with the proliferation in advanced non-small cell lung cancer (NSCLC) than that from imaging with FDG. The aim of this prospective study was to evaluate the potential of 4DST in early therapy monitoring for advanced NSCLC, and to compare the results with those from CT and FDG PET/CT. RESULTS: Patients who had been pathologically diagnosed with advanced NSCLC and were scheduled to receive platinum-doublet chemotherapy (PT-DC) were eligible. PET/CT imaging with 4DST and with FDG, and CT were performed at baseline and after 2 cycles of PT-DC (interim). Patients were evaluated semi-quantitatively after the 2 cycles of PT-DC using several PET parameters, response evaluation criteria in solid tumors (RECIST) 1.1 based on CT measurements, European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Baseline measurement data and metabolic response were compared between patients with progression-free survival (PFS) > 4 months and ≤ 4 months, and PFS and overall survival (OS) were compared between patients with and without metabolic response measured with each of the different parameters, using Kaplan-Meier statistics and log-rank testing. A total of 22 patients were included in this study. For predicting PFS > 4 months and ≤ 4 months, metabolic tumor volume (MTV) of baseline 4DST showed the highest area under the curve (0.73), positive predictive value (80.0%), negative predictive value (66.7%), and accuracy (72.7%) among baseline measurement data and metabolic responses from 4DST PET/CT, FDG PET/CT, and CT. Kaplan-Meier curves and log-rank tests for PFS with MTV of baseline FDG and baseline 4DST, and for OS with MTV of baseline FDG and baseline TLG, and MTV of baseline 4DST revealed significant results. CONCLUSIONS: MTV of baseline 4DST PET/CT along with MTV of baseline FDG PET/CT represent promising predictors of PFS, and MTV of baseline 4DST PET/CT along with MTV and TLG of baseline FDG PET/CT are possible predictors of OS in patients with advanced NSCLC. More... »

PAGES

4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13550-019-0472-2

DOI

http://dx.doi.org/10.1186/s13550-019-0472-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111442797

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30649637


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": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Division of Nuclear Medicine, Department of Radiology, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Minamimoto", 
        "givenName": "Ryogo", 
        "id": "sg:person.0714511602.66", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714511602.66"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Department of Respiratory Medicine, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takeda", 
        "givenName": "Yuichiro", 
        "id": "sg:person.011712164272.85", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011712164272.85"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Division of Nuclear Medicine, Department of Radiology, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hotta", 
        "givenName": "Masatoshi", 
        "id": "sg:person.07643060755.91", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07643060755.91"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Metropolitan Institute of Gerontology", 
          "id": "https://www.grid.ac/institutes/grid.420122.7", 
          "name": [
            "Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 1-1 Naka-cho, Itabashi-ku, 173-0022, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Toyohara", 
        "givenName": "Jun", 
        "id": "sg:person.01372710717.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01372710717.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Division of Nuclear Medicine, Department of Radiology, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakajima", 
        "givenName": "Kazuhiko", 
        "id": "sg:person.0707626025.09", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707626025.09"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Department of Respiratory Medicine, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Naka", 
        "givenName": "Go", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Center For Global Health and Medicine", 
          "id": "https://www.grid.ac/institutes/grid.45203.30", 
          "name": [
            "Department of Respiratory Medicine, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sugiyama", 
        "givenName": "Haruhito", 
        "id": "sg:person.0632256244.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632256244.05"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/bjc.1996.163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000048663", 
          "https://doi.org/10.1038/bjc.1996.163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/bjc.1996.163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000048663", 
          "https://doi.org/10.1038/bjc.1996.163"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-08-0312", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000677605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.109.071217", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005967644"
        ], 
        "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/10.1097/mnm.0000000000000382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012984345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/mnm.0000000000000382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012984345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-006-0292-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017008016", 
          "https://doi.org/10.1007/s00259-006-0292-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00259-006-0292-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017008016", 
          "https://doi.org/10.1007/s00259-006-0292-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.111.094458", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017438010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nucmedbio.2007.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018924078"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrobp.2008.12.039", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019232833"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-13-3141", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020699602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijrobp.2010.12.055", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021442938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1158/1078-0432.ccr-06-3025", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022857290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/cam4.689", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024110606"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0053081", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027896488"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jtho.2015.12.104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035836472"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.nucmedbio.2012.10.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036973960"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2016.66.9929", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037103051"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00261-015-0601-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040386661", 
          "https://doi.org/10.1007/s00261-015-0601-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13550-017-0258-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041671827", 
          "https://doi.org/10.1186/s13550-017-0258-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13550-017-0258-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041671827", 
          "https://doi.org/10.1186/s13550-017-0258-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.111.098426", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043952404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nri2216", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044452926", 
          "https://doi.org/10.1038/nri2216"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.113.131631", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047269886"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/2191-219x-4-10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047897396", 
          "https://doi.org/10.1186/2191-219x-4-10"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0959-8049(99)00229-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049505783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.111.095539", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050386319"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmoa011954", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052159806"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2967/jnumed.111.088435", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052406147"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2010.32.4939", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053639601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2002.02.068", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064202925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2003.12.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064203986"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1200/jco.2001.19.13.3210", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074842562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1076627945", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1077303951", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1967/s002449910136", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078937896"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-12", 
    "datePublishedReg": "2019-12-01", 
    "description": "BACKGROUND: 4'-[Methyl-11C] thiothymidine (4DST) PET/CT provides DNA synthesis imaging, which represented a higher correlation with the proliferation in advanced non-small cell lung cancer (NSCLC) than that from imaging with FDG. The aim of this prospective study was to evaluate the potential of 4DST in early therapy monitoring for advanced NSCLC, and to compare the results with those from CT and FDG PET/CT.\nRESULTS: Patients who had been pathologically diagnosed with advanced NSCLC and were scheduled to receive platinum-doublet chemotherapy (PT-DC) were eligible. PET/CT imaging with 4DST and with FDG, and CT were performed at baseline and after 2\u2009cycles of PT-DC (interim). Patients were evaluated semi-quantitatively after the 2\u2009cycles of PT-DC using several PET parameters, response evaluation criteria in solid tumors (RECIST) 1.1 based on CT measurements, European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Baseline measurement data and metabolic response were compared between patients with progression-free survival (PFS) >\u20094\u2009months and \u2264\u20094\u2009months, and PFS and overall survival (OS) were compared between patients with and without metabolic response measured with each of the different parameters, using Kaplan-Meier statistics and log-rank testing. A total of 22 patients were included in this study. For predicting PFS >\u20094\u2009months and \u2264\u20094\u2009months, metabolic tumor volume (MTV) of baseline 4DST showed the highest area under the curve (0.73), positive predictive value (80.0%), negative predictive value (66.7%), and accuracy (72.7%) among baseline measurement data and metabolic responses from 4DST PET/CT, FDG PET/CT, and CT. Kaplan-Meier curves and log-rank tests for PFS with MTV of baseline FDG and baseline 4DST, and for OS with MTV of baseline FDG and baseline TLG, and MTV of baseline 4DST revealed significant results.\nCONCLUSIONS: MTV of baseline 4DST PET/CT along with MTV of baseline FDG PET/CT represent promising predictors of PFS, and MTV of baseline 4DST PET/CT along with MTV and TLG of baseline FDG PET/CT are possible predictors of OS in patients with advanced NSCLC.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13550-019-0472-2", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6096543", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1045165", 
        "issn": [
          "2191-219X"
        ], 
        "name": "EJNMMI Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "9"
      }
    ], 
    "name": "18F-FDG and 11C-4DST PET/CT for evaluating response to platinum-based doublet chemotherapy in advanced non-small cell lung cancer: a prospective study", 
    "pagination": "4", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "a0bd4a5a64c33714291c3979a039e2b61836779b2927f1d4246bbbc24ecee9dc"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30649637"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101560946"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13550-019-0472-2"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111442797"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13550-019-0472-2", 
      "https://app.dimensions.ai/details/publication/pub.1111442797"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:42", 
    "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/v90/0000000321_0000000321/records_74940_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs13550-019-0472-2"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13550-019-0472-2'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13550-019-0472-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13550-019-0472-2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13550-019-0472-2'


 

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

221 TRIPLES      21 PREDICATES      63 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13550-019-0472-2 schema:about anzsrc-for:11
2 anzsrc-for:1112
3 schema:author N1cebd5ce8c0b40dcbdb49d8bb8767a61
4 schema:citation sg:pub.10.1007/s00259-006-0292-2
5 sg:pub.10.1007/s00261-015-0601-y
6 sg:pub.10.1038/bjc.1996.163
7 sg:pub.10.1038/nri2216
8 sg:pub.10.1186/2191-219x-4-10
9 sg:pub.10.1186/s13550-017-0258-3
10 https://app.dimensions.ai/details/publication/pub.1076627945
11 https://app.dimensions.ai/details/publication/pub.1077303951
12 https://doi.org/10.1002/cam4.689
13 https://doi.org/10.1016/j.ijrobp.2008.12.039
14 https://doi.org/10.1016/j.ijrobp.2010.12.055
15 https://doi.org/10.1016/j.jtho.2015.12.104
16 https://doi.org/10.1016/j.nucmedbio.2007.10.001
17 https://doi.org/10.1016/j.nucmedbio.2012.10.008
18 https://doi.org/10.1016/s0959-8049(99)00229-4
19 https://doi.org/10.1056/nejmoa011954
20 https://doi.org/10.1097/mnm.0000000000000382
21 https://doi.org/10.1158/1078-0432.ccr-06-3025
22 https://doi.org/10.1158/1078-0432.ccr-08-0312
23 https://doi.org/10.1158/1078-0432.ccr-13-3141
24 https://doi.org/10.1200/jco.2001.19.13.3210
25 https://doi.org/10.1200/jco.2002.02.068
26 https://doi.org/10.1200/jco.2003.12.004
27 https://doi.org/10.1200/jco.2010.32.4939
28 https://doi.org/10.1200/jco.2016.66.9929
29 https://doi.org/10.1371/journal.pone.0053081
30 https://doi.org/10.1967/s002449910136
31 https://doi.org/10.2967/jnumed.108.057307
32 https://doi.org/10.2967/jnumed.109.071217
33 https://doi.org/10.2967/jnumed.111.088435
34 https://doi.org/10.2967/jnumed.111.094458
35 https://doi.org/10.2967/jnumed.111.095539
36 https://doi.org/10.2967/jnumed.111.098426
37 https://doi.org/10.2967/jnumed.113.131631
38 schema:datePublished 2019-12
39 schema:datePublishedReg 2019-12-01
40 schema:description BACKGROUND: 4'-[Methyl-11C] thiothymidine (4DST) PET/CT provides DNA synthesis imaging, which represented a higher correlation with the proliferation in advanced non-small cell lung cancer (NSCLC) than that from imaging with FDG. The aim of this prospective study was to evaluate the potential of 4DST in early therapy monitoring for advanced NSCLC, and to compare the results with those from CT and FDG PET/CT. RESULTS: Patients who had been pathologically diagnosed with advanced NSCLC and were scheduled to receive platinum-doublet chemotherapy (PT-DC) were eligible. PET/CT imaging with 4DST and with FDG, and CT were performed at baseline and after 2 cycles of PT-DC (interim). Patients were evaluated semi-quantitatively after the 2 cycles of PT-DC using several PET parameters, response evaluation criteria in solid tumors (RECIST) 1.1 based on CT measurements, European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Baseline measurement data and metabolic response were compared between patients with progression-free survival (PFS) > 4 months and ≤ 4 months, and PFS and overall survival (OS) were compared between patients with and without metabolic response measured with each of the different parameters, using Kaplan-Meier statistics and log-rank testing. A total of 22 patients were included in this study. For predicting PFS > 4 months and ≤ 4 months, metabolic tumor volume (MTV) of baseline 4DST showed the highest area under the curve (0.73), positive predictive value (80.0%), negative predictive value (66.7%), and accuracy (72.7%) among baseline measurement data and metabolic responses from 4DST PET/CT, FDG PET/CT, and CT. Kaplan-Meier curves and log-rank tests for PFS with MTV of baseline FDG and baseline 4DST, and for OS with MTV of baseline FDG and baseline TLG, and MTV of baseline 4DST revealed significant results. CONCLUSIONS: MTV of baseline 4DST PET/CT along with MTV of baseline FDG PET/CT represent promising predictors of PFS, and MTV of baseline 4DST PET/CT along with MTV and TLG of baseline FDG PET/CT are possible predictors of OS in patients with advanced NSCLC.
41 schema:genre research_article
42 schema:inLanguage en
43 schema:isAccessibleForFree false
44 schema:isPartOf N58334e3c015e4de79d9cdd9f003df5ec
45 Na12f0a7504db478b9c79845580b0c853
46 sg:journal.1045165
47 schema:name 18F-FDG and 11C-4DST PET/CT for evaluating response to platinum-based doublet chemotherapy in advanced non-small cell lung cancer: a prospective study
48 schema:pagination 4
49 schema:productId N3147fbc8959b45ba81a39d41d946c434
50 Na151af9996e34856a268fed78910f691
51 Nc56e83b218be4a16a6aba538486acabb
52 Nc852965e89b54f58a9684a5d5415c391
53 Ned11e667b53440adabc8b5cce5e43b7b
54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111442797
55 https://doi.org/10.1186/s13550-019-0472-2
56 schema:sdDatePublished 2019-04-11T08:42
57 schema:sdLicense https://scigraph.springernature.com/explorer/license/
58 schema:sdPublisher Ne758be9a742c440c8614c033e3d1b81b
59 schema:url https://link.springer.com/10.1186%2Fs13550-019-0472-2
60 sgo:license sg:explorer/license/
61 sgo:sdDataset articles
62 rdf:type schema:ScholarlyArticle
63 N01c20758b3304299979dbfd1efbf76b1 rdf:first sg:person.07643060755.91
64 rdf:rest N9f3a2460137b454aa2c965cc896e337b
65 N1c796fcd053a4b4f85dc7c86866c00d8 rdf:first sg:person.011712164272.85
66 rdf:rest N01c20758b3304299979dbfd1efbf76b1
67 N1cebd5ce8c0b40dcbdb49d8bb8767a61 rdf:first sg:person.0714511602.66
68 rdf:rest N1c796fcd053a4b4f85dc7c86866c00d8
69 N3147fbc8959b45ba81a39d41d946c434 schema:name doi
70 schema:value 10.1186/s13550-019-0472-2
71 rdf:type schema:PropertyValue
72 N43fdefc85aa349c88742b4fde9c49d3f rdf:first N4e6ce7bd72bd47a19dc6bb3e9db37649
73 rdf:rest N5ce09c7f96724cc397d6f464219a8734
74 N472988644e194ad7b29601fd5adb0400 rdf:first sg:person.0707626025.09
75 rdf:rest N43fdefc85aa349c88742b4fde9c49d3f
76 N4e6ce7bd72bd47a19dc6bb3e9db37649 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
77 schema:familyName Naka
78 schema:givenName Go
79 rdf:type schema:Person
80 N58334e3c015e4de79d9cdd9f003df5ec schema:volumeNumber 9
81 rdf:type schema:PublicationVolume
82 N5ce09c7f96724cc397d6f464219a8734 rdf:first sg:person.0632256244.05
83 rdf:rest rdf:nil
84 N9f3a2460137b454aa2c965cc896e337b rdf:first sg:person.01372710717.35
85 rdf:rest N472988644e194ad7b29601fd5adb0400
86 Na12f0a7504db478b9c79845580b0c853 schema:issueNumber 1
87 rdf:type schema:PublicationIssue
88 Na151af9996e34856a268fed78910f691 schema:name dimensions_id
89 schema:value pub.1111442797
90 rdf:type schema:PropertyValue
91 Nc56e83b218be4a16a6aba538486acabb schema:name readcube_id
92 schema:value a0bd4a5a64c33714291c3979a039e2b61836779b2927f1d4246bbbc24ecee9dc
93 rdf:type schema:PropertyValue
94 Nc852965e89b54f58a9684a5d5415c391 schema:name nlm_unique_id
95 schema:value 101560946
96 rdf:type schema:PropertyValue
97 Ne758be9a742c440c8614c033e3d1b81b schema:name Springer Nature - SN SciGraph project
98 rdf:type schema:Organization
99 Ned11e667b53440adabc8b5cce5e43b7b schema:name pubmed_id
100 schema:value 30649637
101 rdf:type schema:PropertyValue
102 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
103 schema:name Medical and Health Sciences
104 rdf:type schema:DefinedTerm
105 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
106 schema:name Oncology and Carcinogenesis
107 rdf:type schema:DefinedTerm
108 sg:grant.6096543 http://pending.schema.org/fundedItem sg:pub.10.1186/s13550-019-0472-2
109 rdf:type schema:MonetaryGrant
110 sg:journal.1045165 schema:issn 2191-219X
111 schema:name EJNMMI Research
112 rdf:type schema:Periodical
113 sg:person.011712164272.85 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
114 schema:familyName Takeda
115 schema:givenName Yuichiro
116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011712164272.85
117 rdf:type schema:Person
118 sg:person.01372710717.35 schema:affiliation https://www.grid.ac/institutes/grid.420122.7
119 schema:familyName Toyohara
120 schema:givenName Jun
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01372710717.35
122 rdf:type schema:Person
123 sg:person.0632256244.05 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
124 schema:familyName Sugiyama
125 schema:givenName Haruhito
126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0632256244.05
127 rdf:type schema:Person
128 sg:person.0707626025.09 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
129 schema:familyName Nakajima
130 schema:givenName Kazuhiko
131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707626025.09
132 rdf:type schema:Person
133 sg:person.0714511602.66 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
134 schema:familyName Minamimoto
135 schema:givenName Ryogo
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0714511602.66
137 rdf:type schema:Person
138 sg:person.07643060755.91 schema:affiliation https://www.grid.ac/institutes/grid.45203.30
139 schema:familyName Hotta
140 schema:givenName Masatoshi
141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07643060755.91
142 rdf:type schema:Person
143 sg:pub.10.1007/s00259-006-0292-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017008016
144 https://doi.org/10.1007/s00259-006-0292-2
145 rdf:type schema:CreativeWork
146 sg:pub.10.1007/s00261-015-0601-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1040386661
147 https://doi.org/10.1007/s00261-015-0601-y
148 rdf:type schema:CreativeWork
149 sg:pub.10.1038/bjc.1996.163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000048663
150 https://doi.org/10.1038/bjc.1996.163
151 rdf:type schema:CreativeWork
152 sg:pub.10.1038/nri2216 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044452926
153 https://doi.org/10.1038/nri2216
154 rdf:type schema:CreativeWork
155 sg:pub.10.1186/2191-219x-4-10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047897396
156 https://doi.org/10.1186/2191-219x-4-10
157 rdf:type schema:CreativeWork
158 sg:pub.10.1186/s13550-017-0258-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041671827
159 https://doi.org/10.1186/s13550-017-0258-3
160 rdf:type schema:CreativeWork
161 https://app.dimensions.ai/details/publication/pub.1076627945 schema:CreativeWork
162 https://app.dimensions.ai/details/publication/pub.1077303951 schema:CreativeWork
163 https://doi.org/10.1002/cam4.689 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024110606
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1016/j.ijrobp.2008.12.039 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019232833
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1016/j.ijrobp.2010.12.055 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021442938
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1016/j.jtho.2015.12.104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035836472
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1016/j.nucmedbio.2007.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018924078
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1016/j.nucmedbio.2012.10.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036973960
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1016/s0959-8049(99)00229-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049505783
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1056/nejmoa011954 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052159806
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1097/mnm.0000000000000382 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012984345
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1158/1078-0432.ccr-06-3025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022857290
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1158/1078-0432.ccr-08-0312 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000677605
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1158/1078-0432.ccr-13-3141 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020699602
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1200/jco.2001.19.13.3210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074842562
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1200/jco.2002.02.068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064202925
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1200/jco.2003.12.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064203986
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1200/jco.2010.32.4939 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053639601
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1200/jco.2016.66.9929 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037103051
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1371/journal.pone.0053081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027896488
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1967/s002449910136 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078937896
200 rdf:type schema:CreativeWork
201 https://doi.org/10.2967/jnumed.108.057307 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009233958
202 rdf:type schema:CreativeWork
203 https://doi.org/10.2967/jnumed.109.071217 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005967644
204 rdf:type schema:CreativeWork
205 https://doi.org/10.2967/jnumed.111.088435 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052406147
206 rdf:type schema:CreativeWork
207 https://doi.org/10.2967/jnumed.111.094458 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017438010
208 rdf:type schema:CreativeWork
209 https://doi.org/10.2967/jnumed.111.095539 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050386319
210 rdf:type schema:CreativeWork
211 https://doi.org/10.2967/jnumed.111.098426 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043952404
212 rdf:type schema:CreativeWork
213 https://doi.org/10.2967/jnumed.113.131631 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047269886
214 rdf:type schema:CreativeWork
215 https://www.grid.ac/institutes/grid.420122.7 schema:alternateName Tokyo Metropolitan Institute of Gerontology
216 schema:name Research Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, 1-1 Naka-cho, Itabashi-ku, 173-0022, Tokyo, Japan
217 rdf:type schema:Organization
218 https://www.grid.ac/institutes/grid.45203.30 schema:alternateName National Center For Global Health and Medicine
219 schema:name Department of Respiratory Medicine, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan
220 Division of Nuclear Medicine, Department of Radiology, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, 162-8655, Tokyo, Japan
221 rdf:type schema:Organization
 




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


...