Correlation of post-contrast T1-weighted MRI surface regularity, tumor bulk, and necrotic volume with Ki67 and p53 in glioblastomas View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-04-24

AUTHORS

Adam Hasse, Mark Dapash, Yong Jeong, Sameer A. Ansari, Timothy J. Carroll, Maciej Lesniak, Daniel Thomas Ginat

ABSTRACT

Purposep53 and Ki67 status can be relevant to the management of glioblastoma. The goal of this study is to determine whether tumor morphology and bulk depicted on MRI correlate with p53 and Ki67 in glioblastoma.MethodsA retrospective review of 223 patients with glioblastoma and corresponding p53 or Ki67 status, along with T1-weighted post-contrast MR images was performed. Enhancing tumors were outlined for determining surface regularity, tumor bulk, and necrotic volume. The median value of 0.1 was chosen for p53 and 0.2 for Ki67 to separate each data set into two classes. T tests and receiver operating characteristic analysis were performed to determine the separation of the classes and the predicting power of each feature.ResultsThere were significant differences between tumor surface regularity (p = 0.01) and necrotic volume (p = 0.0429) according to Ki67 levels, although neither had statistically significant predictive power (AUC = 0.697, p = 0.0506 and AUC = 0.577, p = 0.164, respectively). There were also significant differences between tumor bulk (p = 0.0239) and necrotic volume (p = 0.0200) according to p53 levels, but again no significant predictive power was found using ROC analysis (AUC = 0.5882, p = 0.0894 and AUC = 0.567, p = 0.155, respectively).ConclusionQuantitative morphological tumor characteristics on post-contrast T1-weighted MRI can to a certain degree provide insights regarding Ki67 and p53 status in patients with glioblastoma. More... »

PAGES

861-867

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00234-019-02204-1

DOI

http://dx.doi.org/10.1007/s00234-019-02204-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113668372

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31020343


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

JSON-LD is the canonical representation for SciGraph data.

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

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1112", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Oncology and Carcinogenesis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Brain Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Glioblastoma", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Ki-67 Antigen", 
        "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": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "ROC Curve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tumor Burden", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tumor Suppressor Protein p53", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Graduate Program in Medical Physics, University of Chicago, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.170205.1", 
          "name": [
            "Graduate Program in Medical Physics, University of Chicago, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hasse", 
        "givenName": "Adam", 
        "id": "sg:person.014135677501.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014135677501.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Pritzker School of Medicine, University of Chicago, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.170205.1", 
          "name": [
            "Pritzker School of Medicine, University of Chicago, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dapash", 
        "givenName": "Mark", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.16753.36", 
          "name": [
            "Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jeong", 
        "givenName": "Yong", 
        "id": "sg:person.0724003000.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724003000.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Northwestern University, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.16753.36", 
          "name": [
            "Department of Radiology, Northwestern University, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ansari", 
        "givenName": "Sameer A.", 
        "id": "sg:person.01330454350.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01330454350.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.170205.1", 
          "name": [
            "Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Carroll", 
        "givenName": "Timothy J.", 
        "id": "sg:person.01017704601.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017704601.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Neurosurgery, Northwestern University, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.16753.36", 
          "name": [
            "Department of Neurosurgery, Northwestern University, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lesniak", 
        "givenName": "Maciej", 
        "id": "sg:person.01143723675.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143723675.45"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA", 
          "id": "http://www.grid.ac/institutes/grid.170205.1", 
          "name": [
            "Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ginat", 
        "givenName": "Daniel Thomas", 
        "id": "sg:person.01017077155.99", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017077155.99"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1186/s12885-016-2659-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042550051", 
          "https://doi.org/10.1186/s12885-016-2659-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s13277-013-0871-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052877697", 
          "https://doi.org/10.1007/s13277-013-0871-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00146086", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008253060", 
          "https://doi.org/10.1007/bf00146086"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/srep16822", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005732020", 
          "https://doi.org/10.1038/srep16822"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.bjc.6603756", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030523104", 
          "https://doi.org/10.1038/sj.bjc.6603756"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1014527929948", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019692547", 
          "https://doi.org/10.1023/a:1014527929948"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04-24", 
    "datePublishedReg": "2019-04-24", 
    "description": "Purposep53 and Ki67 status can be relevant to the management of glioblastoma. The goal of this study is to determine whether tumor morphology and bulk depicted on MRI correlate with p53 and Ki67 in glioblastoma.MethodsA retrospective review of 223 patients with glioblastoma and corresponding p53 or Ki67 status, along with T1-weighted post-contrast MR images was performed. Enhancing tumors were outlined for determining surface regularity, tumor bulk, and necrotic volume. The median value of 0.1 was chosen for p53 and 0.2 for Ki67 to separate each data set into two classes. T tests and receiver operating characteristic analysis were performed to determine the separation of the classes and the predicting power of each feature.ResultsThere were significant differences between tumor surface regularity (p\u2009=\u20090.01) and necrotic volume (p\u2009=\u20090.0429) according to Ki67 levels, although neither had statistically significant predictive power (AUC\u2009=\u20090.697, p\u2009=\u20090.0506 and AUC\u2009=\u20090.577, p\u2009=\u20090.164, respectively). There were also significant differences between tumor bulk (p\u2009=\u20090.0239) and necrotic volume (p\u2009=\u20090.0200) according to p53 levels, but again no significant predictive power was found using ROC analysis (AUC\u2009=\u20090.5882, p\u2009=\u20090.0894 and AUC\u2009=\u20090.567, p\u2009=\u20090.155, respectively).ConclusionQuantitative morphological tumor characteristics on post-contrast T1-weighted MRI can to a certain degree provide insights regarding Ki67 and p53 status in patients with glioblastoma.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00234-019-02204-1", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2683430", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1055404", 
        "issn": [
          "0028-3940", 
          "1432-1920"
        ], 
        "name": "Neuroradiology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "8", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "61"
      }
    ], 
    "keywords": [
      "tumor bulk", 
      "necrotic volume", 
      "Ki67 status", 
      "MethodsA retrospective review", 
      "management of glioblastoma", 
      "post-contrast T1-weighted MRI", 
      "significant differences", 
      "morphological tumor characteristics", 
      "post-contrast MR images", 
      "surface regularity", 
      "T1-weighted MRI", 
      "retrospective review", 
      "Ki67 levels", 
      "tumor characteristics", 
      "MRI correlates", 
      "tumor morphology", 
      "Ki67", 
      "ROC analysis", 
      "p53 status", 
      "glioblastoma", 
      "p53", 
      "patients", 
      "t-test", 
      "p53 levels", 
      "median value", 
      "characteristic analysis", 
      "significant predictive power", 
      "status", 
      "MR images", 
      "tumors", 
      "ResultsThere", 
      "predictive power", 
      "MRI", 
      "volume", 
      "differences", 
      "levels", 
      "correlates", 
      "review", 
      "management", 
      "study", 
      "test", 
      "analysis", 
      "correlation", 
      "data", 
      "provide insights", 
      "receiver", 
      "features", 
      "goal", 
      "characteristics", 
      "values", 
      "class", 
      "insights", 
      "morphology", 
      "images", 
      "regularity", 
      "power", 
      "bulk", 
      "separation"
    ], 
    "name": "Correlation of post-contrast T1-weighted MRI surface regularity, tumor bulk, and necrotic volume with Ki67 and p53 in glioblastomas", 
    "pagination": "861-867", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1113668372"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00234-019-02204-1"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "31020343"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00234-019-02204-1", 
      "https://app.dimensions.ai/details/publication/pub.1113668372"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:46", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_810.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00234-019-02204-1"
  }
]
 

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.10.1007/s00234-019-02204-1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00234-019-02204-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00234-019-02204-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00234-019-02204-1'


 

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

253 TRIPLES      21 PREDICATES      103 URIs      89 LITERALS      21 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00234-019-02204-1 schema:about N12156bf1744b4489967888eaf9b82cc1
2 N1e87c24627264bd8bb7125534faec9a3
3 N1f00c9f4cde843628080769933c75210
4 N414c0c93013c43bc80d5ca23f0d2ddd3
5 N469e30d863ef404181ed3059befa3252
6 N488807f4c53d4ea7935aa47afa16f8cf
7 N7041feaa25f64ccf80ab718918b22e5e
8 N741000f1a01e44aebeb1caa260659ec9
9 N7af9dbd703c4409db9f0f566b5bd7f8a
10 N8b88d172bf5049609ae750f62a349874
11 N9bade8aa942d4593b0dfa81879cfb998
12 Naa3310e564e44468bcf49bbb5e915a0a
13 Nb7a676a3317743f688e44ceffcb0ee99
14 Ne08999157738448b983b8e2b006ed753
15 anzsrc-for:11
16 anzsrc-for:1112
17 schema:author Nf0cf627ec0fd44099dda1eadc59940c0
18 schema:citation sg:pub.10.1007/bf00146086
19 sg:pub.10.1007/s13277-013-0871-3
20 sg:pub.10.1023/a:1014527929948
21 sg:pub.10.1038/sj.bjc.6603756
22 sg:pub.10.1038/srep16822
23 sg:pub.10.1186/s12885-016-2659-5
24 schema:datePublished 2019-04-24
25 schema:datePublishedReg 2019-04-24
26 schema:description Purposep53 and Ki67 status can be relevant to the management of glioblastoma. The goal of this study is to determine whether tumor morphology and bulk depicted on MRI correlate with p53 and Ki67 in glioblastoma.MethodsA retrospective review of 223 patients with glioblastoma and corresponding p53 or Ki67 status, along with T1-weighted post-contrast MR images was performed. Enhancing tumors were outlined for determining surface regularity, tumor bulk, and necrotic volume. The median value of 0.1 was chosen for p53 and 0.2 for Ki67 to separate each data set into two classes. T tests and receiver operating characteristic analysis were performed to determine the separation of the classes and the predicting power of each feature.ResultsThere were significant differences between tumor surface regularity (p = 0.01) and necrotic volume (p = 0.0429) according to Ki67 levels, although neither had statistically significant predictive power (AUC = 0.697, p = 0.0506 and AUC = 0.577, p = 0.164, respectively). There were also significant differences between tumor bulk (p = 0.0239) and necrotic volume (p = 0.0200) according to p53 levels, but again no significant predictive power was found using ROC analysis (AUC = 0.5882, p = 0.0894 and AUC = 0.567, p = 0.155, respectively).ConclusionQuantitative morphological tumor characteristics on post-contrast T1-weighted MRI can to a certain degree provide insights regarding Ki67 and p53 status in patients with glioblastoma.
27 schema:genre article
28 schema:isAccessibleForFree true
29 schema:isPartOf N226f76a13b444644a61948371b051688
30 Na0177ee12e414846a200227449f65a5b
31 sg:journal.1055404
32 schema:keywords Ki67
33 Ki67 levels
34 Ki67 status
35 MR images
36 MRI
37 MRI correlates
38 MethodsA retrospective review
39 ROC analysis
40 ResultsThere
41 T1-weighted MRI
42 analysis
43 bulk
44 characteristic analysis
45 characteristics
46 class
47 correlates
48 correlation
49 data
50 differences
51 features
52 glioblastoma
53 goal
54 images
55 insights
56 levels
57 management
58 management of glioblastoma
59 median value
60 morphological tumor characteristics
61 morphology
62 necrotic volume
63 p53
64 p53 levels
65 p53 status
66 patients
67 post-contrast MR images
68 post-contrast T1-weighted MRI
69 power
70 predictive power
71 provide insights
72 receiver
73 regularity
74 retrospective review
75 review
76 separation
77 significant differences
78 significant predictive power
79 status
80 study
81 surface regularity
82 t-test
83 test
84 tumor bulk
85 tumor characteristics
86 tumor morphology
87 tumors
88 values
89 volume
90 schema:name Correlation of post-contrast T1-weighted MRI surface regularity, tumor bulk, and necrotic volume with Ki67 and p53 in glioblastomas
91 schema:pagination 861-867
92 schema:productId Nd08995891d904c978464f8d4a929edf4
93 Nee1413fef6e54f328014cc4141642e7a
94 Nf81a4f6377da46b1a053ff5bce3270e1
95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113668372
96 https://doi.org/10.1007/s00234-019-02204-1
97 schema:sdDatePublished 2022-10-01T06:46
98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
99 schema:sdPublisher Nff4559e9a50e480ab01508907004553e
100 schema:url https://doi.org/10.1007/s00234-019-02204-1
101 sgo:license sg:explorer/license/
102 sgo:sdDataset articles
103 rdf:type schema:ScholarlyArticle
104 N12156bf1744b4489967888eaf9b82cc1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name ROC Curve
106 rdf:type schema:DefinedTerm
107 N19ba9e350b984519932e4549917538a2 schema:affiliation grid-institutes:grid.170205.1
108 schema:familyName Dapash
109 schema:givenName Mark
110 rdf:type schema:Person
111 N1e87c24627264bd8bb7125534faec9a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Male
113 rdf:type schema:DefinedTerm
114 N1f00c9f4cde843628080769933c75210 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Female
116 rdf:type schema:DefinedTerm
117 N226f76a13b444644a61948371b051688 schema:issueNumber 8
118 rdf:type schema:PublicationIssue
119 N414c0c93013c43bc80d5ca23f0d2ddd3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Tumor Burden
121 rdf:type schema:DefinedTerm
122 N4252ef1ee7c14612b0ef87e47a4d35df rdf:first N19ba9e350b984519932e4549917538a2
123 rdf:rest Nf76a4809246d470a8240846ff30d8151
124 N4266419f59e641479b9b7de02d788f45 rdf:first sg:person.01330454350.72
125 rdf:rest Neb7618d976b54388bbacf401882ac8e8
126 N469e30d863ef404181ed3059befa3252 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Adult
128 rdf:type schema:DefinedTerm
129 N488807f4c53d4ea7935aa47afa16f8cf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Retrospective Studies
131 rdf:type schema:DefinedTerm
132 N5382a0a5cb624bf6b132cdd91a8eabcd rdf:first sg:person.01017077155.99
133 rdf:rest rdf:nil
134 N7041feaa25f64ccf80ab718918b22e5e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Humans
136 rdf:type schema:DefinedTerm
137 N741000f1a01e44aebeb1caa260659ec9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Aged
139 rdf:type schema:DefinedTerm
140 N7af9dbd703c4409db9f0f566b5bd7f8a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
141 schema:name Tumor Suppressor Protein p53
142 rdf:type schema:DefinedTerm
143 N8b88d172bf5049609ae750f62a349874 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
144 schema:name Ki-67 Antigen
145 rdf:type schema:DefinedTerm
146 N9bade8aa942d4593b0dfa81879cfb998 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
147 schema:name Magnetic Resonance Imaging
148 rdf:type schema:DefinedTerm
149 Na0177ee12e414846a200227449f65a5b schema:volumeNumber 61
150 rdf:type schema:PublicationVolume
151 Naa3310e564e44468bcf49bbb5e915a0a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name Middle Aged
153 rdf:type schema:DefinedTerm
154 Nb7a676a3317743f688e44ceffcb0ee99 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Glioblastoma
156 rdf:type schema:DefinedTerm
157 Ncc9c34d06cbc4aa9a7742e29a359c887 rdf:first sg:person.01143723675.45
158 rdf:rest N5382a0a5cb624bf6b132cdd91a8eabcd
159 Nd08995891d904c978464f8d4a929edf4 schema:name pubmed_id
160 schema:value 31020343
161 rdf:type schema:PropertyValue
162 Ne08999157738448b983b8e2b006ed753 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
163 schema:name Brain Neoplasms
164 rdf:type schema:DefinedTerm
165 Neb7618d976b54388bbacf401882ac8e8 rdf:first sg:person.01017704601.70
166 rdf:rest Ncc9c34d06cbc4aa9a7742e29a359c887
167 Nee1413fef6e54f328014cc4141642e7a schema:name doi
168 schema:value 10.1007/s00234-019-02204-1
169 rdf:type schema:PropertyValue
170 Nf0cf627ec0fd44099dda1eadc59940c0 rdf:first sg:person.014135677501.55
171 rdf:rest N4252ef1ee7c14612b0ef87e47a4d35df
172 Nf76a4809246d470a8240846ff30d8151 rdf:first sg:person.0724003000.90
173 rdf:rest N4266419f59e641479b9b7de02d788f45
174 Nf81a4f6377da46b1a053ff5bce3270e1 schema:name dimensions_id
175 schema:value pub.1113668372
176 rdf:type schema:PropertyValue
177 Nff4559e9a50e480ab01508907004553e schema:name Springer Nature - SN SciGraph project
178 rdf:type schema:Organization
179 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
180 schema:name Medical and Health Sciences
181 rdf:type schema:DefinedTerm
182 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
183 schema:name Oncology and Carcinogenesis
184 rdf:type schema:DefinedTerm
185 sg:grant.2683430 http://pending.schema.org/fundedItem sg:pub.10.1007/s00234-019-02204-1
186 rdf:type schema:MonetaryGrant
187 sg:journal.1055404 schema:issn 0028-3940
188 1432-1920
189 schema:name Neuroradiology
190 schema:publisher Springer Nature
191 rdf:type schema:Periodical
192 sg:person.01017077155.99 schema:affiliation grid-institutes:grid.170205.1
193 schema:familyName Ginat
194 schema:givenName Daniel Thomas
195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017077155.99
196 rdf:type schema:Person
197 sg:person.01017704601.70 schema:affiliation grid-institutes:grid.170205.1
198 schema:familyName Carroll
199 schema:givenName Timothy J.
200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01017704601.70
201 rdf:type schema:Person
202 sg:person.01143723675.45 schema:affiliation grid-institutes:grid.16753.36
203 schema:familyName Lesniak
204 schema:givenName Maciej
205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143723675.45
206 rdf:type schema:Person
207 sg:person.01330454350.72 schema:affiliation grid-institutes:grid.16753.36
208 schema:familyName Ansari
209 schema:givenName Sameer A.
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01330454350.72
211 rdf:type schema:Person
212 sg:person.014135677501.55 schema:affiliation grid-institutes:grid.170205.1
213 schema:familyName Hasse
214 schema:givenName Adam
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014135677501.55
216 rdf:type schema:Person
217 sg:person.0724003000.90 schema:affiliation grid-institutes:grid.16753.36
218 schema:familyName Jeong
219 schema:givenName Yong
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0724003000.90
221 rdf:type schema:Person
222 sg:pub.10.1007/bf00146086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008253060
223 https://doi.org/10.1007/bf00146086
224 rdf:type schema:CreativeWork
225 sg:pub.10.1007/s13277-013-0871-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052877697
226 https://doi.org/10.1007/s13277-013-0871-3
227 rdf:type schema:CreativeWork
228 sg:pub.10.1023/a:1014527929948 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019692547
229 https://doi.org/10.1023/a:1014527929948
230 rdf:type schema:CreativeWork
231 sg:pub.10.1038/sj.bjc.6603756 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030523104
232 https://doi.org/10.1038/sj.bjc.6603756
233 rdf:type schema:CreativeWork
234 sg:pub.10.1038/srep16822 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005732020
235 https://doi.org/10.1038/srep16822
236 rdf:type schema:CreativeWork
237 sg:pub.10.1186/s12885-016-2659-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042550051
238 https://doi.org/10.1186/s12885-016-2659-5
239 rdf:type schema:CreativeWork
240 grid-institutes:grid.16753.36 schema:alternateName Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
241 Department of Neurosurgery, Northwestern University, Chicago, IL, USA
242 Department of Radiology, Northwestern University, Chicago, IL, USA
243 schema:name Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA
244 Department of Neurosurgery, Northwestern University, Chicago, IL, USA
245 Department of Radiology, Northwestern University, Chicago, IL, USA
246 rdf:type schema:Organization
247 grid-institutes:grid.170205.1 schema:alternateName Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA
248 Graduate Program in Medical Physics, University of Chicago, Chicago, IL, USA
249 Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
250 schema:name Department of Radiology, University of Chicago, 5841 S Maryland Avenue, 60637, Chicago, IL, USA
251 Graduate Program in Medical Physics, University of Chicago, Chicago, IL, USA
252 Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
253 rdf:type schema:Organization
 




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


...