Histological differences in cancer cells, stroma, and luminal spaces strongly correlate with in vivo MRI-detectability of prostate cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-06-07

AUTHORS

Kosuke Miyai, Ayako Mikoshi, Fumiko Hamabe, Kuniaki Nakanishi, Keiichi Ito, Hitoshi Tsuda, Hiroshi Shinmoto

ABSTRACT

The current study aimed to investigate the plausible histopathological factors that affect the detectability of prostate cancers on multiparametric magnetic resonance imaging (MP-MRI). This retrospective study included 59 consecutive patients who had undergone MP-MRI and subsequent radical prostatectomy. The cases were standardized according to the tumor size ranging from 10 to 20 mm on the final pathological diagnosis. Histopathological review and semi-automated imaging analysis were performed to evaluate the relative area fractions of the histological components, including cancer cells, stroma, and luminal spaces. Among the 59 prostatectomy specimens, no case showed two or more foci of cancer that matched the size criteria. Of the 59 lesions, 35 were MRI-detectable [Prostate Imaging Reporting and Data System (PIRADS) score of 3 or greater] and 24 were MRI-undetectable (PIRADS score of 2 or less). No significant differences were observed in Gleason Grade Group, percentage of Gleason pattern 4, and predominant subtype of Gleason pattern 4 between MRI-detectable and MRI-undetectable cancers. On the other hand, significantly higher mean area fraction of cancer cells (60.9% vs. 42.7%, P < 0.0001) and lower mean area fractions of stroma (33.8% vs. 45.1%, P = 0.00089) and luminal spaces (5.2% vs. 12.2%, P < 0.0001) were observed in MRI-detectable cancers than in MRI-undetectable cancers. In a multivariable analysis performed upon exclusion of area fraction of stroma due to its multicollinearity with that of cancer cells, area fractions of cancer cells (P = 0.0031) and luminal space (P = 0.0035) demonstrated strong positive and negative correlation with MRI-detectability, respectively. Changes in cancer cells, stroma, and luminal spaces, rather than conventional histological parameters, could be considered one of the best predictors to clinical, in vivo MRI-detectability of prostate cancer. More... »

PAGES

1536-1543

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41379-019-0292-y

DOI

http://dx.doi.org/10.1038/s41379-019-0292-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117003776

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31175330


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": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Image Interpretation, Computer-Assisted", 
        "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": "Multiparametric Magnetic Resonance Imaging", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Prostatic Neoplasms", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
            "Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Miyai", 
        "givenName": "Kosuke", 
        "id": "sg:person.01307144321.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307144321.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mikoshi", 
        "givenName": "Ayako", 
        "id": "sg:person.014466411413.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014466411413.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hamabe", 
        "givenName": "Fumiko", 
        "id": "sg:person.01320106105.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320106105.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakanishi", 
        "givenName": "Kuniaki", 
        "id": "sg:person.01062147203.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01062147203.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Urology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Urology, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ito", 
        "givenName": "Keiichi", 
        "id": "sg:person.0742101353.31", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742101353.31"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tsuda", 
        "givenName": "Hitoshi", 
        "id": "sg:person.07547136242.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07547136242.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan", 
          "id": "http://www.grid.ac/institutes/grid.416614.0", 
          "name": [
            "Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shinmoto", 
        "givenName": "Hiroshi", 
        "id": "sg:person.01340067051.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01340067051.56"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/modpathol.2014.116", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023739568", 
          "https://doi.org/10.1038/modpathol.2014.116"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11604-007-0218-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024213492", 
          "https://doi.org/10.1007/s11604-007-0218-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.bjc.6605422", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040163717", 
          "https://doi.org/10.1038/sj.bjc.6605422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11547-008-0246-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040530994", 
          "https://doi.org/10.1007/s11547-008-0246-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/modpathol.2017.29", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085441815", 
          "https://doi.org/10.1038/modpathol.2017.29"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-06-07", 
    "datePublishedReg": "2019-06-07", 
    "description": "The current study aimed to investigate the plausible histopathological factors that affect the detectability of prostate cancers on multiparametric magnetic resonance imaging (MP-MRI). This retrospective study included 59 consecutive patients who had undergone MP-MRI and subsequent radical prostatectomy. The cases were standardized according to the tumor size ranging from 10 to 20\u2009mm on the final pathological diagnosis. Histopathological review and semi-automated imaging analysis were performed to evaluate the relative area fractions of the histological components, including cancer cells, stroma, and luminal spaces. Among the 59 prostatectomy specimens, no case showed two or more foci of cancer that matched the size criteria. Of the 59 lesions, 35 were MRI-detectable [Prostate Imaging Reporting and Data System (PIRADS) score of 3 or greater] and 24 were MRI-undetectable (PIRADS score of 2 or less). No significant differences were observed in Gleason Grade Group, percentage of Gleason pattern 4, and predominant subtype of Gleason pattern 4 between MRI-detectable and MRI-undetectable cancers. On the other hand, significantly higher mean area fraction of cancer cells (60.9% vs. 42.7%, P\u2009<\u20090.0001) and lower mean area fractions of stroma (33.8% vs. 45.1%, P\u2009=\u20090.00089) and luminal spaces (5.2% vs. 12.2%, P\u2009<\u20090.0001) were observed in MRI-detectable cancers than in MRI-undetectable cancers. In a multivariable analysis performed upon exclusion of area fraction of stroma due to its multicollinearity with that of cancer cells, area fractions of cancer cells (P\u2009=\u20090.0031) and luminal space (P\u2009=\u20090.0035) demonstrated strong positive and negative correlation with MRI-detectability, respectively. Changes in cancer cells, stroma, and luminal spaces, rather than conventional histological parameters, could be considered one of the best predictors to clinical, in vivo MRI-detectability of prostate cancer.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/s41379-019-0292-y", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1098208", 
        "issn": [
          "0893-3952", 
          "1530-0285"
        ], 
        "name": "Modern Pathology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "10", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "32"
      }
    ], 
    "keywords": [
      "Gleason pattern 4", 
      "prostate cancer", 
      "cancer cells", 
      "mean area fraction", 
      "pattern 4", 
      "multiparametric magnetic resonance imaging", 
      "conventional histological parameters", 
      "final pathological diagnosis", 
      "Gleason grade group", 
      "subsequent radical prostatectomy", 
      "magnetic resonance imaging", 
      "histopathological factors", 
      "consecutive patients", 
      "luminal space", 
      "multivariable analysis", 
      "retrospective study", 
      "tumor size", 
      "histopathological review", 
      "radical prostatectomy", 
      "pathological diagnosis", 
      "predominant subtype", 
      "histological parameters", 
      "mp-MRI", 
      "prostatectomy specimens", 
      "resonance imaging", 
      "histological differences", 
      "cancer", 
      "histological components", 
      "grade group", 
      "stroma", 
      "MRI detectability", 
      "MRI", 
      "significant differences", 
      "size criteria", 
      "cells", 
      "negative correlation", 
      "current study", 
      "best predictor", 
      "vivo", 
      "patients", 
      "prostatectomy", 
      "lesions", 
      "subtypes", 
      "diagnosis", 
      "differences", 
      "predictors", 
      "cases", 
      "study", 
      "relative area fraction", 
      "imaging", 
      "more focus", 
      "review", 
      "group", 
      "percentage", 
      "fraction", 
      "factors", 
      "criteria", 
      "specimens", 
      "correlation", 
      "exclusion", 
      "analysis", 
      "changes", 
      "hand", 
      "area fraction", 
      "focus", 
      "detectability", 
      "components", 
      "size", 
      "parameters", 
      "space", 
      "multicollinearity"
    ], 
    "name": "Histological differences in cancer cells, stroma, and luminal spaces strongly correlate with in vivo MRI-detectability of prostate cancer", 
    "pagination": "1536-1543", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1117003776"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/s41379-019-0292-y"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "31175330"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/s41379-019-0292-y", 
      "https://app.dimensions.ai/details/publication/pub.1117003776"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-11-24T21:05", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/article/article_808.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/s41379-019-0292-y"
  }
]
 

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.10.1038/s41379-019-0292-y'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41379-019-0292-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41379-019-0292-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41379-019-0292-y'


 

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

232 TRIPLES      21 PREDICATES      109 URIs      96 LITERALS      15 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/s41379-019-0292-y schema:about N1a225b453f0e4b93a83b2bd270b54bca
2 N4010e666c25e4ce8b92c3bd8593751b3
3 N6157bc6071aa4c0690d78aa4b39eaa97
4 N6354822fc37a43afaede2b342d3d9a72
5 N7a30db385b6e459494c034a11d3d7d8b
6 N96bc91b05adc467da0bf6edbb834b2e5
7 Na607738b7b5e47268e1dbfdece4ff313
8 Ne2ea8ef8627140a893c3fe4de5dda4b2
9 anzsrc-for:11
10 anzsrc-for:1112
11 schema:author N8bc5ffac2a1a40efb17ec6444b21c493
12 schema:citation sg:pub.10.1007/s11547-008-0246-9
13 sg:pub.10.1007/s11604-007-0218-3
14 sg:pub.10.1038/modpathol.2014.116
15 sg:pub.10.1038/modpathol.2017.29
16 sg:pub.10.1038/sj.bjc.6605422
17 schema:datePublished 2019-06-07
18 schema:datePublishedReg 2019-06-07
19 schema:description The current study aimed to investigate the plausible histopathological factors that affect the detectability of prostate cancers on multiparametric magnetic resonance imaging (MP-MRI). This retrospective study included 59 consecutive patients who had undergone MP-MRI and subsequent radical prostatectomy. The cases were standardized according to the tumor size ranging from 10 to 20 mm on the final pathological diagnosis. Histopathological review and semi-automated imaging analysis were performed to evaluate the relative area fractions of the histological components, including cancer cells, stroma, and luminal spaces. Among the 59 prostatectomy specimens, no case showed two or more foci of cancer that matched the size criteria. Of the 59 lesions, 35 were MRI-detectable [Prostate Imaging Reporting and Data System (PIRADS) score of 3 or greater] and 24 were MRI-undetectable (PIRADS score of 2 or less). No significant differences were observed in Gleason Grade Group, percentage of Gleason pattern 4, and predominant subtype of Gleason pattern 4 between MRI-detectable and MRI-undetectable cancers. On the other hand, significantly higher mean area fraction of cancer cells (60.9% vs. 42.7%, P < 0.0001) and lower mean area fractions of stroma (33.8% vs. 45.1%, P = 0.00089) and luminal spaces (5.2% vs. 12.2%, P < 0.0001) were observed in MRI-detectable cancers than in MRI-undetectable cancers. In a multivariable analysis performed upon exclusion of area fraction of stroma due to its multicollinearity with that of cancer cells, area fractions of cancer cells (P = 0.0031) and luminal space (P = 0.0035) demonstrated strong positive and negative correlation with MRI-detectability, respectively. Changes in cancer cells, stroma, and luminal spaces, rather than conventional histological parameters, could be considered one of the best predictors to clinical, in vivo MRI-detectability of prostate cancer.
20 schema:genre article
21 schema:isAccessibleForFree true
22 schema:isPartOf N50406203ca4444f089eeb66eb67c982c
23 N66da3aa1a08d43d7875f1e7909103f64
24 sg:journal.1098208
25 schema:keywords Gleason grade group
26 Gleason pattern 4
27 MRI
28 MRI detectability
29 analysis
30 area fraction
31 best predictor
32 cancer
33 cancer cells
34 cases
35 cells
36 changes
37 components
38 consecutive patients
39 conventional histological parameters
40 correlation
41 criteria
42 current study
43 detectability
44 diagnosis
45 differences
46 exclusion
47 factors
48 final pathological diagnosis
49 focus
50 fraction
51 grade group
52 group
53 hand
54 histological components
55 histological differences
56 histological parameters
57 histopathological factors
58 histopathological review
59 imaging
60 lesions
61 luminal space
62 magnetic resonance imaging
63 mean area fraction
64 more focus
65 mp-MRI
66 multicollinearity
67 multiparametric magnetic resonance imaging
68 multivariable analysis
69 negative correlation
70 parameters
71 pathological diagnosis
72 patients
73 pattern 4
74 percentage
75 predictors
76 predominant subtype
77 prostate cancer
78 prostatectomy
79 prostatectomy specimens
80 radical prostatectomy
81 relative area fraction
82 resonance imaging
83 retrospective study
84 review
85 significant differences
86 size
87 size criteria
88 space
89 specimens
90 stroma
91 study
92 subsequent radical prostatectomy
93 subtypes
94 tumor size
95 vivo
96 schema:name Histological differences in cancer cells, stroma, and luminal spaces strongly correlate with in vivo MRI-detectability of prostate cancer
97 schema:pagination 1536-1543
98 schema:productId Nb1991efa722444709080fd5f3bfa0a31
99 Nc9628eb4a1af4dd3a51b08430c0533b9
100 Nf4697378bbb0437890e52cd149258ddb
101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117003776
102 https://doi.org/10.1038/s41379-019-0292-y
103 schema:sdDatePublished 2022-11-24T21:05
104 schema:sdLicense https://scigraph.springernature.com/explorer/license/
105 schema:sdPublisher N4ed0fffcf53545ef8ccd2f0752058f8a
106 schema:url https://doi.org/10.1038/s41379-019-0292-y
107 sgo:license sg:explorer/license/
108 sgo:sdDataset articles
109 rdf:type schema:ScholarlyArticle
110 N0c74be459b5f4fac88bdce16714f2538 rdf:first sg:person.0742101353.31
111 rdf:rest Nffe44376714240908257258e17babf54
112 N1a225b453f0e4b93a83b2bd270b54bca schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Male
114 rdf:type schema:DefinedTerm
115 N227c9f8465fa41c790af118d92c9d15c rdf:first sg:person.01340067051.56
116 rdf:rest rdf:nil
117 N3af9fe3d3d7a4f4e814ed1c2dff5c6e0 rdf:first sg:person.014466411413.51
118 rdf:rest N7fa9008047044c5eabe9e9f7c596fec0
119 N4010e666c25e4ce8b92c3bd8593751b3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Image Interpretation, Computer-Assisted
121 rdf:type schema:DefinedTerm
122 N4ed0fffcf53545ef8ccd2f0752058f8a schema:name Springer Nature - SN SciGraph project
123 rdf:type schema:Organization
124 N50406203ca4444f089eeb66eb67c982c schema:issueNumber 10
125 rdf:type schema:PublicationIssue
126 N6157bc6071aa4c0690d78aa4b39eaa97 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Aged
128 rdf:type schema:DefinedTerm
129 N6354822fc37a43afaede2b342d3d9a72 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Middle Aged
131 rdf:type schema:DefinedTerm
132 N66da3aa1a08d43d7875f1e7909103f64 schema:volumeNumber 32
133 rdf:type schema:PublicationVolume
134 N7a30db385b6e459494c034a11d3d7d8b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Retrospective Studies
136 rdf:type schema:DefinedTerm
137 N7fa9008047044c5eabe9e9f7c596fec0 rdf:first sg:person.01320106105.40
138 rdf:rest Nc4b9dd4b90234a1e9e895f3ea518942c
139 N8bc5ffac2a1a40efb17ec6444b21c493 rdf:first sg:person.01307144321.06
140 rdf:rest N3af9fe3d3d7a4f4e814ed1c2dff5c6e0
141 N96bc91b05adc467da0bf6edbb834b2e5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Humans
143 rdf:type schema:DefinedTerm
144 Na607738b7b5e47268e1dbfdece4ff313 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Multiparametric Magnetic Resonance Imaging
146 rdf:type schema:DefinedTerm
147 Nb1991efa722444709080fd5f3bfa0a31 schema:name pubmed_id
148 schema:value 31175330
149 rdf:type schema:PropertyValue
150 Nc4b9dd4b90234a1e9e895f3ea518942c rdf:first sg:person.01062147203.33
151 rdf:rest N0c74be459b5f4fac88bdce16714f2538
152 Nc9628eb4a1af4dd3a51b08430c0533b9 schema:name dimensions_id
153 schema:value pub.1117003776
154 rdf:type schema:PropertyValue
155 Ne2ea8ef8627140a893c3fe4de5dda4b2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
156 schema:name Prostatic Neoplasms
157 rdf:type schema:DefinedTerm
158 Nf4697378bbb0437890e52cd149258ddb schema:name doi
159 schema:value 10.1038/s41379-019-0292-y
160 rdf:type schema:PropertyValue
161 Nffe44376714240908257258e17babf54 rdf:first sg:person.07547136242.70
162 rdf:rest N227c9f8465fa41c790af118d92c9d15c
163 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
164 schema:name Medical and Health Sciences
165 rdf:type schema:DefinedTerm
166 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
167 schema:name Oncology and Carcinogenesis
168 rdf:type schema:DefinedTerm
169 sg:journal.1098208 schema:issn 0893-3952
170 1530-0285
171 schema:name Modern Pathology
172 schema:publisher Springer Nature
173 rdf:type schema:Periodical
174 sg:person.01062147203.33 schema:affiliation grid-institutes:grid.416614.0
175 schema:familyName Nakanishi
176 schema:givenName Kuniaki
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01062147203.33
178 rdf:type schema:Person
179 sg:person.01307144321.06 schema:affiliation grid-institutes:grid.416614.0
180 schema:familyName Miyai
181 schema:givenName Kosuke
182 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01307144321.06
183 rdf:type schema:Person
184 sg:person.01320106105.40 schema:affiliation grid-institutes:grid.416614.0
185 schema:familyName Hamabe
186 schema:givenName Fumiko
187 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01320106105.40
188 rdf:type schema:Person
189 sg:person.01340067051.56 schema:affiliation grid-institutes:grid.416614.0
190 schema:familyName Shinmoto
191 schema:givenName Hiroshi
192 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01340067051.56
193 rdf:type schema:Person
194 sg:person.014466411413.51 schema:affiliation grid-institutes:grid.416614.0
195 schema:familyName Mikoshi
196 schema:givenName Ayako
197 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014466411413.51
198 rdf:type schema:Person
199 sg:person.0742101353.31 schema:affiliation grid-institutes:grid.416614.0
200 schema:familyName Ito
201 schema:givenName Keiichi
202 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0742101353.31
203 rdf:type schema:Person
204 sg:person.07547136242.70 schema:affiliation grid-institutes:grid.416614.0
205 schema:familyName Tsuda
206 schema:givenName Hitoshi
207 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07547136242.70
208 rdf:type schema:Person
209 sg:pub.10.1007/s11547-008-0246-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040530994
210 https://doi.org/10.1007/s11547-008-0246-9
211 rdf:type schema:CreativeWork
212 sg:pub.10.1007/s11604-007-0218-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024213492
213 https://doi.org/10.1007/s11604-007-0218-3
214 rdf:type schema:CreativeWork
215 sg:pub.10.1038/modpathol.2014.116 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023739568
216 https://doi.org/10.1038/modpathol.2014.116
217 rdf:type schema:CreativeWork
218 sg:pub.10.1038/modpathol.2017.29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085441815
219 https://doi.org/10.1038/modpathol.2017.29
220 rdf:type schema:CreativeWork
221 sg:pub.10.1038/sj.bjc.6605422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040163717
222 https://doi.org/10.1038/sj.bjc.6605422
223 rdf:type schema:CreativeWork
224 grid-institutes:grid.416614.0 schema:alternateName Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan
225 Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan
226 Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
227 Department of Urology, National Defense Medical College, Tokorozawa, Saitama, Japan
228 schema:name Department of Basic Pathology, National Defense Medical College, Tokorozawa, Saitama, Japan
229 Department of Laboratory Medicine, National Defense Medical College, Tokorozawa, Saitama, Japan
230 Department of Radiology, National Defense Medical College, Tokorozawa, Saitama, Japan
231 Department of Urology, National Defense Medical College, Tokorozawa, Saitama, Japan
232 rdf:type schema:Organization
 




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


...