Underestimation of the ejection fraction using the quantitative gated SPECT for patients with myocardial hypertrophy View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-03-15

AUTHORS

Hidenori Yamaguchi, Masahiro Toba, Yasuo Amano, Keiichi Ishihara, Kyoichi Mizuno, Shin-ichiro Kumita

ABSTRACT

BackgroundThe aim of the present study is to quantify the degree of the error as a function of the left ventricular (LV) wall thickness, in calculation of the ejection fraction (EF) using gated single-photon emission computed tomography (SPECT). The essential error of quantitative gated SPECT (QGS) software in patients with myocardial hypertrophy has not been quantitatively estimated.MethodsForty-six patients with known or suspected hypertrophic cardiomyopathy underwent gated myocardial perfusion SPECT and cardiac magnetic resonance (MR) imaging. The EF value was automatically calculated from gated SPECT using the QGS software. Twelve points of regional LV wall thickness and the EF value were estimated from MR images.ResultsOnly a fair correlation was found between the QGS-EF and the MR-EF values (r = 0.48, y = 0.49x + 26.80, p < 0.01), and the QGS-EF was underestimated (r = 0.25, y = 0.90x) in 30 patients with myocardial hypertrophy (mean wall thickness > 12 mm). The magnitude of the error of the EF quantification from gated SPECT showed a significant negative correlation with the mean 12-point LV wall thickness in all 46 patients (r = −0.67, y = −4.12x + 40.44, p < 0.0001). The degree of the error of the ESV and that of the EDV showed positive correlation with the mean LV wall thickness (r = 0.55, y = 5.46x − 56.13, p < 0.0001; r = 0.31, y = 4.20x − 55.28, p < 0.05, respectively).ConclusionsThe underestimation of EF increases with the degree of myocardial hypertrophy, because of the overestimation of the LV cavity especially in the end-systolic phase. More... »

PAGES

502-507

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12149-013-0713-9

DOI

http://dx.doi.org/10.1007/s12149-013-0713-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043950591

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23494211


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/2008/1102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Cardiorespiratory Medicine and Haematology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adolescent", 
        "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": "Aged, 80 and over", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diagnostic Errors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Heart Ventricles", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hypertrophy", 
        "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": "Myocardium", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Software", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Stroke Volume", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Young Adult", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamaguchi", 
        "givenName": "Hidenori", 
        "id": "sg:person.0770717233.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0770717233.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Toba", 
        "givenName": "Masahiro", 
        "id": "sg:person.01015206307.54", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01015206307.54"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Amano", 
        "givenName": "Yasuo", 
        "id": "sg:person.0651160643.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651160643.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ishihara", 
        "givenName": "Keiichi", 
        "id": "sg:person.01035121045.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035121045.59"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Cardiology, Hepatology, Geriatrics and Integrated Medicine, Department of Internal Medicine, Nippon Medical School, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Division of Cardiology, Hepatology, Geriatrics and Integrated Medicine, Department of Internal Medicine, Nippon Medical School, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mizuno", 
        "givenName": "Kyoichi", 
        "id": "sg:person.01224612517.39", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01224612517.39"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kumita", 
        "givenName": "Shin-ichiro", 
        "id": "sg:person.016646761437.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016646761437.40"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1016/s1071-3581(98)90178-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027961359", 
          "https://doi.org/10.1016/s1071-3581(98)90178-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf03006666", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011682616", 
          "https://doi.org/10.1007/bf03006666"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2013-03-15", 
    "datePublishedReg": "2013-03-15", 
    "description": "BackgroundThe aim of the present study is to quantify the degree of the error as a function of the left ventricular (LV) wall thickness, in calculation of the ejection fraction (EF) using gated single-photon emission computed tomography (SPECT). The essential error of quantitative gated SPECT (QGS) software in patients with myocardial hypertrophy has not been quantitatively estimated.MethodsForty-six patients with known or suspected hypertrophic cardiomyopathy underwent gated myocardial perfusion SPECT and cardiac magnetic resonance (MR) imaging. The EF value was automatically calculated from gated SPECT using the QGS software. Twelve points of regional LV wall thickness and the EF value were estimated from MR images.ResultsOnly a fair correlation was found between the QGS-EF and the MR-EF values (r\u00a0=\u00a00.48, y\u00a0=\u00a00.49x\u00a0+\u00a026.80, p\u00a0<\u00a00.01), and the QGS-EF was underestimated (r\u00a0=\u00a00.25, y\u00a0=\u00a00.90x) in 30 patients with myocardial hypertrophy (mean wall thickness\u00a0>\u00a012\u00a0mm). The magnitude of the error of the EF quantification from gated SPECT showed a significant negative correlation with the mean 12-point LV wall thickness in all 46 patients (r\u00a0=\u00a0\u22120.67, y\u00a0=\u00a0\u22124.12x\u00a0+\u00a040.44, p\u00a0<\u00a00.0001). The degree of the error of the ESV and that of the EDV showed positive correlation with the mean LV wall thickness (r\u00a0=\u00a00.55, y\u00a0=\u00a05.46x\u00a0\u2212\u00a056.13, p\u00a0<\u00a00.0001; r\u00a0=\u00a00.31, y\u00a0=\u00a04.20x\u00a0\u2212\u00a055.28, p\u00a0<\u00a00.05, respectively).ConclusionsThe underestimation of EF increases with the degree of myocardial hypertrophy, because of the overestimation of the LV cavity especially in the end-systolic phase.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s12149-013-0713-9", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1099601", 
        "issn": [
          "0914-7187", 
          "1864-6433"
        ], 
        "name": "Annals of Nuclear Medicine", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "27"
      }
    ], 
    "keywords": [
      "LV wall thickness", 
      "myocardial hypertrophy", 
      "ejection fraction", 
      "gated SPECT", 
      "left ventricular wall thickness", 
      "cardiac magnetic resonance imaging", 
      "MethodsForty-six patients", 
      "mean LV wall thickness", 
      "ventricular wall thickness", 
      "quantitative gated SPECT software", 
      "magnetic resonance imaging", 
      "single photon emission", 
      "myocardial perfusion SPECT", 
      "gated SPECT software", 
      "regional LV wall thickness", 
      "wall thickness", 
      "cardiomyopathy underwent", 
      "end-systolic phase", 
      "patients", 
      "perfusion SPECT", 
      "QGS software", 
      "resonance imaging", 
      "significant negative correlation", 
      "hypertrophy", 
      "SPECT software", 
      "LV cavity", 
      "SPECT", 
      "present study", 
      "fair correlation", 
      "EF quantification", 
      "positive correlation", 
      "MR images", 
      "negative correlation", 
      "EF increase", 
      "underwent", 
      "EDV", 
      "tomography", 
      "correlation", 
      "ESV", 
      "EF values", 
      "imaging", 
      "aim", 
      "degree", 
      "study", 
      "fraction", 
      "underestimation", 
      "increase", 
      "cavity", 
      "values", 
      "function", 
      "quantification", 
      "thickness", 
      "overestimation", 
      "point", 
      "software", 
      "magnitude", 
      "phase", 
      "images", 
      "error", 
      "essential errors", 
      "emission", 
      "calculations"
    ], 
    "name": "Underestimation of the ejection fraction using the quantitative gated SPECT for patients with myocardial hypertrophy", 
    "pagination": "502-507", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1043950591"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12149-013-0713-9"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "23494211"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12149-013-0713-9", 
      "https://app.dimensions.ai/details/publication/pub.1043950591"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:38", 
    "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_594.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s12149-013-0713-9"
  }
]
 

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/s12149-013-0713-9'

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/s12149-013-0713-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12149-013-0713-9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12149-013-0713-9'


 

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

232 TRIPLES      21 PREDICATES      105 URIs      95 LITERALS      23 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12149-013-0713-9 schema:about N0ffed87074014f3f85259ccdb3fd80a3
2 N243f389b05ed49f7bc41b12f90ce6299
3 N37897150e91145d7a86d5f506cda8e62
4 N3bbc6fe7ff614b0b8d54bd31b31dd269
5 N68905a73d2374d508642cd5f9d19217a
6 N7feef2647ea74e2394ab8c7cb914da5f
7 N91247551fbfa4495a321424b50c2dd14
8 Na12e9aec01ab4cdfbbc4f73b9196d1d5
9 Na26cbe550f9645568706466651b8d4fe
10 Ncdca2a210bd04ceab4e66d56fd6a353b
11 Ncf8a84a88d6e4de0a68efa151ba12df9
12 Nd17da714525a40c19261c050be07dcba
13 Ne7d9fa833f5842f5b2baefbdb7307c73
14 Ne848802699ee49938e303890062916d9
15 Nfc760cfde50345e1a22a4a7c86735e66
16 Nfd130c3fdf804aa1b8957ab488e3c220
17 anzsrc-for:11
18 anzsrc-for:1102
19 schema:author Nc6bd309795e34cb88772f3527e83738e
20 schema:citation sg:pub.10.1007/bf03006666
21 sg:pub.10.1016/s1071-3581(98)90178-7
22 schema:datePublished 2013-03-15
23 schema:datePublishedReg 2013-03-15
24 schema:description BackgroundThe aim of the present study is to quantify the degree of the error as a function of the left ventricular (LV) wall thickness, in calculation of the ejection fraction (EF) using gated single-photon emission computed tomography (SPECT). The essential error of quantitative gated SPECT (QGS) software in patients with myocardial hypertrophy has not been quantitatively estimated.MethodsForty-six patients with known or suspected hypertrophic cardiomyopathy underwent gated myocardial perfusion SPECT and cardiac magnetic resonance (MR) imaging. The EF value was automatically calculated from gated SPECT using the QGS software. Twelve points of regional LV wall thickness and the EF value were estimated from MR images.ResultsOnly a fair correlation was found between the QGS-EF and the MR-EF values (r = 0.48, y = 0.49x + 26.80, p < 0.01), and the QGS-EF was underestimated (r = 0.25, y = 0.90x) in 30 patients with myocardial hypertrophy (mean wall thickness > 12 mm). The magnitude of the error of the EF quantification from gated SPECT showed a significant negative correlation with the mean 12-point LV wall thickness in all 46 patients (r = −0.67, y = −4.12x + 40.44, p < 0.0001). The degree of the error of the ESV and that of the EDV showed positive correlation with the mean LV wall thickness (r = 0.55, y = 5.46x − 56.13, p < 0.0001; r = 0.31, y = 4.20x − 55.28, p < 0.05, respectively).ConclusionsThe underestimation of EF increases with the degree of myocardial hypertrophy, because of the overestimation of the LV cavity especially in the end-systolic phase.
25 schema:genre article
26 schema:isAccessibleForFree false
27 schema:isPartOf Nc4875a8121d240c48b0fc2d4832a0419
28 Ne571350604334107a49f805a33919985
29 sg:journal.1099601
30 schema:keywords EDV
31 EF increase
32 EF quantification
33 EF values
34 ESV
35 LV cavity
36 LV wall thickness
37 MR images
38 MethodsForty-six patients
39 QGS software
40 SPECT
41 SPECT software
42 aim
43 calculations
44 cardiac magnetic resonance imaging
45 cardiomyopathy underwent
46 cavity
47 correlation
48 degree
49 ejection fraction
50 emission
51 end-systolic phase
52 error
53 essential errors
54 fair correlation
55 fraction
56 function
57 gated SPECT
58 gated SPECT software
59 hypertrophy
60 images
61 imaging
62 increase
63 left ventricular wall thickness
64 magnetic resonance imaging
65 magnitude
66 mean LV wall thickness
67 myocardial hypertrophy
68 myocardial perfusion SPECT
69 negative correlation
70 overestimation
71 patients
72 perfusion SPECT
73 phase
74 point
75 positive correlation
76 present study
77 quantification
78 quantitative gated SPECT software
79 regional LV wall thickness
80 resonance imaging
81 significant negative correlation
82 single photon emission
83 software
84 study
85 thickness
86 tomography
87 underestimation
88 underwent
89 values
90 ventricular wall thickness
91 wall thickness
92 schema:name Underestimation of the ejection fraction using the quantitative gated SPECT for patients with myocardial hypertrophy
93 schema:pagination 502-507
94 schema:productId N7c952b9d6240492990c265c10f7aa48b
95 N7e6707fa839d4547b68dc2205efff2db
96 Nab5fdf5eca7b41209af4ea017c201858
97 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043950591
98 https://doi.org/10.1007/s12149-013-0713-9
99 schema:sdDatePublished 2022-10-01T06:38
100 schema:sdLicense https://scigraph.springernature.com/explorer/license/
101 schema:sdPublisher Nd7a1012aa6384efdbe047db7f70d8249
102 schema:url https://doi.org/10.1007/s12149-013-0713-9
103 sgo:license sg:explorer/license/
104 sgo:sdDataset articles
105 rdf:type schema:ScholarlyArticle
106 N0ffed87074014f3f85259ccdb3fd80a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Female
108 rdf:type schema:DefinedTerm
109 N18672319de3542e9814b61ce9e3ec1d9 rdf:first sg:person.01224612517.39
110 rdf:rest N8489b18e53184d1ba65bce49bc30222c
111 N243f389b05ed49f7bc41b12f90ce6299 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Middle Aged
113 rdf:type schema:DefinedTerm
114 N37897150e91145d7a86d5f506cda8e62 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Myocardium
116 rdf:type schema:DefinedTerm
117 N3b108d4fac084726a08976129e7d4f1e rdf:first sg:person.01015206307.54
118 rdf:rest Nf8e047fd5def400abd103b13224087f0
119 N3bbc6fe7ff614b0b8d54bd31b31dd269 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Stroke Volume
121 rdf:type schema:DefinedTerm
122 N68905a73d2374d508642cd5f9d19217a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Heart Ventricles
124 rdf:type schema:DefinedTerm
125 N7c952b9d6240492990c265c10f7aa48b schema:name doi
126 schema:value 10.1007/s12149-013-0713-9
127 rdf:type schema:PropertyValue
128 N7e6707fa839d4547b68dc2205efff2db schema:name dimensions_id
129 schema:value pub.1043950591
130 rdf:type schema:PropertyValue
131 N7feef2647ea74e2394ab8c7cb914da5f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Cardiac-Gated Single-Photon Emission Computer-Assisted Tomography
133 rdf:type schema:DefinedTerm
134 N8489b18e53184d1ba65bce49bc30222c rdf:first sg:person.016646761437.40
135 rdf:rest rdf:nil
136 N91247551fbfa4495a321424b50c2dd14 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
137 schema:name Adult
138 rdf:type schema:DefinedTerm
139 Na12e9aec01ab4cdfbbc4f73b9196d1d5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name Young Adult
141 rdf:type schema:DefinedTerm
142 Na26cbe550f9645568706466651b8d4fe schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Adolescent
144 rdf:type schema:DefinedTerm
145 Nab5fdf5eca7b41209af4ea017c201858 schema:name pubmed_id
146 schema:value 23494211
147 rdf:type schema:PropertyValue
148 Nc4875a8121d240c48b0fc2d4832a0419 schema:volumeNumber 27
149 rdf:type schema:PublicationVolume
150 Nc6bd309795e34cb88772f3527e83738e rdf:first sg:person.0770717233.47
151 rdf:rest N3b108d4fac084726a08976129e7d4f1e
152 Ncbd3afc24c9641318e9a2a038da4d5a6 rdf:first sg:person.01035121045.59
153 rdf:rest N18672319de3542e9814b61ce9e3ec1d9
154 Ncdca2a210bd04ceab4e66d56fd6a353b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Diagnostic Errors
156 rdf:type schema:DefinedTerm
157 Ncf8a84a88d6e4de0a68efa151ba12df9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Aged, 80 and over
159 rdf:type schema:DefinedTerm
160 Nd17da714525a40c19261c050be07dcba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
161 schema:name Hypertrophy
162 rdf:type schema:DefinedTerm
163 Nd7a1012aa6384efdbe047db7f70d8249 schema:name Springer Nature - SN SciGraph project
164 rdf:type schema:Organization
165 Ne571350604334107a49f805a33919985 schema:issueNumber 6
166 rdf:type schema:PublicationIssue
167 Ne7d9fa833f5842f5b2baefbdb7307c73 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name Male
169 rdf:type schema:DefinedTerm
170 Ne848802699ee49938e303890062916d9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
171 schema:name Aged
172 rdf:type schema:DefinedTerm
173 Nf8e047fd5def400abd103b13224087f0 rdf:first sg:person.0651160643.16
174 rdf:rest Ncbd3afc24c9641318e9a2a038da4d5a6
175 Nfc760cfde50345e1a22a4a7c86735e66 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
176 schema:name Humans
177 rdf:type schema:DefinedTerm
178 Nfd130c3fdf804aa1b8957ab488e3c220 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
179 schema:name Software
180 rdf:type schema:DefinedTerm
181 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
182 schema:name Medical and Health Sciences
183 rdf:type schema:DefinedTerm
184 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
185 schema:name Cardiorespiratory Medicine and Haematology
186 rdf:type schema:DefinedTerm
187 sg:journal.1099601 schema:issn 0914-7187
188 1864-6433
189 schema:name Annals of Nuclear Medicine
190 schema:publisher Springer Nature
191 rdf:type schema:Periodical
192 sg:person.01015206307.54 schema:affiliation grid-institutes:grid.410821.e
193 schema:familyName Toba
194 schema:givenName Masahiro
195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01015206307.54
196 rdf:type schema:Person
197 sg:person.01035121045.59 schema:affiliation grid-institutes:grid.410821.e
198 schema:familyName Ishihara
199 schema:givenName Keiichi
200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035121045.59
201 rdf:type schema:Person
202 sg:person.01224612517.39 schema:affiliation grid-institutes:grid.410821.e
203 schema:familyName Mizuno
204 schema:givenName Kyoichi
205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01224612517.39
206 rdf:type schema:Person
207 sg:person.016646761437.40 schema:affiliation grid-institutes:grid.410821.e
208 schema:familyName Kumita
209 schema:givenName Shin-ichiro
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016646761437.40
211 rdf:type schema:Person
212 sg:person.0651160643.16 schema:affiliation grid-institutes:grid.410821.e
213 schema:familyName Amano
214 schema:givenName Yasuo
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651160643.16
216 rdf:type schema:Person
217 sg:person.0770717233.47 schema:affiliation grid-institutes:grid.410821.e
218 schema:familyName Yamaguchi
219 schema:givenName Hidenori
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0770717233.47
221 rdf:type schema:Person
222 sg:pub.10.1007/bf03006666 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011682616
223 https://doi.org/10.1007/bf03006666
224 rdf:type schema:CreativeWork
225 sg:pub.10.1016/s1071-3581(98)90178-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027961359
226 https://doi.org/10.1016/s1071-3581(98)90178-7
227 rdf:type schema:CreativeWork
228 grid-institutes:grid.410821.e schema:alternateName Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan
229 Division of Cardiology, Hepatology, Geriatrics and Integrated Medicine, Department of Internal Medicine, Nippon Medical School, Tokyo, Japan
230 schema:name Department of Radiology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, 113-8603, Tokyo, Japan
231 Division of Cardiology, Hepatology, Geriatrics and Integrated Medicine, Department of Internal Medicine, Nippon Medical School, Tokyo, Japan
232 rdf:type schema:Organization
 




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


...