Quantitative colorimetry of atherosclerotic plaque using the L*a*b* color space during angioscopy for the detection of lipid cores underneath thin ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-02-22

AUTHORS

Fumiyuki Ishibashi, Shinya Yokoyama, Kengo Miyahara, Alexandra Dabreo, Eric R. Weiss, Mark Iafrati, Masamichi Takano, Kentaro Okamatsu, Kyoichi Mizuno, Sergio Waxman

ABSTRACT

ObjectivesYellow plaques seen during angioscopy are thought to represent lipid cores underneath thin fibrous caps (LCTCs) and may be indicative of vulnerable sites. However, plaque color assessment during angioscopy has been criticized because of its qualitative nature. The purpose of the present study was to test the ability of a quantitative colorimetric system to measure yellow color intensity of atherosclerotic plaques during angioscopy and to characterize the color of LCTCs.MethodsUsing angioscopy and a quantitative colorimetry system based on the L*a*b* color space [L* describes brightness (−100 to +100), b* describes blue to yellow (−100 to +100)], the optimal conditions for measuring plaque color were determined in three flat standard color samples and five artificial plaque models in cylinder porcine carotid arteries. In 88 human tissue samples, the colorimetric characteristics of LCTCs were then evaluated.ResultsIn in-vitro samples and ex-vivo plaque models, brightness L* between 40 and 80 was determined to be optimal for acquiring b* values, and the variables unique to angioscopy in color perception did not impact b* values after adjusting for brightness L* by manipulating light or distance. In ex-vivo human tissue samples, b* value ≥23 (35.91 ± 8.13) with L* between 40 and 80 was associated with LCTCs (fibrous caps <100 μm).ConclusionsAtherosclerotic plaque color can be consistently measured during angioscopy with quantitative colorimetry. High yellow color intensity, determined by this system, was associated with LCTCs. Quantitative colorimetry during angioscopy may be used for detection of LCTCs, which may be markers of vulnerability. More... »

PAGES

679-691

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10554-007-9212-1

DOI

http://dx.doi.org/10.1007/s10554-007-9212-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017336855

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17318361


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": "Angioscopy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Atherosclerosis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Colorimetry", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Coronary Vessels", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "In Vitro Techniques", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lipids", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Statistics, Nonparametric", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Swine", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.67033.31", 
          "name": [
            "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ishibashi", 
        "givenName": "Fumiyuki", 
        "id": "sg:person.0734777155.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734777155.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yokoyama", 
        "givenName": "Shinya", 
        "id": "sg:person.010736012462.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010736012462.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute of Archaeological Research Kyoto, Kyoto, Japan", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Institute of Archaeological Research Kyoto, Kyoto, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Miyahara", 
        "givenName": "Kengo", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.67033.31", 
          "name": [
            "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Dabreo", 
        "givenName": "Alexandra", 
        "id": "sg:person.01000427437.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000427437.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.67033.31", 
          "name": [
            "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Weiss", 
        "givenName": "Eric R.", 
        "id": "sg:person.01356013173.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01356013173.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Vascular Surgery, Tufts New England Medical Center, Boston, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.67033.31", 
          "name": [
            "Department of Vascular Surgery, Tufts New England Medical Center, Boston, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Iafrati", 
        "givenName": "Mark", 
        "id": "sg:person.01100171343.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01100171343.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takano", 
        "givenName": "Masamichi", 
        "id": "sg:person.0611573717.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611573717.76"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okamatsu", 
        "givenName": "Kentaro", 
        "id": "sg:person.0727046016.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727046016.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan", 
          "id": "http://www.grid.ac/institutes/grid.410821.e", 
          "name": [
            "Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, 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": "Lahey Clinic Medical Center, 41 Mall Road, 01805, Burlington, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.415731.5", 
          "name": [
            "Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA", 
            "Lahey Clinic Medical Center, 41 Mall Road, 01805, Burlington, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Waxman", 
        "givenName": "Sergio", 
        "id": "sg:person.01312304602.88", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01312304602.88"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1023/b:caim.0000021951.03735.60", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001059525", 
          "https://doi.org/10.1023/b:caim.0000021951.03735.60"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2007-02-22", 
    "datePublishedReg": "2007-02-22", 
    "description": "ObjectivesYellow plaques seen during angioscopy are thought to represent lipid cores underneath thin fibrous caps (LCTCs) and may be indicative of vulnerable sites. However, plaque color assessment during angioscopy has been criticized because of its qualitative nature. The purpose of the present study was to test the ability of a quantitative colorimetric system to measure yellow color intensity of atherosclerotic plaques during angioscopy and to characterize the color of LCTCs.MethodsUsing angioscopy and a quantitative colorimetry system based on the L*a*b* color space [L* describes brightness (\u2212100 to +100), b* describes blue to yellow (\u2212100 to +100)], the optimal conditions for measuring plaque color were determined in three flat standard color samples and five artificial plaque models in cylinder porcine carotid arteries. In 88 human tissue samples, the colorimetric characteristics of LCTCs were then evaluated.ResultsIn in-vitro samples and ex-vivo plaque models, brightness L* between 40 and 80 was determined to be optimal for acquiring b* values, and the variables unique to angioscopy in color perception did not impact b* values after adjusting for brightness L* by manipulating light or distance. In ex-vivo human tissue samples, b* value \u226523 (35.91\u00a0\u00b1\u00a08.13) with L* between 40 and 80 was associated with LCTCs (fibrous caps <100\u00a0\u03bcm).ConclusionsAtherosclerotic plaque color can be consistently measured during angioscopy with quantitative colorimetry. High yellow color intensity, determined by this system, was associated with LCTCs. Quantitative colorimetry during angioscopy may be used for detection of LCTCs, which may be markers of vulnerability.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s10554-007-9212-1", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1025429", 
        "issn": [
          "1569-5794", 
          "1573-0743"
        ], 
        "name": "The International Journal of Cardiovascular Imaging", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "23"
      }
    ], 
    "keywords": [
      "thin fibrous cap", 
      "atherosclerotic plaques", 
      "fibrous cap", 
      "human tissue samples", 
      "plaque color", 
      "plaque model", 
      "tissue samples", 
      "lipid core", 
      "marker of vulnerability", 
      "carotid artery", 
      "angioscopy", 
      "porcine carotid arteries", 
      "quantitative colorimetry", 
      "plaques", 
      "yellow color intensity", 
      "present study", 
      "vulnerable sites", 
      "artery", 
      "ResultsIn", 
      "color assessment", 
      "markers", 
      "samples", 
      "assessment", 
      "color perception", 
      "study", 
      "detection", 
      "colorimetry", 
      "LCTC", 
      "values", 
      "purpose", 
      "cap", 
      "ability", 
      "color intensity", 
      "intensity", 
      "sites", 
      "variables", 
      "perception", 
      "vulnerability", 
      "model", 
      "characteristics", 
      "system", 
      "qualitative nature", 
      "conditions", 
      "standard color samples", 
      "color", 
      "light", 
      "nature", 
      "colorimetric system", 
      "optimal conditions", 
      "space", 
      "distance", 
      "core", 
      "color samples", 
      "brightness L", 
      "color space", 
      "colorimetric characteristics", 
      "colorimetry system"
    ], 
    "name": "Quantitative colorimetry of atherosclerotic plaque using the L*a*b* color space during angioscopy for the detection of lipid cores underneath thin fibrous caps", 
    "pagination": "679-691", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1017336855"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10554-007-9212-1"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "17318361"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10554-007-9212-1", 
      "https://app.dimensions.ai/details/publication/pub.1017336855"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T15:53", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_436.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s10554-007-9212-1"
  }
]
 

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/s10554-007-9212-1'

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/s10554-007-9212-1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10554-007-9212-1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10554-007-9212-1'


 

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

240 TRIPLES      21 PREDICATES      94 URIs      85 LITERALS      18 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10554-007-9212-1 schema:about N2ac261a0e15c42e1a9b339b78e63bb37
2 N30241b0ac74d469c8cfd3c4cb6aa7919
3 N4bf3f1a1d8124db4ae7a452f17f66c30
4 N775f5a396799479d824788ed8a188bab
5 N788ab1d4af824ee3a0a15b6c54720b9f
6 Na28396bb154140caae76f76b080c3c95
7 Na5af2819ebf04fe590f2c99dca6faba9
8 Nbb36403b4fda480da68a5eefa0b52d4a
9 Ne3710d3ff7664fa18b4f18890de0a4d5
10 Ne38f93f20c6c48e1b9e6bc879581687f
11 Nf2a7ace843f640bdb851b4d3af5b4ee8
12 anzsrc-for:11
13 anzsrc-for:1102
14 schema:author N323a3f1d4d2e4c7c87ea60dddbfb185c
15 schema:citation sg:pub.10.1023/b:caim.0000021951.03735.60
16 schema:datePublished 2007-02-22
17 schema:datePublishedReg 2007-02-22
18 schema:description ObjectivesYellow plaques seen during angioscopy are thought to represent lipid cores underneath thin fibrous caps (LCTCs) and may be indicative of vulnerable sites. However, plaque color assessment during angioscopy has been criticized because of its qualitative nature. The purpose of the present study was to test the ability of a quantitative colorimetric system to measure yellow color intensity of atherosclerotic plaques during angioscopy and to characterize the color of LCTCs.MethodsUsing angioscopy and a quantitative colorimetry system based on the L*a*b* color space [L* describes brightness (−100 to +100), b* describes blue to yellow (−100 to +100)], the optimal conditions for measuring plaque color were determined in three flat standard color samples and five artificial plaque models in cylinder porcine carotid arteries. In 88 human tissue samples, the colorimetric characteristics of LCTCs were then evaluated.ResultsIn in-vitro samples and ex-vivo plaque models, brightness L* between 40 and 80 was determined to be optimal for acquiring b* values, and the variables unique to angioscopy in color perception did not impact b* values after adjusting for brightness L* by manipulating light or distance. In ex-vivo human tissue samples, b* value ≥23 (35.91 ± 8.13) with L* between 40 and 80 was associated with LCTCs (fibrous caps <100 μm).ConclusionsAtherosclerotic plaque color can be consistently measured during angioscopy with quantitative colorimetry. High yellow color intensity, determined by this system, was associated with LCTCs. Quantitative colorimetry during angioscopy may be used for detection of LCTCs, which may be markers of vulnerability.
19 schema:genre article
20 schema:isAccessibleForFree false
21 schema:isPartOf N4656ec8ed6e94dcbaf5255af77c9246a
22 Ne4e32a1b9c5040b9a63a64cf476e3997
23 sg:journal.1025429
24 schema:keywords LCTC
25 ResultsIn
26 ability
27 angioscopy
28 artery
29 assessment
30 atherosclerotic plaques
31 brightness L
32 cap
33 carotid artery
34 characteristics
35 color
36 color assessment
37 color intensity
38 color perception
39 color samples
40 color space
41 colorimetric characteristics
42 colorimetric system
43 colorimetry
44 colorimetry system
45 conditions
46 core
47 detection
48 distance
49 fibrous cap
50 human tissue samples
51 intensity
52 light
53 lipid core
54 marker of vulnerability
55 markers
56 model
57 nature
58 optimal conditions
59 perception
60 plaque color
61 plaque model
62 plaques
63 porcine carotid arteries
64 present study
65 purpose
66 qualitative nature
67 quantitative colorimetry
68 samples
69 sites
70 space
71 standard color samples
72 study
73 system
74 thin fibrous cap
75 tissue samples
76 values
77 variables
78 vulnerability
79 vulnerable sites
80 yellow color intensity
81 schema:name Quantitative colorimetry of atherosclerotic plaque using the L*a*b* color space during angioscopy for the detection of lipid cores underneath thin fibrous caps
82 schema:pagination 679-691
83 schema:productId N692cc556222144a7b316c86b7f70dda7
84 N7c15ebf48fca4d118d771d9377707349
85 Nfbfe9a453d2142a99c2ea008a8a1915a
86 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017336855
87 https://doi.org/10.1007/s10554-007-9212-1
88 schema:sdDatePublished 2022-09-02T15:53
89 schema:sdLicense https://scigraph.springernature.com/explorer/license/
90 schema:sdPublisher N5fe99753afac4b718cf8c07b57d5d737
91 schema:url https://doi.org/10.1007/s10554-007-9212-1
92 sgo:license sg:explorer/license/
93 sgo:sdDataset articles
94 rdf:type schema:ScholarlyArticle
95 N1919858c4800478e96f2fdc8b0b5e99f rdf:first sg:person.01356013173.52
96 rdf:rest N22599c00de464e9fb9ebaafbf34b4e9e
97 N22599c00de464e9fb9ebaafbf34b4e9e rdf:first sg:person.01100171343.20
98 rdf:rest Nfe82bc5bc80a49fe88c3ef2251f3aa62
99 N2ac261a0e15c42e1a9b339b78e63bb37 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Humans
101 rdf:type schema:DefinedTerm
102 N30241b0ac74d469c8cfd3c4cb6aa7919 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
103 schema:name In Vitro Techniques
104 rdf:type schema:DefinedTerm
105 N323a3f1d4d2e4c7c87ea60dddbfb185c rdf:first sg:person.0734777155.06
106 rdf:rest N97da0092a0de42ecbda01005fdac3a24
107 N4656ec8ed6e94dcbaf5255af77c9246a schema:issueNumber 6
108 rdf:type schema:PublicationIssue
109 N484be2c1927e4514b2f493eb8ca23ed4 rdf:first sg:person.01312304602.88
110 rdf:rest rdf:nil
111 N4bf3f1a1d8124db4ae7a452f17f66c30 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Angioscopy
113 rdf:type schema:DefinedTerm
114 N5fe99753afac4b718cf8c07b57d5d737 schema:name Springer Nature - SN SciGraph project
115 rdf:type schema:Organization
116 N692cc556222144a7b316c86b7f70dda7 schema:name doi
117 schema:value 10.1007/s10554-007-9212-1
118 rdf:type schema:PropertyValue
119 N719943cf152e4458b53eb3c664936b8a rdf:first sg:person.0727046016.53
120 rdf:rest Nb05b91b54de44be6955d3522a580d5bc
121 N775f5a396799479d824788ed8a188bab schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
122 schema:name Swine
123 rdf:type schema:DefinedTerm
124 N788ab1d4af824ee3a0a15b6c54720b9f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Animals
126 rdf:type schema:DefinedTerm
127 N7c15ebf48fca4d118d771d9377707349 schema:name pubmed_id
128 schema:value 17318361
129 rdf:type schema:PropertyValue
130 N8ed1e9b22192403b9f6e7e257585615c rdf:first sg:person.01000427437.80
131 rdf:rest N1919858c4800478e96f2fdc8b0b5e99f
132 N97da0092a0de42ecbda01005fdac3a24 rdf:first sg:person.010736012462.52
133 rdf:rest Nacdaf3ef7d4746aa9de44001f5d70937
134 Na28396bb154140caae76f76b080c3c95 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name Atherosclerosis
136 rdf:type schema:DefinedTerm
137 Na5af2819ebf04fe590f2c99dca6faba9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Coronary Vessels
139 rdf:type schema:DefinedTerm
140 Nabee906acf2c4bb5b24ebb5bba8c4804 schema:affiliation grid-institutes:None
141 schema:familyName Miyahara
142 schema:givenName Kengo
143 rdf:type schema:Person
144 Nacdaf3ef7d4746aa9de44001f5d70937 rdf:first Nabee906acf2c4bb5b24ebb5bba8c4804
145 rdf:rest N8ed1e9b22192403b9f6e7e257585615c
146 Nb05b91b54de44be6955d3522a580d5bc rdf:first sg:person.01224612517.39
147 rdf:rest N484be2c1927e4514b2f493eb8ca23ed4
148 Nbb36403b4fda480da68a5eefa0b52d4a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
149 schema:name Lipids
150 rdf:type schema:DefinedTerm
151 Ne3710d3ff7664fa18b4f18890de0a4d5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name Colorimetry
153 rdf:type schema:DefinedTerm
154 Ne38f93f20c6c48e1b9e6bc879581687f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Statistics, Nonparametric
156 rdf:type schema:DefinedTerm
157 Ne4e32a1b9c5040b9a63a64cf476e3997 schema:volumeNumber 23
158 rdf:type schema:PublicationVolume
159 Nf2a7ace843f640bdb851b4d3af5b4ee8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
160 schema:name Reproducibility of Results
161 rdf:type schema:DefinedTerm
162 Nfbfe9a453d2142a99c2ea008a8a1915a schema:name dimensions_id
163 schema:value pub.1017336855
164 rdf:type schema:PropertyValue
165 Nfe82bc5bc80a49fe88c3ef2251f3aa62 rdf:first sg:person.0611573717.76
166 rdf:rest N719943cf152e4458b53eb3c664936b8a
167 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
168 schema:name Medical and Health Sciences
169 rdf:type schema:DefinedTerm
170 anzsrc-for:1102 schema:inDefinedTermSet anzsrc-for:
171 schema:name Cardiorespiratory Medicine and Haematology
172 rdf:type schema:DefinedTerm
173 sg:journal.1025429 schema:issn 1569-5794
174 1573-0743
175 schema:name The International Journal of Cardiovascular Imaging
176 schema:publisher Springer Nature
177 rdf:type schema:Periodical
178 sg:person.01000427437.80 schema:affiliation grid-institutes:grid.67033.31
179 schema:familyName Dabreo
180 schema:givenName Alexandra
181 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01000427437.80
182 rdf:type schema:Person
183 sg:person.010736012462.52 schema:affiliation grid-institutes:grid.410821.e
184 schema:familyName Yokoyama
185 schema:givenName Shinya
186 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010736012462.52
187 rdf:type schema:Person
188 sg:person.01100171343.20 schema:affiliation grid-institutes:grid.67033.31
189 schema:familyName Iafrati
190 schema:givenName Mark
191 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01100171343.20
192 rdf:type schema:Person
193 sg:person.01224612517.39 schema:affiliation grid-institutes:grid.410821.e
194 schema:familyName Mizuno
195 schema:givenName Kyoichi
196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01224612517.39
197 rdf:type schema:Person
198 sg:person.01312304602.88 schema:affiliation grid-institutes:grid.415731.5
199 schema:familyName Waxman
200 schema:givenName Sergio
201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01312304602.88
202 rdf:type schema:Person
203 sg:person.01356013173.52 schema:affiliation grid-institutes:grid.67033.31
204 schema:familyName Weiss
205 schema:givenName Eric R.
206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01356013173.52
207 rdf:type schema:Person
208 sg:person.0611573717.76 schema:affiliation grid-institutes:grid.410821.e
209 schema:familyName Takano
210 schema:givenName Masamichi
211 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0611573717.76
212 rdf:type schema:Person
213 sg:person.0727046016.53 schema:affiliation grid-institutes:grid.410821.e
214 schema:familyName Okamatsu
215 schema:givenName Kentaro
216 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0727046016.53
217 rdf:type schema:Person
218 sg:person.0734777155.06 schema:affiliation grid-institutes:grid.67033.31
219 schema:familyName Ishibashi
220 schema:givenName Fumiyuki
221 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734777155.06
222 rdf:type schema:Person
223 sg:pub.10.1023/b:caim.0000021951.03735.60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001059525
224 https://doi.org/10.1023/b:caim.0000021951.03735.60
225 rdf:type schema:CreativeWork
226 grid-institutes:None schema:alternateName Institute of Archaeological Research Kyoto, Kyoto, Japan
227 schema:name Institute of Archaeological Research Kyoto, Kyoto, Japan
228 rdf:type schema:Organization
229 grid-institutes:grid.410821.e schema:alternateName Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan
230 schema:name Department of Internal Medicine, Chiba-Hokusoh Hospital, Nippon Medical School, Chiba, Japan
231 rdf:type schema:Organization
232 grid-institutes:grid.415731.5 schema:alternateName Lahey Clinic Medical Center, 41 Mall Road, 01805, Burlington, MA, USA
233 schema:name Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA
234 Lahey Clinic Medical Center, 41 Mall Road, 01805, Burlington, MA, USA
235 rdf:type schema:Organization
236 grid-institutes:grid.67033.31 schema:alternateName Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA
237 Department of Vascular Surgery, Tufts New England Medical Center, Boston, MA, USA
238 schema:name Center for Translational Cardiovascular Research, Tufts New England Medical Center, Boston, MA, USA
239 Department of Vascular Surgery, Tufts New England Medical Center, Boston, MA, USA
240 rdf:type schema:Organization
 




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


...