Specificity of unenhanced CT for non-invasive diagnosis of hepatic steatosis: implications for the investigation of the natural history of incidental ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2011-12-04

AUTHORS

Perry J. Pickhardt, Seong Ho Park, Luke Hahn, Sung-Gyu Lee, Kyongtae T. Bae, Eun Sil Yu

ABSTRACT

ObjectivesTo determine a highly specific liver attenuation threshold at unenhanced CT for biopsy-proven moderate to severe hepatic steatosis (≥30% at histology).Methods315 asymptomatic adults (mean age ± SD, 31.5 ± 10.1 years; 207 men, 108 women) underwent same-day unenhanced liver CT and ultrasound-guided liver biopsy. Blinded to biopsy results, CT liver attenuation was measured using standard region-of-interest methodology. Multiple linear regression analysis was used to assess the relationship of CT liver attenuation with patient age, gender, BMI, CT system, and hepatic fat and iron content.ResultsThirty-nine subjects had moderate to severe steatosis and 276 had mild or no steatosis. A liver attenuation threshold of 48 HU was 100% specific (276/276) for moderate to severe steatosis, with no false-positives. Sensitivity, PPV and NPV at this HU threshold was 53.8%, 100% and 93.9%. Hepatic fat content was the overwhelming determinant of liver attenuation values, but CT system (P < 0.001), and hepatic iron (P = 0.035) also had a statistically significant independent association.ConclusionsUnenhanced CT liver attenuation alone is highly specific for moderate to severe hepatic steatosis, allowing for confident non-invasive identification of large retrospective/prospective cohorts for natural history evaluation of incidental non-alcoholic fatty liver disease. Low sensitivity, however, precludes effective population screening at this threshold.Key Points• Unenhanced CT liver attenuation is highly specific for diagnosing moderate/severe hepatic steatosis.• Unenhanced CT can identify large cohorts for epidemiological studies of incidental steatosis.• Unenhanced CT is not, however, effective for population screening for hepatic steatosis. More... »

PAGES

1075-1082

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-011-2349-2

DOI

http://dx.doi.org/10.1007/s00330-011-2349-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047959732

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22138733


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/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Contrast Media", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Fatty Liver", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Incidental Findings", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Prevalence", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reproducibility of Results", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Republic of Korea", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sensitivity and Specificity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Single-Blind Method", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Tomography, X-Ray Computed", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA", 
          "id": "http://www.grid.ac/institutes/grid.14003.36", 
          "name": [
            "Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pickhardt", 
        "givenName": "Perry J.", 
        "id": "sg:person.0655054701.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655054701.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea", 
          "id": "http://www.grid.ac/institutes/grid.413967.e", 
          "name": [
            "Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Park", 
        "givenName": "Seong Ho", 
        "id": "sg:person.015772471604.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015772471604.12"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA", 
          "id": "http://www.grid.ac/institutes/grid.14003.36", 
          "name": [
            "Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hahn", 
        "givenName": "Luke", 
        "id": "sg:person.01225600520.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225600520.97"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Division of Hepatobiliary Surgery and Liver Transplantation, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea", 
          "id": "http://www.grid.ac/institutes/grid.413967.e", 
          "name": [
            "Division of Hepatobiliary Surgery and Liver Transplantation, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Sung-Gyu", 
        "id": "sg:person.01141712025.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01141712025.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, University of Pittsburgh, 3950 Presbyterian South Tower, 200 Lothrop Street, 15213, Pittsburgh, PA, USA", 
          "id": "http://www.grid.ac/institutes/grid.21925.3d", 
          "name": [
            "Department of Radiology, University of Pittsburgh, 3950 Presbyterian South Tower, 200 Lothrop Street, 15213, Pittsburgh, PA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bae", 
        "givenName": "Kyongtae T.", 
        "id": "sg:person.0643713263.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0643713263.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea", 
          "id": "http://www.grid.ac/institutes/grid.413967.e", 
          "name": [
            "Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yu", 
        "givenName": "Eun Sil", 
        "id": "sg:person.01067052537.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01067052537.11"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00330-009-1560-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005865660", 
          "https://doi.org/10.1007/s00330-009-1560-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1111/j.1572-0241.2008.02034.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051861633", 
          "https://doi.org/10.1111/j.1572-0241.2008.02034.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1111/j.1572-0241.2003.07486.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049967292", 
          "https://doi.org/10.1111/j.1572-0241.2003.07486.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1111/j.1572-0241.1999.01377.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015032643", 
          "https://doi.org/10.1111/j.1572-0241.1999.01377.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1111/j.1572-0241.2008.02188.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045256414", 
          "https://doi.org/10.1111/j.1572-0241.2008.02188.x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1005416727424", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003973437", 
          "https://doi.org/10.1023/a:1005416727424"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-12-04", 
    "datePublishedReg": "2011-12-04", 
    "description": "ObjectivesTo determine a highly specific liver attenuation threshold at unenhanced CT for biopsy-proven moderate to severe hepatic steatosis (\u226530% at histology).Methods315 asymptomatic adults (mean age\u2009\u00b1\u2009SD, 31.5\u2009\u00b1\u200910.1\u00a0years; 207 men, 108 women) underwent same-day unenhanced liver CT and ultrasound-guided liver biopsy. Blinded to biopsy results, CT liver attenuation was measured using standard region-of-interest methodology. Multiple linear regression analysis was used to assess the relationship of CT liver attenuation with patient age, gender, BMI, CT system, and hepatic fat and iron content.ResultsThirty-nine subjects had moderate to severe steatosis and 276 had mild or no steatosis. A liver attenuation threshold of 48 HU was 100% specific (276/276) for moderate to severe steatosis, with no false-positives. Sensitivity, PPV and NPV at this HU threshold was 53.8%, 100% and 93.9%. Hepatic fat content was the overwhelming determinant of liver attenuation values, but CT system (P\u2009<\u20090.001), and hepatic iron (P\u2009=\u20090.035) also had a statistically significant independent association.ConclusionsUnenhanced CT liver attenuation alone is highly specific for moderate to severe hepatic steatosis, allowing for confident non-invasive identification of large retrospective/prospective cohorts for natural history evaluation of incidental non-alcoholic fatty liver disease. Low sensitivity, however, precludes effective population screening at this threshold.Key Points\u2022 Unenhanced CT liver attenuation is highly specific for diagnosing moderate/severe hepatic steatosis.\u2022 Unenhanced CT can identify large cohorts for epidemiological studies of incidental steatosis.\u2022 Unenhanced CT is not, however, effective for population screening for hepatic steatosis.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00330-011-2349-2", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1289120", 
        "issn": [
          "0938-7994", 
          "1432-1084"
        ], 
        "name": "European Radiology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "22"
      }
    ], 
    "keywords": [
      "severe hepatic steatosis", 
      "hepatic steatosis", 
      "liver attenuation", 
      "unenhanced CT", 
      "severe steatosis", 
      "non-alcoholic fatty liver disease", 
      "ultrasound-guided liver biopsy", 
      "fatty liver disease", 
      "liver attenuation values", 
      "significant independent association", 
      "hepatic fat content", 
      "non-invasive diagnosis", 
      "attenuation threshold", 
      "prospective cohort", 
      "liver biopsy", 
      "patient age", 
      "asymptomatic adults", 
      "liver disease", 
      "biopsy results", 
      "hepatic fat", 
      "multiple linear regression analysis", 
      "independent association", 
      "hepatic iron", 
      "large cohort", 
      "steatosis", 
      "epidemiological studies", 
      "linear regression analysis", 
      "interest methodology", 
      "natural history", 
      "HU threshold", 
      "liver CT", 
      "CT", 
      "non-invasive identification", 
      "history evaluation", 
      "regression analysis", 
      "cohort", 
      "attenuation values", 
      "low sensitivity", 
      "fat content", 
      "BMI", 
      "biopsy", 
      "population", 
      "ObjectivesTo", 
      "disease", 
      "diagnosis", 
      "CT system", 
      "overwhelming determinant", 
      "adults", 
      "age", 
      "standard region", 
      "fat", 
      "attenuation", 
      "PPV", 
      "association", 
      "subjects", 
      "sensitivity", 
      "threshold", 
      "gender", 
      "NPV", 
      "specificity", 
      "determinants", 
      "iron content", 
      "HU", 
      "history", 
      "evaluation", 
      "study", 
      "effective population", 
      "identification", 
      "relationship", 
      "investigation", 
      "analysis", 
      "implications", 
      "results", 
      "content", 
      "values", 
      "region", 
      "system", 
      "iron", 
      "methodology", 
      "specific liver attenuation threshold", 
      "liver attenuation threshold", 
      "Methods315 asymptomatic adults", 
      "same-day unenhanced liver CT", 
      "unenhanced liver CT", 
      "CT liver attenuation", 
      "ConclusionsUnenhanced CT liver attenuation", 
      "confident non-invasive identification", 
      "natural history evaluation", 
      "incidental non-alcoholic fatty liver disease", 
      "Unenhanced CT liver attenuation", 
      "incidental steatosis"
    ], 
    "name": "Specificity of unenhanced CT for non-invasive diagnosis of hepatic steatosis: implications for the investigation of the natural history of incidental steatosis", 
    "pagination": "1075-1082", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1047959732"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00330-011-2349-2"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22138733"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00330-011-2349-2", 
      "https://app.dimensions.ai/details/publication/pub.1047959732"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-11-01T18:16", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211101/entities/gbq_results/article/article_544.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00330-011-2349-2"
  }
]
 

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

HOW TO GET THIS DATA PROGRAMMATICALLY:

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

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00330-011-2349-2'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00330-011-2349-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-011-2349-2'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-011-2349-2'


 

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

274 TRIPLES      22 PREDICATES      136 URIs      122 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00330-011-2349-2 schema:about N186532e4aee9493fa37284baf28bc709
2 N3091d82971c248ec9a955a8d6bf67848
3 N400e03cd068e46d2b355bc6750df54f4
4 N48f6444300cc488888edab99c649eb3c
5 N552495a942914f7294cb36e38d5aedaa
6 N5e75a7803f9f4809bc6f0a522969e36b
7 N7ff14ad6ebae45118beaa677ec6c6588
8 N8458da52941249e48e31ee8d0adb1d71
9 N8f43e0b50966452889f36c32a45ffebb
10 N9d3ad5d2bab342e49225f4c02ba98239
11 Na5fc0c10a09e4adc868fb0e4e9c964ee
12 Nc7096d4c4bcd4b039b59ca1648668a84
13 Ne926442c9073416f9beac633ccc1a8f1
14 anzsrc-for:11
15 anzsrc-for:1103
16 schema:author Ne18336c4eed5452a9d6c22cdaab78d81
17 schema:citation sg:pub.10.1007/s00330-009-1560-x
18 sg:pub.10.1023/a:1005416727424
19 sg:pub.10.1111/j.1572-0241.1999.01377.x
20 sg:pub.10.1111/j.1572-0241.2003.07486.x
21 sg:pub.10.1111/j.1572-0241.2008.02034.x
22 sg:pub.10.1111/j.1572-0241.2008.02188.x
23 schema:datePublished 2011-12-04
24 schema:datePublishedReg 2011-12-04
25 schema:description ObjectivesTo determine a highly specific liver attenuation threshold at unenhanced CT for biopsy-proven moderate to severe hepatic steatosis (≥30% at histology).Methods315 asymptomatic adults (mean age ± SD, 31.5 ± 10.1 years; 207 men, 108 women) underwent same-day unenhanced liver CT and ultrasound-guided liver biopsy. Blinded to biopsy results, CT liver attenuation was measured using standard region-of-interest methodology. Multiple linear regression analysis was used to assess the relationship of CT liver attenuation with patient age, gender, BMI, CT system, and hepatic fat and iron content.ResultsThirty-nine subjects had moderate to severe steatosis and 276 had mild or no steatosis. A liver attenuation threshold of 48 HU was 100% specific (276/276) for moderate to severe steatosis, with no false-positives. Sensitivity, PPV and NPV at this HU threshold was 53.8%, 100% and 93.9%. Hepatic fat content was the overwhelming determinant of liver attenuation values, but CT system (P < 0.001), and hepatic iron (P = 0.035) also had a statistically significant independent association.ConclusionsUnenhanced CT liver attenuation alone is highly specific for moderate to severe hepatic steatosis, allowing for confident non-invasive identification of large retrospective/prospective cohorts for natural history evaluation of incidental non-alcoholic fatty liver disease. Low sensitivity, however, precludes effective population screening at this threshold.Key Points• Unenhanced CT liver attenuation is highly specific for diagnosing moderate/severe hepatic steatosis.• Unenhanced CT can identify large cohorts for epidemiological studies of incidental steatosis.• Unenhanced CT is not, however, effective for population screening for hepatic steatosis.
26 schema:genre article
27 schema:inLanguage en
28 schema:isAccessibleForFree false
29 schema:isPartOf N2c28bc9ed3b645e1a6131665c2dcc85b
30 Nde845a2cdd1041ed98cdf9d4e324863f
31 sg:journal.1289120
32 schema:keywords BMI
33 CT
34 CT liver attenuation
35 CT system
36 ConclusionsUnenhanced CT liver attenuation
37 HU
38 HU threshold
39 Methods315 asymptomatic adults
40 NPV
41 ObjectivesTo
42 PPV
43 Unenhanced CT liver attenuation
44 adults
45 age
46 analysis
47 association
48 asymptomatic adults
49 attenuation
50 attenuation threshold
51 attenuation values
52 biopsy
53 biopsy results
54 cohort
55 confident non-invasive identification
56 content
57 determinants
58 diagnosis
59 disease
60 effective population
61 epidemiological studies
62 evaluation
63 fat
64 fat content
65 fatty liver disease
66 gender
67 hepatic fat
68 hepatic fat content
69 hepatic iron
70 hepatic steatosis
71 history
72 history evaluation
73 identification
74 implications
75 incidental non-alcoholic fatty liver disease
76 incidental steatosis
77 independent association
78 interest methodology
79 investigation
80 iron
81 iron content
82 large cohort
83 linear regression analysis
84 liver CT
85 liver attenuation
86 liver attenuation threshold
87 liver attenuation values
88 liver biopsy
89 liver disease
90 low sensitivity
91 methodology
92 multiple linear regression analysis
93 natural history
94 natural history evaluation
95 non-alcoholic fatty liver disease
96 non-invasive diagnosis
97 non-invasive identification
98 overwhelming determinant
99 patient age
100 population
101 prospective cohort
102 region
103 regression analysis
104 relationship
105 results
106 same-day unenhanced liver CT
107 sensitivity
108 severe hepatic steatosis
109 severe steatosis
110 significant independent association
111 specific liver attenuation threshold
112 specificity
113 standard region
114 steatosis
115 study
116 subjects
117 system
118 threshold
119 ultrasound-guided liver biopsy
120 unenhanced CT
121 unenhanced liver CT
122 values
123 schema:name Specificity of unenhanced CT for non-invasive diagnosis of hepatic steatosis: implications for the investigation of the natural history of incidental steatosis
124 schema:pagination 1075-1082
125 schema:productId N31ea90f0743d4a788eb607938f975635
126 N79ba051e5e59405ebf86d2330848e180
127 Nb110ec2b599a476ea3650f493eb1ba0c
128 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047959732
129 https://doi.org/10.1007/s00330-011-2349-2
130 schema:sdDatePublished 2021-11-01T18:16
131 schema:sdLicense https://scigraph.springernature.com/explorer/license/
132 schema:sdPublisher N3535c02903334c1da96544831ecf6477
133 schema:url https://doi.org/10.1007/s00330-011-2349-2
134 sgo:license sg:explorer/license/
135 sgo:sdDataset articles
136 rdf:type schema:ScholarlyArticle
137 N186532e4aee9493fa37284baf28bc709 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Contrast Media
139 rdf:type schema:DefinedTerm
140 N2c28bc9ed3b645e1a6131665c2dcc85b schema:volumeNumber 22
141 rdf:type schema:PublicationVolume
142 N2c4205f79fce4bdf86e1fabb351a11d5 rdf:first sg:person.01141712025.28
143 rdf:rest N6dd6fba73b824d64aee94b6f4744a30e
144 N3091d82971c248ec9a955a8d6bf67848 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name Humans
146 rdf:type schema:DefinedTerm
147 N31ea90f0743d4a788eb607938f975635 schema:name pubmed_id
148 schema:value 22138733
149 rdf:type schema:PropertyValue
150 N3417b8043ded48eabd83125e804a3e38 rdf:first sg:person.01067052537.11
151 rdf:rest rdf:nil
152 N3535c02903334c1da96544831ecf6477 schema:name Springer Nature - SN SciGraph project
153 rdf:type schema:Organization
154 N400e03cd068e46d2b355bc6750df54f4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Tomography, X-Ray Computed
156 rdf:type schema:DefinedTerm
157 N48f6444300cc488888edab99c649eb3c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Incidental Findings
159 rdf:type schema:DefinedTerm
160 N552495a942914f7294cb36e38d5aedaa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
161 schema:name Prevalence
162 rdf:type schema:DefinedTerm
163 N5e75a7803f9f4809bc6f0a522969e36b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
164 schema:name Reproducibility of Results
165 rdf:type schema:DefinedTerm
166 N6d589cf387b748a39bd584084e0dcfec rdf:first sg:person.015772471604.12
167 rdf:rest Nf2430a2fee13468e9a75b813f755d172
168 N6dd6fba73b824d64aee94b6f4744a30e rdf:first sg:person.0643713263.46
169 rdf:rest N3417b8043ded48eabd83125e804a3e38
170 N79ba051e5e59405ebf86d2330848e180 schema:name dimensions_id
171 schema:value pub.1047959732
172 rdf:type schema:PropertyValue
173 N7ff14ad6ebae45118beaa677ec6c6588 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
174 schema:name Single-Blind Method
175 rdf:type schema:DefinedTerm
176 N8458da52941249e48e31ee8d0adb1d71 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
177 schema:name Fatty Liver
178 rdf:type schema:DefinedTerm
179 N8f43e0b50966452889f36c32a45ffebb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
180 schema:name Female
181 rdf:type schema:DefinedTerm
182 N9d3ad5d2bab342e49225f4c02ba98239 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
183 schema:name Republic of Korea
184 rdf:type schema:DefinedTerm
185 Na5fc0c10a09e4adc868fb0e4e9c964ee schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
186 schema:name Male
187 rdf:type schema:DefinedTerm
188 Nb110ec2b599a476ea3650f493eb1ba0c schema:name doi
189 schema:value 10.1007/s00330-011-2349-2
190 rdf:type schema:PropertyValue
191 Nc7096d4c4bcd4b039b59ca1648668a84 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
192 schema:name Sensitivity and Specificity
193 rdf:type schema:DefinedTerm
194 Nde845a2cdd1041ed98cdf9d4e324863f schema:issueNumber 5
195 rdf:type schema:PublicationIssue
196 Ne18336c4eed5452a9d6c22cdaab78d81 rdf:first sg:person.0655054701.18
197 rdf:rest N6d589cf387b748a39bd584084e0dcfec
198 Ne926442c9073416f9beac633ccc1a8f1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
199 schema:name Adult
200 rdf:type schema:DefinedTerm
201 Nf2430a2fee13468e9a75b813f755d172 rdf:first sg:person.01225600520.97
202 rdf:rest N2c4205f79fce4bdf86e1fabb351a11d5
203 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
204 schema:name Medical and Health Sciences
205 rdf:type schema:DefinedTerm
206 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
207 schema:name Clinical Sciences
208 rdf:type schema:DefinedTerm
209 sg:journal.1289120 schema:issn 0938-7994
210 1432-1084
211 schema:name European Radiology
212 schema:publisher Springer Nature
213 rdf:type schema:Periodical
214 sg:person.01067052537.11 schema:affiliation grid-institutes:grid.413967.e
215 schema:familyName Yu
216 schema:givenName Eun Sil
217 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01067052537.11
218 rdf:type schema:Person
219 sg:person.01141712025.28 schema:affiliation grid-institutes:grid.413967.e
220 schema:familyName Lee
221 schema:givenName Sung-Gyu
222 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01141712025.28
223 rdf:type schema:Person
224 sg:person.01225600520.97 schema:affiliation grid-institutes:grid.14003.36
225 schema:familyName Hahn
226 schema:givenName Luke
227 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01225600520.97
228 rdf:type schema:Person
229 sg:person.015772471604.12 schema:affiliation grid-institutes:grid.413967.e
230 schema:familyName Park
231 schema:givenName Seong Ho
232 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015772471604.12
233 rdf:type schema:Person
234 sg:person.0643713263.46 schema:affiliation grid-institutes:grid.21925.3d
235 schema:familyName Bae
236 schema:givenName Kyongtae T.
237 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0643713263.46
238 rdf:type schema:Person
239 sg:person.0655054701.18 schema:affiliation grid-institutes:grid.14003.36
240 schema:familyName Pickhardt
241 schema:givenName Perry J.
242 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0655054701.18
243 rdf:type schema:Person
244 sg:pub.10.1007/s00330-009-1560-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1005865660
245 https://doi.org/10.1007/s00330-009-1560-x
246 rdf:type schema:CreativeWork
247 sg:pub.10.1023/a:1005416727424 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003973437
248 https://doi.org/10.1023/a:1005416727424
249 rdf:type schema:CreativeWork
250 sg:pub.10.1111/j.1572-0241.1999.01377.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1015032643
251 https://doi.org/10.1111/j.1572-0241.1999.01377.x
252 rdf:type schema:CreativeWork
253 sg:pub.10.1111/j.1572-0241.2003.07486.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1049967292
254 https://doi.org/10.1111/j.1572-0241.2003.07486.x
255 rdf:type schema:CreativeWork
256 sg:pub.10.1111/j.1572-0241.2008.02034.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1051861633
257 https://doi.org/10.1111/j.1572-0241.2008.02034.x
258 rdf:type schema:CreativeWork
259 sg:pub.10.1111/j.1572-0241.2008.02188.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1045256414
260 https://doi.org/10.1111/j.1572-0241.2008.02188.x
261 rdf:type schema:CreativeWork
262 grid-institutes:grid.14003.36 schema:alternateName Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA
263 schema:name Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave., 53792-3252, Madison, WI, USA
264 rdf:type schema:Organization
265 grid-institutes:grid.21925.3d schema:alternateName Department of Radiology, University of Pittsburgh, 3950 Presbyterian South Tower, 200 Lothrop Street, 15213, Pittsburgh, PA, USA
266 schema:name Department of Radiology, University of Pittsburgh, 3950 Presbyterian South Tower, 200 Lothrop Street, 15213, Pittsburgh, PA, USA
267 rdf:type schema:Organization
268 grid-institutes:grid.413967.e schema:alternateName Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
269 Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
270 Division of Hepatobiliary Surgery and Liver Transplantation, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
271 schema:name Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
272 Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
273 Division of Hepatobiliary Surgery and Liver Transplantation, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Asanbyeongwon-gil 86, Songpa-gu, 138-736, Seoul, Korea
274 rdf:type schema:Organization
 




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


...