Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-02-22

AUTHORS

Huimin Lin, Hongjiang Wei, Naying He, Caixia Fu, Shu Cheng, Jun Shen, Baisong Wang, Xu Yan, Chunlei Liu, Fuhua Yan

ABSTRACT

PurposesTo evaluate the feasibility of simultaneous quantification of liver iron concentration (LIC) and fat fraction (FF) using water-fat separation and quantitative susceptibility mapping (QSM).MethodsForty-five patients suspected of liver iron overload (LIO) were included. A volumetric interpolated breath-hold examination sequence for QSM and FF, a fat-saturated gradient echo sequence for R2*, a spin echo sequence for LIC measurements and MRS analyses for FF (FF-MRS) were performed. Magnetic susceptibility and FF were calculated using a water-fat separation method (FF-MRI). Correlation and receiver operating characteristic analyses were performed.ResultsMagnetic susceptibility showed strong correlation with LIC (rs=0.918). The optimal susceptibility cut-off values were 0.34, 0.63, 1.29 and 2.23 ppm corresponding to LIC thresholds of 1.8, 3.2, 7.0 and 15.0 mg/g dry weight. The area under the curve (AUC) were 0.948, 0.970, 1 and 1, respectively. No difference in AUC was found between susceptibility and R2* at all LIC thresholds. Correlation was found between FF-MRI and FF-MRS (R2=0.910).ConclusionsQSM has a high diagnostic performance for LIC quantification, similar to that of R2*. FF-MRI provides simultaneous fat quantification. Findings suggest QSM in combination with water-fat separation has potential value for evaluating LIO, especially in cases with coexisting steatosis.Key Points• Magnetic susceptibility showed strong correlation with LIC (rs=0.918).• QSM showed high diagnostic performance for LIC, similar to that of R2*.• Simultaneously estimated FF-MRI showed strong correlation with MR-Spectroscopy-based FF (R2=0.910).• QSM combining water-fat separation has quantitative value for LIO with coexisted steatosis. More... »

PAGES

3494-3504

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-017-5263-4

DOI

http://dx.doi.org/10.1007/s00330-017-5263-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101172092

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29470640


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": "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": "Fatty Liver", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Feasibility Studies", 
        "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": "Iron", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Iron Overload", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Liver", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Magnetic Resonance Spectroscopy", 
        "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": "Prospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "ROC Curve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Water", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Young Adult", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lin", 
        "givenName": "Huimin", 
        "id": "sg:person.01135534766.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01135534766.57"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.47840.3f", 
          "name": [
            "Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wei", 
        "givenName": "Hongjiang", 
        "id": "sg:person.0734623073.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734623073.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "He", 
        "givenName": "Naying", 
        "id": "sg:person.0624343701.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624343701.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fu", 
        "givenName": "Caixia", 
        "id": "sg:person.01113325663.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113325663.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cheng", 
        "givenName": "Shu", 
        "id": "sg:person.01211625611.73", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211625611.73"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shen", 
        "givenName": "Jun", 
        "id": "sg:person.013114572124.97", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013114572124.97"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biological Statistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Biological Statistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Baisong", 
        "id": "sg:person.0777460172.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0777460172.41"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.452598.7", 
          "name": [
            "MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yan", 
        "givenName": "Xu", 
        "id": "sg:person.01265137305.80", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265137305.80"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.47840.3f", 
          "name": [
            "Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA", 
            "Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Chunlei", 
        "id": "sg:person.01153363405.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01153363405.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China", 
          "id": "http://www.grid.ac/institutes/grid.16821.3c", 
          "name": [
            "Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yan", 
        "givenName": "Fuhua", 
        "id": "sg:person.0755107271.57", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755107271.57"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00261-017-1048-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053762367", 
          "https://doi.org/10.1007/s00261-017-1048-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00330-012-2506-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020522015", 
          "https://doi.org/10.1007/s00330-012-2506-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00431-007-0604-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041401761", 
          "https://doi.org/10.1007/s00431-007-0604-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-02-22", 
    "datePublishedReg": "2018-02-22", 
    "description": "PurposesTo evaluate the feasibility of simultaneous quantification of liver iron concentration (LIC) and fat fraction (FF) using water-fat separation and quantitative susceptibility mapping (QSM).MethodsForty-five patients suspected of liver iron overload (LIO) were included. A volumetric interpolated breath-hold examination sequence for QSM and FF, a fat-saturated gradient echo sequence for R2*, a spin echo sequence for LIC measurements and MRS analyses for FF (FF-MRS) were performed. Magnetic susceptibility and FF were calculated using a water-fat separation method (FF-MRI). Correlation and receiver operating characteristic analyses were performed.ResultsMagnetic susceptibility showed strong correlation with LIC (rs=0.918). The optimal susceptibility cut-off values were 0.34, 0.63, 1.29 and 2.23 ppm corresponding to LIC thresholds of 1.8, 3.2, 7.0 and 15.0 mg/g dry weight. The area under the curve (AUC) were 0.948, 0.970, 1 and 1, respectively. No difference in AUC was found between susceptibility and R2* at all LIC thresholds. Correlation was found between FF-MRI and FF-MRS (R2=0.910).ConclusionsQSM has a high diagnostic performance for LIC quantification, similar to that of R2*. FF-MRI provides simultaneous fat quantification. Findings suggest QSM in combination with water-fat separation has potential value for evaluating LIO, especially in cases with coexisting steatosis.Key Points\u2022 Magnetic susceptibility showed strong correlation with LIC (rs=0.918).\u2022 QSM showed high diagnostic performance for LIC, similar to that of R2*.\u2022 Simultaneously estimated FF-MRI showed strong correlation with MR-Spectroscopy-based FF (R2=0.910).\u2022 QSM combining water-fat separation has quantitative value for LIO with coexisted steatosis.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s00330-017-5263-4", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3536947", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3804700", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2552667", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.8359777", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3859259", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1289120", 
        "issn": [
          "0938-7994", 
          "1432-1084"
        ], 
        "name": "European Radiology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "8", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "28"
      }
    ], 
    "keywords": [
      "liver iron concentration", 
      "liver iron overload", 
      "water-fat separation", 
      "high diagnostic performance", 
      "quantitative susceptibility mapping", 
      "fat fraction", 
      "diagnostic performance", 
      "MethodsForty-five patients", 
      "breath-hold examination (VIBE) sequence", 
      "iron overload", 
      "liver iron", 
      "echo sequence", 
      "water-fat separation method", 
      "MR spectroscopy", 
      "gradient echo sequence", 
      "MRS analysis", 
      "LIC measurements", 
      "strong correlation", 
      "spin-echo sequence", 
      "steatosis", 
      "fat quantification", 
      "separation method", 
      "characteristic analysis", 
      "examination sequence", 
      "fat fraction quantification", 
      "susceptibility", 
      "susceptibility mapping", 
      "patients", 
      "PurposesTo", 
      "separation", 
      "optimal susceptibility", 
      "iron concentration", 
      "correlation", 
      "AUC", 
      "performance", 
      "potential value", 
      "simultaneous quantification", 
      "overload", 
      "magnetic susceptibility", 
      "findings", 
      "quantitative values", 
      "quantification", 
      "combination", 
      "R2", 
      "differences", 
      "feasibility", 
      "weight", 
      "cases", 
      "measurements", 
      "values", 
      "iron", 
      "analysis", 
      "concentration", 
      "receiver", 
      "ppm", 
      "method", 
      "curves", 
      "mapping", 
      "fraction", 
      "dry weight", 
      "area", 
      "sequence"
    ], 
    "name": "Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification", 
    "pagination": "3494-3504", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1101172092"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00330-017-5263-4"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "29470640"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00330-017-5263-4", 
      "https://app.dimensions.ai/details/publication/pub.1101172092"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:44", 
    "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_787.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s00330-017-5263-4"
  }
]
 

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/s00330-017-5263-4'

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/s00330-017-5263-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-5263-4'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00330-017-5263-4'


 

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

291 TRIPLES      21 PREDICATES      107 URIs      96 LITERALS      24 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00330-017-5263-4 schema:about N06566fcf83e7498e80de614827b5c9f2
2 N1f54eea0927b4634a605dc312822343f
3 N342ea2131d3949cd9a81ea00d9ff2bf4
4 N4282cbcf062e4c54bf3409b648888fef
5 N479f75e9d16c43d7bb8a9237a62b635d
6 N54cec2f43b354efbb25e84f57f708f82
7 N7b3859345bc24c96a01d307acff8c3a3
8 N7c9f1f270a0d4dc9a550e22300003b81
9 N879e76655c044a7db14673cbceea640c
10 N888130e1c0c94272818d2c80252e2529
11 N8a5bf43811e24e6babe38c80abf1ebdf
12 N9aa6c2794b3c4b3eb8e8771f9c809424
13 N9b2e21a708714f17b6d54afc81d9201e
14 Na4810db11d49484bbe6afdebfad1b285
15 Na664f06e78c64b96923eb34ed2207d0c
16 Nae6f7d7729784409b23349da04a55ac5
17 Nd03da398ef884a429cd1a49757a03b45
18 anzsrc-for:11
19 anzsrc-for:1103
20 schema:author N091423f4e49d4b2ab0cdb438b680a418
21 schema:citation sg:pub.10.1007/s00261-017-1048-0
22 sg:pub.10.1007/s00330-012-2506-2
23 sg:pub.10.1007/s00431-007-0604-y
24 schema:datePublished 2018-02-22
25 schema:datePublishedReg 2018-02-22
26 schema:description PurposesTo evaluate the feasibility of simultaneous quantification of liver iron concentration (LIC) and fat fraction (FF) using water-fat separation and quantitative susceptibility mapping (QSM).MethodsForty-five patients suspected of liver iron overload (LIO) were included. A volumetric interpolated breath-hold examination sequence for QSM and FF, a fat-saturated gradient echo sequence for R2*, a spin echo sequence for LIC measurements and MRS analyses for FF (FF-MRS) were performed. Magnetic susceptibility and FF were calculated using a water-fat separation method (FF-MRI). Correlation and receiver operating characteristic analyses were performed.ResultsMagnetic susceptibility showed strong correlation with LIC (rs=0.918). The optimal susceptibility cut-off values were 0.34, 0.63, 1.29 and 2.23 ppm corresponding to LIC thresholds of 1.8, 3.2, 7.0 and 15.0 mg/g dry weight. The area under the curve (AUC) were 0.948, 0.970, 1 and 1, respectively. No difference in AUC was found between susceptibility and R2* at all LIC thresholds. Correlation was found between FF-MRI and FF-MRS (R2=0.910).ConclusionsQSM has a high diagnostic performance for LIC quantification, similar to that of R2*. FF-MRI provides simultaneous fat quantification. Findings suggest QSM in combination with water-fat separation has potential value for evaluating LIO, especially in cases with coexisting steatosis.Key Points• Magnetic susceptibility showed strong correlation with LIC (rs=0.918).• QSM showed high diagnostic performance for LIC, similar to that of R2*.• Simultaneously estimated FF-MRI showed strong correlation with MR-Spectroscopy-based FF (R2=0.910).• QSM combining water-fat separation has quantitative value for LIO with coexisted steatosis.
27 schema:genre article
28 schema:isAccessibleForFree true
29 schema:isPartOf N4ebbdbbb612c40ccacbbacbee0b81a48
30 Ncaf6670f3e9a4c78a63428b91d0adeeb
31 sg:journal.1289120
32 schema:keywords AUC
33 LIC measurements
34 MR spectroscopy
35 MRS analysis
36 MethodsForty-five patients
37 PurposesTo
38 R2
39 analysis
40 area
41 breath-hold examination (VIBE) sequence
42 cases
43 characteristic analysis
44 combination
45 concentration
46 correlation
47 curves
48 diagnostic performance
49 differences
50 dry weight
51 echo sequence
52 examination sequence
53 fat fraction
54 fat fraction quantification
55 fat quantification
56 feasibility
57 findings
58 fraction
59 gradient echo sequence
60 high diagnostic performance
61 iron
62 iron concentration
63 iron overload
64 liver iron
65 liver iron concentration
66 liver iron overload
67 magnetic susceptibility
68 mapping
69 measurements
70 method
71 optimal susceptibility
72 overload
73 patients
74 performance
75 potential value
76 ppm
77 quantification
78 quantitative susceptibility mapping
79 quantitative values
80 receiver
81 separation
82 separation method
83 sequence
84 simultaneous quantification
85 spin-echo sequence
86 steatosis
87 strong correlation
88 susceptibility
89 susceptibility mapping
90 values
91 water-fat separation
92 water-fat separation method
93 weight
94 schema:name Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification
95 schema:pagination 3494-3504
96 schema:productId N28cbf92bf73f4c5380f6df7e9a15e754
97 N986b5ad8dd0740c0a9f21716dfd678b7
98 Nafa059147ee54b5ead84a4b78ff7d361
99 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101172092
100 https://doi.org/10.1007/s00330-017-5263-4
101 schema:sdDatePublished 2022-10-01T06:44
102 schema:sdLicense https://scigraph.springernature.com/explorer/license/
103 schema:sdPublisher N61984c2c1d8049c0983c66162d5f5bab
104 schema:url https://doi.org/10.1007/s00330-017-5263-4
105 sgo:license sg:explorer/license/
106 sgo:sdDataset articles
107 rdf:type schema:ScholarlyArticle
108 N06566fcf83e7498e80de614827b5c9f2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name ROC Curve
110 rdf:type schema:DefinedTerm
111 N091423f4e49d4b2ab0cdb438b680a418 rdf:first sg:person.01135534766.57
112 rdf:rest N182ed5a4c0ac42e2bbc3b44613bccef9
113 N0b74bbc91ffe4ba9b1e58cfe4519ff70 rdf:first sg:person.01113325663.07
114 rdf:rest N4f3b91f074a94eef86bd6881b7867916
115 N182ed5a4c0ac42e2bbc3b44613bccef9 rdf:first sg:person.0734623073.42
116 rdf:rest Na5b93380c4f2409fb0c436159bf2cf30
117 N1f54eea0927b4634a605dc312822343f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Female
119 rdf:type schema:DefinedTerm
120 N226cce47aeba42f5b0aa1e822df0c9c3 rdf:first sg:person.013114572124.97
121 rdf:rest N78e18bef43b34c93954d506f65bbc8f5
122 N28cbf92bf73f4c5380f6df7e9a15e754 schema:name doi
123 schema:value 10.1007/s00330-017-5263-4
124 rdf:type schema:PropertyValue
125 N342ea2131d3949cd9a81ea00d9ff2bf4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
126 schema:name Humans
127 rdf:type schema:DefinedTerm
128 N3d65ed721d1046098aaec248430124c0 rdf:first sg:person.01153363405.15
129 rdf:rest Nf5ce2dd580eb47d585ad113f55a3adad
130 N4282cbcf062e4c54bf3409b648888fef schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Feasibility Studies
132 rdf:type schema:DefinedTerm
133 N479f75e9d16c43d7bb8a9237a62b635d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Liver
135 rdf:type schema:DefinedTerm
136 N4ebbdbbb612c40ccacbbacbee0b81a48 schema:issueNumber 8
137 rdf:type schema:PublicationIssue
138 N4f3b91f074a94eef86bd6881b7867916 rdf:first sg:person.01211625611.73
139 rdf:rest N226cce47aeba42f5b0aa1e822df0c9c3
140 N54cec2f43b354efbb25e84f57f708f82 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
141 schema:name Adult
142 rdf:type schema:DefinedTerm
143 N61984c2c1d8049c0983c66162d5f5bab schema:name Springer Nature - SN SciGraph project
144 rdf:type schema:Organization
145 N78e18bef43b34c93954d506f65bbc8f5 rdf:first sg:person.0777460172.41
146 rdf:rest Ne79ffa3ca5514fcba8c63acbc381d243
147 N7b3859345bc24c96a01d307acff8c3a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Middle Aged
149 rdf:type schema:DefinedTerm
150 N7c9f1f270a0d4dc9a550e22300003b81 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
151 schema:name Prospective Studies
152 rdf:type schema:DefinedTerm
153 N879e76655c044a7db14673cbceea640c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
154 schema:name Young Adult
155 rdf:type schema:DefinedTerm
156 N888130e1c0c94272818d2c80252e2529 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
157 schema:name Iron Overload
158 rdf:type schema:DefinedTerm
159 N8a5bf43811e24e6babe38c80abf1ebdf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
160 schema:name Fatty Liver
161 rdf:type schema:DefinedTerm
162 N986b5ad8dd0740c0a9f21716dfd678b7 schema:name dimensions_id
163 schema:value pub.1101172092
164 rdf:type schema:PropertyValue
165 N9aa6c2794b3c4b3eb8e8771f9c809424 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
166 schema:name Adolescent
167 rdf:type schema:DefinedTerm
168 N9b2e21a708714f17b6d54afc81d9201e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
169 schema:name Aged
170 rdf:type schema:DefinedTerm
171 Na4810db11d49484bbe6afdebfad1b285 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
172 schema:name Magnetic Resonance Spectroscopy
173 rdf:type schema:DefinedTerm
174 Na5b93380c4f2409fb0c436159bf2cf30 rdf:first sg:person.0624343701.28
175 rdf:rest N0b74bbc91ffe4ba9b1e58cfe4519ff70
176 Na664f06e78c64b96923eb34ed2207d0c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
177 schema:name Male
178 rdf:type schema:DefinedTerm
179 Nae6f7d7729784409b23349da04a55ac5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
180 schema:name Iron
181 rdf:type schema:DefinedTerm
182 Nafa059147ee54b5ead84a4b78ff7d361 schema:name pubmed_id
183 schema:value 29470640
184 rdf:type schema:PropertyValue
185 Ncaf6670f3e9a4c78a63428b91d0adeeb schema:volumeNumber 28
186 rdf:type schema:PublicationVolume
187 Nd03da398ef884a429cd1a49757a03b45 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
188 schema:name Water
189 rdf:type schema:DefinedTerm
190 Ne79ffa3ca5514fcba8c63acbc381d243 rdf:first sg:person.01265137305.80
191 rdf:rest N3d65ed721d1046098aaec248430124c0
192 Nf5ce2dd580eb47d585ad113f55a3adad rdf:first sg:person.0755107271.57
193 rdf:rest rdf:nil
194 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
195 schema:name Medical and Health Sciences
196 rdf:type schema:DefinedTerm
197 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
198 schema:name Clinical Sciences
199 rdf:type schema:DefinedTerm
200 sg:grant.2552667 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-017-5263-4
201 rdf:type schema:MonetaryGrant
202 sg:grant.3536947 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-017-5263-4
203 rdf:type schema:MonetaryGrant
204 sg:grant.3804700 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-017-5263-4
205 rdf:type schema:MonetaryGrant
206 sg:grant.3859259 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-017-5263-4
207 rdf:type schema:MonetaryGrant
208 sg:grant.8359777 http://pending.schema.org/fundedItem sg:pub.10.1007/s00330-017-5263-4
209 rdf:type schema:MonetaryGrant
210 sg:journal.1289120 schema:issn 0938-7994
211 1432-1084
212 schema:name European Radiology
213 schema:publisher Springer Nature
214 rdf:type schema:Periodical
215 sg:person.01113325663.07 schema:affiliation grid-institutes:None
216 schema:familyName Fu
217 schema:givenName Caixia
218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113325663.07
219 rdf:type schema:Person
220 sg:person.01135534766.57 schema:affiliation grid-institutes:grid.16821.3c
221 schema:familyName Lin
222 schema:givenName Huimin
223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01135534766.57
224 rdf:type schema:Person
225 sg:person.01153363405.15 schema:affiliation grid-institutes:grid.47840.3f
226 schema:familyName Liu
227 schema:givenName Chunlei
228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01153363405.15
229 rdf:type schema:Person
230 sg:person.01211625611.73 schema:affiliation grid-institutes:grid.16821.3c
231 schema:familyName Cheng
232 schema:givenName Shu
233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211625611.73
234 rdf:type schema:Person
235 sg:person.01265137305.80 schema:affiliation grid-institutes:grid.452598.7
236 schema:familyName Yan
237 schema:givenName Xu
238 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265137305.80
239 rdf:type schema:Person
240 sg:person.013114572124.97 schema:affiliation grid-institutes:grid.16821.3c
241 schema:familyName Shen
242 schema:givenName Jun
243 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013114572124.97
244 rdf:type schema:Person
245 sg:person.0624343701.28 schema:affiliation grid-institutes:grid.16821.3c
246 schema:familyName He
247 schema:givenName Naying
248 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624343701.28
249 rdf:type schema:Person
250 sg:person.0734623073.42 schema:affiliation grid-institutes:grid.47840.3f
251 schema:familyName Wei
252 schema:givenName Hongjiang
253 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0734623073.42
254 rdf:type schema:Person
255 sg:person.0755107271.57 schema:affiliation grid-institutes:grid.16821.3c
256 schema:familyName Yan
257 schema:givenName Fuhua
258 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0755107271.57
259 rdf:type schema:Person
260 sg:person.0777460172.41 schema:affiliation grid-institutes:grid.16821.3c
261 schema:familyName Wang
262 schema:givenName Baisong
263 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0777460172.41
264 rdf:type schema:Person
265 sg:pub.10.1007/s00261-017-1048-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053762367
266 https://doi.org/10.1007/s00261-017-1048-0
267 rdf:type schema:CreativeWork
268 sg:pub.10.1007/s00330-012-2506-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020522015
269 https://doi.org/10.1007/s00330-012-2506-2
270 rdf:type schema:CreativeWork
271 sg:pub.10.1007/s00431-007-0604-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1041401761
272 https://doi.org/10.1007/s00431-007-0604-y
273 rdf:type schema:CreativeWork
274 grid-institutes:None schema:alternateName Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
275 schema:name Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
276 rdf:type schema:Organization
277 grid-institutes:grid.16821.3c schema:alternateName Department of Biological Statistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
278 Department of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
279 Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China
280 schema:name Department of Biological Statistics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
281 Department of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
282 Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, NO. 197 Ruijin Er Road, 200025, Shanghai, China
283 rdf:type schema:Organization
284 grid-institutes:grid.452598.7 schema:alternateName MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China
285 schema:name MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China
286 rdf:type schema:Organization
287 grid-institutes:grid.47840.3f schema:alternateName Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
288 Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
289 schema:name Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
290 Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
291 rdf:type schema:Organization
 




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


...