Using a 3% Proton Density Fat Fraction as a Cut-Off Value Increases Sensitivity of Detection of Hepatic Steatosis, Based on Results From Histopathology Analysis

It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to d...

Full description

Saved in:
Bibliographic Details
Published inGastroenterology Vol. 153; no. 1; pp. 53 - 55.e7
Main Authors Nasr, Patrik, Forsgren, Mikael F., Ignatova, Simone, Dahlström, Nils, Cedersund, Gunnar, Leinhard, Olof Dahlqvist, Norén, Bengt, Ekstedt, Mattias, Lundberg, Peter, Kechagias, Stergios
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.07.2017
Elsevier BV
Subjects
Online AccessGet full text

Cover

Loading…
Abstract It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of 1H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, 1H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the 1H-MRS PDFF findings with SPCs (r = 0.92; P < .001). 1H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.
AbstractList It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy ( H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the H-MRS PDFF findings with SPCs (r = 0.92; P < .001). H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of 1H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, 1H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the 1H-MRS PDFF findings with SPCs (r = 0.92; P < .001). 1H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of 1H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, 1H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the 1H-MRS PDFF findings with SPCs (r = 0.92; P < .001). 1H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of 1H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, 1H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the 1H-MRS PDFF findings with SPCs (r = 0.92; P < .001). 1H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS), instead of collecting and analyzing liver biopsies to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF in measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic, less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (6 months or more) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereological point counts (SPCs). We correlated less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF findings with SPCs (r = 0.92; P less than.001). less thansuperscriptgreater than1less than/superscriptgreater thanH-MRS PDFF results correlated with histopathology results (ρ = 0.87; P less than.001), and SPCs correlated with histopathology results (ρ = 0.88; P less than.001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values below 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve non-invasive detection of steatosis.
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1 H-MRS), instead of collecting and analyzing liver biopsy specimens to detect steatosis. However, the current PDFF cut-off value (5%) used to define steatosis by magnetic resonance was derived from studies that did not use histopathology as the reference standard. We performed a prospective study to determine the accuracy of1 H-MRS PDFF in the measurement of steatosis using histopathology analysis as the standard. We collected clinical, serologic,1 H-MRS PDFF, and liver biopsy data from 94 adult patients with increased levels of liver enzymes (≥6 mo) referred to the Department of Gastroenterology and Hepatology at Linköping University Hospital in Sweden from 2007 through 2014. Steatosis was graded using the conventional histopathology method and fat content was quantified in biopsy samples using stereologic point counts (SPCs). We correlated the1 H-MRS PDFF findings with SPCs (r = 0.92; P < .001).1 H-MRS PDFF results correlated with histopathology results (ρ = 0.87; P < .001), and SPCs correlated with histopathology results (ρ = 0.88; P < .001). All 25 subjects with PDFF values of 5.0% or more had steatosis based on histopathology findings (100% specificity for PDFF). However, of 69 subjects with PDFF values less than 5.0% (negative result), 22 were determined to have steatosis based on histopathology findings (53% sensitivity for PDFF). Reducing the PDFF cut-off value to 3.0% identified patients with steatosis with 100% specificity and 79% sensitivity; a PDFF cut-off value of 2.0% identified patients with steatosis with 94% specificity and 87% sensitivity. These findings might be used to improve noninvasive detection of steatosis.
Author Ignatova, Simone
Ekstedt, Mattias
Kechagias, Stergios
Forsgren, Mikael F.
Norén, Bengt
Nasr, Patrik
Dahlström, Nils
Leinhard, Olof Dahlqvist
Cedersund, Gunnar
Lundberg, Peter
Author_xml – sequence: 1
  givenname: Patrik
  surname: Nasr
  fullname: Nasr, Patrik
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 2
  givenname: Mikael F.
  surname: Forsgren
  fullname: Forsgren, Mikael F.
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 3
  givenname: Simone
  surname: Ignatova
  fullname: Ignatova, Simone
  organization: Department of Clinical and Experimental Medicine, University Hospital, Linköping, Sweden
– sequence: 4
  givenname: Nils
  surname: Dahlström
  fullname: Dahlström, Nils
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 5
  givenname: Gunnar
  surname: Cedersund
  fullname: Cedersund, Gunnar
  organization: Department of Clinical and Experimental Medicine, University Hospital, Linköping, Sweden
– sequence: 6
  givenname: Olof Dahlqvist
  surname: Leinhard
  fullname: Leinhard, Olof Dahlqvist
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 7
  givenname: Bengt
  surname: Norén
  fullname: Norén, Bengt
  organization: Center for Medical Image Science and Visualization (CMIV), University Hospital, Linköping, Sweden
– sequence: 8
  givenname: Mattias
  surname: Ekstedt
  fullname: Ekstedt, Mattias
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 9
  givenname: Peter
  surname: Lundberg
  fullname: Lundberg, Peter
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
– sequence: 10
  givenname: Stergios
  surname: Kechagias
  fullname: Kechagias, Stergios
  email: stergios.kechagias@liu.se
  organization: Department of Medical and Health Sciences, University Hospital, Linköping, Sweden
BackLink https://cir.nii.ac.jp/crid/1872835442883020544$$DView record in CiNii
https://www.ncbi.nlm.nih.gov/pubmed/28286210$$D View this record in MEDLINE/PubMed
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-136544$$DView record from Swedish Publication Index
BookMark eNqFUl1v0zAUjdAQ6wb_ACE_gMQDKf7Ih4MQUukonTRpiI69Wo57U1zSuNjOUP8NP5UbsvEwCe3FlpPz4XuOT5KjznWQJM8ZnTKai7fb6UaH6N2UU1ZOqZhSmj9KJiznMqWU8aNkgluR5lTmx8lJCFtKaSUke5Icc8llwRmdJL-_BdttiCbiFfniXXQdOYMu2HggCx3JwmsTLX7UATHzPqaXTUOuddsDOe-MBx0gkNVfhr0ZWK5BgQgjCw9L2OtoDVlF0NEFG96Qj0haE_z9FULfxoAubkeWNkSH2O-udZsDmXW6PSD8afK40W2AZ7f7aXK1-HQ1X6YXl5_P57OL1BRUxLSuZc6gKmiGQ1aZ1ByaTNR1U-m8whjKOhcco1jnJS-btcmFrIUoSq5ZU8hKnCbpKBt-wb6v1d7bnfYH5bRVZ_Z6ppzfqNb2iokizzLEvx7xe-9-9hCi2tlgoG11B64PismykKyitEToi1toX-9g_U_6rgQEvBsBxrsQPDTK2KiHAKPXtlWMqqFxtVVj42poXFGhsHEkZ_fId_oP0F6OtM5atBtWvDKXAofjUgrK6TjmhxEGGP2NBa-CsdAZWFuPHau1sw_53BcwLboZ3f6AA4St6z0WjXmpwBVVq-HJDi-WlXiFoixQ4P3_BR72_wMVKvqX
CitedBy_id crossref_primary_10_1007_s11428_020_00602_1
crossref_primary_10_1016_j_jrras_2023_100658
crossref_primary_10_1186_s13000_017_0671_y
crossref_primary_10_3748_wjg_v23_i36_6571
crossref_primary_10_1002_oby_23865
crossref_primary_10_1259_bjr_20180701
crossref_primary_10_3390_diagnostics14111138
crossref_primary_10_1007_s00330_023_09798_4
crossref_primary_10_1007_s00330_024_10798_1
crossref_primary_10_1259_bjr_20170959
crossref_primary_10_1002_oby_23174
crossref_primary_10_1016_j_mri_2020_09_027
crossref_primary_10_1177_0379572119858486
crossref_primary_10_1007_s11901_017_0378_2
crossref_primary_10_1210_clinem_dgab541
crossref_primary_10_1259_bjr_20201377
crossref_primary_10_3390_nu11030522
crossref_primary_10_1016_j_metabol_2020_154183
crossref_primary_10_20517_mtod_2023_20
crossref_primary_10_1002_jmri_26601
crossref_primary_10_1097_MOG_0000000000000942
crossref_primary_10_1007_s00261_019_02079_z
crossref_primary_10_1007_s00261_019_02350_3
crossref_primary_10_1016_j_cgh_2020_01_020
crossref_primary_10_1007_s42000_022_00377_8
crossref_primary_10_3748_wjg_v25_i12_1513
crossref_primary_10_1186_s12879_025_10455_y
crossref_primary_10_1210_jc_2018_02795
crossref_primary_10_3748_wjg_v25_i11_1307
crossref_primary_10_1002_hep4_1188
crossref_primary_10_1097_QAD_0000000000002161
crossref_primary_10_1111_liv_14414
crossref_primary_10_1002_mrm_27065
crossref_primary_10_3803_EnM_2020_35_2_243
crossref_primary_10_1186_s12916_024_03779_0
crossref_primary_10_1007_s00125_019_4956_4
crossref_primary_10_3389_fcvm_2022_813427
crossref_primary_10_1111_dom_14905
crossref_primary_10_1371_journal_pone_0255768
crossref_primary_10_1007_s00330_023_09864_x
crossref_primary_10_5812_hepatmon_65537
crossref_primary_10_1016_j_envres_2021_110980
crossref_primary_10_1007_s00330_024_10655_1
crossref_primary_10_4093_dmj_2020_0010
crossref_primary_10_1002_cad_20463
crossref_primary_10_1016_j_jhepr_2020_100197
crossref_primary_10_1111_1471_0528_16199
crossref_primary_10_1007_s00535_024_02096_w
crossref_primary_10_1080_00365521_2020_1786599
crossref_primary_10_1016_j_jhepr_2021_100256
Cites_doi 10.1016/j.jhep.2015.11.004
10.1002/jmri.21809
10.1002/jmri.22580
10.1152/ajpendo.00064.2004
10.1016/0730-725X(94)92543-7
10.1002/nbm.1622
10.1001/archinte.158.16.1789
10.1148/radiol.12120896
10.1002/hep.20701
10.1007/s00330-015-3724-1
10.1007/BF02668096
10.1002/hep.28012
10.1053/j.gastro.2005.03.084
10.1148/radiol.14140754
10.1038/modpathol.3800370
10.1002/hep.27368
10.1002/jmri.22583
10.1097/SLA.0b013e3181bcd6dd
10.1053/j.gastro.2015.04.043
10.1016/j.ejrad.2007.06.004
10.1006/jmre.1997.1244
10.1002/jmri.1880050311
10.1002/jmri.23741
ContentType Journal Article
Copyright 2017 AGA Institute
AGA Institute
Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.
Copyright_xml – notice: 2017 AGA Institute
– notice: AGA Institute
– notice: Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.
DBID RYH
AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
ADTPV
AOWAS
DG8
DOI 10.1053/j.gastro.2017.03.005
DatabaseName CiNii Complete
CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
SwePub
SwePub Articles
SWEPUB Linköpings universitet
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList MEDLINE
MEDLINE - Academic




Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1528-0012
EndPage 55.e7
ExternalDocumentID oai_DiVA_org_liu_136544
28286210
10_1053_j_gastro_2017_03_005
S0016508517302676
1_s2_0_S0016508517302676
Genre Research Support, Non-U.S. Gov't
Journal Article
GroupedDBID ---
--K
.1-
.55
.FO
.GJ
0R~
1B1
1CY
1P~
1~5
3O-
4.4
457
4G.
53G
5GY
5RE
5VS
7-5
AAEDT
AAEDW
AAFWJ
AAIKJ
AALRI
AAQFI
AAQOH
AAQQT
AAQXK
AAXUO
ABCQX
ABDPE
ABJNI
ABLJU
ABMAC
ABOCM
ABWVN
ACRPL
ACVFH
ADBBV
ADCNI
ADMUD
ADNMO
AENEX
AEVXI
AFFNX
AFHKK
AFJKZ
AFRHN
AFTJW
AGCQF
AGHFR
AGQPQ
AI.
AITUG
AJUYK
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
ASPBG
AVWKF
AZFZN
BELOY
BR6
C5W
CAG
COF
CS3
DU5
EBS
EFJIC
EFKBS
EJD
F5P
FD8
FDB
FEDTE
FGOYB
GBLVA
HVGLF
HZ~
IHE
J1W
J5H
K-O
KOM
L7B
M41
MO0
N4W
N9A
NQ-
O9-
OC.
OHT
ON0
P2P
PC.
QTD
R2-
ROL
RPZ
SEL
SES
SJN
SSZ
UDS
UGJ
UV1
VH1
WH7
X7M
XH2
Y6R
YQJ
Z5R
ZGI
ZXP
AAYOK
ADPAM
AFCTW
PKN
RIG
AAIAV
AGZHU
AHPSJ
ALXNB
G8K
TWZ
ZA5
RYH
AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
ADTPV
AOWAS
DG8
ID FETCH-LOGICAL-c603t-bb851e9604009948a2ef43bbf9a590167b532508d5727fdc538b33672a1f6893
ISSN 0016-5085
1528-0012
IngestDate Thu Aug 21 07:05:47 EDT 2025
Tue Aug 05 11:40:53 EDT 2025
Wed Feb 19 02:40:25 EST 2025
Tue Jul 01 02:08:30 EDT 2025
Thu Apr 24 23:04:52 EDT 2025
Thu Jun 26 21:38:28 EDT 2025
Fri Feb 23 02:41:20 EST 2024
Tue Feb 25 20:05:16 EST 2025
Tue Aug 26 20:03:44 EDT 2025
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords 1H-MRS
PDFF
NAFLD
Diagnostic Tests
MRI
Nonalcoholic Fatty Liver Disease
SPC
NASH
magnetic resonance imaging
stereologic point counting
proton density fat fraction
proton magnetic resonance spectroscopy
Language English
License Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c603t-bb851e9604009948a2ef43bbf9a590167b532508d5727fdc538b33672a1f6893
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ORCID 0000-0001-8661-2232
0000-0001-7614-739x
0000-0002-5590-8601
0000-0003-4630-6550
PMID 28286210
PQID 1876819007
PQPubID 23479
ParticipantIDs swepub_primary_oai_DiVA_org_liu_136544
proquest_miscellaneous_1876819007
pubmed_primary_28286210
crossref_citationtrail_10_1053_j_gastro_2017_03_005
crossref_primary_10_1053_j_gastro_2017_03_005
nii_cinii_1872835442883020544
elsevier_sciencedirect_doi_10_1053_j_gastro_2017_03_005
elsevier_clinicalkeyesjournals_1_s2_0_S0016508517302676
elsevier_clinicalkey_doi_10_1053_j_gastro_2017_03_005
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2017-07-01
PublicationDateYYYYMMDD 2017-07-01
PublicationDate_xml – month: 07
  year: 2017
  text: 2017-07-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle Gastroenterology
PublicationTitleAlternate Gastroenterology
PublicationYear 2017
Publisher Elsevier Inc
Elsevier BV
Publisher_xml – name: Elsevier Inc
– name: Elsevier BV
References Franzén (bib2) 2005; 18
Szczepaniak (bib5) 2005; 288
Tang (bib7) 2015; 274
Bannas, Kramer (bib4) 2015; 62
Ekstedt, Hagström (bib9) 2015; 61
Angulo (bib10) 2015; 149
Kleiner (bib1) 2005; 41
Tang (bib6) 2013; 267
(bib8) 2016; 64
Reeder (bib3) 2011; 34
Rehm (bib11) 2015; 25
Kleiner (10.1053/j.gastro.2017.03.005_bib1) 2005; 41
Hamilton (10.1053/j.gastro.2017.03.005_bib27) 2009; 30
Vanhamme (10.1053/j.gastro.2017.03.005_bib15) 1997; 129
Bush (10.1053/j.gastro.2017.03.005_bib12) 1998; 158
10.1053/j.gastro.2017.03.005_bib13
Ratziu (10.1053/j.gastro.2017.03.005_bib28) 2005; 128
Franzén (10.1053/j.gastro.2017.03.005_bib2) 2005; 18
Angulo (10.1053/j.gastro.2017.03.005_bib10) 2015; 149
Rehm (10.1053/j.gastro.2017.03.005_bib11) 2015; 25
El-Badry (10.1053/j.gastro.2017.03.005_bib24) 2009; 250
Reeder (10.1053/j.gastro.2017.03.005_bib3) 2011; 34
Szczepaniak (10.1053/j.gastro.2017.03.005_bib5) 2005; 288
Ekstedt (10.1053/j.gastro.2017.03.005_bib9) 2015; 61
Longo (10.1053/j.gastro.2017.03.005_bib19) 1995; 5
Bannas (10.1053/j.gastro.2017.03.005_bib4) 2015; 62
Thomsen (10.1053/j.gastro.2017.03.005_bib17) 1994; 12
Kleiner (10.1053/j.gastro.2017.03.005_bib20) 2005; 41
(10.1053/j.gastro.2017.03.005_bib8) 2016; 64
Turlin (10.1053/j.gastro.2017.03.005_bib22) 1998; 15
Tang (10.1053/j.gastro.2017.03.005_bib7) 2015; 274
Franzén (10.1053/j.gastro.2017.03.005_bib21) 2005; 18
Hamilton (10.1053/j.gastro.2017.03.005_bib16) 2011; 24
Norén (10.1053/j.gastro.2017.03.005_bib23) 2008; 66
Tang (10.1053/j.gastro.2017.03.005_bib6) 2013; 267
Lee (10.1053/j.gastro.2017.03.005_bib18) 2011; 33
Bannas (10.1053/j.gastro.2017.03.005_bib26) 2015; 62
Naressi (10.1053/j.gastro.2017.03.005_bib14) 2001; 12
Reeder (10.1053/j.gastro.2017.03.005_bib25) 2012; 36
References_xml – volume: 62
  start-page: 1444
  year: 2015
  end-page: 1455
  ident: bib4
  publication-title: Hepatology
– volume: 25
  start-page: 2921
  year: 2015
  end-page: 2930
  ident: bib11
  publication-title: Eur Radiol
– volume: 274
  start-page: 416
  year: 2015
  end-page: 425
  ident: bib7
  publication-title: Radiology
– volume: 288
  start-page: E462
  year: 2005
  end-page: E468
  ident: bib5
  publication-title: Am J Physiol Endocrinol Metab
– volume: 18
  start-page: 912
  year: 2005
  end-page: 916
  ident: bib2
  publication-title: Mod Pathol
– volume: 267
  start-page: 422
  year: 2013
  end-page: 431
  ident: bib6
  publication-title: Radiology
– volume: 149
  start-page: 389
  year: 2015
  end-page: 397
  ident: bib10
  publication-title: Gastroenterology
– volume: 41
  start-page: 1313
  year: 2005
  end-page: 1321
  ident: bib1
  publication-title: Hepatology
– volume: 61
  start-page: 1547
  year: 2015
  end-page: 1554
  ident: bib9
  publication-title: Hepatology
– volume: 34
  start-page: 729
  year: 2011
  end-page: 749
  ident: bib3
  publication-title: J Magn Reson Imaging
– volume: 64
  start-page: 1388
  year: 2016
  end-page: 1402
  ident: bib8
  publication-title: J Hepatol
– volume: 64
  start-page: 1388
  year: 2016
  ident: 10.1053/j.gastro.2017.03.005_bib8
  publication-title: J Hepatol
  doi: 10.1016/j.jhep.2015.11.004
– volume: 30
  start-page: 145
  year: 2009
  ident: 10.1053/j.gastro.2017.03.005_bib27
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.21809
– volume: 34
  start-page: 729
  year: 2011
  ident: 10.1053/j.gastro.2017.03.005_bib3
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.22580
– volume: 288
  start-page: E462
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib5
  publication-title: Am J Physiol Endocrinol Metab
  doi: 10.1152/ajpendo.00064.2004
– volume: 12
  start-page: 487
  year: 1994
  ident: 10.1053/j.gastro.2017.03.005_bib17
  publication-title: Magn Reson Imaging
  doi: 10.1016/0730-725X(94)92543-7
– volume: 15
  start-page: 237
  year: 1998
  ident: 10.1053/j.gastro.2017.03.005_bib22
  publication-title: Semin Diagn Pathol
– volume: 24
  start-page: 784
  year: 2011
  ident: 10.1053/j.gastro.2017.03.005_bib16
  publication-title: NMR Biomed
  doi: 10.1002/nbm.1622
– volume: 158
  start-page: 1789
  year: 1998
  ident: 10.1053/j.gastro.2017.03.005_bib12
  publication-title: Arch Intern Med
  doi: 10.1001/archinte.158.16.1789
– volume: 267
  start-page: 422
  year: 2013
  ident: 10.1053/j.gastro.2017.03.005_bib6
  publication-title: Radiology
  doi: 10.1148/radiol.12120896
– volume: 41
  start-page: 1313
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib1
  publication-title: Hepatology
  doi: 10.1002/hep.20701
– volume: 25
  start-page: 2921
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib11
  publication-title: Eur Radiol
  doi: 10.1007/s00330-015-3724-1
– ident: 10.1053/j.gastro.2017.03.005_bib13
– volume: 41
  start-page: 1313
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib20
  publication-title: Hepatology
  doi: 10.1002/hep.20701
– volume: 12
  start-page: 141
  year: 2001
  ident: 10.1053/j.gastro.2017.03.005_bib14
  publication-title: MAGMA
  doi: 10.1007/BF02668096
– volume: 62
  start-page: 1444
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib26
  publication-title: Hepatology
  doi: 10.1002/hep.28012
– volume: 128
  start-page: 1898
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib28
  publication-title: Gastroenterology
  doi: 10.1053/j.gastro.2005.03.084
– volume: 274
  start-page: 416
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib7
  publication-title: Radiology
  doi: 10.1148/radiol.14140754
– volume: 18
  start-page: 912
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib21
  publication-title: Mod Pathol
  doi: 10.1038/modpathol.3800370
– volume: 61
  start-page: 1547
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib9
  publication-title: Hepatology
  doi: 10.1002/hep.27368
– volume: 33
  start-page: 1390
  year: 2011
  ident: 10.1053/j.gastro.2017.03.005_bib18
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.22583
– volume: 250
  start-page: 691
  year: 2009
  ident: 10.1053/j.gastro.2017.03.005_bib24
  publication-title: Ann Surg
  doi: 10.1097/SLA.0b013e3181bcd6dd
– volume: 149
  start-page: 389
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib10
  publication-title: Gastroenterology
  doi: 10.1053/j.gastro.2015.04.043
– volume: 66
  start-page: 313
  year: 2008
  ident: 10.1053/j.gastro.2017.03.005_bib23
  publication-title: Eur J Radiol
  doi: 10.1016/j.ejrad.2007.06.004
– volume: 129
  start-page: 35
  year: 1997
  ident: 10.1053/j.gastro.2017.03.005_bib15
  publication-title: J Magn Reson
  doi: 10.1006/jmre.1997.1244
– volume: 5
  start-page: 281
  year: 1995
  ident: 10.1053/j.gastro.2017.03.005_bib19
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.1880050311
– volume: 36
  start-page: 1011
  year: 2012
  ident: 10.1053/j.gastro.2017.03.005_bib25
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.23741
– volume: 18
  start-page: 912
  year: 2005
  ident: 10.1053/j.gastro.2017.03.005_bib2
  publication-title: Mod Pathol
  doi: 10.1038/modpathol.3800370
– volume: 62
  start-page: 1444
  year: 2015
  ident: 10.1053/j.gastro.2017.03.005_bib4
  publication-title: Hepatology
  doi: 10.1002/hep.28012
SSID ssj0009381
ssib001235813
ssib050995411
ssib058492786
ssib001224110
ssib000829698
ssib003106730
ssib042166837
Score 2.4546077
Snippet It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy...
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (1...
It is possible to estimate hepatic triglyceride content by calculating the proton density fat fraction (PDFF), using proton magnetic resonance spectroscopy (...
SourceID swepub
proquest
pubmed
crossref
nii
elsevier
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 53
SubjectTerms Adiposity
Adult
Aged
Biopsy
Diagnostic Tests
Female
Gastroenterology and Hepatology
Humans
Liver
Liver - pathology
Magnetic Resonance Spectroscopy
Male
Middle Aged
NASH
Non-alcoholic Fatty Liver Disease
Non-alcoholic Fatty Liver Disease - diagnosis
Non-alcoholic Fatty Liver Disease - pathology
Nonalcoholic Fatty Liver Disease
Prospective Studies
Reference Values
Sensitivity and Specificity
Triglycerides
Triglycerides - analysis
Title Using a 3% Proton Density Fat Fraction as a Cut-Off Value Increases Sensitivity of Detection of Hepatic Steatosis, Based on Results From Histopathology Analysis
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0016508517302676
https://www.clinicalkey.es/playcontent/1-s2.0-S0016508517302676
https://dx.doi.org/10.1053/j.gastro.2017.03.005
https://cir.nii.ac.jp/crid/1872835442883020544
https://www.ncbi.nlm.nih.gov/pubmed/28286210
https://www.proquest.com/docview/1876819007
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-136544
Volume 153
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1fb9MwELdGJyFeEP8pMGQkxktJl8Rxkj5uK92EYEhsTHuznNQpZaGd4oQHPg2fj0_BXeyk7VTYxkuUJraT-n7x3dnn3xHyOpYq4qnHnIHMmBPw2HPiDLdxJSrk4zQBm72O8j0KD78E78_42cbG76WopapM-unPtftK_keqcA3kirtkbyDZtlG4AOcgXziChOF4LRmb9X7ZY9s-x5B_pMgYYkQ6WNYj8PxHRZMJXEOp_ap0PmVZ71TmFUZMor2olYbhAmuYJBJgOg5VqdLGjjxUFzWlK4b9lnNtCAn2oNoYVxk-K13lpYbnzL8bwhFMcGxYnRq2k2Xr90DqspgjC2hhCq1JBdTzBsHy7O-R1IUxdctier5QmoWeFMpG_p9LlfdG_Rbmkxm87I_aLD4GLC4iB4byaw6vgNEBe6H9EvKVmQ8vaqNk29HcCx0wMPnKaG64h1dga8Zme8Noec77KlqrQtw6D8i3_qTuEgz-iwwNLl-ozCZM4JImbeMb65V9zsCzMq0IbEW4TNR0u5s-uDR-h2we7H043V1QRLPY5He0_6rZ6MnZzrq3-ZshdWs2na5zly5x4db208k9ctc6PnTXoPg-2VCzB-T2Rxva8ZD8qsFMJWXb1ECZWihTgDJtoEylhjIWyrSGMm2hTJegTOcZbaGMPyyUaQvlt7QGMoXbFsgUgUxXgUwbID8iJ6N3J_uHjk0f4qShy0onScCbUEg-hG5QEEtfZQFLkmwgccN1GCWcgQMQjznY8Nk4BdWfMBZGvvSyEMz4x6QzA4Q-JTSNI5m6WRKM3SxIPV-CWx3xAfPGQRpAK13CGlGI1FLrY4aXXPwLCF3itLUuDLXMFeV5I2XRbJsGRS8AuFfUi9bVU9qOZFp4QvvCFccIPUSeB2rfD6NwuaY1yI2hfY1nbgEMoTPw6MURsjoGAWY2B_cUzrrkVQNQAfoMFynlTM0rjYVD9FLcqEueGOS2vYPTQ6HvuV3yxkC5vYMk-cPp6a6YFxORTyuB0btB8OyGXfyc3FkMNC9IpywqtQVOR5m8tF_rH6KKKgE
linkProvider Elsevier
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Using+a+3%25+Proton+Density+Fat+Fraction+as+a+Cut-Off+Value+Increases+Sensitivity+of+Detection+of+Hepatic+Steatosis%2C+Based+on+Results+From+Histopathology+Analysis&rft.jtitle=Gastroenterology+%28New+York%2C+N.Y.+1943%29&rft.au=Nasr%2C+Patrik&rft.au=Forsgren%2C+Mikael+F.&rft.au=Ignatova%2C+Simone&rft.au=Dahlstr%C3%B6m%2C+Nils&rft.date=2017-07-01&rft.issn=0016-5085&rft.volume=153&rft.issue=1&rft.spage=53&rft.epage=55.e7&rft_id=info:doi/10.1053%2Fj.gastro.2017.03.005&rft.externalDBID=n%2Fa&rft.externalDocID=10_1053_j_gastro_2017_03_005
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0016-5085&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0016-5085&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0016-5085&client=summon