Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy

The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference...

Full description

Saved in:
Bibliographic Details
Published inAmerican journal of roentgenology (1976) Vol. 208; no. 1; pp. 92 - 100
Main Authors Kramer, Harald, Pickhardt, Perry J., Kliewer, Mark A., Hernando, Diego, Chen, Guang-Hong, Zagzebski, James A., Reeder, Scott B.
Format Journal Article
LanguageEnglish
Published United States 01.01.2017
Subjects
Online AccessGet full text

Cover

Loading…
Abstract The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard. Fifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS. There was excellent correlation between MRS and both proton-density fat-fraction MRI (r = 0.992; slope, 0.974; intercept, -0.943) and SECT (r = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r = 0.004; slope, 0.069; intercept, 6.168). Quantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.
AbstractList OBJECTIVEThe purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard.SUBJECTS AND METHODSFifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS.RESULTSThere was excellent correlation between MRS and both proton-density fat-fraction MRI (r2 = 0.992; slope, 0.974; intercept, -0.943) and SECT (r2 = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r2 = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r2 = 0.004; slope, 0.069; intercept, 6.168).CONCLUSIONQuantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.
The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard. Fifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS. There was excellent correlation between MRS and both proton-density fat-fraction MRI (r = 0.992; slope, 0.974; intercept, -0.943) and SECT (r = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r = 0.004; slope, 0.069; intercept, 6.168). Quantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.
Author Reeder, Scott B.
Pickhardt, Perry J.
Chen, Guang-Hong
Hernando, Diego
Zagzebski, James A.
Kliewer, Mark A.
Kramer, Harald
AuthorAffiliation 3 Department of Medical Physics, University of Wisconsin—Madison, Madison, WI
2 Department of Radiology, University of Wisconsin—Madison, Madison, WI
1 Department of Clinical Radiology, University Hospitals Munich, Ludwig Maximilians University, Marchioninistr 15, 81377 Munich, Germany
4 Departments of Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin—Madison, Madison, WI
AuthorAffiliation_xml – name: 4 Departments of Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin—Madison, Madison, WI
– name: 3 Department of Medical Physics, University of Wisconsin—Madison, Madison, WI
– name: 2 Department of Radiology, University of Wisconsin—Madison, Madison, WI
– name: 1 Department of Clinical Radiology, University Hospitals Munich, Ludwig Maximilians University, Marchioninistr 15, 81377 Munich, Germany
Author_xml – sequence: 1
  givenname: Harald
  surname: Kramer
  fullname: Kramer, Harald
  organization: Department of Clinical Radiology, University Hospitals Munich, Ludwig Maximilians University, Marchioninistr 15, 81377 Munich, Germany., Department of Radiology, University of Wisconsin—Madison, Madison, WI
– sequence: 2
  givenname: Perry J.
  surname: Pickhardt
  fullname: Pickhardt, Perry J.
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI
– sequence: 3
  givenname: Mark A.
  surname: Kliewer
  fullname: Kliewer, Mark A.
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI
– sequence: 4
  givenname: Diego
  surname: Hernando
  fullname: Hernando, Diego
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI
– sequence: 5
  givenname: Guang-Hong
  surname: Chen
  fullname: Chen, Guang-Hong
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI., Department of Medical Physics, University of Wisconsin—Madison, Madison, WI
– sequence: 6
  givenname: James A.
  surname: Zagzebski
  fullname: Zagzebski, James A.
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI., Department of Medical Physics, University of Wisconsin—Madison, Madison, WI
– sequence: 7
  givenname: Scott B.
  surname: Reeder
  fullname: Reeder, Scott B.
  organization: Department of Radiology, University of Wisconsin—Madison, Madison, WI., Department of Medical Physics, University of Wisconsin—Madison, Madison, WI., Departments of Biomedical Engineering, Medicine, and Emergency Medicine, University of Wisconsin—Madison, Madison, WI
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27726414$$D View this record in MEDLINE/PubMed
BookMark eNptkc1v0zAYxi00xLqNG2fkI4dm-CtOwgGpqhgMddooneBmOY5NjVI7s51KvfKX424rAjTLki29z_t77Oc9AUfOOw3AK4zOCcHs7ezz8hzzvEtePgMTXDJeUMzwEZggynFRI_r9GJzE-BMhVNVN9QIck6oinGE2Ab9mSo1Bqh30Bi7sVgd4IRP8MkqXrLFKJusd_GbTGs66rXRKd3C-msKr5eUUStfB2z4FGf2Yryut1s7ejTq-gzfBx0GrlIlw7jeDDDYeQFdL-HVfyxLlh90ZeG5kH_XLx_MU3F58WM0_FYvrj5fz2aJQtGapkEi3LWENxaTkeRlkKtNwwqSUvDO8Rryj0hCkG00VblVtKs5IV-OG04619BS8f-AOY7vRndIuv7wXQ7AbGXbCSyv-rTi7Fj_8VpQEMVbyDHjzCAh-_8skNjYq3ffSaT9GgWta0hpjXGXp67-9_pgcgs8C8iBQOYUYtBHKpvuws7XtBUZiP12RpyswF_fTzU3T_5oO3CflvwHsSqcm
CitedBy_id crossref_primary_10_1097_MCG_0000000000001380
crossref_primary_10_4254_wjh_v10_i8_530
crossref_primary_10_1016_j_crad_2018_01_018
crossref_primary_10_1088_1361_6560_ab7503
crossref_primary_10_1007_s00761_023_01415_9
crossref_primary_10_1016_j_jhep_2018_03_018
crossref_primary_10_1002_mrm_29310
crossref_primary_10_1007_s00256_021_03979_2
crossref_primary_10_1142_S1793545822300142
crossref_primary_10_1002_oby_23865
crossref_primary_10_2214_AJR_23_29651
crossref_primary_10_3348_kjr_2021_0112
crossref_primary_10_1016_j_rgmx_2020_04_002
crossref_primary_10_2214_AJR_20_24415
crossref_primary_10_3390_app9040661
crossref_primary_10_4329_wjr_v15_i10_293
crossref_primary_10_1002_jum_15154
crossref_primary_10_1007_s00261_024_04448_9
crossref_primary_10_1002_mp_14241
crossref_primary_10_1007_s00330_020_06757_1
crossref_primary_10_1007_s00261_021_03266_7
crossref_primary_10_1007_s00261_019_01960_1
crossref_primary_10_1186_s43055_019_0061_4
crossref_primary_10_1002_mrm_29021
crossref_primary_10_1002_lt_25733
crossref_primary_10_1111_ctr_14786
crossref_primary_10_1016_j_clinimag_2021_02_039
crossref_primary_10_1371_journal_pone_0202666
crossref_primary_10_1148_radiol_2017170550
crossref_primary_10_3348_kjr_2020_1262
crossref_primary_10_1007_s00330_017_5189_x
crossref_primary_10_12998_wjcc_v10_i25_8906
crossref_primary_10_1016_j_rcl_2022_05_006
crossref_primary_10_1097_MPA_0000000000001252
crossref_primary_10_3390_metabo11090625
crossref_primary_10_1016_j_rxeng_2022_06_003
crossref_primary_10_1590_1806_9282_20210760
crossref_primary_10_3390_diagnostics11050842
crossref_primary_10_1371_journal_pone_0314542
crossref_primary_10_1007_s11605_017_3562_3
crossref_primary_10_1007_s12094_020_02514_4
crossref_primary_10_1038_s41598_024_62887_2
crossref_primary_10_3389_fphys_2017_00906
crossref_primary_10_3390_diagnostics10060431
crossref_primary_10_2174_1573405614666181029115243
crossref_primary_10_4239_wjd_v13_i9_668
crossref_primary_10_1016_j_ejrad_2017_10_026
crossref_primary_10_1016_j_jceh_2021_02_008
crossref_primary_10_3390_diagnostics13101673
crossref_primary_10_1111_joim_20053
crossref_primary_10_1371_journal_pone_0246837
crossref_primary_10_1097_RLI_0000000000000858
crossref_primary_10_1177_87564793221112107
crossref_primary_10_1016_j_ejmp_2024_103210
crossref_primary_10_1007_s00261_020_02783_1
crossref_primary_10_1007_s00261_024_04407_4
crossref_primary_10_1007_s00261_022_03434_3
crossref_primary_10_1016_j_ultrasmedbio_2023_06_020
crossref_primary_10_1016_j_acra_2018_03_029
crossref_primary_10_2147_DMSO_S349153
crossref_primary_10_1097_j_pbj_0000000000000228
crossref_primary_10_1148_radiol_2019190467
crossref_primary_10_7759_cureus_75340
crossref_primary_10_1097_RTI_0000000000000393
crossref_primary_10_1186_s12876_023_02717_3
crossref_primary_10_1186_s43066_023_00269_5
crossref_primary_10_1259_bjr_20170378
crossref_primary_10_1148_radiol_240038
crossref_primary_10_3179_jjmu_JJMU_R_222
crossref_primary_10_1055_s_0043_1763483
crossref_primary_10_1016_j_nut_2022_111736
crossref_primary_10_1088_1361_6560_ac4562
crossref_primary_10_3390_nu11030544
crossref_primary_10_1148_rg_2021200056
crossref_primary_10_3390_biomedicines8090298
crossref_primary_10_1016_j_acra_2019_04_001
crossref_primary_10_1097_RCT_0000000000001193
crossref_primary_10_1002_edm2_335
crossref_primary_10_1016_j_ejrad_2020_109227
crossref_primary_10_1016_j_jrras_2023_100658
crossref_primary_10_1016_j_rx_2022_06_007
crossref_primary_10_1002_hep_29797
crossref_primary_10_1016_j_ejrad_2021_109741
crossref_primary_10_1016_j_ejrad_2023_110734
crossref_primary_10_1097_TXD_0000000000001431
crossref_primary_10_1007_s00330_019_06076_0
crossref_primary_10_1016_j_jfma_2024_04_012
crossref_primary_10_1161_CIRCIMAGING_117_005447
crossref_primary_10_1186_s43066_022_00216_w
crossref_primary_10_1007_s00261_022_03482_9
crossref_primary_10_1055_s_0040_1708824
crossref_primary_10_1007_s00330_023_09731_9
crossref_primary_10_2214_AJR_16_17741
crossref_primary_10_1016_j_ejrad_2024_111552
crossref_primary_10_1186_s41747_023_00387_0
crossref_primary_10_1016_j_cld_2023_01_020
crossref_primary_10_1080_17474124_2019_1621164
crossref_primary_10_2214_AJR_21_26728
crossref_primary_10_35366_93885
crossref_primary_10_1097_RLI_0000000000000797
crossref_primary_10_1148_radiol_2021204288
crossref_primary_10_1016_j_mric_2021_05_002
crossref_primary_10_1007_s00261_017_1289_y
crossref_primary_10_1016_j_pan_2024_10_005
crossref_primary_10_1007_s11427_023_2305_0
crossref_primary_10_3390_app13010432
crossref_primary_10_1097_HC9_0000000000000310
crossref_primary_10_1148_rg_240176
crossref_primary_10_1259_bjr_20170959
crossref_primary_10_1016_j_media_2023_102987
crossref_primary_10_3390_diagnostics10080557
crossref_primary_10_1186_s13244_021_01082_7
crossref_primary_10_1007_s10396_021_01136_9
crossref_primary_10_1210_jc_2017_02294
crossref_primary_10_1016_j_rgmxen_2018_05_024
crossref_primary_10_1007_s00261_020_02702_4
crossref_primary_10_1111_ctr_13013
crossref_primary_10_3389_fmed_2024_1425145
crossref_primary_10_1164_rccm_202203_0597OC
crossref_primary_10_5812_jkums_142386
crossref_primary_10_1259_bjr_20201377
crossref_primary_10_2214_AJR_18_20947
crossref_primary_10_2214_AJR_20_22842
crossref_primary_10_1007_s44326_024_00025_y
crossref_primary_10_1016_j_rgmxen_2020_04_004
crossref_primary_10_3348_kjr_2020_1343
crossref_primary_10_3390_nu11081830
crossref_primary_10_1016_j_rcl_2019_01_004
crossref_primary_10_1038_s41598_023_39390_1
crossref_primary_10_2147_JHC_S268288
crossref_primary_10_1016_j_rgmx_2018_05_007
crossref_primary_10_1016_j_ejrad_2021_109845
crossref_primary_10_1016_j_jacadv_2024_101175
crossref_primary_10_3390_medicina59030469
crossref_primary_10_1111_ctr_14339
crossref_primary_10_1007_s00330_023_09856_x
crossref_primary_10_1055_s_0042_1742432
crossref_primary_10_4103_ijmr_IJMR_1777_18
crossref_primary_10_3390_medicina59030500
crossref_primary_10_2463_jjmrm_2023_1800
crossref_primary_10_1136_bmjopen_2021_057820
crossref_primary_10_1007_s00330_024_10660_4
crossref_primary_10_1148_radiol_241677
crossref_primary_10_1053_j_sult_2021_03_001
crossref_primary_10_1088_1361_6560_ac1023
crossref_primary_10_1016_j_ultrasmedbio_2019_03_021
crossref_primary_10_1002_hep_30672
crossref_primary_10_1111_1753_0407_13086
crossref_primary_10_3390_gastroent15030043
crossref_primary_10_1007_s00330_024_10816_2
crossref_primary_10_2214_AJR_17_19391
crossref_primary_10_1007_s42000_018_0012_x
crossref_primary_10_1136_jim_2018_000722
crossref_primary_10_1016_j_jacr_2024_12_014
crossref_primary_10_1002_acm2_13368
crossref_primary_10_1002_mp_15038
crossref_primary_10_1007_s00247_024_06133_x
crossref_primary_10_1016_j_ejrad_2024_111840
crossref_primary_10_1097_MD_0000000000038276
crossref_primary_10_2214_AJR_17_17812
crossref_primary_10_1016_j_xcrm_2022_100855
crossref_primary_10_1007_s40134_017_0226_8
crossref_primary_10_3390_nu12040891
crossref_primary_10_1016_j_jceh_2019_09_002
crossref_primary_10_1055_s_0041_1731964
crossref_primary_10_1055_a_1212_6017
crossref_primary_10_3348_kjr_2018_0557
crossref_primary_10_1016_j_jhep_2019_04_013
crossref_primary_10_1016_j_liver_2022_100091
Cites_doi 10.1007/s10654-007-9181-7
10.1007/s00330-015-3703-6
10.1007/s00330-006-0517-6
10.1016/j.acra.2011.08.014
10.1097/RLI.0b013e3181df2afb
10.1002/mrm.22177
10.3748/wjg.v20.i23.7392
10.1016/j.mri.2014.10.001
10.1097/RLI.0b013e31824baff3
10.1097/RLI.0b013e31822b124c
10.1007/s00330-015-3724-1
10.1016/j.cld.2009.07.006
10.1016/S0168-8278(98)80228-6
10.1097/RLI.0b013e31820e1486
10.1097/RLI.0b013e318261fad0
10.1002/hep.22845
10.1002/hep.23135
10.1038/sj.ejcn.1602588
10.1148/radiology.153.1.6089263
10.1053/j.gastro.2005.03.084
10.1152/ajpendo.00064.2004
10.1002/mrm.20126
10.1002/hep.20466
10.1148/radiol.2015141779
10.1001/jama.295.13.1549
10.14366/usg.14003
10.1148/radiol.2303021331
10.2214/AJR.14.12457
10.1148/radiol.2511080666
10.1002/jmri.22514
10.1002/jmri.23741
10.1136/bmj.292.6512.13
10.1055/s-2007-985075
10.1053/j.gastro.2009.12.052
10.1002/mrm.21301
10.1097/00004728-198202000-00009
10.1002/jmri.21957
10.1002/mrm.23044
10.1111/j.1872-034X.2009.00620.x
10.1002/jmri.21090
10.1002/jmri.21809
10.1111/j.1478-3231.2008.01691.x
10.1002/jmri.22580
10.1148/radiol.10100708
10.1016/j.jhep.2012.12.005
10.1002/mrm.1910180211
10.1007/BF02570192
10.1097/RLI.0b013e3181da1343
ContentType Journal Article
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
5PM
DOI 10.2214/AJR.16.16565
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList MEDLINE - Academic
MEDLINE
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 1546-3141
EndPage 100
ExternalDocumentID PMC5204456
27726414
10_2214_AJR_16_16565
Genre Journal Article
GrantInformation_xml – fundername: NIDDK NIH HHS
  grantid: K24 DK102595
– fundername: NIDDK NIH HHS
  grantid: R01 DK083380
– fundername: NIDDK NIH HHS
  grantid: R01 DK100651
– fundername: NIDDK NIH HHS
  grantid: R01 DK088925
GroupedDBID ---
-DD
.55
.GJ
1CY
1KJ
23M
2WC
34G
39C
3O-
53G
5GY
5RE
AAEJM
AAWTL
AAYXX
ABOCM
ADBBV
AENEX
AFFNX
AI.
AJJEV
ALMA_UNASSIGNED_HOLDINGS
BAWUL
C1A
CITATION
CS3
DIK
E3Z
EBS
EJD
F5P
GX1
H13
J5H
L7B
LSO
MJL
P2P
SJN
TR2
TRR
TWZ
UDS
VH1
W2D
W8F
WH7
WOQ
X7M
YJK
YQI
YQJ
ZGI
ZVN
ZXP
ACRZS
CGR
CUY
CVF
ECM
EIF
NPM
7X8
5PM
ID FETCH-LOGICAL-c384t-a0ebb24931256666f0f7f9624aaa6df6806d3af20e9e3c1bc8f7642d81963d4b3
ISSN 0361-803X
IngestDate Thu Aug 21 18:35:44 EDT 2025
Fri Jul 11 03:14:23 EDT 2025
Thu Apr 03 06:57:30 EDT 2025
Tue Jul 01 01:22:26 EDT 2025
Thu Apr 24 23:01:21 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords CT
fat quantification
MRI
ultrasound
MR spectroscopy
hepatic steatosis
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c384t-a0ebb24931256666f0f7f9624aaa6df6806d3af20e9e3c1bc8f7642d81963d4b3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
OpenAccessLink https://www.ncbi.nlm.nih.gov/pmc/articles/5204456
PMID 27726414
PQID 1835381117
PQPubID 23479
PageCount 9
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_5204456
proquest_miscellaneous_1835381117
pubmed_primary_27726414
crossref_citationtrail_10_2214_AJR_16_16565
crossref_primary_10_2214_AJR_16_16565
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2017-01-01
PublicationDateYYYYMMDD 2017-01-01
PublicationDate_xml – month: 01
  year: 2017
  text: 2017-01-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
PublicationTitle American journal of roentgenology (1976)
PublicationTitleAlternate AJR Am J Roentgenol
PublicationYear 2017
References Reeder SB (R27) 2011; 34
R21
R20
R23
R22
R25
R24
R26
R29
R28
Mendonça PR (R19) 2013; 16
R1
R2
R3
R4
R5
Radu C (R6) 2008; 17
R7
R8
R9
R30
R32
R31
R34
R33
R36
R38
R37
R39
R40
R43
R42
R45
R47
R46
R49
R48
Lupşor-Platon M (R16) 2014; 16
R50
Hernando D (R41) 2010; 63
R52
Springer F (R35) 2010; 45
R51
R10
R12
R11
R14
R13
R15
R18
R17
References_xml – ident: R4
  doi: 10.1007/s10654-007-9181-7
– ident: R48
  doi: 10.1007/s00330-015-3703-6
– ident: R51
  doi: 10.1007/s00330-006-0517-6
– ident: R24
  doi: 10.1016/j.acra.2011.08.014
– volume: 45
  start-page: 484
  year: 2010
  ident: R35
  publication-title: Invest Radiol
  doi: 10.1097/RLI.0b013e3181df2afb
– volume: 63
  start-page: 79
  year: 2010
  ident: R41
  publication-title: Magn Reson Med
  doi: 10.1002/mrm.22177
– ident: R46
  doi: 10.3748/wjg.v20.i23.7392
– ident: R50
  doi: 10.1016/j.mri.2014.10.001
– ident: R33
  doi: 10.1097/RLI.0b013e31824baff3
– ident: R34
  doi: 10.1097/RLI.0b013e31822b124c
– ident: R12
  doi: 10.1007/s00330-015-3724-1
– ident: R10
  doi: 10.1016/j.cld.2009.07.006
– ident: R21
  doi: 10.1016/S0168-8278(98)80228-6
– ident: R22
  doi: 10.1097/RLI.0b013e31820e1486
– ident: R23
  doi: 10.1097/RLI.0b013e318261fad0
– ident: R2
  doi: 10.1002/hep.22845
– ident: R3
  doi: 10.1002/hep.23135
– ident: R7
  doi: 10.1038/sj.ejcn.1602588
– ident: R28
  doi: 10.1148/radiology.153.1.6089263
– ident: R15
  doi: 10.1053/j.gastro.2005.03.084
– volume: 17
  start-page: 255
  year: 2008
  ident: R6
  publication-title: J Gastrointestin Liver Dis
– ident: R47
  doi: 10.1152/ajpendo.00064.2004
– ident: R31
  doi: 10.1002/mrm.20126
– ident: R1
  doi: 10.1002/hep.20466
– ident: R52
  doi: 10.1148/radiol.2015141779
– ident: R5
  doi: 10.1001/jama.295.13.1549
– ident: R18
  doi: 10.14366/usg.14003
– ident: R45
  doi: 10.1148/radiol.2303021331
– ident: R39
  doi: 10.2214/AJR.14.12457
– ident: R38
  doi: 10.1148/radiol.2511080666
– ident: R37
  doi: 10.1002/jmri.22514
– volume: 16
  start-page: 324
  year: 2013
  ident: R19
  publication-title: Med Image Comput Comput Assist Interv
– ident: R26
  doi: 10.1002/jmri.23741
– ident: R17
  doi: 10.1136/bmj.292.6512.13
– ident: R8
  doi: 10.1055/s-2007-985075
– ident: R11
  doi: 10.1053/j.gastro.2009.12.052
– ident: R30
  doi: 10.1002/mrm.21301
– ident: R20
  doi: 10.1097/00004728-198202000-00009
– ident: R40
  doi: 10.1002/jmri.21957
– ident: R42
  doi: 10.1002/mrm.23044
– ident: R25
  doi: 10.1111/j.1872-034X.2009.00620.x
– ident: R32
  doi: 10.1002/jmri.21090
– ident: R43
  doi: 10.1002/jmri.21809
– ident: R14
  doi: 10.1111/j.1478-3231.2008.01691.x
– volume: 16
  start-page: 236
  year: 2014
  ident: R16
  publication-title: Med Ultrason
– volume: 34
  year: 2011
  ident: R27
  publication-title: J Magn Reson Imaging
  doi: 10.1002/jmri.22580
– ident: R36
  doi: 10.1148/radiol.10100708
– ident: R9
  doi: 10.1016/j.jhep.2012.12.005
– ident: R29
  doi: 10.1002/mrm.1910180211
– ident: R13
  doi: 10.1007/BF02570192
– ident: R49
  doi: 10.1097/RLI.0b013e3181da1343
SSID ssj0007897
Score 2.581247
Snippet The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale...
OBJECTIVEThe purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT),...
SourceID pubmedcentral
proquest
pubmed
crossref
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 92
SubjectTerms Adiposity - physiology
Elasticity Imaging Techniques - methods
Female
Humans
Intra-Abdominal Fat - diagnostic imaging
Intra-Abdominal Fat - physiology
Liver - diagnostic imaging
Liver - physiology
Magnetic Resonance Imaging - methods
Male
Middle Aged
Proton Magnetic Resonance Spectroscopy - methods
Reproducibility of Results
Sensitivity and Specificity
Tomography, X-Ray Computed - methods
Title Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy
URI https://www.ncbi.nlm.nih.gov/pubmed/27726414
https://www.proquest.com/docview/1835381117
https://pubmed.ncbi.nlm.nih.gov/PMC5204456
Volume 208
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Zj9MwELbKIiFeVtx0OWQkeOq2xI7jJLxVhVVZVARVK_oW2TmgYtWssqmQeOT_8Z-YsXN1u0gLL1GVxOkxX-fyzDeEvHSThMehdoaZQlJtkbjDUIEyZJ5SiknFdIjNybOPcroUpytv1ev97lQtbUs9in9e2VfyP1KFcyBX7JL9B8k2D4UT8BrkC0eQMByvJeNxHG8LnNeOiX4ssBicQLz_eatsBZCV7RfMtI7rrf7Jwtbuvq_LNpdnZaEucLiSTbMjn6spk_tU5HUbptUadlqhedxsbgbXl0iFmZ_v7Aw3W0AdTooiB9OGbLCG7wmpocA96eQgPmCFmIHOVGGKrNHX6_g7doVVlcQFFviNmkXgPf-wq7DhaDBurkxtbtwkgd-u0695N7XB_E5qo27pYmBCzcBgMFaVhhYSDIdly6pVOHeCPaxahWwH7VWmnRlS1D2rwTkTyF5xOh8xOUI6Iq-1jnVFwCWj2ZQyQhCF6yNYHTEZmdU3yE0OUYvpPV-1FUd-YGb9NN_K9mHg6tfd9971kPbCnsvVux13aHGHHFZxDB1bUN4lvXRzj9yaVZUa98mvGps0z6jBJgVs0l1sUgQTrbFJJ4tjCsg8piA82uKStrh8QzuopC0q7YNmc9pF5QOyPHm3mEyH1byPYewGohwqJ9Wai9AFpxuiapk5mZ-FkgtQGzLJZODIxFUZd9IwdWOm4yDzIXxOArQiidDuQ3KwyTfpY0J1Bqu46yZKhII7vnZT7fqe1B73mZ-xPhnUv3EUV2T4OJPlLLpKnn3yqrn73JLA_OW-F7W4ItDSuPWmNmm-vYjAcIJnAX6F3yePrPiaJyFUpGCiT_wdwTY3IAP87pXN-pthgve4IyACOrrm53tCbrd_s6fkoCy26TPwqUv93CD1D2NEzHw
linkProvider Geneva Foundation for Medical Education and Research
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=Accuracy+of+Liver+Fat+Quantification+With+Advanced+CT%2C+MRI%2C+and+Ultrasound+Techniques%3A+Prospective+Comparison+With+MR+Spectroscopy&rft.jtitle=American+journal+of+roentgenology+%281976%29&rft.au=Kramer%2C+Harald&rft.au=Pickhardt%2C+Perry+J.&rft.au=Kliewer%2C+Mark+A.&rft.au=Hernando%2C+Diego&rft.date=2017-01-01&rft.issn=0361-803X&rft.eissn=1546-3141&rft.volume=208&rft.issue=1&rft.spage=92&rft.epage=100&rft_id=info:doi/10.2214%2FAJR.16.16565&rft.externalDBID=n%2Fa&rft.externalDocID=10_2214_AJR_16_16565
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0361-803X&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0361-803X&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0361-803X&client=summon