Long-term inter-platform reproducibility, bias, and linearity of commercial PDFF MRI methods for fat quantification: a multi-center, multi-vendor phantom study
Objectives Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using...
        Saved in:
      
    
          | Published in | European radiology Vol. 31; no. 10; pp. 7566 - 7574 | 
|---|---|
| Main Authors | , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Berlin/Heidelberg
          Springer Berlin Heidelberg
    
        01.10.2021
     Springer Nature B.V  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0938-7994 1432-1084 1432-1084  | 
| DOI | 10.1007/s00330-021-07851-8 | 
Cover
| Abstract | Objectives
Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors.
Methods
Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject’s examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed.
Results
Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (
p
< 0.001) and field strength (
p
< 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%).
Conclusions
This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength–dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference.
Key Points
• Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated.
• Non-linear effects were negligible (linear slope of 0.94) over 0–100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0–100 weight% fat, respectively.
• Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems. | 
    
|---|---|
| AbstractList | Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors.OBJECTIVESProton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors.Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject's examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed.METHODSOver 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject's examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed.Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%).RESULTSThree hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%).This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength-dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference.CONCLUSIONSThis study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength-dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference.• Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0-100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0-100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems.KEY POINTS• Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0-100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0-100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems. ObjectivesProton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors.MethodsOver 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject’s examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed.ResultsThree hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%).ConclusionsThis study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength–dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference.Key Points• Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated.• Non-linear effects were negligible (linear slope of 0.94) over 0–100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0–100 weight% fat, respectively.• Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems. Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors. Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject's examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed. Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%). This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength-dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference. • Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0-100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0-100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems. Objectives Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors. Methods Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject’s examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed. Results Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor ( p < 0.001) and field strength ( p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%). Conclusions This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength–dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference. Key Points • Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0–100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0–100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems.  | 
    
| Author | Ding, Xiaobo Schneider, Erika McKenzie, Charles A. Navaneethan, Sankar D. Obuchowski, Nancy A. Remer, Erick M.  | 
    
| Author_xml | – sequence: 1 givenname: Erika surname: Schneider fullname: Schneider, Erika organization: Imaging Institute, Cleveland Clinic – sequence: 2 givenname: Erick M. orcidid: 0000-0003-0379-606X surname: Remer fullname: Remer, Erick M. email: remere1@ccf.org organization: Imaging Institute, Cleveland Clinic, Glickman Urological and Kidney Institute, Cleveland Clinic – sequence: 3 givenname: Nancy A. surname: Obuchowski fullname: Obuchowski, Nancy A. organization: Imaging Institute, Cleveland Clinic, Department of Quantitative Health Sciences, Cleveland Clinic – sequence: 4 givenname: Charles A. surname: McKenzie fullname: McKenzie, Charles A. organization: CAnatomical Research Services and Medical Biophysics, University of Western Ontario – sequence: 5 givenname: Xiaobo surname: Ding fullname: Ding, Xiaobo organization: Imaging Institute, Cleveland Clinic, Department of Radiology, First Hospital of Jilin University – sequence: 6 givenname: Sankar D. surname: Navaneethan fullname: Navaneethan, Sankar D. organization: Glickman Urological and Kidney Institute, Cleveland Clinic, Department of Medicine-Nephrology, Baylor College of Medicine  | 
    
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33768291$$D View this record in MEDLINE/PubMed | 
    
| BookMark | eNp9kctuEzEUhi3UiqaFF2CBLLFhEbe-TTxmVxUClVKBEKwtx5fW1Yyd2h6kPA2vitMEkLro6ugcff-5_afgKKboAHhD8DnBWFwUjBnDCFOCsOg7gvoXYEY4o4jgnh-BGZasR0JKfgJOS7nHGEvCxUtwwphY9FSSGfi9SvEWVZdHGGILaDPo6lNLs9vkZCcT1mEIdTuH66DLHOpo4RCi07kVYfLQpHF02QQ9wG8fl0t48_0ajq7eJVtgawS9rvBh0rEGH4yuIcUPUMNxGmpAxu1mzg_ZLxdtE2zuGpxGWOpkt6_AsddDca8P8Qz8XH76cfUFrb5-vr66XCHDRFcRMY5i53vupW9Hd1LqVvBMdwxrToVg2nJLhbR0Qb1x2BrBJJXcCuPXpGNn4P2-bzv6YXKlqjEU44ZBR5emomiHF7Q9uduh756g92nKsW3XKMG7biGlbNTbAzWtR2fVJodR5636-_oG0D1gciolO_8PIVjt_FV7f1XzVz36q_om6p-ITKiPT61Zh-F5KdtLS5sTb13-v_Yzqj9rZbsM | 
    
| CitedBy_id | crossref_primary_10_1007_s10334_024_01148_9 crossref_primary_10_1016_S2468_1253_23_00064_X crossref_primary_10_1007_s00330_024_11164_x crossref_primary_10_1007_s00261_024_04448_9 crossref_primary_10_1109_TIM_2023_3268480 crossref_primary_10_1002_jmri_29756 crossref_primary_10_1038_s41598_023_42422_5 crossref_primary_10_1007_s10334_022_01053_z crossref_primary_10_1007_s10334_024_01181_8 crossref_primary_10_1002_jcsm_13192 crossref_primary_10_1016_j_mri_2024_110223 crossref_primary_10_1186_s12903_023_03024_9 crossref_primary_10_14309_ajg_0000000000002020  | 
    
| Cites_doi | 10.1002/mrm.23016 10.1002/jmri.20831 10.1148/radiol.13121360 10.1002/jmri.23741 10.1148/rg.295085186 10.1148/radiol.2017170550 10.1152/ajpendo.00064.2004 10.1111/j.1365-2036.2012.05121.x 10.1002/jmri.21957 10.1016/j.jbi.2008.08.010 10.1148/radiol.2017161786 10.1002/mrm.26228 10.1002/jmri.24842 10.1002/jmri.22580 10.1007/s10334-017-0642-z 10.1148/radiol.2017160606 10.1002/mrm.1201 10.1002/mrm.22840 10.1002/mrm.27065 10.1002/jmri.24526 10.1016/j.mric.2014.04.010 10.1148/radiol.10100659 10.1002/jmri.23928 10.1007/s00330-020-06858-x 10.1097/01.ASN.0000070149.78399.CE 10.1002/mrm.28669  | 
    
| ContentType | Journal Article | 
    
| Copyright | European Society of Radiology 2021 European Society of Radiology 2021. 2021. European Society of Radiology.  | 
    
| Copyright_xml | – notice: European Society of Radiology 2021 – notice: European Society of Radiology 2021. – notice: 2021. European Society of Radiology.  | 
    
| DBID | AAYXX CITATION NPM 3V. 7QO 7RV 7X7 7XB 88E 8AO 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABUWG AFKRA ARAPS AZQEC BBNVY BENPR BGLVJ BHPHI CCPQU DWQXO FR3 FYUFA GHDGH GNUQQ HCIFZ K9. KB0 LK8 M0S M1P M7P NAPCQ P5Z P62 P64 PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS 7X8  | 
    
| DOI | 10.1007/s00330-021-07851-8 | 
    
| DatabaseName | CrossRef PubMed ProQuest Central (Corporate) Biotechnology Research Abstracts Nursing & Allied Health Database Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Journals Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials - QC Biological Science Collection ProQuest Central Technology Collection Natural Science Collection ProQuest One Community College ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Database (Alumni Edition) Biological Sciences ProQuest Health & Medical Collection Medical Database Biological Science Database Nursing & Allied Health Premium Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Proquest Central Premium ProQuest One Academic ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic  | 
    
| DatabaseTitle | CrossRef PubMed ProQuest Central Student Technology Collection Technology Research Database ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection Health Research Premium Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) Advanced Technologies & Aerospace Collection ProQuest Biological Science Collection ProQuest One Academic Eastern Edition ProQuest Nursing & Allied Health Source ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Advanced Technologies & Aerospace Database Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest Nursing & Allied Health Source (Alumni) Engineering Research Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic  | 
    
| DatabaseTitleList | MEDLINE - Academic ProQuest Central Student PubMed  | 
    
| 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: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database  | 
    
| DeliveryMethod | fulltext_linktorsrc | 
    
| Discipline | Medicine | 
    
| EISSN | 1432-1084 | 
    
| EndPage | 7574 | 
    
| ExternalDocumentID | 33768291 10_1007_s00330_021_07851_8  | 
    
| Genre | Journal Article | 
    
| GrantInformation_xml | – fundername: National Institute of Diabetes and Digestive and Kidney Diseases grantid: R01DK101500-01 funderid: http://dx.doi.org/10.13039/100000062 – fundername: NIDDK NIH HHS grantid: R01DK101500-01  | 
    
| GroupedDBID | --- -53 -5E -5G -BR -EM -Y2 -~C .86 .VR 04C 06C 06D 0R~ 0VY 1N0 1SB 2.D 203 28- 29G 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 36B 3V. 4.4 406 408 409 40D 40E 53G 5GY 5QI 5VS 67Z 6NX 6PF 7RV 7X7 88E 8AO 8FE 8FG 8FH 8FI 8FJ 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANXM AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAWTL AAYIU AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDZT ABECU ABFTV ABHLI ABHQN ABIPD ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABPLI ABQBU ABQSL ABSXP ABTEG ABTKH ABTMW ABULA ABUWG ABUWZ ABWNU ABXPI ACAOD ACBXY ACDTI ACGFO ACGFS ACHSB ACHVE ACHXU ACIHN ACIWK ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACPRK ACREN ACUDM ACZOJ ADBBV ADHHG ADHIR ADIMF ADINQ ADJJI ADKNI ADKPE ADOJX ADRFC ADTPH ADURQ ADYFF ADYOE ADZKW AEAQA AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFJLC AFKRA AFLOW AFQWF AFRAH AFWTZ AFYQB AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGVAE AGWIL AGWZB AGYKE AHAVH AHBYD AHIZS AHKAY AHMBA AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ AKMHD ALIPV ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMTXH AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ ASPBG AVWKF AXYYD AZFZN B-. BA0 BBNVY BBWZM BDATZ BENPR BGLVJ BGNMA BHPHI BKEYQ BMSDO BPHCQ BSONS BVXVI CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EBD EBLON EBS ECF ECT EIHBH EIOEI EJD EMB EMOBN EN4 ESBYG EX3 F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC FYUFA G-Y G-Z GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GRRUI GXS H13 HCIFZ HF~ HG5 HG6 HMCUK HMJXF HQYDN HRMNR HVGLF HZ~ I-F I09 IHE IJ- IKXTQ IMOTQ IWAJR IXC IXD IXE IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KOW KPH LAS LK8 LLZTM M1P M4Y M7P MA- N2Q N9A NAPCQ NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P19 P2P P62 P9S PF0 PQQKQ PROAC PSQYO PT4 PT5 Q2X QOK QOR QOS R4E R89 R9I RHV RIG RNI RNS ROL RPX RRX RSV RZK S16 S1Z S26 S27 S28 S37 S3B SAP SCLPG SDE SDH SDM SHX SISQX SJYHP SMD SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW SSXJD STPWE SV3 SZ9 SZN T13 T16 TEORI TSG TSK TSV TT1 TUC U2A U9L UDS UG4 UKHRP UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WJK WK8 WOW YLTOR Z45 Z7R Z7U Z7X Z7Y Z7Z Z82 Z83 Z85 Z87 Z88 Z8M Z8O Z8R Z8S Z8T Z8V Z8W Z8Z Z91 Z92 ZMTXR ZOVNA ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PJZUB PPXIY PQGLB PUEGO NPM 7QO 7XB 8FD 8FK AZQEC DWQXO FR3 GNUQQ K9. P64 PKEHL PQEST PQUKI PRINS 7X8  | 
    
| ID | FETCH-LOGICAL-c375t-1ce20ef84f9f938599ae20f3a530a42773ad4d279d262fce0dc739294d7cfb153 | 
    
| IEDL.DBID | BENPR | 
    
| ISSN | 0938-7994 1432-1084  | 
    
| IngestDate | Fri Sep 05 10:26:08 EDT 2025 Tue Oct 07 06:17:42 EDT 2025 Mon Jul 21 06:00:38 EDT 2025 Wed Oct 01 03:47:39 EDT 2025 Thu Apr 24 23:05:47 EDT 2025 Fri Feb 21 02:48:11 EST 2025  | 
    
| IsPeerReviewed | true | 
    
| IsScholarly | true | 
    
| Issue | 10 | 
    
| Keywords | Abdominal fat Adipose tissue Magnetic resonance imaging Quality control  | 
    
| Language | English | 
    
| LinkModel | DirectLink | 
    
| MergedId | FETCHMERGED-LOGICAL-c375t-1ce20ef84f9f938599ae20f3a530a42773ad4d279d262fce0dc739294d7cfb153 | 
    
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23  | 
    
| ORCID | 0000-0003-0379-606X | 
    
| PMID | 33768291 | 
    
| PQID | 2574556999 | 
    
| PQPubID | 54162 | 
    
| PageCount | 9 | 
    
| ParticipantIDs | proquest_miscellaneous_2506278555 proquest_journals_2574556999 pubmed_primary_33768291 crossref_primary_10_1007_s00330_021_07851_8 crossref_citationtrail_10_1007_s00330_021_07851_8 springer_journals_10_1007_s00330_021_07851_8  | 
    
| ProviderPackageCode | CITATION AAYXX  | 
    
| PublicationCentury | 2000 | 
    
| PublicationDate | 2021-10-01 | 
    
| PublicationDateYYYYMMDD | 2021-10-01 | 
    
| PublicationDate_xml | – month: 10 year: 2021 text: 2021-10-01 day: 01  | 
    
| PublicationDecade | 2020 | 
    
| PublicationPlace | Berlin/Heidelberg | 
    
| PublicationPlace_xml | – name: Berlin/Heidelberg – name: Germany – name: Heidelberg  | 
    
| PublicationTitle | European radiology | 
    
| PublicationTitleAbbrev | Eur Radiol | 
    
| PublicationTitleAlternate | Eur Radiol | 
    
| PublicationYear | 2021 | 
    
| Publisher | Springer Berlin Heidelberg Springer Nature B.V  | 
    
| Publisher_xml | – name: Springer Berlin Heidelberg – name: Springer Nature B.V  | 
    
| References | Mamidipalli, Fowler, Hamilton (CR27) 2020; 30 Szczepaniak, Nurenberg, Leonard (CR24) 2005; 288 Ma, Holalkere, Kambadakone, Mino-Kenudson, Hahn, Sahani (CR3) 2009; 29 CR17 Alecci, Collins, Smith, Jezzard (CR21) 2001; 46 Yu, Shimakawa, Hines (CR5) 2011; 66 Wermter, Mitschke, Bock (CR20) 2017; 30 Reeder, McKenzie, Pineda (CR7) 2007; 25 Serai, Dillman, Trout (CR11) 2017; 284 Yokoo, Shiehmorteza, Hamilton (CR12) 2011; 258 Artz, Haufe, Hooker (CR15) 2015; 42 Reeder, Hu, Sirlin (CR2) 2012; 36 Feldman, Appel, Chertow (CR16) 2003; 14 Mashhood, Railkar, Yokoo (CR13) 2013; 37 Reeder, Bice, Yu, Hernando, Pineda (CR4) 2012; 67 Harris, Taylor, Thielke, Payne, Gonzalez, Conde (CR18) 2009; 42 Addeman, Kutty, Perkins (CR19) 2015; 41 Roberts, Hernando, Holmes, Wiens, Reeder (CR28) 2018; 80 Hines, Yu, Shimakawa, McKenzie, Brittain, Reeder (CR6) 2009; 30 Yokoo, Serai, Pirasteh (CR9) 2018; 286 Reeder, Cruite, Hamilton, Sirlin (CR1) 2011; 34 Hernando, Sharma, Aliyari Ghasabeh (CR10) 2017; 77 Reeder, Hines, Yu, McKenzie, Brittain (CR22) 2009; 17 CR23 Permutt, Le, Peterson (CR25) 2012; 36 Middleton, Haufe, Hooker (CR14) 2017; 283 Wells (CR8) 2014; 22 Idilman, Aniktar, Idilman (CR26) 2013; 267 7851_CR17 HI Feldman (7851_CR16) 2003; 14 BY Addeman (7851_CR19) 2015; 41 NS Artz (7851_CR15) 2015; 42 SB Reeder (7851_CR22) 2009; 17 Z Permutt (7851_CR25) 2012; 36 SB Reeder (7851_CR7) 2007; 25 T Yokoo (7851_CR9) 2018; 286 IS Idilman (7851_CR26) 2013; 267 SB Reeder (7851_CR2) 2012; 36 NT Roberts (7851_CR28) 2018; 80 A Mamidipalli (7851_CR27) 2020; 30 SB Reeder (7851_CR4) 2012; 67 CD Hines (7851_CR6) 2009; 30 T Yokoo (7851_CR12) 2011; 258 PA Harris (7851_CR18) 2009; 42 7851_CR23 SA Wells (7851_CR8) 2014; 22 LS Szczepaniak (7851_CR24) 2005; 288 SD Serai (7851_CR11) 2017; 284 MS Middleton (7851_CR14) 2017; 283 H Yu (7851_CR5) 2011; 66 A Mashhood (7851_CR13) 2013; 37 D Hernando (7851_CR10) 2017; 77 FC Wermter (7851_CR20) 2017; 30 X Ma (7851_CR3) 2009; 29 M Alecci (7851_CR21) 2001; 46 SB Reeder (7851_CR1) 2011; 34  | 
    
| References_xml | – volume: 67 start-page: 389 year: 2012 end-page: 404 ident: CR4 article-title: On the performance of T2* correction methods for quantification of hepatic fat content publication-title: Magn Reson Med doi: 10.1002/mrm.23016 – volume: 25 start-page: 644 year: 2007 end-page: 652 ident: CR7 article-title: Water-fat separation with IDEAL gradient-echo imaging publication-title: J Magn Reson Imaging doi: 10.1002/jmri.20831 – volume: 267 start-page: 767 year: 2013 end-page: 775 ident: CR26 article-title: Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy publication-title: Radiology doi: 10.1148/radiol.13121360 – volume: 36 start-page: 1011 year: 2012 end-page: 1014 ident: CR2 article-title: Proton density fat-fraction: a standardized MR-based biomarker of tissue fat concentration publication-title: J Magn Reson Imaging doi: 10.1002/jmri.23741 – volume: 29 start-page: 1253 year: 2009 end-page: 1277 ident: CR3 article-title: Imaging-based quantification of hepatic fat: methods and clinical applications publication-title: Radiographics doi: 10.1148/rg.295085186 – volume: 286 start-page: 486 year: 2018 end-page: 498 ident: CR9 article-title: RSNA-QIBA PDFF Biomarker Committee. Linearity, bias, and precision of hepatic proton density fat fraction measurements by using MR imaging: a meta-analysis publication-title: Radiology doi: 10.1148/radiol.2017170550 – volume: 288 start-page: E462 year: 2005 end-page: E468 ident: CR24 article-title: Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population publication-title: Am J Physiol Endocrinol Metab doi: 10.1152/ajpendo.00064.2004 – volume: 36 start-page: 22 year: 2012 end-page: 29 ident: CR25 article-title: Correlation between liver histology and novel magnetic resonance imaging in adult patients with non-alcoholic fatty liver disease – MRI accurately quantifies hepatic steatosis in NAFLD publication-title: Aliment Pharmacol Ther doi: 10.1111/j.1365-2036.2012.05121.x – volume: 30 start-page: 1215 year: 2009 end-page: 1222 ident: CR6 article-title: T1 independent, T2* corrected MRI with accurate spectral modeling for quantification of fat: validation in a fat-water-SPIO phantom publication-title: J Magn Reson Imaging doi: 10.1002/jmri.21957 – volume: 42 start-page: 377 year: 2009 end-page: 381 ident: CR18 article-title: Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support publication-title: J Biomed Inform doi: 10.1016/j.jbi.2008.08.010 – ident: CR23 – volume: 284 start-page: 244 year: 2017 end-page: 254 ident: CR11 article-title: Proton density fat fraction measurements at 1.5- and 3-T hepatic MR imaging: same-day agreement among readers and across two imager manufacturers publication-title: Radiology doi: 10.1148/radiol.2017161786 – volume: 77 start-page: 1516 year: 2017 end-page: 1524 ident: CR10 article-title: Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom publication-title: Magn Reson Med doi: 10.1002/mrm.26228 – volume: 42 start-page: 811 year: 2015 end-page: 817 ident: CR15 article-title: Reproducibility of MR-based liver fat quantification across field strength: same-day comparison between 1.5T and 3T in obese subjects publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24842 – volume: 34 start-page: 729 year: 2011 end-page: 749 ident: CR1 article-title: Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy publication-title: J Magn Reson Imaging doi: 10.1002/jmri.22580 – ident: CR17 – volume: 30 start-page: 579 year: 2017 end-page: 590 ident: CR20 article-title: Temperature dependence of 1H NMR chemical shifts and its influence on estimated metabolite concentrations publication-title: Magn Reson Mater Phys doi: 10.1007/s10334-017-0642-z – volume: 283 start-page: 438 year: 2017 end-page: 449 ident: CR14 article-title: Quantifying abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction: repeatability and accuracy of an MR imaging–based, semi-automated analysis method publication-title: Radiology doi: 10.1148/radiol.2017160606 – volume: 46 start-page: 379 year: 2001 end-page: 385 ident: CR21 article-title: Radio frequency magnetic field mapping of a 3 Tesla birdcage coil: experimental and theoretical dependence on sample properties publication-title: Magn Reson Med doi: 10.1002/mrm.1201 – volume: 66 start-page: 199 year: 2011 end-page: 206 ident: CR5 article-title: Combination of complex-based and magnitude-based multiecho water-fat separation for accurate quantification of fat-fraction publication-title: Magn Reson Med doi: 10.1002/mrm.22840 – volume: 80 start-page: 685 year: 2018 end-page: 695 ident: CR28 article-title: Noise properties of proton density fat fraction estimated using chemical shift-encoded MRI publication-title: Magn Reson Med doi: 10.1002/mrm.27065 – volume: 41 start-page: 233 year: 2015 end-page: 241 ident: CR19 article-title: Validation of volumetric and single-slice MRI adipose analysis using a novel fully automated segmentation method publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24526 – volume: 22 start-page: 397 year: 2014 end-page: 416 ident: CR8 article-title: Quantification of hepatic fat and iron with magnetic resonance imaging publication-title: Magn Reson Imaging Clin N Am doi: 10.1016/j.mric.2014.04.010 – volume: 258 start-page: 749 year: 2011 end-page: 759 ident: CR12 article-title: Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T publication-title: Radiology doi: 10.1148/radiol.10100659 – volume: 37 start-page: 1359 issue: 6 year: 2013 end-page: 1370 ident: CR13 article-title: Reproducibility of hepatic fat fraction measurement by magnetic resonance imaging publication-title: J Magn Reson Imaging doi: 10.1002/jmri.23928 – volume: 17 start-page: 211 year: 2009 ident: CR22 article-title: On the definition of fat-fraction for in vivo fat quantification with magnetic resonance imaging publication-title: Proc Int Soc Mag Reson Med – volume: 30 start-page: 5120 year: 2020 end-page: 5129 ident: CR27 article-title: Prospective comparison of longitudinal change in hepatic proton density fat fraction (PDFF) estimated by magnitude-based MRI and complex-base MRI publication-title: Eur Radiol doi: 10.1007/s00330-020-06858-x – volume: 14 start-page: S148 year: 2003 end-page: S153 ident: CR16 article-title: Chronic Renal Insufficiency Cohort (CRIC) study investigators. The Chronic Renal Insufficiency Cohort (CRIC) Study: design and methods publication-title: J Am Soc Nephrol doi: 10.1097/01.ASN.0000070149.78399.CE – volume: 25 start-page: 644 year: 2007 ident: 7851_CR7 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.20831 – volume: 22 start-page: 397 year: 2014 ident: 7851_CR8 publication-title: Magn Reson Imaging Clin N Am doi: 10.1016/j.mric.2014.04.010 – volume: 258 start-page: 749 year: 2011 ident: 7851_CR12 publication-title: Radiology doi: 10.1148/radiol.10100659 – volume: 14 start-page: S148 year: 2003 ident: 7851_CR16 publication-title: J Am Soc Nephrol doi: 10.1097/01.ASN.0000070149.78399.CE – volume: 41 start-page: 233 year: 2015 ident: 7851_CR19 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24526 – volume: 66 start-page: 199 year: 2011 ident: 7851_CR5 publication-title: Magn Reson Med doi: 10.1002/mrm.22840 – volume: 36 start-page: 22 year: 2012 ident: 7851_CR25 publication-title: Aliment Pharmacol Ther doi: 10.1111/j.1365-2036.2012.05121.x – volume: 267 start-page: 767 year: 2013 ident: 7851_CR26 publication-title: Radiology doi: 10.1148/radiol.13121360 – volume: 36 start-page: 1011 year: 2012 ident: 7851_CR2 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.23741 – volume: 284 start-page: 244 year: 2017 ident: 7851_CR11 publication-title: Radiology doi: 10.1148/radiol.2017161786 – volume: 30 start-page: 579 year: 2017 ident: 7851_CR20 publication-title: Magn Reson Mater Phys doi: 10.1007/s10334-017-0642-z – volume: 42 start-page: 377 year: 2009 ident: 7851_CR18 publication-title: J Biomed Inform doi: 10.1016/j.jbi.2008.08.010 – volume: 288 start-page: E462 year: 2005 ident: 7851_CR24 publication-title: Am J Physiol Endocrinol Metab doi: 10.1152/ajpendo.00064.2004 – volume: 77 start-page: 1516 year: 2017 ident: 7851_CR10 publication-title: Magn Reson Med doi: 10.1002/mrm.26228 – ident: 7851_CR23 doi: 10.1002/mrm.28669 – volume: 30 start-page: 1215 year: 2009 ident: 7851_CR6 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.21957 – volume: 286 start-page: 486 year: 2018 ident: 7851_CR9 publication-title: Radiology doi: 10.1148/radiol.2017170550 – volume: 46 start-page: 379 year: 2001 ident: 7851_CR21 publication-title: Magn Reson Med doi: 10.1002/mrm.1201 – volume: 34 start-page: 729 year: 2011 ident: 7851_CR1 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.22580 – volume: 67 start-page: 389 year: 2012 ident: 7851_CR4 publication-title: Magn Reson Med doi: 10.1002/mrm.23016 – volume: 37 start-page: 1359 issue: 6 year: 2013 ident: 7851_CR13 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.23928 – volume: 42 start-page: 811 year: 2015 ident: 7851_CR15 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24842 – volume: 283 start-page: 438 year: 2017 ident: 7851_CR14 publication-title: Radiology doi: 10.1148/radiol.2017160606 – ident: 7851_CR17 – volume: 17 start-page: 211 year: 2009 ident: 7851_CR22 publication-title: Proc Int Soc Mag Reson Med – volume: 30 start-page: 5120 year: 2020 ident: 7851_CR27 publication-title: Eur Radiol doi: 10.1007/s00330-020-06858-x – volume: 29 start-page: 1253 year: 2009 ident: 7851_CR3 publication-title: Radiographics doi: 10.1148/rg.295085186 – volume: 80 start-page: 685 year: 2018 ident: 7851_CR28 publication-title: Magn Reson Med doi: 10.1002/mrm.27065  | 
    
| SSID | ssj0009147 | 
    
| Score | 2.44237 | 
    
| Snippet | Objectives
Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or... Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center... ObjectivesProton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or...  | 
    
| SourceID | proquest pubmed crossref springer  | 
    
| SourceType | Aggregation Database Index Database Enrichment Source Publisher  | 
    
| StartPage | 7566 | 
    
| SubjectTerms | Accuracy Bias Biomarkers Confidence intervals Diagnostic Radiology Field strength Imaging Internal Medicine Interventional Radiology Linearity Magnetic Resonance Magnetic resonance imaging Medicine Medicine & Public Health Neuroradiology Nonlinear systems Proton density (concentration) Radiology Reproducibility Statistical analysis Ultrasound Variability Weight  | 
    
| SummonAdditionalLinks | – databaseName: SpringerLink Journals (ICM) dbid: U2A link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwELZKKyEuCFoeCwUZiRtrKevH2uZWAau26iJUsVJvkeMHILXZZTd76K_pX2XGeVSogMQxydhJPOPxWDP-PkLeJq5ELJxgskIKM2MCM8pb5nHt16kqdMKN4vzz9HghTy_URXcobNNXu_cpyeyph8NuSDtWMCwpKJBRnpl7ZE8hnBdY8YIf3ULtTjKtGGzVDdPWyu6ozJ_7-H05uhNj3smP5mVn9og87OJFetQq-DHZifU-uT_vMuIH5OZsWX9j6F8pIj-s2erSNRiIUoSrRDTXtvz1ekyrH24zpq4OFENLh6x1dJko_P0V0i7BW758nM3o_PyEtrzSGwod0eQa-nPr2qKirMf31NFciMiwtDOux90V-M0ADVbfkZj4imbk2idkMfv09cMx60gXmBdaNWziIy9iMjLZBCOorHVwIwmnROEk11q4IAPXNvApTz4WwWuMsWTQPlXgP5-S3XpZx-eEoohMMgruYR8mtDVcuiJgkIXpTTMik37sS98hkiMxxmU5YClnfZWgrzLrq4Q274Y2qxaP45_Sh71Ky25ubkpwUlKpKUTGI_JmeAyzClMlro7LLcogfLNRSo3Is9YUhtcJ8MmG28mIjHvbuO3879_y4v_EX5IHHO001w0ekt1mvY2vIP5pqtfZ3H8BMXr6KQ priority: 102 providerName: Springer Nature  | 
    
| Title | Long-term inter-platform reproducibility, bias, and linearity of commercial PDFF MRI methods for fat quantification: a multi-center, multi-vendor phantom study | 
    
| URI | https://link.springer.com/article/10.1007/s00330-021-07851-8 https://www.ncbi.nlm.nih.gov/pubmed/33768291 https://www.proquest.com/docview/2574556999 https://www.proquest.com/docview/2506278555  | 
    
| Volume | 31 | 
    
| hasFullText | 1 | 
    
| inHoldings | 1 | 
    
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVLSH databaseName: SpringerLink Journals customDbUrl: mediaType: online eissn: 1432-1084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: AFBBN dateStart: 19970101 isFulltext: true providerName: Library Specific Holdings – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1432-1084 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: 7X7 dateStart: 20210101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: Proquest Central customDbUrl: http://www.proquest.com/pqcentral?accountid=15518 eissn: 1432-1084 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: BENPR dateStart: 20210101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Technology Collection customDbUrl: eissn: 1432-1084 dateEnd: 20241102 omitProxy: true ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: 8FG dateStart: 19970101 isFulltext: true titleUrlDefault: https://search.proquest.com/technologycollection1 providerName: ProQuest – providerCode: PRVAVX databaseName: SpringerLINK - Czech Republic Consortium customDbUrl: eissn: 1432-1084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: AGYKE dateStart: 19970101 isFulltext: true titleUrlDefault: http://link.springer.com providerName: Springer Nature – providerCode: PRVAVX databaseName: SpringerLink Journals (ICM) customDbUrl: eissn: 1432-1084 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0009147 issn: 0938-7994 databaseCode: U2A dateStart: 19970101 isFulltext: true titleUrlDefault: http://www.springerlink.com/journals/ providerName: Springer Nature  | 
    
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3db9MwED9trYR4QXzTMSoj8UYtUseuHSSECjQbH62miUrlKXJiGyZtademD_w1_Kv4nKQVmthLpCR2bPnO53Pu_PsBvHJMxDbSMeU5UpgpZagSRUILXPulyyPpcKM4nY1O5_zLQiwOYNaehcG0ytYmBkNtlgX-I3_jVYsLMfL-zPvVNUXWKIyuthQauqFWMO8CxNghdBkiY3Wg-2EyOzvfw_AOA-WY38YrKpOEN8dowmE6pDWLKKYsRMhYT9W_S9UN__NG7DQsSel9uNf4kmRcC_8BHNjyIdyZNtHyR_Dn27L8SdH2EkSFWNPVpa7QSSUIZYlIr3Vq7O8ByS_0ZkB0aQi6nRoZ7cjSET80V0jJ5Fs5-5SmZHr-mdSc0xviP0Scrsj1VtcJR0HGb4kmIUmRYtqnXQ-aO29Tja-w-oWkxVckoNo-hnk6-f7xlDaEDLSIpajosLAssk5xlzg_giJJtH_gYi3iSHMmZawNN0wmho2YK2xkCon-FzeycLm3rU-gUy5L-wwIFuGO25gVfo8Wy0QxriODDhiGPlUPhu3YZ0WDVo6kGZfZDmc5yCvz8sqCvDJf5_WuzqrG6ri19HEr0qyZt5tsr2U9eLl77WcchlF0aZdbLIPQzkoI0YOntSrsmou9vVYsGfZg0OrG_uP_78vR7X15DncZ6mXIITyGTrXe2hfeF6ryPhzKhfRXlZ70oTs--fF10m-U3j-ds_Ff9cIIUg | 
    
| linkProvider | ProQuest | 
    
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1fb9MwELemTQJeEONvYYCR4IlaJP7T2EgTAraqZW01TZu0t-DENiBtademQvs0fBM-23yO0wpN7G2PSWzHyp3vzrnz74fQW0cFs4lmhBdAYSalIVKUipTg-zNXJJmDjeJ40huc8G-n4nQD_W3PwkBZZWsTg6E20xL-kX_wqsWF6Pl45tPsggBrFGRXWwoNHakVzG6AGIsHOw7s5W-_hVvsDve8vN9R2t8__jogkWWAlCwTNUlLSxPrJHfKKSaFUtrfcEwLlmhOs4xpww3NlKE96kqbmDKDoIKbrHRFCqwR3gVsccaV3_xtfdmfHB6tYX_TQHGW-IFJphSPx3bC4T2gUUsIlEh4Ny1SIv91jdfi3Wu52uAC-w_Q_Ri74s-Nsm2jDVs9RHfGMTv_CP0ZTasfBGw9BhSKOZmd6RqCYgzQmYAs25TiXnZx8UsvulhXBkOYq4FBD08d9qI4Bwoo_5bDvX4fj4-GuOG4XmA_EHa6xhdL3RQ4BZ36iDUORZEEykztvBuvvA03vsPsJ5Akn-OAovsYndyKaJ6gzWpa2WcIQxPuuGW09HtClilJuU4MBHyQapUdlLbfPi8jOjqQdJzlK1znIK_cyysP8sp9n_erPrMGG-TG1jutSPNoJxb5Wqs76M3qsV_hkLbRlZ0uoQ1ASUshRAc9bVRh9Trm_YOkKu2gbqsb68H_P5fnN8_lNbo7OB6P8tFwcvAC3aOgo6F-cQdt1vOlfenjsLp4FZUdo--3vb6uALbDQOo | 
    
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1db9MwFLWmIU28IL4pDDASPFFriT_qGAkhxKhWtk4IMalvwYltQNqSrk2F9mv4H_w67nWSVmhib3tsaztR7sm9173H9xDyMnAlfGIFkwVKmGWZY5kqDSsx9utQJDrgRnF6PDo4kZ9marZF_vRnYZBW2fvE6KhdXeJ_5HsALanUCPKZvdDRIj7vj9_NzxkqSGGltZfTaCFy6C9-wfZt-XayD7Z-xfn449cPB6xTGGCl0Kphael54kMmgwlGZMoYC18EYZVIrORaC-uk49o4PuKh9IkrNSYU0ukyFCkqRoD7v6GFMEgn1DO9afibRnGzBJZl2hjZHdiJx_ZQQC1hSI6AAK1Slv0bFC9lupeqtDH4jW-TW13WSt-3MLtDtnx1l-xMu7r8PfL7qK6-M_TyFPtPLNj81DaYDlNsmok9ZVsS7sWQFj_tckht5SgmuBa182gdKBjhDMWf4CrwwMd0-mVCW3XrJYWFaLANPV_ZltoU0fSGWhrpkAwJpn4x7D6B93YwYf4D5ZHPaOyfe5-cXIthHpDtqq78I0JxiAzSC17CblBok3FpE4epHhZZswFJ-2efl11fdJTnOM3XHZ2jvXKwVx7tlcOc1-s587YryJWjd3uT5p2HWOYbPA_Ii_XP8G5jwcZWvl7hGGwinSmlBuRhC4X15QREhoybdECGPTY2i___Xh5ffS_PyQ4YOT-aHB8-ITc5QjQSF3fJdrNY-aeQgDXFs4h0Sr5d96v1F92IPoQ | 
    
| 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=Long-term+inter-platform+reproducibility%2C+bias%2C+and+linearity+of+commercial+PDFF+MRI+methods+for+fat+quantification%3A+a+multi-center%2C+multi-vendor+phantom+study&rft.jtitle=European+radiology&rft.au=Schneider%2C+Erika&rft.au=Remer%2C+Erick+M.&rft.au=Obuchowski%2C+Nancy+A.&rft.au=McKenzie%2C+Charles+A.&rft.date=2021-10-01&rft.issn=0938-7994&rft.eissn=1432-1084&rft.volume=31&rft.issue=10&rft.spage=7566&rft.epage=7574&rft_id=info:doi/10.1007%2Fs00330-021-07851-8&rft.externalDBID=n%2Fa&rft.externalDocID=10_1007_s00330_021_07851_8 | 
    
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0938-7994&client=summon | 
    
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0938-7994&client=summon | 
    
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0938-7994&client=summon |