Cited by 376Liver Disease Diagnosis and TreatmentUltrasound Imaging and ElastographyLiver Disease and Transplantation

The DOI matches its Crossref record; 106 of the 107 references it cites were found in a registry or an index.

Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: A systematic review and meta-analysis

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Selvaraj, Emmanuel Anandraj, Mózes, Ferenc Emil, Jayaswal, Arjun Narayan Ajmer, Zafarmand, Mohammad Hadi, Vali, Yasaman, Lee, Jenny A., Levick, Christina Kim, Young, Liam Arnold Joseph, Palaniyappan, Naaventhan, Liu, Chang-Hai, Aithal, Guruprasad Padur, Romero-Gómez, Manuel, Brosnan, M. Julia, Tuthill, Theresa A., Anstee, Quentin M., Neubauer, Stefan, Harrison, Stephen A., Bossuyt, Patrick M., Pavlides, Michael, Anstee, Quentin, Daly, Ann, Johnson, Katherine, Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Bedossa, Pierre, Oakley, Fiona, Cordell, Heather, Day, Chris, Wonders, Kristy, Bossuyt, Patrick, Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Ratziu, Vlad, Clement, Karine, Pais, Raluca, Schuppan, Detlef, Schattenberg, Jörn, Vidal-Puig, Toni, Vacca, Michele, Rodrigues-Cuenca, Sergio, Allison, Mike, Kamzolas, Ioannis, Petsalaki, Evangelia, Oresic, Matej, Hyötyläinen, Tuulia, McGlinchey, Aiden, Mato, Jose M., Millet, Oscar, Dufour, Jean-François, Berzigotti, Annalisa, Pavlides, Michael, Harrison, Stephen, Neubauer, Stefan, Cobbold, Jeremy, Mozes, Ferenc, Akhtar, Salma, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Erpicum, Charlotte, Romero-Gómez, Manuel, Gómez-González, Emilio, Ampuero, Javier, Castell, Javier, Gallego-Durán, Rocío, Fernández, Isabel, Montero-Vallejo, Rocío, Karsdal, Morten, Erhardtsen, Elisabeth, Rasmussen, Daniel, Leeming, Diana Julie, Fisker, Mette Juul, Sinisi, Antonia, Musa, Kishwar, Betsou, Fay, Sandt, Estelle, Tonini, Manuela, Bugianesi, Elisabetta, Rosso, Chiara, Armandi, Angelo, Marra, Fabio, Gastaldelli, Amalia, Svegliati, Gianluca, Boursier, Jérôme, Francque, Sven, Vonghia, Luisa, Ekstedt, Mattias, Kechagias, Stergios, Yki-Jarvinen, Hannele, Luukkonen, Panu, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Valenti, Luca, Petta, Salvatore, Miele, Luca, Geier, Andreas, Trautwein, Christian, Aithal, Guru, Hockings, Paul, Newsome, Philip, Wenn, David, Pereira Rodrigues, Cecília Maria, Chaumat, Pierre, Hanf, Rémy, Trylesinski, Aldo, Ortiz, Pablo, Duffin, Kevin, Brosnan, Julia, Tuthill, Theresa, McLeod, Euan, Ertle, Judith, Younes, Ramy, Ostroff, Rachel, Alexander, Leigh, Kjær, Mette Skalshøi, Mikkelsen, Lars Friis, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Loeffler, Juergen, Hanauer, Guido, Shankar, Sudha, Fournier, Céline, Pepin, Kay, Ehman, Richard, Myers, Joel, Ho, Gideon, Torstenson, Richard, Myers, Rob, Doward, Lynda·2021·Journal of Hepatology

DOI 10.1016/j.jhep.2021.04.044

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Abstract

BACKGROUND AND AIMS: Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), 2-dimensional shear wave elastography (2DSWE), magnetic resonance elastography (MRE), and magnetic resonance imaging (MRI) have been proposed as non-invasive tests for patients with non-alcoholic fatty liver disease (NAFLD). This study evaluated their diagnostic accuracy for liver fibrosis and non-alcoholic steatohepatitis (NASH). METHODS: PubMED/MEDLINE, EMBASE and the Cochrane Library were searched for studies examining the diagnostic accuracy of these index tests, against histology as the reference standard, in adult patients with NAFLD. Two authors independently screened and assessed methodological quality of studies and extracted data. Summary estimates of sensitivity, specificity and area under the curve (sAUC) were calculated for fibrosis stages and NASH, using a random effects bivariate logit-normal model. RESULTS: We included 82 studies (14,609 patients). Meta-analysis for diagnosing fibrosis stages was possible in 53 VCTE, 11 MRE, 12 pSWE and 4 2DSWE studies, and for diagnosing NASH in 4 MRE studies. sAUC for diagnosis of significant fibrosis were: 0.83 for VCTE, 0.91 for MRE, 0.86 for pSWE and 0.75 for 2DSWE. sAUC for diagnosis of advanced fibrosis were: 0.85 for VCTE, 0.92 for MRE, 0.89 for pSWE and 0.72 for 2DSWE. sAUC for diagnosis of cirrhosis were: 0.89 for VCTE, 0.90 for MRE, 0.90 for pSWE and 0.88 for 2DSWE. MRE had sAUC of 0.83 for diagnosis of NASH. Three (4%) studies reported intention-to-diagnose analyses and 15 (18%) studies reported diagnostic accuracy against pre-specified cut-offs. CONCLUSIONS: When elastography index tests are acquired successfully, they have acceptable diagnostic accuracy for advanced fibrosis and cirrhosis. The potential clinical impact of these index tests cannot be assessed fully as intention-to-diagnose analyses and validation of pre-specified thresholds are lacking. LAY SUMMARY: Non-invasive tests that measure liver stiffness or use magnetic resonance imaging (MRI) have been suggested as alternatives to liver biopsy for assessing the severity of liver scarring (fibrosis) and fatty inflammation (steatohepatitis) in patients with non-alcoholic fatty liver disease (NAFLD). In this study, we summarise the results of previously published studies on how accurately these non-invasive tests can diagnose liver fibrosis and inflammation, using liver biopsy as the reference. We found that some techniques that measure liver stiffness had a good performance for the diagnosis of severe liver scarring.

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QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies
Whiting, P. F., Rutjes, A. W. S., Westwood, M. E., Mallett, S., Deeks, J. J., Reitsma, J. B., Leeflang, M. M. G., Sterne, J. A. C., Bossuyt, P. M. M., & the QUADAS-2 Group* (2011) · Annals of Internal Medicine · doi:10.7326/0003-4819-155-8-201110180-00009 · Cited by 14,199
Self-citation
Design and validation of a histological scoring system for nonalcoholic fatty liver disease†
Kleiner, D. E., Brunt, E. M., Van Natta, M., Behling, C., Contos, M. J., Cummings, O. W., Ferrell, L. D., Liu, Y., Torbenson, M. S., Unalp‐Arida, A., et al. (2005) · Hepatology · doi:10.1002/hep.20701 · Cited by 10,791
Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes
Younossi, Z. M., Koenig, A. B., Abdelatif, D., Fazel, Y., Henry, L., & Wymer, M. (2016) · Hepatology · doi:10.1002/hep.28431 · Cited by 10,781
EASL–EASD–EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease
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Increased risk of mortality by fibrosis stage in nonalcoholic fatty liver disease: Systematic review and meta‐analysis
Dulai, P. S., Singh, S., Patel, J., Soni, M., Prokop, L. J., Younossi, Z., Sebastiani, G., Ekstedt, M., Hagstrom, H., Nasr, P., et al. (2017) · Hepatology · doi:10.1002/hep.29085 · Cited by 1,965
Self-citation
Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis
Anstee, Q. M., Targher, G., & Day, C. P. (2013) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2013.41 · Cited by 1,747
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Castera, L., Friedrich-Rust, M., & Loomba, R. (2019) · Gastroenterology · doi:10.1053/j.gastro.2018.12.036 · Cited by 1,494
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Eddowes, P. J., Sasso, M., Allison, M., Tsochatzis, E. A., Anstee, Q. M., Sheridan, D. A., Guha, I. N., Cobbold, J., Deeks, J. J., Paradis, V., et al. (2019) · Gastroenterology · doi:10.1053/j.gastro.2019.01.042 · Cited by 1,425
Diagnosis of Fibrosis and Cirrhosis Using Liver Stiffness Measurement in Nonalcoholic Fatty Liver Disease
Wong, V. W.-S., Vergniol, J., Wong, G. L.-H., Foucher, J., Chan, H. L.-Y., Le Bail, B., Choi, P. C.-L., Kowo, M., Chan, A. W.-H., Merrouche, W., et al. (2010) · Hepatology · doi:10.1002/hep.23312 · Cited by 1,322

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Al Juboori, 2018, The utility of liver elastography in evaluation of liver fibrosis in obese patients undergoing bariatric surgery, Hepatology, 68
Clet, 2018, Expanding the Use of the VCTE XL probe in morbid obese patients: validation of a new automated adaptive measurement depths algorithm in a large UK multicenter cohort, Hepatology, 68
Hee, 2014, Comparison of NAFLD Fibrosis Score (NFS) and transient elastography (Fibroscan), alone and in combination, as non-invasive methods for the evaluation of fibrosis in non-alcoholic fatty liver disease (NAFLD), J Gastroenterol Hepatol, 29, 76
Pais, 2011, Validation of a simple algorithm combining serum markers and elastometry for the diagnosis of fibrosis in NAFLD, Hepatology, 54

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Yang, X., Xia, M., Chang, X., Zhu, X., Sun, X., Yang, Y., Wang, L., Liu, Q., Zhang, Y., Xu, Y., et al. (2022) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3570 · Cited by 10
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Shahryari, M., Keller, S., Meierhofer, D., Wallach, I., Safraou, Y., Guo, J., Garcia, S. R. M., Braun, J., Makowski, M. R., Sack, I., et al. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.1042711 · Cited by 10
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Li, Q., Gao, Y., Wang, D., Zhu, X., Jia, J., Liu, L.-L., Tian, H., Wang, L., Zhang, Y., & Zhang, D. (2025) · Academic Radiology · doi:10.1016/j.acra.2025.04.009 · Cited by 11
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Shi, Y., & Fan, J. (2022) · Clinical and Molecular Hepatology · doi:10.3350/cmh.2022.0401 · Cited by 9
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Authors: Selvaraj, E. A., Mózes, F. E., Jayaswal, A. N. A., Zafarmand, M. H., Vali, Y., Lee, J. A., Levick, C. K., Young, L. A. J., Palaniyappan, N., Liu, C.-H., Aithal, G. P., Romero-Gómez, M., Brosnan, M. J., Tuthill, T. A., Anstee, Q. M., Neubauer, S., Harrison, S. A., Bossuyt, P. M., Pavlides, M., Anstee, Q., Daly, A., Johnson, K., Govaere, O., Cockell, S., Tiniakos, D., Bedossa, P., Oakley, F., Cordell, H., Day, C., Wonders, K., Bossuyt, P., Zafarmand, H., Vali, Y., Lee, J., Ratziu, V., Clement, K., Pais, R., Schuppan, D., Schattenberg, J., Vidal-Puig, T., Vacca, M., Rodrigues-Cuenca, S., Allison, M., Kamzolas, I., Petsalaki, E., Oresic, M., Hyötyläinen, T., McGlinchey, A., Mato, J. M., Millet, O., Dufour, J.-F., Berzigotti, A., Pavlides, M., Harrison, S., Neubauer, S., Cobbold, J., Mozes, F., Akhtar, S., Banerjee, R., Kelly, M., Shumbayawonda, E., Dennis, A., Erpicum, C., Romero-Gómez, M., Gómez-González, E., Ampuero, J., Castell, J., Gallego-Durán, R., Fernández, I., Montero-Vallejo, R., Karsdal, M., Erhardtsen, E., Rasmussen, D., Leeming, D. J., Fisker, M. J., Sinisi, A., Musa, K., Betsou, F., Sandt, E., Tonini, M., Bugianesi, E., Rosso, C., Armandi, A., Marra, F., Gastaldelli, A., Svegliati, G., Boursier, J., Francque, S., Vonghia, L., Ekstedt, M., Kechagias, S., Yki-Jarvinen, H., Luukkonen, P., van Mil, S., Papatheodoridis, G., Cortez-Pinto, H., Valenti, L., Petta, S., Miele, L., Geier, A., Trautwein, C., Aithal, G., Hockings, P., Newsome, P., Wenn, D., Pereira Rodrigues, C. M., Chaumat, P., Hanf, R., Trylesinski, A., Ortiz, P., Duffin, K., Brosnan, J., Tuthill, T., McLeod, E., Ertle, J., Younes, R., Ostroff, R., Alexander, L., Kjær, M. S., Mikkelsen, L. F., Balp, M.-M., Brass, C., Jennings, L., Martic, M., Loeffler, J., Hanauer, G., Shankar, S., Fournier, C., Pepin, K., Ehman, R., Myers, J., Ho, G., Torstenson, R., Myers, R., & Doward, L.
Affiliations: University of Oxford (GB)
Nottingham University Hospitals NHS Trust (GB)
Pfizer (United States) (US)
Amsterdam University Medical Centers (NL)
Instituto de Biomedicina de Sevilla (ES)
ORCID: Selvaraj, Emmanuel Anandraj
Jayaswal, Arjun Narayan Ajmer
Lee, Jenny A.
Levick, Christina Kim
Young, Liam Arnold Joseph
Palaniyappan, Naaventhan
Liu, Chang-Hai
Aithal, Guruprasad Padur
Tuthill, Theresa A.
Anstee, Quentin M.
Daly, Ann
Johnson, Katherine
Govaere, Olivier
Cockell, Simon
Tiniakos, Dina
Oakley, Fiona
Cordell, Heather
Day, Chris
Wonders, Kristy
Ratziu, Vlad
Pais, Raluca
Schuppan, Detlef
Schattenberg, Jörn
Kamzolas, Ioannis
Petsalaki, Evangelia
Hyötyläinen, Tuulia
Dufour, Jean-François
Berzigotti, Annalisa
Cobbold, Jeremy
Banerjee, Rajarshi
Kelly, Matt
Shumbayawonda, Elizabeth
Dennis, Andrea
Gómez-González, Emilio
Ampuero, Javier
Karsdal, Morten
Rasmussen, Daniel
Betsou, Fay
Bugianesi, Elisabetta
Rosso, Chiara
Armandi, Angelo
Marra, Fabio
Gastaldelli, Amalia
Boursier, Jérôme
Francque, Sven
Vonghia, Luisa
Ekstedt, Mattias
Kechagias, Stergios
Luukkonen, Panu
Papatheodoridis, George
Valenti, Luca
Petta, Salvatore
Miele, Luca
Geier, Andreas
Trautwein, Christian
Hockings, Paul
Newsome, Philip
Ortiz, Pablo
Duffin, Kevin
Ertle, Judith
Younes, Ramy
Ostroff, Rachel
Alexander, Leigh
Kjær, Mette Skalshøi
Mikkelsen, Lars Friis
Balp, Maria-Magdalena
Jennings, Lori
Loeffler, Juergen
Shankar, Sudha
Fournier, Céline
Pepin, Kay
Ehman, Richard
Ho, Gideon
Doward, Lynda
Venue: Journal of Hepatology
Publisher: Elsevier BV
Published: 2021-10
Volume: 75
Issue: 4
Pages: 770-785
ISSN: 0168-8278 (ISSN-L)
DOI: 10.1016/j.jhep.2021.04.044
OpenAlex: W3161701468
Cited by: 376
References: 107
Citations by year: 2026: 67 · 2025: 84 · 2024: 77 · 2023: 81 · 2022: 52 · 2021: 14
FWCI: 8.58
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc-nd
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)
Locations: Journal of Hepatology (publishedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Deposito de Investigacion Universidad de Sevilla (University of Seville) (publishedVersion, cc-by-nc-nd)
Pure Amsterdam UMC (publishedVersion, cc-by)
University of Birmingham Research Portal (University of Birmingham) (publishedVersion, cc-by-nc-nd)
Repository@Nottingham (University of Nottingham) (acceptedVersion, other-oa)
Florence Research (University of Florence) (submittedVersion, cc-by-nc-nd)
Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by-nc-nd)
Lirias (KU Leuven) (submittedVersion, cc-by-nc-nd)
Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
HAL (submittedVersion)
Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by-nc-nd)
Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Nova Science Publishers (Nova Science Publishers, Inc.) (submittedVersion, other-oa)
PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by-nc-nd)
CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) (submittedVersion, cc-by-nc-nd)
Newcastle University ePrints (Newcastle Univesity) (cc-by-nc-nd)
Funders: European Federation of Pharmaceutical Industries and Associations
Innovative Medicines Initiative (777377)
Topics: Health Sciences › Medicine › Hepatology › Liver Disease Diagnosis and Treatment
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Ultrasound Imaging and Elastography
Health Sciences › Medicine › Hepatology › Liver Disease and Transplantation
Keywords: non-alcoholic fatty liver disease, liver fibrosis, nonalcoholic steatohepatitis, vibration-controlled transient elastography, point shear wave elastography, two-dimensional shear wave elastography, magnetic resonance elastography, magnetic resonance imaging, noninvasive fibrosis assessment, liver cirrhosis, diagnostic accuracy
MeSH terms: Adult, Humans, Magnetic Resonance Imaging, ROC Curve, Area Under Curve, Elasticity Imaging Techniques, Non-alcoholic Fatty Liver Disease

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