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Cited by 498

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease

Open access
Banerjee, Rajarshi, Pavlides, Michael, Tunnicliffe, Elizabeth M., Piechnik, Stefan K., Sarania, Nikita, Philips, Rachel, Collier, Jane D., Booth, Jonathan C., Schneider, Jurgen E., Wang, Lai Mun, Delaney, David W., Fleming, Ken A., Robson, Matthew D., Barnes, Eleanor, Neubauer, Stefan·2014·Journal of Hepatology
DOI 10.1016/j.jhep.2013.09.002
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Abstract

BACKGROUND & AIMS: With the increasing prevalence of liver disease worldwide, there is an urgent clinical need for reliable methods to diagnose and stage liver pathology. Liver biopsy, the current gold standard, is invasive and limited by sampling and observer dependent variability. In this study, we aimed to assess the diagnostic accuracy of a novel magnetic resonance protocol for liver tissue characterisation. METHODS: We conducted a prospective study comparing our magnetic resonance technique against liver biopsy. The individual components of the scanning protocol were T1 mapping, proton spectroscopy and T2* mapping, which quantified liver fibrosis, steatosis and haemosiderosis, respectively. Unselected adult patients referred for liver biopsy as part of their routine care were recruited. Scans performed prior to liver biopsy were analysed by physicians blinded to the histology results. The associations between magnetic resonance and histology variables were assessed. Receiver-operating characteristic analyses were also carried out. RESULTS: Paired magnetic resonance and biopsy data were obtained in 79 patients. Magnetic resonance measures correlated strongly with histology (r(s)=0.68 p<0.0001 for fibrosis; r(s)=0.89 p<0.001 for steatosis; r(s)=-0.69 p<0.0001 for haemosiderosis). The area under the receiver operating characteristic curve was 0.94, 0.93, and 0.94 for the diagnosis of any degree of fibrosis, steatosis and haemosiderosis respectively. CONCLUSION: The novel scanning method described here provides high diagnostic accuracy for the assessment of liver fibrosis, steatosis and haemosiderosis and could potentially replace liver biopsy for many indications. This is the first demonstration of a non-invasive test to differentiate early stages of fibrosis from normal liver.

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Metadata

Authors
Banerjee, R., Pavlides, M., Tunnicliffe, E. M., Piechnik, S. K., Sarania, N., Philips, R., Collier, J. D., Booth, J. C., Schneider, J. E., Wang, L. M., Delaney, D. W., Fleming, K. A., Robson, M. D., Barnes, E., & Neubauer, S.
Venue
Journal of Hepatology
Publisher
Elsevier BV
Published
2014-01
Volume
60
Issue
1
Pages
69-77
ISSN
0168-8278 (ISSN-L)
DOI
10.1016/j.jhep.2013.09.002
OpenAlex
W2006766845
Cited by
498
References
27
FWCI
11.89
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. https://app.cochat.ai/papers/10.1016/j.jhep.2013.09.002
The paper
Banerjee, R., Pavlides, M., Tunnicliffe, E. M., Piechnik, S. K., Sarania, N., Philips, R., Collier, J. D., Booth, J. C., Schneider, J. E., Wang, L. M., Delaney, D. W., Fleming, K. A., Robson, M. D., Barnes, E., & Neubauer, S. (2014). Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. Journal of Hepatology. https://doi.org/10.1016/j.jhep.2013.09.002

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.