Multiparametric magnetic resonance imaging for quantitation of liver disease: a two-centre cross-sectional observational study

Natasha McDonald, Peter J Eddowes, James Hodson, Scott I K Semple, Nigel P Davies, Catherine J Kelly, Stella Kin, Miranda Phillips, Amy H Herlihy, Timothy J Kendall, Rachel M Brown, Desley A H Neil, Stefan G Hübscher, Gideon M Hirschfield, Jonathan A Fallowfield, Natasha McDonald, Peter J Eddowes, James Hodson, Scott I K Semple, Nigel P Davies, Catherine J Kelly, Stella Kin, Miranda Phillips, Amy H Herlihy, Timothy J Kendall, Rachel M Brown, Desley A H Neil, Stefan G Hübscher, Gideon M Hirschfield, Jonathan A Fallowfield

Abstract

LiverMultiScan is an emerging diagnostic tool using multiparametric MRI to quantify liver disease. In a two-centre prospective validation study, 161 consecutive adult patients who had clinically-indicated liver biopsies underwent contemporaneous non-contrast multiparametric MRI at 3.0 tesla (proton density fat fraction (PDFF), T1 and T2* mapping), transient elastography (TE) and Enhanced Liver Fibrosis (ELF) test. Non-invasive liver tests were correlated with gold standard histothological measures. Reproducibility of LiverMultiScan was investigated in 22 healthy volunteers. Iron-corrected T1 (cT1), TE, and ELF demonstrated a positive correlation with hepatic collagen proportionate area (all p < 0·001). TE was superior to ELF and cT1 for predicting fibrosis stage. cT1 maintained good predictive accuracy for diagnosing significant fibrosis in cases with indeterminate ELF, but not for cases with indeterminate TE values. PDFF had high predictive accuracy for individual steatosis grades, with AUROCs ranging from 0.90-0.94. T2* mapping diagnosed iron accumulation with AUROC of 0.79 (95% CI: 0.67-0.92) and negative predictive value of 96%. LiverMultiScan showed excellent test/re-test reliability (coefficients of variation ranging from 1.4% to 2.8% for cT1). Overall failure rates for LiverMultiScan, ELF and TE were 4.3%, 1.9% and 15%, respectively. LiverMultiScan is an emerging point-of-care diagnostic tool that is comparable with the established non-invasive tests for assessment of liver fibrosis, whilst at the same time offering a superior technical success rate and contemporaneous measurement of liver steatosis and iron accumulation.

Conflict of interest statement

Neither the sponsor nor funding body had a role in study design, data collection, data analysis, data interpretation, or writing the report. The corresponding author had full access to all the study data and final responsibility for the decision to submit for publication. Catherine J. Kelly, Stella Kin, Miranda Phillips and Amy H. Herlihy are employees of Perspectum Diagnostics Ltd., the developer of LiverMultiScanTM. All other authors declare no competing interests.

Figures

Figure 1
Figure 1
Study flowchart.
Figure 2
Figure 2
Multivariable analysis of inflammation and fibrosis. Plotted values are arithmetic means for cT1 and ELF score, and geometric means for TE, with the error bars representing 95% confidence intervals. Only one patient had no/minimal inflammation and a modified Ishak score (MIS) of 0, hence this point was excluded from the plots.

References

    1. Younossi ZM, et al. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64(1):73–84. doi: 10.1002/hep.28431.
    1. Davies, S.C. Chief Medical Officer Annual Report 2011. Preprint at, (2011).
    1. The All-Party Parliamentary Hepatology Group (APPHG) Inquiry into Improving Outcomes in Liver Disease. Liver Disease: Today’s complacency, tomorrow’s catastrophe. Preprint at, (2014).
    1. Williams R, et al. Addressing liver disease in the UK: a blueprint for attaining excellence in health care and reducing premature mortality from lifestyle issues of excess consumption of alcohol, obesity, and viral hepatitis. Lancet. 2014;384(9958):1953–1997. doi: 10.1016/S0140-6736(14)61838-9.
    1. Blachier M, Leleu H, Peck-Radosavljevic M, Valla DC, Roudot-Thoraval F. The burden of liver disease in Europe: a review of available epidemiological data. J. Hepatol. 2013;58(3):593–608. doi: 10.1016/j.jhep.2012.12.005.
    1. Kan VY, et al. Patient preference and willingness to pay for transient elastography versus liver biopsy: A perspective from British Columbia. Can. J Gastroenterol Hepatol. 2015;29(2):72–76. doi: 10.1155/2015/169190.
    1. Pang JX, et al. Liver stiffness by transient elastography predicts liver-related complications and mortality in patients with chronic liver disease. PLoS One. 2014;9(4):e95776. doi: 10.1371/journal.pone.0095776.
    1. Castera L, et al. Pitfalls of liver stiffness measurement: a 5-year prospective study of 13,369 examinations. Hepatology. 2010;51(3):828–835.
    1. Pavlov CS, et al. Transient elastography for diagnosis of stages of hepatic fibrosis and cirrhosis in people with alcoholic liver disease. Cochrane Database Syst Rev. 2015;1:CD010542.
    1. Nascimbeni F, et al. Significant variations in elastometry measurements made within short-term in patients with chronic liver diseases. Clin. Gastroenterol Hepatol. 2015;13(4):763–771. doi: 10.1016/j.cgh.2014.07.037.
    1. Irvine KM, et al. The Enhanced liver fibrosis score is associated with clinical outcomes and disease progression in patients with chronic liver disease. Liver Int. 2016;36(3):370–377. doi: 10.1111/liv.12896.
    1. Poynard T, et al. Slow regression of liver fibrosis presumed by repeated biomarkers after virological cure in patients with chronic hepatitis C. J. Hepatol. 2013;59(4):675–683. doi: 10.1016/j.jhep.2013.05.015.
    1. Ahmed HU, et al. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet. 2017;389(10071):815–822. doi: 10.1016/S0140-6736(16)32401-1.
    1. Kang GH, et al. Reproducibility of MRI-determined proton density fat fraction across two different MR scanner platforms. J. Magn Reson Imaging. 2011;34(4):928–934. doi: 10.1002/jmri.22701.
    1. Noureddin M, et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology. 2013;58(6):1930–1940. doi: 10.1002/hep.26455.
    1. Singh S, et al. Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clin. Gastroenterol Hepatol. 2015;13(3):440–451. doi: 10.1016/j.cgh.2014.09.046.
    1. Banerjee R, et al. Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. J. Hepatol. 2014;60(1):69–77. doi: 10.1016/j.jhep.2013.09.002.
    1. Pavlides M, et al. Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease. J. Hepatol. 2016;64(2):308–315. doi: 10.1016/j.jhep.2015.10.009.
    1. Philips, B. et al. Oxford Centre for Evidence-based Medicine – Levels of Evidence. Preprint at, (2009).
    1. Cohen JF, et al. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open. 2016;6(11):e012799. doi: 10.1136/bmjopen-2016-012799.
    1. Wyatt, J., Hubscher, S. & Bellamy, C. Tissue pathways for liver biopsies for the investigation of medical disease and for focal lesions. Preprint at, (2014).
    1. Calvaruso V, et al. Computer-assisted image analysis of liver collagen: relationship to Ishak scoring and hepatic venous pressure gradient. Hepatology. 2009;49(4):1236–1244. doi: 10.1002/hep.22745.
    1. Brunt EM, Janney CG, Di Bisceglie AM, Neuschwander-Tetri BA, Bacon BR. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am. J Gastroenterol. 1999;94(9):2467–2474. doi: 10.1111/j.1572-0241.1999.01377.x.
    1. Scheuer PJ, Williams R, Muir AR. Hepatic pathology in relatives of patients with haemochromatosis. J. Pathol Bacteriol. 1962;84:53–64. doi: 10.1002/path.1700840107.
    1. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–174. doi: 10.2307/2529310.
    1. Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic. Fam. Med. 2005;37(5):360–363.
    1. Hoad CL, et al. A study of T(1) relaxation time as a measure of liver fibrosis and the influence of confounding histological factors. NMR Biomed. 2015;28(6):706–714. doi: 10.1002/nbm.3299.
    1. Mozes FE, Tunnicliffe EM, Pavlides M, Robson MD. Influence of fat on liver T1 measurements using modified Look-Locker inversion recovery (MOLLI) methods at 3T. J. Magn Reson Imaging. 2016;44(1):105–111. doi: 10.1002/jmri.25146.
    1. National Institute for Health and Care Excellence (NICE). Non-alcoholic fatty liver disease (NAFLD): assessment and management. Preprint at, (2016).
    1. Blake L, Duarte RV, Cummins C. Decision analytic model of the diagnostic pathways for patients with suspected non-alcoholic fatty liver disease using non-invasive transient elastography and multiparametric magnetic resonance imaging. BMJ Open. 2016;6(9):e010507. doi: 10.1136/bmjopen-2015-010507.
    1. Wilman HR, et al. Characterisation of liver fat in the UK Biobank cohort. PLoS One. 2017;12(2):e0172921. doi: 10.1371/journal.pone.0172921.
    1. Byrne CD, Targher G. Time to Replace Assessment of Liver Histology With MR-Based Imaging Tests to Assess Efficacy of Interventions for Nonalcoholic Fatty Liver Disease. Gastroenterology. 2016;150(1):7–10. doi: 10.1053/j.gastro.2015.11.016.
    1. Eddowes PJ, et al. Utility and cost evaluation of multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease. Aliment. Pharmacol Ther. 2018;47(5):631–644. doi: 10.1111/apt.14469.
    1. Hernando D, Levin YS, Sirlin CB, Reeder SB. Quantification of liver iron with MRI: state of the art and remaining challenges. J. Magn Reson Imaging. 2014;40(5):1003–1021. doi: 10.1002/jmri.24584.
    1. Sarigianni M, et al. Accuracy of magnetic resonance imaging in diagnosis of liver iron overload: a systematic review and meta-analysis. Clin. Gastroenterol Hepatol. 2015;13(1):55–63 e55. doi: 10.1016/j.cgh.2014.05.027.

Source: PubMed

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