Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease

Michael Pavlides, Rajarshi Banerjee, Joanne Sellwood, Catherine J Kelly, Matthew D Robson, Jonathan C Booth, Jane Collier, Stefan Neubauer, Eleanor Barnes, Michael Pavlides, Rajarshi Banerjee, Joanne Sellwood, Catherine J Kelly, Matthew D Robson, Jonathan C Booth, Jane Collier, Stefan Neubauer, Eleanor Barnes

Abstract

Background & aims: Multiparametric magnetic resonance (MR) imaging has been demonstrated to quantify hepatic fibrosis, iron, and steatosis. The aim of this study was to determine if MR can be used to predict negative clinical outcomes in liver disease patients.

Methods: Patients with chronic liver disease (n=112) were recruited for MR imaging and data on the development of liver related clinical events were collected by medical records review. The median follow-up was 27months. MR data were analysed blinded for the Liver Inflammation and Fibrosis score (LIF; <1, 1-1.99, 2-2.99, and ⩾3 representing normal, mild, moderate, and severe liver disease, respectively), T2∗ for liver iron content and proportion of liver fat. Baseline liver biopsy was performed in 102 patients.

Results: Liver disease aetiologies included non-alcoholic fatty liver disease (35%) and chronic viral hepatitis (30%). Histologically, fibrosis was mild in 54 (48%), moderate in 17 (15%), and severe in 31 (28%) patients. Overall mortality was 5%. Ten patients (11%) developed at least one liver related clinical event. The negative predictive value of LIF<2 was 100%. Two patients with LIF 2-2.99 and eight with LIF⩾3 had a clinical event. Patients with LIF⩾3 had a higher cumulative risk for developing clinical events, compared to those with LIF<1 (p=0.02) and LIF 1-1.99 (p=0.03). Cox regression analysis including all 3 variables (fat, iron, LIF) resulted in an enhanced LIF predictive value.

Conclusions: Non-invasive standardised multiparametric MR technology may be used to predict clinical outcomes in patients with chronic liver disease.

Keywords: Iron corrected T(1); LIF score; LiverMultiScan; T(1) mapping.

Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Figures

Graphical abstract
Graphical abstract
Fig. 1
Fig. 1
Study flow chart. The Liver Inflammation and Fibrosis (LIF) score is a standardised continuous score (0–4) derived from liver T1 and T2∗ values. T1 primarily reflects the amount of extracellular fluid and can change with inflammation and fibrosis and T2∗ primarily reflects the amount of iron deposition. Liver iron has a confounding effect on T1, and this is accounted for in the LIF score calculation. ∗Liver iron concentration from T2∗ maps and hence LIF calculation was not possible in 4 cases. MR, magnetic resonance; 1H-MRS: proton (1H) magnetic resonance spectroscopy; LIF, Liver Inflammation and Fibrosis score.
Fig. 2
Fig. 2
Examples of LiverMultiScan MR data. Representative images from patients in each Liver Inflammation and Fibrosis (LIF) severity category, produced by analysis of the raw data using LiverMultiScan. LIF was measured in operator chosen regions of interest in the right liver lobe, in the liver parenchyma, away from vascular and biliary structures. The LIF scores measured for each image in this figure are indicated under each image. The predefined colour scale used to generate these maps is also included. LIF, Liver Inflammation and Fibrosis score. (This figure appears in colour on the web.)
Fig. 3
Fig. 3
Kaplan–Meier curves for liver related event free survival with patients stratified according to Liver Inflammation and Fibrosis scores. In the entire cohort, (A) there were significant differences between those with Liver Inflammation and Fibrosis (LIF) ⩾3 vs. LIF <1 (p = 0.02) and vs. LIF 1–1.99 (p = 0.003). There was a strong trend towards significance between LIF 2–2.99 vs. LIF 1–1.99 (p = 0.054). Including only compensated patients at baseline, (B) there was a significant difference between LIF ⩾ 3 vs. LIF 1–1.99 (p = 0.023) and a strong trend towards significance between LIF 2–2.99 vs. LIF 1–1.99 (p = 0.058). (This figure appears in colour on the web.)
Fig. 4
Fig. 4
Kaplan–Meier curves for liver related event free survival with patients stratified according to severity of liver iron and fat. There were no significant differences between the curves for (A) iron or (B) fat. Liver fat was categorised according to the liver fat content measured by proton magnetic resonance spectroscopy as 0: <1.5%, 1: 1.5% <fat <7.5% and 2: ⩾7.5%. Liver iron was categorised according to T2∗ as low iron: T2∗ >12.5 ms or high iron: T2∗ ⩽12.5 ms. (This figure appears in colour on the web.)

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