Multiparametric magnetic resonance imaging for quantitation of liver disease: a two-centre cross-sectional observational study.
Sci Rep
; 8(1): 9189, 2018 06 15.
Article
em En
| MEDLINE
| ID: mdl-29907829
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.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Imageamento por Ressonância Magnética
/
Fígado Gorduroso
/
Ferro
/
Fígado
/
Cirrose Hepática
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article