Quantitative multiparametric MRI as a non-invasive stratification tool in children and adolescents with autoimmune liver disease

Author:

Janowski Kamil,Shumbayawonda Elizabeth,Cheng Lin,Langford Caitlin,Dennis Andrea,Kelly Matt,Pronicki Maciej,Grajkowska Wieslawa,Wozniak Malgorzata,Pawliszak Piotr,Chełstowska Sylwia,Jurkiewicz Elzbieta,Banerjee Rajarshi,Socha Piotr

Abstract

AbstractAutoimmune hepatitis (AIH) and autoimmune sclerosing cholangitis (ASC) are two very closely related autoimmune liver diseases with overlapping clinical features and similar management strategies. The purpose of this study was to assess the utility of quantitative imaging markers to distinguish ASC from AIH in paediatrics. 66 participants (N = 52 AIH, N = 14 ASC) aged 14.4 ± 3.3 years scheduled to undergo routine biopsy and baseline serum liver biochemistry testing were invited to undergo MRI (non-contrast abdominal MRI and 3D fast spin-echo MRCP). Multiparametric MRI was used to measure fibro-inflammation with corrected T1 (cT1), while the biliary tree was modelled   using quantitative MRCP (MRCP +). Mann–Whitney U tests were performed to compare liver function tests with imaging markers between patient groups (ASC vs AIH). Receiver operating characteristic curves and stepwise logistic regressions were used to identify the best combination of markers to discriminate between ASC and AIH. Correlations between liver function tests and imaging markers were performed using Spearman’s rank correlation. cT1 was significantly correlated with liver function tests (range 0.33 ≤ R ≤ 56, p < 0.05), as well as with fibrosis, lobular and portal inflammation (range 0.31 ≤ R ≤ 42, p < 0.05). 19 MRCP + metrics correlated significantly with liver function tests (range 0.29 ≤ R ≤ 0.43, p < 0.05). GGT and MRCP + metrics were significantly higher in ASC compared to those with AIH. The best multivariable model for distinguishing ASC from AIH included total number of ducts and the sum of relative severity of both strictures and dilatations AUC: 0.91 (95% CI 0.78–1). Quantitative MRCP metrics are a good discriminator of ASC from AIH.

Funder

Eurostars

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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