Magnetic resonance elastography is useful to determine the severity of liver fibrosis according to liver biopsy in post-fontan patients

Objective The reliability of various modalities for assessing and monitoring Fontan-associated liver disease compared to liver biopsy remains an intriguing subject of inquiry. Our objective was to assess the efficacy of multiple modalities in comparison to liver histology for evaluating liver fibrosis in post-Fontan patients. Methods We conducted a cross-sectional study involving Fontan patients without known liver disease. Eligible patients underwent cardiac and hepatic evaluations, including ultrasound liver elastography, magnetic resonance elastography (MRE) of the liver, computerized tomography (CT) scan of the upper abdomen, echocardiography, cardiac catheterization, and liver biopsy. The severity of liver fibrosis was categorized using the METAVIR score derived from liver biopsy results: F0/F1 indicated no or mild fibrosis, F2 indicated significant fibrosis, F3 indicated advanced fibrosis and F4 indicated cirrhosis. Results A total of 38 patients (mean age 21 ± 6.5 years, 52.6% female) were included in the cross-sectional study, with a mean time elapsed since the Fontan operation of 13 years. Parameters obtained from echocardiography, ultrasound liver elastography, and CT scan of the upper abdomen did not exhibit significant differences among the groups. Notably, liver biopsy revealed advanced cirrhosis in 23 out of 38 patients and none were diagnosed with hepatocellular carcinoma. Multivariate logistic regression analysis demonstrated that the factor significantly associated with significant liver fibrosis or cirrhosis in post-Fontan patients was liver stiffness with MRE > 4.4 kPa [OR 13.5 (95% CI 1.2-152.2)]. Conclusions Our findings suggest that post-Fontan patients with liver stiffness of MRE > 4.4 kPa should undergo further investigation. These results contribute to understanding the liver fibrosis assessment in post-Fontan patients and highlight the importance of MRE in predicting significant liver disease. Graphical Abstract