Satapathy SK, Gonzalez HC, Vanatta J, Dyer A, Angel W, Nouer SS, Kocak M, Kedia SK, Jiang Y, Clark I, Yadak N, Nezakagtoo N, Helmick R, Horton P, Campos L, Agbim U, Maliakkal B, Maluf D, Nair S, Halford HH, and Eason JD. A pilot study of ex-vivo MRI-PDFF of donor livers for assessment of steatosis and predicting early graft dysfunction. PLoS One 2020; 15(5).
BACKGROUND: The utility of ex vivo Magnetic resonance imaging proton density fat fraction (MRI-PDFF) in donor liver fat quantification is unknown.
PURPOSE: To evaluate the diagnostic accuracy and utility in predicting early allograft dysfunction (EAD) of ex vivo MRI-PDFF measurement of fat in deceased donor livers using histology as the gold standard.
METHODS: We performed Ex vivo, 1.5 Tesla MRI-PDFF on 33 human deceased donor livers before implantation, enroute to the operating room. After the exclusion of 4 images (technical errors), 29 MRI images were evaluable. Histology was evaluable in 27 of 29 patients. EAD was defined as a peak value of aminotransferase >2000 IU/mL during the first week or an INR of ≥1.6 or bilirubin ≥10 mg/dL at day 7.
RESULTS: MRI-PDFF values showed a strong positive correlation (Pearson's correlation coefficient) when histology (macro-steatosis) was included (r = 0.78, 95% confidence interval 0.57-0.89, p<0.0001). The correlation appeared much stronger when macro plus micro-steatosis were included (r = 0.87, 95% confidence interval 0.72-0.94, p<0.0001). EAD was noted in 7(25%) subjects. AUC (Area Under the Curve) for macro steatosis (histology) predicted EAD in 73% (95% CI: 48-99), micro plus macro steatosis in 76% (95% CI: 49-100). AUC for PDFF values predicted EAD in 67(35-98). Comparison of the ROC curves in a multivariate model revealed, adding MRI PDFF values to macro steatosis increased the ability of the model in predicting EAD (AUC: 79%, 95% CI: 59-99), and addition of macro plus micro steatosis based on histology predicted EAD even better (AUC: 90%: 79-100, P = 0.054).
CONCLUSION: In this pilot study, MRI-PDFF imaging showed potential utility in quantifying hepatic steatosis ex-vivo donor liver evaluation and the ability to predict EAD related to severe allograft steatosis in the recipient.