Prediction of survival after hepatectomy using a physiologically based pharmacokinetic model of indocyanine green liver function tests
The evaluation of hepatic function and functional capacity of the liver are essential tasks in hepatology, especially in the context of liver surgery. Indocyanine Green (ICG) is a widely applied test compound that is used in clinical routine to evaluate hepatic function. Important questions for the functional evaluation with ICG in the context of hepatectomy are how liver disease such as cirrhosis alters ICG elimination, and if postoperative survival can be predicted from preoperative ICG measurements. Within this work a physiologically based pharmacokinetic (PBPK) model of ICG pharmacokinetics was developed and applied to the prediction of liver resection under various degrees of cirrhosis. For the parametrization of the computational model and validation of model predictions a database of ICG pharmacokinetic data was established. The model was applied (i) to study the effect of liver cirrhosis and hepatectomy on ICG pharmacokinetics; and (ii) to evaluate model-based prediction of postoperative ICG-R15 as a measure for postoperative outcome. Key results were that the model is able to accurately predict changes in ICG pharmacokinetics caused by liver cirrhosis and postoperative changes of ICG-elimination after liver resection, as validated with a wide range of data sets. Based on the PBPK model predictions a classifier allowed to predict survival after hepatectomy, demonstrating its potential value as a clinical tool.