A physiologically based computational model of incocyanine green (ICG) liver function tests
Channel: Systems Medicine of the Liver - König Lab
Date: 2021-08-25

Within this work a physiological-based model of ICG pharmacokinetics was developed and applied to the prediction of liver resection under various degrees of cirrhosis. For the parametrization and validation of the model a database of ICG pharmacokinetic data was established. The model was applied to study (i) the effect of liver disease, specifically liver cirrhosis, on ICG pharmacokinetics; and (ii) the effect of liver resection on ICG-elimination and the value of ICG as a predictive measure for postoperative outcome. The model performance could be validated on a wide range of clinical studies. The model is able to accurately predict changes in ICG pharmacokinetics caused by liver cirrhosis. Furthermore, the model is able to accurately predict postoperative changes of ICG-elimination after liver resection and outcome of liver resection, showing its potential value as a clinical tool.


[1] Adrian Köller, Jan Grzegorzewski and Matthias König
Physiologically based modeling of the effect of physiological and anthropometric variability on indocyanine green based liver function tests
bioRxiv 2021.08.11.455999; https://doi.org/10.1101/2021.08.11.455999



[2] Adrian Köller, Jan Grzegorzewski, Michael Tautenhahn, Matthias König
Prediction of survival after hepatectomy using a physiologically based pharmacokinetic model of indocyanine green liver function tests
bioRxiv 2021.06.15.448411;  https://doi.org/10.1101/2021.06.15.448411