DEVELOPMENT OF A QUANTITATIVE REAL-TIME MONITORING SYSTEM FOR LIVER TWO-STEP PERFUSION

Abstract

Isolated hepatocyte is vital in liver-related research, therapeutics, and drug testing. The widely-adopted two-step perfusion for hepatocyte isolation introduced by Seglen in 1976 relies on qualitative parameters to monitor perfusion. Such parameters cannot be objectively measured and thus there is a need for quantitative parameters. Here, we utilise weight and pressure changes in the liver throughout collagenase perfusion to monitor the hepatocyte isolation in real-time. We have trained an artificial neural network that can predict hepatocyte isolation performance from pressure measurements and determine the optimum collagenase perfusion duration using weight measurements. Optimal hepatocyte isolation is achieved when liver weight has increased by a minimal ~70% and ~80 s after liver weight reaches 1%-plateau. We have validated our observations from pressure and weight measurements by visualising and quantifying the structural changes in the liver during the perfusion process. Pressure and weight measurements can serve as real-time indicators of hepatocyte isolation performance.