Coupled experimental-modeling analyses of heat transfer in ex-vivo VS55-perfused porcine hepatic tissue being plunged in liquid nitrogen for vitreous cryopreservation

Vitreous cryopreservation refers to preserve biomaterials without or with very limited amount ice formation, which has been regarded to be the most promising method for large scale biopreservation (e.g., tissues and organs). However, the thermal stresses, internal stresses and residual stresses induced by ultra-rapid cooling and non-uniform temperature distribution have greatly hindered the application of this novel technology. To precisely predict the transient temperature distribution in the bio-samples during freezing is the prerequisite for theory based optimization of vitrification. Although it's of primary importance, modeling on vitrification of large scale biomaterials is very limited, as may be due to the fact that the key thermo-physical parameters are very scarce at such low temperatures with a so wide range (typically, -196 to 37 degrees C). In this study, we developed a coupled experimental-modeling approach for high-precision prediction of the transient temperature during vitrification of biomaterials by liquid nitrogen. The thermal conductivities of VS55 solution and VS55-perfused porcine hepatic tissue at subzero temperatures were measured using a self-made while validated tiny heat probe, and the convective heat transfer coefficient on the outer wall of the cryovial during being plunged into liquid nitrogen was computed with an inverse problem method, and then all these experimentally determined thermo-physical parameters were incorporated into a theoretical model to predict the transient temperature fields in the porcine hepatic tissue. It follows that the predictions using the developed model in this study are consistent with the experimental results, as may benefit from the fact that the parameters used in this typical model are predetermined by real-vitrification-preservation-process-oriented. Besides that the coupled experimental-modeling approach established in this study leads to potential applications in optimization of vitreous cryopreservation of large scale biomaterials. (C) 2016 Elsevier Ltd. All rights reserved.