Studying the thermal effects of a clinically-extracted vascular tissue during cryo-freezing

Cryosurgery is known to be a suitable treatment for unresectable tumors by employing extremely low temperature to induce cryo-lesion. However, large blood vessels in the tissue may induce insufficient freezing at the targeted area. In this work, we have developed a cryo-freezing model specifically dedicated to tumors with a complex blood vessel network taken from CT-scanned images. The model was validated with in-vitro experimental data. Adopting an appropriate mesh size, the simulated results achieved an excellent agreement with the experimental data at a maximum error of 3.4%. The validated model was applied to study an optimal cryotherapy in the treatment of a human liver. The movement of 265 K isotherm and the thermal influence of blood flow were investigated. Key results indicated that large neighboring vessels could significantly influence the shape of the ice fronts, but they exerted less impact on the development of the lethal temperature boundary. The freezing duration, distance to the vessel, blood flow rate and blood vessel size were observed to be key parameters in determining the optimal cryoablation. A case study further demonstrated that by precisely controlling the cryo-freezing process, up to 44.6% of the unintended tissue freezing could be achieved. Pragmatically, this work provides surgeons with essential information on how to precisely tune key parameters to promote greater surgical success.

► We develop a bioheat model incorporating a CT-scanned blood vessel network. ► Precise cryo-freezing control reduces unintended tissue freezing up to 44.6%. ► Blood vessels with high flow rate markedly affect the tissue temperature profiles. ► Reduced thermal impact of blood vessels on tumor located further away from vessels.