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Both cryosurgery and radiofrequency ablation (RFA) for solid liver tumor treatment are available as minimally invasive procedures that induce changes to the tumor’s thermal environment in order to destroy cancer cells. However, one of the critical factors that impedes cryosurgery and RFA’s successful outcomes is the relatively high recurrence rate caused by the inability to ablate a large damaged tissue zone that envelopes targeted tumors, resulting in therapy failure. To overcome these challenges, a hybrid cryo-RFA system under thermal stress control is proposed in this study. A three-dimensional finite difference analysis is employed to simulate the combined cryosurgery and RF heating protocol. Based on the data acquired from measured experiments, the simulated results derived have demonstrated close agreement with experimental data, with a maximum deviation of 4.8%. We investigated the impacts of varying cryoprobe’s holding temperature and cooling rates on tissue damage. Results have revealed that the tissue damage region is enhanced by properly increasing the cryoprobe’s cooling rate, but the increase of cryoprobe’s cooling rate cannot enlarges the tissue damage area without limit in the freezing process. In addition, the employment of a hybrid cryo-RFA system markedly promotes the destruction of cancer tissue in contrast to conventional stand-alone RF heating or cryosurgery.

Cryosurgery is becoming an effective method to treat undesired tumor tissue via the application of extremely low temperature coolant flowing through a probe. To maximize cryoinjury in the targeted tumor region, multiple cryoprobes are simultaneously employed to freeze the surrounding tumor tissues. In order to minimize cryosurgical injury to the surrounding health tissues, the cryoprobe localization for each specific tumor is critical. We developed finite difference analysis to calculate the freezing process during cryosurgery. According to our experimental data, the simulation results from the Pennes equation coupled with immersion boundary method (IBM) are consistent with the experimental data, with a maximum error of ± 8.12 %.We further incorporate a genetic algorithm as a planning tool to address the problem in connection to be interactive positioning of the cryoprobes and the freezing process duration during the pre-operative stage. Several optimization scenarios are judiciously investigated to emphasize different performance variables. Key results have revealed that this computerized approach is highly efficient one for selecting optimized multiple operational parameters.

Molecular dynamics simulations of liquid transition metals Ni and Cu have been performed with the tight-binding potential model. The surface tensions of the liquid metals at different temperatures are evaluated using both methods of calculating the work of cohesion and of using the mechanical expression for the surface stress. The calculated surface tension data are compared with available experimental values. The simulated results for Ni are in good agreement with experiment, but those for Cu show about 10–20% underestimation. Comparing with the mechanical method, the data of surface tension calculated using the method of cohesive work show remarkable dependence on temperature, and the estimated temperature coefficients of liquid Ni and Cu are consistent with the experimental data.