Novel tumor localization model and prediction of ablation zone using an intertwined helical antenna for the treatment of hepatocellular carcinoma.

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Hepatocellular carcinoma has been the leading cause of death in recent centuries and with the advent of newer technologies, several thermal and cryo-ablation techniques have been introduced in the recent past. In this regard, microwave ablation has developed into a promising method for thermal ablation technique. However, due to clinical obligations, in-vivo analysis is not feasible and ex-vivo analysis is inaccurate due to changes in the electrical and thermal properties of the tissue. Therefore, in this study, temperature-dependent permittivity, electrical conductivity, and thermal conductivity along with phase change effect due to temperature reaching above 100°C are incorporated using finite element method model. Further, using an intertwined normal mode helical antenna ablation probe, a change in resonant frequency (Δf) and reflection coefficient (ΔS11 ) from the actual value (antenna parameter in the air at 5GHz) is modeled using second-order polynomial curve fitting to predict the surrounding permittivity in the range of 30-70. A maximum deviation of 0.8 value in permittivity from the actual value is observed. However, to obtain a generalized methodology, XG Boost and CAT Boost algorithms are used. Further, since ablation diameter plays a crucial role in achieving optimal tumor ablation, an artificial neural network (ANN) algorithm with three different optimizers is incorporated to predict ablation diameter using five critical parameters. Such an ANN algorithm which can predict the transversal and axial ablation zone may provide optimal ablation outcomes.