Computational evaluation of an adaptive ferroelectric-based impedance matching network for microwave ablation in heterogeneous tissue environments.

Microwave ablation (MWA) efficiency is strongly influenced by impedance mismatch caused by inter-organ dielectric variability, tumor heterogeneity, and temperature-dependent tissue evolution during treatment. This work presents a computational feasibility study of an adaptive impedance matching framework for MWA based on ferroelectric tunable elements and feedback-controlled impedance retuning. A proposed closed-loop feedback architecture is presented as a potential future means of automating the computationally demonstrated retuning principle for dielectric variations under heterogeneous tissue conditions. Full-wave electromagnetic and thermal simulations were performed at 915 MHz across 47 representative scenarios involving liver, lung, kidney, and breast tissues, including variations in tumor size, heterogeneous tumor composition, percolation-driven dielectric transitions, anisotropic tumor geometries, and temperature-dependent dielectric properties. Compensating ferroelectric tuning states were identified through manual parametric retuning based on reflected-power minimization and restoration of the input impedance toward 50 + j0 Ω. The adaptive matching framework maintained reflection coefficients below -20 dB across all simulated cases, while substantially improving impedance stability relative to conventional fixed matching configurations. Additional frequency-domain analysis demonstrated improved matching behavior across the ISM operating band. The simulations produced localized specific absorption rate and thermal distributions for the investigated tissue configurations, while the adaptive matching states restored low reflection under the corresponding dielectric conditions. The results support the feasibility of adaptive ferroelectric-based impedance matching as a promising strategy for improving MWA robustness under heterogeneous and thermally evolving tissue environments. Experimental validation and hardware implementation remain subjects of future investigation.