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 microwave ablation based on ferroelectric tunable elements and feedback-controlled impedance retuning. The proposed architecture employs voltagecontrolled ferroelectric segments integrated into the matching network to dynamically compensate 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. A closed-loop feedback strategy based on reflected-power minimization was computationally modeled to evaluate adaptive tuning behavior. 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 proposed framework also preserved localized SAR distributions and stable thermal coverage under dynamically evolving dielectric conditions. The results support the feasibility of adaptive ferroelectric-based impedance matching as a promising strategy for improving microwave ablation robustness under heterogeneous and thermally evolving tissue environments. Experimental validation and hardware implementation remain subjects of future investigation.