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Dielectric parameters, blood perfusion rate, and the temperature interval across which the tissue changes phase were found to have the most significant impact on MWA model outputs. The latent heat of tissue water vaporization and the volumetric heat capacity of the vaporized tissue were recognized as the least influential parameters. Uncertainties in model outputs identified in this study can be incorporated to provide probabilistic maps of expected ablation outcome for patient-specific treatment planning.

These results suggest the applicator may be suitable for creating localised directional ablation zones for treating small and medium-sized targets with a percutaneous approach.

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Purpose Computational models of microwave tissue ablation are widely used to guide the development of ablation devices, and are increasingly being used for the development of treatment planning and monitoring platforms. Knowledge of temperature‐dependent dielectric properties of lung tissue is essential for accurate modeling of microwave ablation (MWA) of the lung. Methods We employed the open‐ended coaxial probe method, coupled with a custom tissue heating apparatus, to measure dielectric properties of ex vivo porcine and bovine lung tissue at temperatures ranging between 31 and 150 ∘C, over the frequency range 500 MHz to 6 GHz. Furthermore, we employed numerical optimization techniques to provide parametric models for characterizing the broadband temperature‐dependent dielectric properties of tissue, and their variability across tissue samples, suitable for use in computational models of microwave tissue ablation. Results Rapid decreases in both relative permittivity and effective conductivity were observed in the temperature range from 94 to 108 ∘C. Over the measured frequency range, both relative permittivity and effective conductivity were suitably modeled by piecewise linear functions [root mean square error (RMSE) = 1.0952 for permittivity and 0.0650 S/m for conductivity]. Detailed characterization of the variability in lung tissue properties was provided to enable uncertainty quantification of models of MWA. Conclusions The reported dielectric properties of lung tissue, and parametric models which also capture their distribution, will aid the development of computational models of microwave lung ablation.