We develop a pre-treatment planning method for optimum hepatic radiofrequency (RF) ablation. In conventional methods, pre-treatment planning is minimal and for a specific tumor size, it only includes reading pre-specified treatment length and input voltage values from a look-up table that lists experimentally obtained ablation parameters. Such planning, in order to assure certain level of cell death, usually results in more healthy cell damage than desired. Different than the conventional methods, here, we develop a model-based pre-treatment optimal planning framework. As an example, we use 1-D axisymmetric tissue geometry and over this geometry, we solve Pennes' bioheat and Laplace equations to model the RF heating. Using the solutions of these equations, we define constrained nonlinear optimization problems to achieve specific temperature profiles in certain areas of the tissue. Results demonstrate that compared to the conventional methods, our approach significantly improves the healthy tissue preservation.
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