Abstract
The treatment of hepatic lesions with radio-frequency (RF) ablation has become a promising minimally invasive alternative to surgical resection during the last decade. In order to achieve treatment qualities similar to surgical R0 resections, patient specific mathematical modeling and simulation of the biophysical processes during RF ablation are valuable tools. They allow for an a priori estimation of the success of the therapy as well as an optimization of the therapy parameters. In this report we discuss our recent efforts in this area: a model of partial differential equations (PDEs) for the patient specific numerical simulation of RF ablation, the optimization of the probe placement under the constraining PDE system and the identification of material parameters from temperature measurements. A particular focus lies on the uncertainties in the patient specific tissue properties. We discuss a stochastic PDE model, allowing for a sensitivity analysis of the optimal probe location under variations in the material properties. Moreover, we optimize the probe location under uncertainty, by considering an objective function, which is based on the expectation of the stochastic distribution of the temperature distribution. The application of our models and algorithms to data from real patient’s CT scans underline their applicability.
Mathematics Subject Classification (2000). 35Q93 and 49J20.
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Altrogge, I., Büskens, C., Kröger, T., Peitgen, HO., Preusser, T., Tiesler, H. (2012). Modeling, Simulation and Optimization of Radio Frequency Ablation. In: Leugering, G., et al. Constrained Optimization and Optimal Control for Partial Differential Equations. International Series of Numerical Mathematics, vol 160. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-0133-1_25
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DOI: https://doi.org/10.1007/978-3-0348-0133-1_25
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