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Sensitivity analysis for the optimization of radiofrequency ablation in the presence of material parameter uncertainty

: Altrogge, I.; Preußer, T.; Kröger, T.; Haase, S.; Pätz, T.; Kirby, R.M.


International journal for uncertainty quantification 2 (2012), No.3, pp.295-321
ISSN: 2152-5080
ISSN: 2152-5099
Journal Article
Fraunhofer MEVIS ()

We present a sensitivity analysis of the optimization of the probe placement in radiofrequency (RF) ablation which takes the uncertainty associated with biophysical tissue properties (electrical and thermal conductivity) into account. Our forward simulation of RF ablation is based upon a system of partial differential equations (PDEs) that describe the electric potential of the probe and the steady state of the induced heat. The probe placement is optimized by minimizing a temperature-based objective function such that the volume of destroyed tumor tissue is maximized. The resulting optimality system is solved with a multilevel gradient descent approach. By evaluating the corresponding optimality system for certain realizations of tissue parameters (i.e., at certain, well-chosen points in the stochastic space) the sensitivity of the system can be analyzed with respect to variations in the tissue parameters. For the interpolation in the stochastic space we use an adaptive sparse grid collocation (ASGC) approach presented by Ma and Zabaras. We underscore the significance of the approach by applying the optimization to CT data obtained from a real RF ablation case.