The application of thermal ablation technique and, in particular, of the radiofrequency ablation (RFA), has become widely used in the treatment of solid tumors. The use of optimization methods to plan the therapy is among the emerging fields of interests. Monitoring of the ablative treatment by using electrical impedance tomography (EIT), allowing real time observations with no ionizing radiations and at low cost, is also considered a relevant goal. In this paper, a proposal for an adaptive RFA treatment based on multiple external electrodes and EIT images is presented. In particular, the distribution of Ohmic power deposition is optimized by controlling the current pattern on multiple external electrodes in such a way to achieve a suitable temperature rise in the tumour volume limiting it at the same time in healthy tissues. The optimization of the RFA heating is based on the knowledge of the electric properties of living tissues; the well known uncertain knowledge of this parameter is at least partially resolved by generating online EIT images.

Adaptive Ablation Treatment Based on Impedance Imaging

FORMISANO, Alessandro;MARTONE, Raffaele
2010

Abstract

The application of thermal ablation technique and, in particular, of the radiofrequency ablation (RFA), has become widely used in the treatment of solid tumors. The use of optimization methods to plan the therapy is among the emerging fields of interests. Monitoring of the ablative treatment by using electrical impedance tomography (EIT), allowing real time observations with no ionizing radiations and at low cost, is also considered a relevant goal. In this paper, a proposal for an adaptive RFA treatment based on multiple external electrodes and EIT images is presented. In particular, the distribution of Ohmic power deposition is optimized by controlling the current pattern on multiple external electrodes in such a way to achieve a suitable temperature rise in the tumour volume limiting it at the same time in healthy tissues. The optimization of the RFA heating is based on the knowledge of the electric properties of living tissues; the well known uncertain knowledge of this parameter is at least partially resolved by generating online EIT images.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/187431
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