Front-tracking image reconstruction algorithm for EIT-monitored cryosurgery using the boundary element method

The effectiveness of cryosurgery, treatment of tumors by freezing, is highly dependent on knowledge of transient freezing extent, and therefore relies heavily on real-time imaging techniques for monitoring. Electrical impedance tomography (EIT) holds much promise for this application. In cryosurgery there is a three order of magnitude change in impedance across the freezing boundary and there is a priori knowledge of the freezing origin. Furthermore, an EIT image of the tissue can be done prior to the cryosurgery. In this study, we have developed an EIT front tracking reconstruction algorithm which takes advantage of these particular attributes of cryosurgery. The method tracks the freezing interface rather than the impedance distribution in the freezing tissue. In addition to drastically reducing the number of parameters needed to define the image, the computational complexity is further reduced by using the more appropriate boundary element method (BEM) for solution to the forward problem. The front-tracking method was found to converge rapidly and accurately to a variety of simulated phantom images.