Towards a predictive model of electroporation-based therapies using pre-pulse electrical measurements

Electroporation-based therapies have been gaining momentum as minimally invasive techniques to facilitate transport of exogenous agents, or directly kill tumors and other undesirable tissue in a non-thermal manner. Typical procedures involve placing electrodes into or around the treatment area and delivering a series of short and intense electric pulses to the tissue/tumor. These pulses create defects in the cell membranes, inducing non-linear changes in the electric conductivity of the tissue. These dynamic conductivity changes redistribute the electric field, and thus the treatment volume. In this study, we develop a statistical model that can be used to determine the baseline conductivity of tissues prior to electroporation and is capable of predicting the non-linear current response with implications for treatment planning and outcome confirmation.