Electrochemical Treatment of Tumors (EChT)
Madi Reddy, Shiv Krishna Reddy
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Electrochemical treatment of cancerous tumors is a minimally invasive, versatile and relatively safe technology in which the direct electric current is changed to destructive reaction products by electrochemical reactions at electrode surfaces. It is believed that extreme cathodic and anodic pH fronts are the major causes of tumor necrosis. In this context, due to the complexity of the system and the fact that in vivo visualization of a process is extremely difficult and costly, in-silico modeling plays a vital role. General and reliable mathematical models can act as powerful tools not only to standardize the therapy but also provide reliable dosage plans and individualize the treatment for different cases. In this study, we present a two dimensional mathematical model of the electrochemical processes during EChT to elucidate the role of pH, electric field and calculate solutes speciation. Firstly, cancerous tumor tissue was treated as a bicarbonate buffer system but later refined by adding the buffer capacity of proteins, organic phosphates and the effect of chlorine bleaching near the anode. The effects of different buffer systems, total current densities on the mass transport and electric field were carefully investigated. The models are capable of describing the generally observed behavior of the electrochemical reactions at electrode surfaces, the variation of ionic species concentrations and electrolyte current density distribution during the treatment. Numerical simulations also revealed the role of different buffer systems present inside the tissue and how they can attenuate the spreading of destruction zones. In addition, results showed that in low currents pH front tracking varies with t^0.5 while scales linearly the time in higher currents. This new modeling approach can pave the way to study the influence of key parameters and conditions on the EChT output in any two-dimensional EChT electrode configuration. Results clearly indicate that the model can be used to predict the lesion zones around each electrode and as a tool for dosage planning.