Mathematical Modeling And Simulation Of Cryo-Probe For Tumor Removal Surgery (Cryo Surgery)

Cancer is a dangerous disease accounting for the highest number of deaths by a single cause all over the world. There are several ways to treat cancerous cells are available and new ways are regularly being proposed. Cryosurgery is one of them and offers many advantages. Cryosurgery is the destruction of undesired biological tissues by freezing. For remove of undesired biological tissue i.e. tumor modern cryosurgery is frequently performed as a simply persistent procedure, in which multiple, hypodermic needle-shaped cryoprobes are inserted into the target area to be treated. It causes freezing the tumor inside body below its critical temperature and forming ice-ball, so tumor being inactive and removed from the body. To use this technique effectively the rate of cooling and extent of cooling needs to be controlled. It helps in achieving total destruction of tumor and minimum harm to adjoining healthy tissue. The aim of the cryosurgeon is to place the cryoprobes so as to maximize cryoinjury within the target region, while minimizing damage to healthy surrounding tissue. The quality of the cryoprobe arrangement, which has a direct impact on the success of the procedure, is dependent upon the cryosurgeon's own skill and experience. From a mathematical point of view, the problem is to predict the time-evolving position of freezing or melting position where phase change occurs. At the same time, the temperature is computed everywhere in the computational domain giving access to the complete thermal history. Bio-heat equation can be solved by using one of various simulation techniques for a single or multi-probes. Simulated results greatly match with the experimental outputs. Thus, the model used can be extrapolated to study the effects of different freezing rates.