Multi-Parameter Estimation in Hyperthermia Problem by Using an Optimal Choice of Descent Parameters in Iterative Methods

This paper describes a numerical procedure conducted to estimate thermo-physical properties of the human tissue during hyperthermia treatment of a cancerous region. The estimation algorithm is based on the solution of an inverse heat conduction problem. The Gauss-Newton method is used to estimate simultaneously the volumetric heat capacity, the thermal conductivity, and the volumetric blood rate (blood perfusion) in the bio-heat transfer equation during a hyperthermia treatment cycle. The treatment quality of hyperthermia is analyzed by the computation of the thermal dose which is obtained from the resulting temperature field in the tissue. The importance of an accurate estimation of the thermo-physical properties of the tissue lies in that they are the most important factors for achieving a high precision heating cycle which results in an optimized treatment. The inverse analysis is based on the temperature measurements taken inside the cancerous tissue region during the transient heating process. An experimental optimization procedure is conducted to make the estimated parameters as accurate as possible. Several numerical tests were performed and show that the developed method provides an accurate estimation of thermo-physical properties in a very short practical time. As the blood perfusion is very sensitive to the temperature variation in the tissue, this estimation tool can be implemented during one cycle treatment which results in an on-line thermo-physical parameter correction while the treatment is performed.