The specific goal of this research is to develop a method of estimating the complete temperature field present in tumors and their surrounding tissues during clinical hyperthermia treatments. Since current clinical thermometry is invasive, temperatures are measured only at a limited number of points, and thus most temperatures in a tumor are unmeasured and unknown. This lack of knowledge is a fundamental problem in hyperthermia, which makes it impossible to perform complete therapy evaluations and to perform proper therapy control. This problem will remain until a method is developed which can predict the unknown tumor and normal tissue temperatures from the measured temperatures. Simple curve-fitting techniques will not suffice since they have no physical basis and are unable to accurately extrapolate data to predict unmeasured maxima or minima. To do this, a mathematical model of the physical processes in the treatment is needed. We propose to utilize such a model along with state and parameter estimation techniques to estimate the complete temperature field from knowledge of measured temperatures at a few locations. The approach uses optimization methods to minimize the difference between the measured temperatures and temperatures predicted by a bio-head transfer equation model of the heated region. Minimization is done by adjusting the model's blood perfusion parameters. The end result is predictions of both the complete temperature field in the region analyzed, and of the blood perfusion distribution and magnitude during the treatment. Our previous work on this problem has shown that the general approach is quite promising, and the proposed work will extend those results by: (1) improving the formulation of the bio-heat transfer equation, (2) improving the state and parameter estimation techniques, (3) extending and improving our simulation programs, (4) testing the results against extensive three dimensional in vitro and in vivo measurements in both normal and tumor tissues, and (5) applying the technique to clinical treatments. While the specific goal is to develop methods for predicting complete temperature fields, this study will also have the general result of improving both (1) knowledge of the temperature and blood perfusion distributions and fundamental heat transfer processes occurring in hyperthermia treatments, and (2) the ability to perform more realistic simulatings of hyperthermia. This will be important for all applications of treatment planning, control and evaluation.
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