Estimation of complete temperature fields from measured transient temperatures

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Abstract
In hyperthermia treatments, it is desirable to be able to predict complete tissue temperature fields from the limited number of sampled temperatures available. Because of the unknown tissue blood perfusion this is a particularly difficult problem, whose eventual solution will require a considerable effort. An initial attempt to develop methods to solve this problem automatically using unconstrained optimization techniques (which minimize the differences between measured steady-state temperatures and the temperatures predicted from treatment simulations) has been reported previously. A second technique using transient temperatures following a step decrease in power has been developed and is presented and discussed in this paper. The results of applying both it and the steady-state technique to simulated hyperthermia treatments are compared for one-dimensional situations. This transient technique predicts complete temperature fields more accurately and robustly than the steady-state approach. In particular, it can better predict the complete temperature fields in situations where the number of unknown blood perfusion parameters is greater than the number of available temperature sensors.