Computational techniques for fast hyperthermia temperature optimization

Hyperthermia temperature optimization involves arriving at a temperature distribution which minimizes a stated goal function, the goal function having a biological basis in maximizing tumor cell kill while not exceeding normal tissue toxicity. This involves the computationally intensive process of multiple evaluations of the temperature goal function, requiring repeated evaluations of the power deposition and its corresponding temperature distribution. Two computational schemes are proposed to expedite the temperature optimization process: (1) temperature distribution evaluation by superpositioning precomputed distributions, and (2) using representative tissue groups (rather than every point in the domain) to evaluate the goal function. The application of these schemes is illustrated with a typical optimization problem, as applied to symmetric and asymmetric, heterogeneous models. Application of these schemes reduced the optimization time on a DEC Alpha 1000 4/266 (Alpha is a registered trademark of Digital Equipment Corporation.) from several h to min, with little difference in results. The computational schemes, though demonstrated in the context of electromagnetic hyperthermia, are generally applicable to other forms of nonionizing radiation employed in hyperthermia therapy.