Adaptive model-following control for hyperthermia treatment systems.

Abstract

The purpose of this research was to develop three real-time adaptive temperature controllers for hyperthermia heating systems. Each scheme is made adaptive by using a transient Gaussian estimation routine to estimate the tissue blood perfusion and by then using these estimated values either in an optimizing routine, or in an observer, or in both. The optimizing routine uses a steady-state Gaussian estimation technique to optimize the power distribution until the best possible match is obtained between the steady-state temperatures predicted by a treatment model and a prespecified ideal temperature distribution. The observer uses a treatment model to control unmeasured locations. The first adaptive control scheme uses the optimizing routine alone, the second uses the observer alone and the third uses both the optimzing routine and observer. The performance of each of the adaptive control schemes is compared to a standard proportional-integral-derivative (PID) control scheme for one-dimensional simulations of typical treatments. Results comparing the deviation of the controlled temperature distribution to the ideal desired temperature distribution for all locations and all times indicate that the adaptive schemes perform better than the PID scheme. It can be concluded that adaptive control yields improved performance if good a priori knowledge of the treated region tissue and perfusion region boundaries is available. While these control schemes were designed for eventual implementation on a scanned focused ultrasound hyperthermia treatment system, the techniques are applicable to any system with the capability to vary specific power with respect to location and with an unknown distributed energy sink proportional to the temperature elevation.