Model-predictive control of hyperthermia treatments

Abstract

A model-predictive controller (MPC) of the thermal dose in hyperthermia cancer treatments has been developed and evaluated using simulations with one-point and one-dimensional models of a tumor. The developed controller is the first effort in: 1) the application of feedback control to pulsed, high-temperature hyperthermia treatments; 2) the direct control of the treatment thermal dose rather than the treatment temperatures; and 3) the application of MPC to hyperthermia treatments. Simulations were performed with different blood flow rates in the tumor and constraints on temperatures in normal tissues. The results demonstrate that 1) thermal dose can be controlled in the presence of plant-model mismatch and 2) constraints on the maximum allowable temperatures in normal tissue and/or the pulsed power magnitude can be directly incorporated into MPC and met while delivering the desired thermal dose to the tumor. For relatively high blood flow rates and low transducer surface intensities--factors that limit the range of temperature variations in the tumor, the linear MPC, obtained by piece-wise linearization of the dose-temperature relationship, provides an adequate performance. For large temperature variations, the development of nonlinear MPC is necessary.

Minimum-Time Thermal Dose Control of Thermal Therapies

“…The previously designed thermal dose controller [14] provides satisfactory performance only for low-temperature therapies, and is inadequate for highintensity, HIFU-type treatments. Compared to [14], [15], we do not assume that the power is applied in a pulsed form. The pulsed application of energy was thought to be necessary to prevent damage to the normal tissue by allowing it to cool during power-off intervals.…”

“…The introduction of a reduced number of controlled variables, such as a temperature, can be used to circumvent the underactuated nature of the temperature control problem. Since T 90 has been shown to be an effective measure of treatment efficacy, we modify the general problem (12), and design the dose controller K D to map the desired final thermal dose into the T 90 temperature trajectory (13) The map (13) may be implemented as (14) where (13), additional conditions must be imposed. Such conditions may include the requirement that the map is optimal in some appropriate sense (e.g., minimum-time solution), or the uniqueness can be obtained by parameterizing the reference temperature (explicit parameterization) or the thermal dose (implicit parameterization) trajectories.…”

“…One exception is our previous work on low-intensity treatments [14], [15], where the direct control of the thermal dose was achieved using continuous linearization of the dose-temperature relationship.…”

“…The proposed approach is equally applicable to low-intensity treatments (e.g., combination therapies, such as hyperthermia + radiation) where the goal is usually to deliver 10 CEM43° T 90 [7], and thermal surgeries, which typically require a higher dose of 240 CEM43 °C [16]. Unlike the results of the previous work [14], [15], the approach developed in this paper does not require linearization of the dose-temperature relationship, which makes it applicable to the control of high intensity treatments.…”

“…Our earlier work [14], [15] utilized direct model-predictive thermal dose control with piecewise linearization of the thermal dose relation (2), (6), which limits its application to the case of relatively low temperature treatments. In particular, our first generation thermal dose controller is inadequate for poorly perfused tumors and high intensity, short duration therapies.…”