Magnetic induction of hyperthermia by a modified self-learning fuzzy temperature controller

Abstract

The aim of this study involved developing a temperature controller for magnetic induction hyperthermia (MIH). A closed-loop controller was applied to track a reference model to guarantee a desired temperature response. The MIH system generated an alternating magnetic field to heat a high magnetic permeability material. This wireless induction heating had few side effects when it was extensively applied to cancer treatment. The effects of hyperthermia strongly depend on the precise control of temperature. However, during the treatment process, the control performance is degraded due to severe perturbations and parameter variations. In this study, a modified self-learning fuzzy logic controller (SLFLC) with a gain tuning mechanism was implemented to obtain high control performance in a wide range of treatment situations. This implementation was performed by appropriately altering the output scaling factor of a fuzzy inverse model to adjust the control rules. In this study, the proposed SLFLC was compared to the classical self-tuning fuzzy logic controller and fuzzy model reference learning control. Additionally, the proposed SLFLC was verified by conducting in vitro experiments with porcine liver. The experimental results indicated that the proposed controller showed greater robustness and excellent adaptability with respect to the temperature control of the MIH system.

Externally Addressable Smart Drug Delivery Vehicles: Current Technologies and Future Directions

“…Overshooting the target temperature can lead to substantial local tissue damage, while undershooting the target temperature would lead to substantially lower or perhaps no significant drug release achieved. While some studies have sought to couple magnetic activation with self-learning controllers , and/or complementary imaging approaches that can either dynamically meter or report in real time the local temperature at the target site, , such approaches require extensive instrumentation availability in addition to introducing complications in the clinical approval process. Alternate approaches to tag the loaded drug with radiolabel(s) or fluorophore(s) to enable real-time quantification of released drug can be effective but also require access to additional (and co-located) advanced imaging tools as well as customized therapeutics that pose both logistical and regulatory challenges .…”