Multi-Objective Adaptive Beamforming Using Partial Knowledge of Dynamic Dielectric Media for Non-Invasive Microwave Hyperthermia

TL;DR

This paper explores adaptive multi-objective beamforming strategies for microwave hyperthermia, aiming to focus heat precisely while minimizing unwanted heating, even with changing dielectric properties of tissues.

Contribution

It evaluates the effectiveness of the LCMP algorithm for real-time adaptive beamforming in inhomogeneous media with changing dielectric properties.

Findings

LCMP beamformer effectively focuses energy in desired regions.

Finite-difference time-domain simulations validate the approach.

Thermal maps show promising results in realistic breast models.

Abstract

We investigate multi-objective adaptive beamformer design strategies for non-invasive microwave hyperthermia. Our focus is to address the challenges of maintaining focused power deposition in desired locations while reducing unwanted heating elsewhere under conditions of changing dielectric properties. The process of heating the media causes changes in the dielectric properties of the media, which can degrade the effectiveness beamformers with static weights. Typical hyperthermic beamformer designs calculate antenna beamforming weights using patient-specific high resolution dielectric maps obtained by MRI or microwave tomography, however this process is time consuming and difficult to perform in real-time. In this work, we explore the efficacy of microwave hyperthermia in various inhomogeneous media under changing dielectric conditions, with the goal of informing the design of future adaptive real-time microwave hyperthermia techniques. We aim to achieve cell apoptosis by obtaining temperatures of $\sim$ 45 $^\circ\text{C}$ through selective absorption of electromagnetic wave focusing at a 2.5 GHz carrier frequency with little to no knowledge of the changes in the dielectric media and simultaneously place nulls to avoid unwanted heating outside of the treatment zone. We investigate the effectiveness of the linear constrained minimum power (LCMP) algorithm for near-field multi-objective beamforming and examine the power density obtained from finite-difference time-domain (FDTD) simulations on simple analytical models and anatomically realistic numerical breast phantoms. To gain a comprehensive knowledge of the efficacy of the beamformer we evaluate the resulting thermal maps of the models in simple homogeneous cases, heterogeneous cases and MRI-derived phantom breast models.