Robust Optimal Power Distribution for Hyperthermia Cancer Treatment

TL;DR

This paper develops a robust optimization framework for ultrasound hyperthermia cancer treatment, ensuring effective power distribution despite model uncertainties, by reformulating a semi-infinite programming problem into a convex one.

Contribution

It introduces a novel robust signal design method for hyperthermia treatment that accounts for uncertainties, improving treatment reliability and expanding application potential.

Findings

Reformulation of SIP as a convex problem.

Enhanced robustness against model errors.

Potential for broader medical and engineering applications.

Abstract

We consider an optimization problem for spatial power distribution generated by an array of transmitting elements. Using ultrasound hyperthermia cancer treatment as a motivating example, the signal design problem consists of optimizing the power distribution across the tumor and healthy tissue regions, respectively. The models used in the optimization problem are, however, invariably subject to errors. deposition as well as inefficient treatment. To combat such unknown model errors, we formulate a robust signal design framework that can take the uncertainty into account using a worst-case approach. This leads to a semi-infinite programming (SIP) robust design problem which we reformulate as a tractable convex problem, potentially has a wider range of applications.