LAUSR

Hyperthermia treatment planning is a deeply patient-specific task which includes the optimal determination of the excitations of an array applicator. To enhance flexibility, various solutions exploiting different frequencies, antenna element, number, and applicator geometries have been proposed in the literature. Amongst them, increasing the frequency and the number of radiating elements have been effective for achieving more conformal heating. However, as each radiating element requires a power amplifier to control it, increasing the number of antennas considerably impacts the overall cost and complexity of the system. Accordingly, a procedure capable of selecting an optimal patient-specific subset of antennas from an oversized phased array applicator (with more antenna elements than available amplifiers) could help improve cost-effectiveness. In this study, we present an original approach, which allows improving performance by adaptively selecting the optimal subset of antennas to be activated for a given (redundant) applicator and a given patient. The proposed approach takes inspiration from the compressive sensing theory by embedding the sparsity promotion paradigm into a treatment planning procedure, which casts power deposition as a constrained convex optimization. Performances were demonstrated for the case of head and neck hyperthermia and benchmarked against the antenna selection procedure presently used in clinical practice.