Abstract
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.
| Original language | English |
|---|---|
| Article number | 8681548 |
| Pages (from-to) | 240-246 |
| Number of pages | 7 |
| Journal | IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2019 |
Funding
Manuscript received December 7, 2018; revised March 6, 2019; accepted March 31, 2019. Date of publication April 4, 2019; date of current version November 21, 2019. This work was supported in part by the MIUR PRIN 2015KJE87K and in part by KWF 11368. This paper was presented in part at the IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Boston, MA, USA, July 8–14, 2018. (Corresponding author: Gennaro G. Bellizzi.) G. G. Bellizzi is with the Hyperthermia Unit, Radiation Oncology Department, Erasmus M.C., Rotterdam 3015, The Netherlands, and also with the Uni-versita Mediterranea di Reggio Calabria, DIIES, Reggio Calabria 89124, Italy (e-mail:,[email protected]).
Keywords
- Compressive sensing
- Constrained power optimization
- Convex Programming
- Hyperthermia treatment planning