Multiple-Focus Patterns of Sparse Random Array Using Particle Swarm Optimization for Ultrasound Surgery - Zhang, Quan; Mao, Jianyun; Zhang, Yi; Lu, Mingzhu; Li, Ruixin; Liu, Xuan; Liu, Yehui; Yang, Rongzheng; Wang, Xuan; Geng, Yizhe; Qi, Tingting; Wan, Mingxi (IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2022)
This study aims to investigate the feasibility and potential of sparse random arrays driven by the particle swarm optimization (PSO) algorithm to generate multiple-focus patterns and a large scanning range without grating lobes, which extends the scanning range of focused ultrasound in the treatment of brain tumors, opening the blood-brain barrier, and neuromodulation. Operating at 1.1 MHz, a random spherical array with 200 square elements (sparseness 58%) and a sparse random array with 660 square elements (sparseness 41%) driven by PSO are employed to simulate different focus patterns. With the same radius of curvature and diameter of transducer and element size, the scanning range of the off-axis single focus of a random 200-element array is two times that of an ordinary array using symmetric arrangement. The focal volume of multiple-focus patterns of the random array is 18 times that of the single focus. The single focus of the sparse random array with 660 elements could steer up to ±23 mm in the radial direction, without grating lobes. The maximum distance between two foci in a multiple-focus "S"-shaped deflection is approximately 25 mm. Simulation results illustrate the capability of a focused beam steered in 3-D space. Multiple-focus patterns could significantly increase the focal volume and shorten the treatment time for large target volumes. Simulation results show the feasibility and potential of the method combining PSO with a sparse random array to generate flexible focus patterns that can adapt to different needs in different tissue treatments.