Abstract
Microbubble enhanced High Intensity Focused Ultrasound (HIFU) is of great interest to tissue ablation for tumor treatment such as in liver and brain cancers, where microbubbles are injected to the targeted region to promote focal heating while reducing pre-focal damage. To accurately characterize the acoustic and thermal fields during this process, a compressible Euler-Lagrange model is used, and a domain decomposition based MPI parallelization scheme is developed for its speedup. The Eulerian computational domain is subdivided into several subdomains, and the Lagrangian bubbles are subdivided based on their locations corresponding to each subdomain. During each time step, MPI processors, each handling one subdomain, are sequentially used to execute 1) the fluid, and 2) bubble computations, 3) followed by the coupling which maps the void fraction from Lagrangian bubbles into Eulerian grids. Steps 1) and 2) are relatively straightforward by routinely following regular MPI procedures. However, step 3) becomes challenging as a bubble near borders needs to spread its effects to cells in different subdomains. This is addressed by a special utilization of ghost cells surrounding each fluid subdomain, which allows bubbles to spread their void effects across subdomain edges without the need of directly exchanging bubble information between subdomains and significantly increasing overhead. This is verified by gas volume conservation before and after spreading the bubble effects. Bubbles' thermal effects are handled in a similar way. This parallelization scheme is validated and illustrated on a typical microbubble enhanced HIFU problem, followed by parallelization scaling tests and efficiency analysis.
In VitroDemonstration of Focused Ultrasound Thrombolysis Using Bifrequency Excitation