What is it about?
We introduced a particle-based virtual ultrasound machine capable of simulating medically relevant MHz wave propagation and its interaction with microbubbles at submicron resolution. The versatility of the method is demonstrated through the simulation of acoustic forces driving microbubble motion toward pressure antinode.
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Photo by Egor Komarov on Unsplash
Why is it important?
Particle-based simulations of ultrasound at mesoscopic scales are essential for understanding how acoustic waves interact with microbubbles, cells, and other soft biological structures, but existing methods struggle to achieve numerical stability, realistic fluid properties, and computational efficiency in the medically relevant MHz–GHz regime. The method establishes a generalizable platform for simulating wave–matter interactions in soft and biological materials and enables predictive particle-based modeling of ultrasound for biomedical applications.
Perspectives
The presented virtual ultrasound machine can be naturally coupled with existing particle-based descriptions of various immersed structures (e.g. red blood cells, encapsulated microbubbles and gas vesicles that are used as ultrasound contrast agents or drug carriers), to allow for computational studies that will provide the optimal experimental range of ultrasound parameters, such as intensities, frequencies, and duration of ultrasound exposure. I anticipate that the method will be broadly useful to the biophysics and biomedical ultrasound communities, particularly in ultrasound-based imaging and therapeutic applications.
Matej Praprotnik
Kemijski institut
Read the Original
This page is a summary of: Virtual ultrasound machine operating in a GHz to MHz frequency range for particle-based biomedical simulations, Proceedings of the National Academy of Sciences, July 2026, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2610567123.
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Resources
Code data
Code data have been deposited in GitHub.
SI Appendix
Supporting Information
ERC Advanced Grant MULTraSonicA (Grant No. 885155)
EXCELLENT SCIENCE - European Research Council (ERC)
EuroHPC JU ID EHPC-REG-2025R02-164
We acknowledge the European High Performance Computing Joint Undertaking (EuroHPC JU) for awarding the project ID EHPC-EG-2025R02-164 access to Vega at the Institute of Information Science (IZUM, Slovenia).
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