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Updated: Nov 1, 2025

Imaging and Quantification of the Area of Fast-Moving Microbubbles Using a High-Speed Camera and Image Analysis
Published on: September 5, 2020
3-D Transcranial Microbubble Cavitation Localization by Four Sensors
Abstract:
Cavitation is the fundamental physical mechanism of various focused ultrasound (FUS)-mediated therapies in the brain. Accurately knowing the three-dimensional (3-D) location of cavitation in real-time can improve the targeting accuracy and avoid off-target tissue damage. Existing techniques for 3-D passive transcranial cavitation detection require the use of expensive and complicated hemispherical phased arrays with 128 or 256 elements. The objective of this study was to investigate the feasibility of using four sensors for transcranial 3-D localization of cavitation. Differential microbubble cavitation detection combined with the time difference of arrival algorithm was developed for the localization using the four sensors. Numerical simulation using k-Wave toolbox was performed to validate the proposed method for transcranial cavitation source localization. The sensors with a center frequency of 2.25 MHz and a 6 dB bandwidth of 1.39 MHz were used to locate cavitation generated by FUS (500 kHz) sonication of microbubbles that were injected into a tube positioned inside an ex vivo human skullcap. Cavitation emissions from the microbubbles were detected transcranially using the four sensors. Both simulation and experimental studies found that the proposed method achieved accurate 3-D cavitation localization. When the cavitation source was located within 30 mm from the geometric center of the sensor network, the accuracy of the localization method with the skull was measured to be 1.9±1.0 mm, which was not significantly different from that without the skull (1.7 ± 0.5 mm). The accuracy decreased as the cavitation source was away from the geometric center of the sensor network. It also decreased as the pulse length increased. Its accuracy was not significantly affected by the sensor position relative to the skull. In summary, four sensors combined with the proposed localization algorithm offer a simple approach for 3-D transcranial cavitation localization.
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