TY - JOUR
T1 - 3-D Transcranial Microbubble Cavitation Localization by Four Sensors
AU - Hu, Zhongtao
AU - Xu, Lu
AU - Chien, Chih Yen
AU - Yang, Yaoheng
AU - Gong, Yan
AU - Ye, Dezhuang
AU - Pacia, Christopher Pham
AU - Chen, Hong
N1 - Publisher Copyright:
© 1986-2012 IEEE.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - 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.
AB - 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.
KW - Cavitation
KW - focused ultrasound (FUS)
KW - microbubbles
KW - transcranial localization
UR - http://www.scopus.com/inward/record.url?scp=85111553836&partnerID=8YFLogxK
U2 - 10.1109/TUFFC.2021.3091950
DO - 10.1109/TUFFC.2021.3091950
M3 - Article
C2 - 34166187
AN - SCOPUS:85111553836
SN - 0885-3010
VL - 68
SP - 3336
EP - 3346
JO - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
JF - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
IS - 11
ER -