Improved Cavitation Monitoring and Detection Methods for Focused Ultrasound Blood-Brain Barrier Disruption
Date
2022-01
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Abstract
Transcranial focused ultrasound (FUS) in combination with microbubbles has demonstrated promising outcomes in treatment of brain disorders by stimulating transient BBB disruption, allowing therapeutics to enter into the brain. Currently, time signals from a hydrophone are transformed into frequency domain to monitor cavitation activity during BBB opening. The area under the curve (AUC) in a 300 Hz bandwidth around the subharmonic is used as a metric to determine cavitation activity. However, given the available frequency resolution, there are very few points within the 300 Hz bandwidth for precisely analysing the AUC. Also, many recorded signals show no detectable subharmonic above the noise as the A/D calibration is overwhelmed due to the strong fundamental. These issues can result in the subject being under treated or over treated. This research aims to better monitor and control the cavitation phenomenon for BBB disruption by developing methods to improve the cavitation spectra. The acoustic signals captured by a hydrophone from the excited microbubble phantom were filtered with a low pass analog filter to improve the system’s dynamics of self-calibration by suppressing the strong fundamental. The acoustic signals were further improved with two proposed signal processing techniques, namely, Fourier interpolation via zero-padding to increase the spectral frequency resolution, and windowing, which allowed us to uncover previously unreported subharmonic side lobes. Additionally, we propose the bandwidth to be wider than the current 300 Hz for AUC to include the useful information in these side bands. Our proposed improvements were validated on animal data. Finally, the performance of our proposed improvements was compared to traditional methods by evaluating metrics for cavitation detection. Previous studies reported a steady increase in the AUC with increase in pressure, whereas our work presented that the AUC would rise drastically at the stable cavitation threshold indicating that maximum energy is concentrated in stable cavitation regime. Then, beyond this threshold, the AUC will drop before rising again, signifying the energy shift towards initiating inertial cavitation. Our findings can be beneficial to enhance cavitation detection metrics and we can actually visualize the different cavitation regimes when the AUC and power are evaluated for subharmonic.
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Keywords
Microbubbles, Interpolation, Windowing, Area under the curve (AUC), Harmonic frequency components
Citation
Khan, S. (2022). Improved cavitation monitoring and detection methods for focused ultrasound Blood-brain barrier disruption (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.