Smith Michael R, Khan Sonia, Curiel Laura
Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Alberta, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Alberta, Canada.
Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Alberta, Canada.
Ultrasound Med Biol. 2023 May;49(5):1118-1128. doi: 10.1016/j.ultrasmedbio.2022.12.012. Epub 2023 Jan 31.
The opening of the blood-brain barrier (BBB) to allow therapeutic drug passage can be achieved by inducing microbubble cavitation using focused ultrasound (FUS). This approach can be monitored through analysis of the received signal to distinguish between stable cavitation associated with safe BBB opening and inertial cavitation associated with blood vessel damage. In this study, FUS phantom and animal studies were used to evaluate the experimental conditions that generate several cross-consistent metrics having the potential to be combined for the reliable, automatic control of cavitation levels.
Typical metrics for cavitation monitoring involve observing changes in the spectrum generated by applying the discrete Fourier transform (DFT) to the time domain signal detected using a hydrophone during FUS. A confocal hydrophone was used to capture emissions during a 10 ms FUS burst, sampled at 32 ns intervals, to produce 321,500 points and a high-resolution spectrum when transformed. The FUS spectra were analyzed to show the impact that equipment-transients and well-known DFT-related distortions had on the metrics used for cavitation control. A new approach, physical sparsification (PH-SP), was introduced to sharpen FUS spectral peaks and minimize the effect of these distortions.
It was demonstrated that the general spectral signal-to-noise ratio (SNR) could be improved by removing the initial noisy phantom hydrophone signal transient. Minor changes in the transient length digitally removed from the sampled values significantly changed the spectral bandwidths of all the harmonically related FUS signals. We evaluated signal processing techniques to minimize the impact these DFT-related distortions on area-under-the-curve (AUC) metric calculations, and we identified the advantages of using PH-SP and proposed new metrics when characterizing FUS spectral properties. The results show many second, third and sub-harmonic metrics provide cross-consistent evidence of changes between stable and inertial cavitation levels. Removing the first harmonic signal component with a hardware low-pass filter allowed the hydrophone gain to be boosted without introducing distortion, leading to an improved analysis of the sub-harmonic signal orders of magnitude smaller in intensity. Metrics that optimized the energy in the real component of the complex-valued PH-SP spectra provided a 32% increase in the sub-harmonic sensitivity compared to standard metrics.
A preliminary investigation of existing and proposed metrics showed that system noise could be large enough to mask the transition between stable and inertial cavitation. Strong narrowing of sub-harmonic peak shapes on applying physical sparsification (PH-SP) were seen in both phantom and animal studies. However, validating equivalent trends of the metrics with pressure were limited by the increased system noise level in the animal study combined with the natural variability between subjects studied. The combined use of hardware low-pass filters and physical sparsification to selectively removing distortions in the spectrum allowed the optimization of metrics for cavitation monitoring by improving the sub-harmonic sensitivity.
通过聚焦超声(FUS)诱导微泡空化,可实现血脑屏障(BBB)开放以允许治疗药物通过。这种方法可通过分析接收信号来监测,以区分与安全的血脑屏障开放相关的稳定空化和与血管损伤相关的惯性空化。在本研究中,使用FUS体模和动物研究来评估产生多个相互一致指标的实验条件,这些指标有可能被组合起来用于可靠、自动地控制空化水平。
空化监测的典型指标包括观察在FUS期间,将离散傅里叶变换(DFT)应用于使用水听器检测到的时域信号所产生的频谱变化。使用共焦水听器在10 ms的FUS脉冲期间捕获发射信号,以32 ns的间隔进行采样,从而产生321,500个点,并在变换后得到高分辨率频谱。对FUS频谱进行分析,以显示设备瞬态和与DFT相关的已知失真对用于空化控制的指标的影响。引入了一种新方法,即物理稀疏化(PH-SP),以锐化FUS频谱峰值并最小化这些失真的影响。
结果表明,通过去除初始的噪声体模水听器信号瞬态,可以提高一般频谱信噪比(SNR)。从采样值中数字去除的瞬态长度的微小变化会显著改变所有谐波相关FUS信号的频谱带宽。我们评估了信号处理技术,以最小化这些与DFT相关的失真对曲线下面积(AUC)指标计算的影响,并确定了在表征FUS频谱特性时使用PH-SP的优势以及提出新的指标。结果表明,许多二次、三次和次谐波指标为稳定和惯性空化水平之间的变化提供了相互一致的证据。使用硬件低通滤波器去除一次谐波信号分量,可以提高水听器增益而不引入失真,从而改进对强度小几个数量级的次谐波信号的分析。与标准指标相比,优化复值PH-SP频谱实部能量的指标使次谐波灵敏度提高了32%。
对现有和提出的指标的初步研究表明,系统噪声可能大到足以掩盖稳定空化和惯性空化之间的转变。在体模和动物研究中均观察到,应用物理稀疏化(PH-SP)后次谐波峰值形状明显变窄。然而,动物研究中系统噪声水平的增加以及所研究对象之间的自然变异性限制了用压力验证指标等效趋势的能力。硬件低通滤波器和物理稀疏化相结合以选择性地去除频谱中的失真,通过提高次谐波灵敏度,实现了空化监测指标的优化。