Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland.
Department of Information Technology and Electrical Engineering , Swiss Federal Institute of Technology (ETH), Zurich, Switzerland.
J Neural Eng. 2021 May 4;18(4). doi: 10.1088/1741-2552/abf68d.
. Low-intensity transcranial ultrasound stimulation (TUS) is a promising non-invasive brain stimulation (NIBS) technique. TUS can reach deeper areas and target smaller regions in the brain than other NIBS techniques, but its application in humans is hampered by the lack of a straightforward and reliable procedure to predict the induced ultrasound exposure. Here, we examined how skull modeling affects computer simulations of TUS.. We characterized the ultrasonic beam after transmission through a sheep skull with a hydrophone and performed computed tomography (CT) image-based simulations of the experimental setup. To study the skull model's impact, we varied: CT acquisition parameters (tube voltage, dose, filter sharpness), image interpolation, segmentation parameters, acoustic property maps (speed-of-sound, density, attenuation), and transducer-position mismatches. We compared the impact of modeling parameter changes on model predictions and on measurement agreement. Spatial-peak intensity and location, total power, and the Gamma metric (a measure for distribution differences) were used as quantitative criteria. Modeling-based sensitivity analysis was also performed for two human head models.. Sheep skull attenuation assignment and transducer positioning had the most important impact on spatial peak intensity (overestimation up to 300%, respectively 30%), followed by filter sharpness and tube voltage (up to 20%), requiring calibration of the mapping functions. Positioning and skull-heterogeneity-structure strongly affected the intensity distribution (gamma tolerances exceeded in>80%, respectively>150%, of the focus-volume in water), necessitating image-based personalized modeling. Simulation results in human models consistently demonstrate a high sensitivity to the skull-heterogeneity model, attenuation tuning, and transducer shifts, the magnitude of which depends on the underlying skull structure complexity.. Our study reveals the importance of properly modeling the skull-heterogeneity and its structure and of accurately reproducing the transducer position. The results raise red flags when translating modeling approaches among clinical sites without proper standardization and/or recalibration of the imaging and modeling parameters.
. 低强度经颅超声刺激(TUS)是一种很有前途的非侵入性脑刺激(NIBS)技术。与其他 NIBS 技术相比,TUS 可以到达更深的区域并靶向大脑中更小的区域,但由于缺乏一种直接可靠的方法来预测诱导超声暴露,其在人体中的应用受到了阻碍。在这里,我们研究了颅骨建模如何影响 TUS 的计算机模拟。我们使用水听器对绵羊颅骨传输后的超声束进行了特性描述,并对实验设置进行了基于计算机断层扫描(CT)图像的模拟。为了研究颅骨模型的影响,我们改变了以下参数:CT 采集参数(管电压、剂量、滤波器锐度)、图像插值、分割参数、声速特性图(声速、密度、衰减)和换能器位置不匹配。我们比较了建模参数变化对模型预测和测量一致性的影响。空间峰值强度和位置、总功率和 Gamma 度量(用于衡量分布差异的度量)被用作定量标准。还对两个人头模型进行了基于建模的敏感性分析。绵羊颅骨衰减分配和换能器定位对空间峰值强度的影响最大(分别高估 300%和 30%),其次是滤波器锐度和管电压(分别高达 20%),需要对映射函数进行校准。定位和颅骨异质性结构对强度分布有很大影响(超过 80%,分别超过 150%的水焦点体积的伽玛容限),需要基于图像的个性化建模。人体模型的模拟结果一致表明,颅骨异质性模型、衰减调整和换能器移位高度敏感,其幅度取决于潜在颅骨结构的复杂性。我们的研究揭示了正确建模颅骨异质性及其结构以及准确再现换能器位置的重要性。当在没有适当的成像和建模参数标准化和/或重新校准的情况下在临床站点之间转换建模方法时,这些结果引起了关注。