Department of Mechanical Engineering, University of Washington, Seattle, WA, 98195, USA.
Department of Radiology, Stanford University, Stanford, USA.
Sci Rep. 2024 Sep 27;14(1):22295. doi: 10.1038/s41598-024-73787-w.
Pulsed high-intensity focused ultrasound (pHIFU) has the capability to induce de novo cavitation bubbles, offering potential applications for enhancing drug delivery and modulating tissue microenvironments. However, imaging and monitoring these cavitation bubbles during the treatment presents a challenge due to their transient nature immediately following pHIFU pulses. A planewave bubble Doppler technique demonstrated its potential, yet this Doppler technique used conventional clutter filter that was originally designed for blood flow imaging. Our recent study introduced a new approach employing dynamic mode decomposition (DMD) to address this in an ex vivo setting. This study demonstrates the feasibility of the application of DMD for in vivo Doppler monitoring of the cavitation bubbles in porcine liver and identifies the candidate monitoring metrics for pHIFU treatment. We propose a fully automated bubble mode identification method using k-means clustering and an image contrast-based algorithm, leading to the generation of DMD-filtered bubble images and corresponding Doppler power maps after each HIFU pulse. These power Doppler maps are then correlated with the extent of tissue damage determined by histological analysis. The results indicate that DMD-enhanced power Doppler map can effectively visualize the bubble distribution with high contrast, and the Doppler power level correlates with the severity of tissue damage by cavitation. Further, the temporal characteristics of the bubble modes, specifically the decay rates derived from DMD, provide information of the bubble dissolution rate, which are correlated with tissue damage level-slower rates imply more severe tissue damage.
脉冲高强度聚焦超声（pHIFU）能够产生新的空化气泡，为增强药物输送和调节组织微环境提供了潜在的应用。然而，由于 pHIFU 脉冲后这些空化气泡的瞬态性质，在治疗过程中对其进行成像和监测是一个挑战。平面波空化气泡多普勒技术展示了其潜力，但这种多普勒技术使用的传统杂波滤波器最初是为血流成像设计的。我们最近的研究在离体环境中引入了一种新的方法，即使用动态模式分解（DMD）来解决这个问题。本研究证明了在体多普勒监测猪肝中空化气泡的 DMD 应用的可行性，并确定了 pHIFU 治疗的候选监测指标。我们提出了一种使用 K 均值聚类和基于图像对比度的算法的全自动气泡模式识别方法，在每个 HIFU 脉冲后生成 DMD 滤波后的气泡图像和相应的多普勒功率图。然后，这些功率多普勒图与组织学分析确定的组织损伤程度相关联。结果表明，DMD 增强的功率多普勒图可以有效地以高对比度可视化气泡分布，并且多普勒功率水平与空化引起的组织损伤严重程度相关。此外，气泡模式的时间特征，特别是 DMD 得出的衰减率，提供了气泡溶解率的信息，这与组织损伤水平相关-较慢的速率意味着更严重的组织损伤。
