Real-Time Ultrasound Doppler Tracking and Autonomous Navigation of a Miniature Helical Robot for Accelerating Thrombolysis in Dynamic Blood Flow

脉动流 机器人 血流 计算机科学 模拟 生物医学工程 人工智能 工程类 医学 放射科 心脏病学
作者
Qianqian Wang,Xingzhou Du,Dongdong Jin,Li Zhang
出处
期刊:ACS Nano [American Chemical Society]
卷期号:16 (1): 604-616 被引量:94
标识
DOI:10.1021/acsnano.1c07830
摘要

Untethered small-scale robots offer great promise for medical applications in complex biological environments. However, challenges remain in the control and medical imaging of a robot for targeted delivery inside a living body, especially in flowing conditions (e.g., blood vessels). In this work, we report a strategy to autonomously navigate a miniature helical robot in dynamic blood flow under ultrasound Doppler imaging guidance. A magnetic torque and force-hybrid control approach is implemented, enabling the actuation of a millimeter-scale helical robot against blood flow under a rotating magnetic field with a controllable field gradient. Experimental results demonstrate that the robot (length 7.30 mm; diameter 2.15 mm) exhibits controlled navigation in vascular environments, including upstream and downstream navigation in flowing and pulsatile flowing blood with flow rates up to 24 mL/min (mean flow velocity: 14.15 mm/s). During navigation, the rotating robot-induced Doppler signals enable real-time localization and tracking in flowing and pulsatile flowing blood environments. Moreover, the robot can be selectively navigated along different paths by actively controlling the robot's orientation. We apply this autonomous strategy for localizing thrombus and accelerating thrombolysis rate. Compared with conventional tissue plasminogen activator (tPA) thrombolysis, the robot-enhanced shear stress and tPA convection near the clot-blood interface increase the unblocking and thrombolysis efficiency up to 4.8- and 3.5-fold, respectively. Such a medical imaging-guided navigation strategy provides simultaneous robot navigation and localization in complex dynamic biological environments, providing an intelligent approach toward real-time targeted delivery and diagnostic applications in vivo.
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