Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA.
A. Linton Department of Mechanical Engineering, Lawrence Technological University, Southfield, MI 48075, USA.
Sensors (Basel). 2020 May 15;20(10):2816. doi: 10.3390/s20102816.
The next generation of intelligent robotic systems has been envisioned as micro-scale mobile and externally controllable robots. Visualization of such small size microrobots to track their motion in nontransparent medium such as human tissue remains a major challenge, limiting translation into clinical applications. Herein, we present a novel, non-invasive, real-time imaging method by integrating ultrasound (US) and photoacoustic (PA) imaging modalities for tracking and detecting the motion of a single microrobot in deep biological tissue. We developed and evaluated a prototyped PA-guided magnetic microrobot tracking system. The microrobots are fabricated using photoresist mixed with nickel (Ni) particles. The microrobot motion was controlled using an externally applied magnetic field. Our experimental results evaluated the capabilities of PA imaging in visualizing and tracking microrobots in opaque tissue and tissue-mimicking phantoms. The results also demonstrate the ability of PA imaging in detecting a microrobot with the sizes less than the minimum detectable size by US imaging (down to 50 µm). The spectroscopic PA imaging studies determined an optimal wavelength (700 nm) for imaging microrobots with embedded Ni particles in oxygenated (fresh) human blood. In addition, we examined the ability of PA imaging to detect the microrobots through a nontransparent tissue mimic and at a depth of 25 mm, where conventional optical methods are unable to be used in tracking the objects. These initial results demonstrate the feasibility of an integrated US and PA imaging method to push the boundaries of microrobot applications into translational applications.
下一代智能机器人系统被设想为微尺度的移动机器人和外部可控制机器人。可视化如此小尺寸的微型机器人以跟踪它们在非透明介质(如人体组织)中的运动仍然是一个主要挑战,限制了其向临床应用的转化。在此,我们提出了一种新颖的、非侵入性的、实时的成像方法,通过集成超声(US)和光声(PA)成像模式来跟踪和检测单个微机器人在深层生物组织中的运动。我们开发并评估了原型 PA 引导的磁性微机器人跟踪系统。微机器人是使用混合有镍(Ni)颗粒的光致抗蚀剂制造的。微机器人的运动通过外部施加的磁场来控制。我们的实验结果评估了 PA 成像在可视化和跟踪不透明组织和组织模拟体模中的微机器人的能力。结果还表明,PA 成像具有检测尺寸小于 US 成像最小可检测尺寸(低至 50 µm)的微机器人的能力。光谱 PA 成像研究确定了用于在含氧(新鲜)人血中嵌入 Ni 颗粒的微机器人成像的最佳波长(700nm)。此外,我们还检查了 PA 成像通过不透明组织模拟体并在 25mm 深度检测微机器人的能力,在这个深度下,传统的光学方法无法用于跟踪物体。这些初步结果证明了集成 US 和 PA 成像方法的可行性,该方法将微机器人应用的界限推向转化应用。