Surgical Robotics Laboratory, Department of Biomechanical Engineering, Faculty of Engineering Technology, University of Twente, 7500 AE Enschede, The Netherlands.
The Department of Biomedical Engineering, Faculty of Medical Sciences, University Medical Centre Groningen, 9713 GZ Groningen, The Netherlands.
Sensors (Basel). 2021 Jan 3;21(1):273. doi: 10.3390/s21010273.
In this study, we introduce a multi-modal sensing and feedback framework aimed at assisting clinicians during endovascular surgeries and catheterization procedures. This framework utilizes state-of-the-art imaging and sensing sub-systems to produce a 3D visualization of an endovascular catheter and surrounding vasculature without the need for intra-operative X-rays.
The catheterization experiments within this study are conducted inside a porcine limb undergoing motions. A hybrid position-force controller of a robotically-actuated ultrasound (US) transducer for uneven porcine tissue surfaces is introduced. The tissue, vasculature, and catheter are visualized by integrated real-time US images, 3D surface imaging, and Fiber Bragg Grating (FBG) sensors.
During externally-induced limb motions, the vasculature and catheter can be reliably reconstructed at mean accuracies of 1.9±0.3 mm and 0.82±0.21 mm, respectively.
The conventional use of intra-operative X-ray imaging to visualize instruments and vasculature in the human body can be reduced by employing improved diagnostic technologies that do not operate via ionizing radiation or nephrotoxic contrast agents.
The presented multi-modal framework enables the radiation-free and accurate reconstruction of significant tissues and instruments involved in catheterization procedures.
在这项研究中，我们引入了一种多模态传感和反馈框架，旨在协助临床医生进行血管内手术和导管插入术。该框架利用最先进的成像和传感子系统，在无需术中 X 射线的情况下，生成血管内导管和周围血管的 3D 可视化图像。
本研究中的导管插入实验是在进行运动的猪肢内部进行的。引入了一种用于非均匀猪组织表面的机器人超声（US）换能器的混合位置-力控制器。组织、血管和导管通过集成的实时 US 图像、3D 表面成像和光纤布拉格光栅（FBG）传感器进行可视化。
在外力诱导的肢体运动期间，血管和导管可以以 1.9±0.3mm 和 0.82±0.21mm 的平均精度可靠地重建。
通过使用不通过电离辐射或肾毒性造影剂工作的改进诊断技术，可以减少传统术中 X 射线成像来可视化人体中的器械和血管。
所提出的多模态框架能够实现导管插入术过程中重要组织和器械的无辐射和精确重建。
