Rabinovich Emily P, Capek Stepan, Kumar Jeyan S, Park Min S
University of Virginia School of Medicine, 1215 Lee Street, Charlottesville, VA 22908, USA.
Department of Neurological Surgery, University of Virginia, 1215 Lee Street, Charlottesville, VA 22908, USA; 2nd Faculty of Medicine, Charles University in Prague, Prague, Czech Republic.
J Clin Neurosci. 2020 Sep;79:129-132. doi: 10.1016/j.jocn.2020.04.125. Epub 2020 Aug 5.
In the last forty years, the field of medicine has experienced dramatic shifts in technology-enhanced surgical procedures - from its initial use in 1985 for neurosurgical biopsies to current implementation of systems such as magnetic-guided catheters for endovascular procedures. Systems such as the Niobe Magnetic Navigation system and CorPath GRX have allowed for utilization of a fully integrated surgical robotic systems for perioperative manipulation, as well as tele-controlled manipulation systems for telemedicine. These robotic systems hold tremendous potential for future implementation in cerebrovascular procedures, but lack of relevant clinical experience and uncharted ethical and legal territory for real-life tele-robotics have stalled their adoption for neurovascular surgery, and might present significant challenges for future development and widespread implementation. Yet, the promise that these technologies hold for dramatically improving the quality and accessibility of cerebrovascular procedures such as thrombectomy for acute stroke, drives the research and development of surgical robotics. These technologies, coupled with artificial intelligence (AI) capabilities such as machine learning, deep-learning, and outcome-based analyses and modifications, have the capability to uncover new dimensions within the realm of cerebrovascular surgery.
在过去的四十年里,医学领域在技术增强型手术程序方面经历了巨大的转变——从1985年首次用于神经外科活检,到目前诸如用于血管内手术的磁导导管等系统的应用。像Niobe磁导航系统和CorPath GRX这样的系统,使得在围手术期操作中能够使用完全集成的手术机器人系统,以及用于远程医疗的远程控制操作系统。这些机器人系统在未来脑血管手术中的应用具有巨大潜力,但缺乏相关临床经验以及现实生活中的远程机器人技术尚未涉足的伦理和法律领域,阻碍了它们在神经血管手术中的应用,并且可能给未来的发展和广泛应用带来重大挑战。然而,这些技术有望显著提高脑血管手术(如急性中风血栓切除术)的质量和可及性,这推动了手术机器人技术的研发。这些技术与人工智能(AI)能力(如机器学习、深度学习以及基于结果的分析和改进)相结合,有能力在脑血管手术领域发现新的维度。