Towards autonomous robot-assisted transcatheter heart valve implantation: in vivo teleoperation and phantom validation of AI-guided positioning

摘要

Transcatheter Aortic Valve Implantation (TAVI) is a minimally invasive procedure in which a transcatheter heart valve (THV) is implanted within the patient’s diseased native aortic valve. The procedure is increasingly chosen even for intermediate-risk and younger patients, as it combines complication rates comparable to open-heart surgery with the advantage of being far less invasive. Despite its benefits, challenges remain in achieving accurate and repeatable valve positioning, with inaccuracies potentially leading to complications such as THV migration, coronary obstruction, and conduction disturbances (CD). The latter often requires a permanent pacemaker implantation as a costly and life-changing mitigation. Robotic assistance may offer solutions, enhancing precision, standardization, and reducing radiation exposure for clinicians. This article introduces a novel solution for robot-assisted TAVI, addressing the growing need for skilled clinicians and improving procedural outcomes. We present an in-vivo animal demonstration of robotic-assisted TAVI, showing feasibility of tele-operative instrument control and THV deployment. This, done at safer distances from radiation sources by a single operator. Furthermore, THV positioning and deployment under supervised autonomy is demonstrated on phantom, and shown to be feasible using both camera- and fluoroscopy-based imaging feedback and AI. Finally, an initial operator study probes performance and potential added value of various technology augmentations with respect to a manual expert operator, indicating equivalent to superior accuracy and repeatability using robotic assistance. It is concluded that robot-assisted TAVI is technically feasible in-vivo , and presents a strong case for a clinically meaningful application of level-3 autonomy. These findings support the potential of surgical robotic technology to enhance TAVI accuracy and repeatability, ultimately improving patient outcomes and expanding procedural accessibility.