Vascular interventional doctors are exposed to radiation hazards during surgery and endure high work intensity. Remote vascular interventional surgery robotics is a hot research field, in which researchers aim to not only protect the health of interventional doctors, but to also improve surgical accuracy and efficiency. However, the current vascular interventional robots have numerous shortcomings, such as poor haptic feedback, few compatible surgeries and instruments, and cumbersome maintenance and operational procedures. Nevertheless, vascular interventional surgery combined with robotics provides more cuttingedge directions, such as Internet remote surgery combined with 5G network technology and the application of artificial intelligence in surgical procedures. To summarize the developmental status and key technical points of intravascular interventional surgical robotics research, we performed a systematic literature search to retrieve original articles related to remote vascular interventional surgery robotics published up to December 2020. This review, which includes 113 articles published in English, introduces the mechanical and structural characteristics of various aspects of vascular interventional surgical robotics, discusses the current key features of vascular interventional surgical robotics in force sensing, haptic feedback, and control methods, and summarizes current frontiers in autonomous surgery, long-distance robotic telesurgery, and magnetic resonance imaging (MRI)-compatible structures. On the basis of summarizing the current research status of remote vascular interventional surgery robotics, we aim to propose a variety of prospects for future robotic systems.

Transcatheter arterial chemoembolization (TACE) is the common choice of non-open surgery for hepatocellular carcinoma (HCC) now. In this study, a simple TACE robotic system of 4-degree-of-freedom is proposed to get higher accuracy and stability of the surgery operation and reduce X-ray exposure time of the surgeons. The master–slave control strategy is adopted in the robotic system and a customized sigmoid function is designed to optimize the joystick control of the master–slave robotic control system. A force-sensing module is developed to sense the resistance of the guide wire in linear delivery motion and an auxiliary bending feedback method based on constraint pipe with a film sensor is proposed. With two force-sensing methods, the safety strategy of robotic motion with 9 different motion constraint coefficients is given and a human–computer interface is developed. The TACE robot would monitor the value of the force sensor and the analog voltage of the film sensor to adopt the corresponding motion constraint coefficient in every 10 ms. Vascular model experiments were performed to validate the robotic system, and the results showed that the safety strategy could improve the reliability of the operation with immediate speed constraint and avoid potential aggressive delivery.

Vascular interventional doctors are exposed to radiation hazards during surgery and endure high work intensity. Remote vascular interventional surgery robotics is a hot research field, in which researchers aim to not only protect the health of interventional doctors, but to also improve surgical accuracy and efficiency. However, the current vascular interventional robots have numerous shortcomings, such as poor haptic feedback, few compatible surgeries and instruments, and cumbersome maintenance and operational procedures. Nevertheless, vascular interventional surgery combined with robotics provides more cutting?edge directions, such as Internet remote surgery combined with 5G network technology and the application of artificial intelligence in surgical procedures. To summarize the developmental status and key technical points of intravascular interventional surgical robotics research, we performed a systematic literature search to retrieve original articles related to remote vascular interventional surgery robotics published up to December 2020. This review, which includes 113 articles published in English, introduces the mechanical and structural characteristics of various aspects of vascular interventional surgical robotics, discusses the current key features of vascular interventional surgical robotics in force sensing, haptic feedback, and control methods, and summarizes current frontiers in autonomous surgery, long-distance robotic telesurgery, and magnetic resonance imaging (MRI)-compatible structures. On the basis of summarizing the current research status of remote vascular interventional surgery robotics, we aim to propose a variety of prospects for future robotic systems

<p>Renal artery embolization is an interventional procedure used to treat conditions such as renal artery rupture and renal cancer. It offers advantages such as minimal damage, fast recovery, and low side effects. The implementation of robotic wire navigation in interventional surgery can effectively assist doctors in performing the procedure. Deep learning and reinforcement learning methods have been widely used for wire navigation tasks. However, they face challenges such as overly simplistic simulation environments, single reward functions, and slow convergence speed. To address these issues, we propose the use of a virtual training environment that models real vascular projections, thereby closely resembling the real environment. We incorporate the distance information between the wire tip and the target point into the reward function and utilize real-time images as input states. We accelerate the convergence of the algorithm using the multi-threaded Proximal Policy Optimization (PPO) algorithm and adopt a multi-stage training approach. The results demonstr-ate that our method effectively achieves wire navigation in the virtual environment, reducing training time and improv-ing the success rate of wire navigation and the robustness of the algorithm.</p>

<p>Renal artery embolization is an interventional procedure used to treat conditions such as renal artery rupture and renal cancer. It offers advantages such as minimal damage, fast recovery, and low side effects. The implementation of robotic wire navigation in interventional surgery can effectively assist doctors in performing the procedure. Deep learning and reinforcement learning methods have been widely used for wire navigation tasks. However, they face challenges such as overly simplistic simulation environments, single reward functions, and slow convergence speed. To address these issues, we propose the use of a virtual training environment that models real vascular projections, thereby closely resembling the real environment. We incorporate the distance information between the wire tip and the target point into the reward function and utilize real-time images as input states. We accelerate the convergence of the algorithm using the multi-threaded Proximal Policy Optimization (PPO) algorithm and adopt a multi-stage training approach. The results demonstr-ate that our method effectively achieves wire navigation in the virtual environment, reducing training time and improv-ing the success rate of wire navigation and the robustness of the algorithm.</p>