Evaluation of the results of perioperative surgical robots in urology - literature review

Introduction: Operations with the use of surgical robots have become an acceptable method of treating urological complaints. The question remains what the perioperative results look like compared to other methods, such as classical surgery or laparoscopy. The aim of the study is to summarize the current state of knowledge about the use of surgical robots in urology, provide information on the types of procedures that can be performed with their help, safety and results Materials and methods: Literature review in databases: [Pubmed; science direct; google scholar]; searched using the words: [robotic surgery, surgical robots, BPH, robot, cystectomy, nephrectomy, retroperitoneal lymphadenectomy, prostatectomy,]. Publications from 2016 to 2023 were reviewed. Results: Data from multiple publications were collected. Promising perioperative results of surgical robots have been shown. Blood loss, length of hospital stay, and complication rate are lower compared to other methods. Positive surgical margins occur with a similar frequency. The safety of performing operations with the use of surgical robots in patients after previous chemotherapy or radiotherapy has been proven. The duration of the operation is usually longer compared to other methods. Conclusions: Performing surgery with the use of surgical robots is a promising method in urology. In many cases, perioperative outcomes are better. However, there is a lack of good quality studies conducted over a long period of time

Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities

Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this work, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page

Identifying barriers in telesurgery by studying current team practices in robot-assisted surgery

This paper investigates challenges in current practices in robot-assisted surgery. In addition, by using the method of proxy technology assessment, we provide insights into the current barriers to wider application of robot-assisted telesurgery, where the surgeon and console are physically remote from the patient and operating team. Research in this field has focused on the financial and technological constraints that limit such application; less has been done to clarify the complex dynamics of an operating team that traditionally works in close symbiosis. Results suggest that there are implications for working practices in transitioning from traditional robot-assisted surgery to remote robotic surgery that need to be addressed, such as possible communication problems which might have a negative impact on patient outcomes

Deep Reinforcement Learning in Surgical Robotics: Enhancing the Automation Level

Surgical robotics is a rapidly evolving field that is transforming the landscape of surgeries. Surgical robots have been shown to enhance precision, minimize invasiveness, and alleviate surgeon fatigue. One promising area of research in surgical robotics is the use of reinforcement learning to enhance the automation level. Reinforcement learning is a type of machine learning that involves training an agent to make decisions based on rewards and punishments. This literature review aims to comprehensively analyze existing research on reinforcement learning in surgical robotics. The review identified various applications of reinforcement learning in surgical robotics, including pre-operative, intra-body, and percutaneous procedures, listed the typical studies, and compared their methodologies and results. The findings show that reinforcement learning has great potential to improve the autonomy of surgical robots. Reinforcement learning can teach robots to perform complex surgical tasks, such as suturing and tissue manipulation. It can also improve the accuracy and precision of surgical robots, making them more effective at performing surgeries

A Timeline of Surgical Robots

Though different from how we think of them today, “robots” have been assisting doctors with surgical procedures since the early 1900s. This artifact takes the shape of a timeline, beginning with the dawn of surgical robots in 1908 and ending with the current state of the art for robotic surgical devices and a look into the future of the field

Collaborative Gaze Channelling for Improved Cooperation During Robotic Assisted Surgery

The use of multiple robots for performing complex tasks is becoming a common practice for many robot applications. When different operators are involved, effective cooperation with anticipated manoeuvres is important for seamless, synergistic control of all the end-effectors. In this paper, the concept of Collaborative Gaze Channelling (CGC) is presented for improved control of surgical robots for a shared task. Through eye tracking, the fixations of each operator are monitored and presented in a shared surgical workspace. CGC permits remote or physically separated collaborators to share their intention by visualising the eye gaze of their counterparts, and thus recovers, to a certain extent, the information of mutual intent that we rely upon in a vis-à-vis working setting. In this study, the efficiency of surgical manipulation with and without CGC for controlling a pair of bimanual surgical robots is evaluated by analysing the level of coordination of two independent operators. Fitts' law is used to compare the quality of movement with or without CGC. A total of 40 subjects have been recruited for this study and the results show that the proposed CGC framework exhibits significant improvement (p<0.05) on all the motion indices used for quality assessment. This study demonstrates that visual guidance is an implicit yet effective way of communication during collaborative tasks for robotic surgery. Detailed experimental validation results demonstrate the potential clinical value of the proposed CGC framework. © 2012 Biomedical Engineering Society.link_to_subscribed_fulltex

MODULAR CABLE - DRIVEN SURGICAL ROBOTS

A surgical robot can be configured for minimally invasive surgery ( MIS ) and other types of surgery with modular link geometry and disposable components. In some examples, the surgical robot includes a cable driver comprising at least one drive motor configured for tensioning a cable. The surgical robot includes an articulated surgical tool coupled to the drive motor by the cable. The articulated surgical tool comprises at least first and second articulated links and a joint coupling the first and second articulated links. The cable passes through the joint, and the joint comprises an elastic antagonist biased in opposition to tension from the cable to allow bidirectional actuation of the joint. The surgical robot includes a safety lock configured to lock the joint from allowing articulation of the first and second articulated links in response to a loss of tension in the cable