For many, the word ‘surgery’ suggests images of surgeons operating with handheld instruments through an open incision in the body. However, in many cases now the reality of surgery is quite different, with surgeons using highly advanced robotic tools to perform minimally invasive procedures.
Robotic-assisted surgery systems are an increasingly important part of a surgeon’s toolkit, enabling unprecedented levels of dexterity and precision in surgical procedures, in turn resulting in better patient outcomes. Such a system typically includes a robotically controlled surgical tool, and a controller enabling the surgeon to remotely control movement of tool. The tool is inserted via an insertion tube (or catheter) which can be introduced through an orifice or a keyhole incision in the body, and a vision system is used to provide the surgeon with a close-up view of a treatment site around the surgical tool.
The field of robotic-assisted surgery is rapidly evolving, with current developments paving the way for new possibilities such as increased automation and integration of artificial intelligence (AI). As robotic-assisted surgery systems become more sophisticated, the line between surgeon and machine is set to blur even further.
Increased automation
Currently, robotic-assisted systems, such as the Da Vinci system manufactured by Intuitive Surgical, are primarily controlled by the surgeon. However, work is being done to increase automation of surgical systems and enable them to perform tasks autonomously. Rather than replace surgeons with fully automated systems, the goal of current work is to assist surgeons in performing surgical procedures, for example allowing them to carry out tasks which would otherwise be difficult or impossible under manual control.
In a recent Science Robotics paper1, a team of researchers from the University of North Carolina demonstrated a medical robot that autonomously navigates a needle inside living tissue around anatomical obstacles to reach target tissue. The demonstration was accomplished in vivo in lungs, which represent a technically challenging area due to the many obstacles and the continuous respiratory motion. The procedure is a multi-stage process, where the surgeon first manually guides a bronchoscope into the lungs and inserts the needle via the bronchoscope, following which the robot takes over to guide the needle along a pre-planned path to the target site. According to the paper, this technique allows access to targets in the body which couldn’t otherwise be reached due to the difficulties in manually navigating around anatomical obstacles.
MURAB (MRI and Ultrasound Robotic Assisted Biopsy) is another ongoing project involving increased automation, where a robot is configured to steer a biopsy-gathering instrument to a target selected by a radiologist based on real-time ultrasound measurements. The ambition of the project is to enable exact targeting of small early-stage lesions, to improve the effectiveness of biopsy gathering for cancer diagnostic operations.
AI Integration
Advances in AI and machine learning (ML) will be a main driver behind improvements in robotic-assisted surgery systems and their increased automation. A major benefit of AI algorithms is their ability to analyse patient data in real-time, whilst leveraging traits they have learned based on huge volumes of training data. Accordingly, integrating AI algorithms into robotic-assisted surgery systems can provide a wide range of benefits, from helping the surgeon with pre-operative planning and decision-making during a surgery, to autonomously carrying out tasks with high levels of precision.
For instance, using image recognition algorithms, a surgical system can be configured to recognise and highlight different types of tissue and anatomical structures to help the surgeon guide the tool to a treatment site in the body. Eventually, such image recognition techniques could be used as part of a control algorithm to enable autonomous navigation to the treatment site. There are also suggestions that AI algorithms could be trained to perform routine tasks, such as tying a suture or a knot, so that the surgeon can focus on more complex issues of the surgery. Another promising application involves leveraging the predictive ability of AI algorithms to monitor a surgery and notify surgeons of complication risks and provide recommendations during surgery, to assist with the surgeon’s decision-making process.
Patent landscape
Robotic-assisted surgery systems such as the Da Vinci system have been in development for over 20 years. Significant advances have been made on the hardware side of these systems, from the robotic actuators allowing fine manipulations, the integrated vision systems providing real-time views of the treatment site, and the control interfaces used by the surgeon for carrying out a surgical procedure. Many of these innovations have been protected by patents over the years, resulting in a relatively crowded patent landscape in this field.
Now however, as focus is shifting towards AI integration and increased automation, there is an opportunity for increased patent protection in these areas. The development of AI algorithms for robotic-assisted surgery is expected to involve innovations in various areas, many of which could be the subject of patent protection. For example, the manner in which the AI algorithms are trained, as well as how they are integrated into robotic systems and how they interact with the hardware may be patentable, if it can be shown that these innovations involve a technical advantage. In order for AI algorithms to reliably assist surgeons with surgical procedures, large volumes of training data representing real surgeries are required. Accordingly, much development work is expected to go into the collection of training data, for example by adapting surgical systems so that they can record data that is usable to train the AI algorithms. So, inventions coming out of the work around collection of training data may also be a promising avenue for patent protection.
Outlook
Recent developments in the fields of robotics and AI are paving the way for a wave of innovation in robotic-assisted surgery, which is likely to change the way we think about surgery in the future. As robotic-assisted surgery systems become more and more advanced, we can expect a wide range of new procedures and techniques to be developed, with surgeons increasingly taking advantage of the enhanced capabilities offered by these systems. With increasing interest in AI integration and automation of these systems, we expect a rise in related patent filings over the coming years as companies seek to establish themselves and protect their IP in this field.
1A. Kuntz et al., “Autonomous medical needle steering in vivo”, Science Robotics, Vol. 8, No. 82, 2023
