|Syed Aftab (pictured above), consultant spinal surgeon and robotic surgical lead at the Royal London Hospital, Barts Health NHS Trust, a major London teaching hospital, uses Brainlab’s Cirq®, a trajectory assistance system in combination with a 3D C-arm. “We were the first surgical unit in the UK to have a robotic spinal system and the first to perform robotic spinal surgery”, says Aftab, who teaches spine and orthopaedic surgery at London’s Queen Mary University, and is also the spinal surgery lead at Complex Spine London. He adds “We chose Brainlab’s Cirq® because it has a small footprint, it’s lightweight, easy to transport from one OR to another and is also cost effective compared to other systems”.
According to Aftab, Brainlab’s second generation system is a significant improvement on its first, “it has a true automatic feature, which finds and holds my screw trajectories based on my preoperative plan. I primarily use the system for pedicle screw insertion. It has applications in the lumbar spine but has significant advantages in the upper cervical spine where the surrounding at risk structures are more challenging and the bony anatomy is less forgiving. The combination of navigation and robotics substantially increases accuracy, reduces the time of surgery, and frequently takes away the need for large dissections to create visual exposure of the operating field. Also, I’ve found the robotic system extremely useful where anatomical localisation is difficult due to previous surgery or altered anatomy, such as in degeneration or ankylosing spondylitis [a form of arthritis in which the spine becomes inflamed and fused]”.
Aftab and his colleagues have found the outcomes of their robotic surgeries “very positive” from both patient and health professional perspectives. “Robotic surgical systems definitely add value to pedicle screw placements compared to traditional open or minimally invasive spine surgery. However, it seems important to point out that it is not altogether clear whether the benefits are derived from the robotic system or from the embedded advanced navigation”, says Aftab. According to a study published in the February 2017 edition of Neurosurgery, the ExelsiusGPS®, “has the potential to revolutionize the field of robotic-assisted spinal surgery. With automated accuracy, reproducible outcomes, efficient integration, automatic patient registration, constrained motion for safety and automatic compensation for patient movement”. The system is like the Mazor and ROSA® Spine but appears to address many of the drawbacks of previous robotic-assisted systems. In November 2019 DePuy Synthes announced a joint venture with TIVANI, to market the TiRobot® for spine surgery in China.
In May 2021 South Korean MedTech company Curexo received FDA approval for its Cuvis-spine robot, which guides pedicle screw insertion and uses a robotic arm to make surgery safer and more efficient. The company expects to market Cuvis in Europe and the US. NuVasive, a US MedTech company, expects its robotic platform, Pulse, to receive FDA approval in summer 2021 for all spinal surgeries, not just complex or low-acuity cases. When launched, it will combine neuromonitoring, surgical planning, rod bending, radiation reduction, imaging, and navigation functions and is expected to compete with other robotic spine offerings on the market, including Medtronic's Mazor X, Globus Medical's ExcelsiusGPS® and Zimmer Biomet's Rosa Spine®.
Compared to traditional fluoroscopic-assisted freehand approaches to pedicle screw placement and other spinal procedures, robotic systems may be more accurate, more efficient, and safer. However, it is worth mentioning that there is a range of robots being used in spine procedures and they do not all guarantee the same accuracy and precision. Errors arise because of their complexity relative to fluoroscopically guided surgery and some existing user interface software can be cumbersome and unintuitive, which suggests that there is a steep learning curve for health professionals wishing to introduce robotic surgical systems into their practice. Studies show that the accuracy of pedicle screw placement increases, and operating time decreases with the number of robotic surgical procedures performed by a clinical team. Thus, there is a learning curve and training is critical; not only for surgeons, but also for other health professionals in the OR.
It is generally accepted that the cost of training and the time it takes could slow the further adoption of robots in spine surgery. Surgical education is just beginning to include robotics as part of standard training for surgeons. However, there are several different robotic systems in clinics and learning curves can vary according to the version of the robotic system used, so standardization of surgical training becomes a challenge, and surgical expertise plays a significant role in obtaining a fair comparison between robotic-assisted and traditional surgery.
Added to the increased training burden associated with robotic techniques are of the high costs of systems. To reduce the financial burden on hospitals, some producers provide innovative financing terms and bundle a robotic system with a range of implants and other devices and services. These issues together with current patchiness of evidence on the efficacy of robotic surgical spine systems are barriers to t the widespread utilization and development of surgical robots.
Tailwinds: China and robotic surgical systems
Over the past two decades Western corporations have dominated the robotic surgical spine market. US, UK, and EU have differed in their approaches to the development and adoption of robotic surgical systems. The US has tended to focus on technical challenges such as tactile sensing and navigating confined spaces, while the UK has been more market driven and focused on the cost effectiveness and regulatory standards of systems. The EU, on the other hand, has attempted to address both R&D and translational issues by promoting academic and industrial collaborations. In recent years, Chinese initiatives, which are more closely aligned with the EU approach, have been gaining momentum and are positioned to impact the spine market in the next decade.
China is challenged by its vast and rapidly ageing population and a shortage of surgical expertise. By 2050 China’s senior citizen population (those ≥60) is projected to grow to >30% of the total population, up from ~12% today, and this is expected to substantially increase the percentage of its retirees relative to workers, which will significantly increase the burden on its healthcare providers.
Beijing believes these challenges can be helped by robotic surgical systems. In addition to acquiring >100 da Vinci systems, China has made the production of domestic robotic surgical systems part of its 2006 15-year plan for science and technology. In 2011 the Chinese government reaffirmed this commitment by including the increased use of robotics in healthcare in its 12th 5-year plan, and over the past decade, Beijing has made substantial R&D investments in the development of robotic surgical systems.
In 2019, China opened the Medical Robotics Institute in Shanghai Jiao Tong University, which is the nation’s first academic establishment dedicated to the study of medical robotics, and appointed Guang-Zhong Yang as its founding dean. Professor Yang formerly was the founding director of the Hamlyn Centre for Robotic Surgery at Imperial College London. According to Yang, medical robotics have been growing in China for the past two decades driven by, “The clinical utilization of robotics; increased funding levels driven by national planning needs; and advances in engineering in areas such as precision mechatronics, medical imaging, artificial intelligence and new materials for making robots”.
China’s robotic surgical industry started later than its foreign peers, but the nation now has ~100 medical robot companies. The Chinese sector is in a transitional phase from R&D and clinical trials to commercialization and mass production. The nation’s medical robot market is expected to be worth ~US$2.5bn by 2026. China’s growing interests in surgical robotic systems is expected to significantly increase competition and accelerate technological developments.
Tinavi Medical Technologies
A notable example of a Chinese enterprise specialising in surgical robotic systems is Tinavi Medical Technologies, a Beijing-based company, backed by China’s Ministry of Science, the Beijing Government, and the Chinese Academy of Science and listed on China’s National Equities Exchange Quotation [an over-the-counter system for trading the shares of a public limited company]. In 2016, Tinavi received fast-tracked approval from the central government to sell the TiRobot®, the first robot-assisted surgical product made in China. As of December 2020, the system had assisted in 10,000 surgical procedures. With its unique algorithm for calculating pedicle screw trajectories, the TiRobot® can precisely move to a planned position and provide surgeons accurate and stable trajectories for implants and pedicle screws; it is expected to make high volume spine surgeries more accurate and standardize less common and more complex spine surgeries. Research published in the January 2021 edition of the Journal of Orthopaedic Surgery and Research, suggests that, “iRobot-assisted vertebroplasty can reduce surgery-related trauma, post-operative complications, and patients’ and operators’ exposure to radiation”.
The production of surgical robotic systems in China is advantaged by the nation’s deep and functional university-industry-research cooperation. It is relatively common in China for technology companies to have strategic alliances with university research institutes with years of accumulated technical expertise. With respect to robotic surgical systems that require application of medical theories and technologies, mechanical engineering, robotics, optics, computer science and AI, such joint ventures bring together interdisciplinary teams with years of multidisciplinary research experience in bio-machine interfaces, integrating bionic techniques, and investigating new materials technologies.
An example of such an interdisciplinary joint venture is a project focussed on making robotic surgery systems more capable of replicating the tactile feel and sensation a surgeon experiences during more invasive traditional procedures. The project is led by researchers at the 3rd Xiangya Hospital of Central South University, in collaboration with Tianjin and Beihang Universities.
Based on their combined experiences of minimally invasive surgery, researchers have built and analysed classified databases on the physical characteristics of patients, on the interaction between human soft tissues and surgical instruments, and on operator-instrument interfaces. This combined knowledge has been used to optimize the design of surgical robotic systems to make them more effective, more intuitive, and safer than exiting robots.
The project team is planning for a multi-centred, prospective, randomised trial to collect more data associated with the system’s safety and effectiveness, which is expected to accelerate the manufacture of their surgical robot. Further, the project team leaders at the 3rd Xiangya Hospital, plan to build a national training institute to educate surgeons in the use of the system, and this is expected to contribute to the robot’s broader use. There are also plans to establish a clinical information centre, by collecting data on the use of the system, and employ AI and machine learning algorithms to analyse them. This is expected to optimize performance, inform upgrades, and make the robot globally competitive.
The “interpretability challenge”
Currently, robotic surgical systems neither make cognitive decisions nor execute autonomous tasks but assist clinicians to enhance pre-operative planning, improve intra-operative guidance, provide superior interpretations of complex in vivo environments, and increases the accuracy, safety, and efficiency of surgical procedures. It seems reasonable to suggest that robotic surgical systems will become more autonomous as they increase their AI and machine learning capabilities, which facilitate instantaneous assessment of complex surgical settings that trigger immediate therapeutic actions, that the surgeon using the robot might not fully understand. This situation can be further complicated by the complexity of algorithms that depend on neural networks comprised of thousands of artificial neurons. This further blurs the reasoning behind specific interpretations and consequent actions of robotic systems. In many such cases the developers of machine learning algorithms cannot explain why an AI driven system arrived at a specific interpretation or a suggested action.
This failure to understand is referred to as an “interpretability challenge”, or more commonly, the “black-box” problem; a concept not broached in surgical studies but discussed in medical ethics.
Reactions from market stakeholders to such a challenge are likely to be mixed. For example, some healthcare providers might welcome more autonomous robotic surgical systems to compensate for shortages of experienced surgeons, others might perceive autonomous robots as having the potential to “level the playing field” among surgeons and contribute to a generally accepted level of surgical services across diverse regions, while other providers might be against surgeons abdicating responsibility to a robot. Whatever the reaction of providers, as robotic surgical systems advance, they are likely to become more complex and less interpretable by the surgeons using them. Increasingly, stakeholders will be required to “place their trust in the system”. Gaining this trust from surgeons, patients and providers could be a more significant obstacle to the further adoption of robotic surgical systems than the obstacles commonly referenced such as costs, scarcity of resources, lack of training, and inconclusive clinical studies.
To counter the “black box” syndrome is “explainable AI” (EAI), an AI solution designed to explain its intent, reasoning and decision-making processes in a manner that can be understood by humans. Until EAI becomes an integral part of robotic surgical systems it seems reasonable to assume that such could face some difficulties progressing beyond their assisted surgical status.
Currently, robotic spine surgery is in its infancy and most of the objective evidence available regarding its benefits draws from the use of robots in a shared-control model to assist with accurately placing of pedicle screws with minimal tissue damage. The performance to-date of robotic surgical systems suggest a new era for spine surgery by their capacity to refine surgical dexterity and augment human capabilities. The current limitations of surgical robots are likely to provide incentives for innovation, which holds out the prospect of developing more advanced robots that further enhance spine surgery outcomes while reducing costs. This is likely to provide a significant boost to well-resourced spine companies developing robotic systems and put pressure on others to change their business models dominated by incremental fixes to their existing product offerings. But keep an eye on Chinese endeavours in robotic surgical systems and the responses to the interpretability challenge in different regions of the world.