Professor Kunzheng Wang delivered a keynote speech titled “AI and the Development of Orthopedics in China”. In fact, AI is also known as “the fourth industrial revolution”, and China’s ability to take the lead in this fourth industrial revolution will dictate the destiny of its orthopedic development in the next several decades. With the advent of precision medicine, computer navigation, three-dimensional (3D) printing and patient-specific instrumentation, the design of new types of joints and the improvement of conventional tools, minimally invasive techniques and robot-assisted surgery have emerged, and they encourage joint surgeons to take new perspectives and set higher goals . Currently, applications of AI in clinical medicine principally involve three main aspects: auxiliary diagnosis, precise positioning and medical robotics. For instance, AI diagnostic models for osteonecrosis of the femoral head, femoral neck fracture and other diseases, established through deep learning algorithms based on X-ray images, allow us to validate the models and adjust parameters using clinical data. In core decompression surgery for avascular necrosis of the femoral head, computer-aided navigation can accurately locate the necrotic area, thereby reducing damage caused by intraoperative fluoroscopy and shortening the operative time. 3D printing enables computer-aided design to move from a virtual space to reality, and its application permits the preoperative simulation of implants in the patient, which substantially improves the precision and safety of joint surgery. What is more, artificial joint design based on computed tomography (CT)/magnetic resonance imaging (MRI) can be individualized with respect to the material, size, shape and biological features of artificial joints. According to Professor Wang, China’s precision medicine program remains in its infancy, and industry guidelines in line with precision medicine plans and the characteristics of Chinese patients needs to be developed to enable precision medicine and joint surgery in China to take a lead in orthopedics by “overtaking on corners”.
Professor Peifu Tang presented a keynote speech on “Applications of the ‘Digital Twin’ Concept in Orthopedics”. The digital twin concept is a reality-transcending concept that enables mapping in the virtual space to reflect the full life cycle of the corresponding physical item through a simulation process involving a multidisciplinary, multiphysical, multiscale and multiprobability integration that makes full use of physical models, sensor updates, operation history and other data. It can be seen as a digital mapping system involving one or more important and interdependent equipment system(s). When applied to orthopedics, it assists in the construction of full-dimensional digital models of “live” human body systems via full-range, cross-scale data perception and digital modeling of the human body for precision and smart medicine. By taking advantage of computer-generated graph and image description techniques, finite element analysis, equivalent mechanics and AI calibration, Dr. Tang’s team conducted a theoretical mechanics analysis and mechanical validation of the three-element stabilization system of the proximal femur. They proposed, for the first time, a machine learning-based fracture classification system upon examining intertrochanteric femoral fracture patterns using the AI clustering algorithm and generated views of anterior, posterior, lateral and medial fractures. They analyzed 504 cases of femoral intertrochanteric fractures and found that most of the fracture lines (anterior view: 85.9%; posterior view: 52.0%; internal lateral view: 49.0%; external lateral view: 62.7%) ran along the intertrochanteric line, which was highly consistent with conventional fracture classification results based on clinical experience, suggesting that the established system is of great significance for describing morphological characteristics and adjuvant therapy [3, 4] (Table 1).
Smart solutions for orthopedic surgery are based mainly on automatic preoperative planning with next-generation AI technology to establish a knowledge- and data-driven method and a systematic, hierarchical and expandable knowledge description system that performs knowledge-aided image processing and preoperative planning and ultimately yields a clear and thorough surgical plan . In recent years, AI and deep learning have flourished in various fields, and the clinical use of robots in joint surgery is a milestone in the development of orthopedics. At this conference, the robot design team presented the process used to design and develop robots for joint surgery. Professor Qinghu Meng from Southern University of Science and Technology first reviewed the development of robots, from industrial robots to conventional medical robots to minimally invasive surgery robots, focusing on wireless capsule endoscopy robots and image-based automatic diagnosis systems, which have a diagnostic accuracy up to 100% . According to Prof. Meng, intelligent medical care will be developed for frequent, real-time and home-based physical examinations, unmanned intelligent care in infectious disease wards and intensive care units (ICU), supermarket- and home-based diagnosis and treatment of digestive diseases, the specialization and miniaturization of robot-assisted surgery, and the digitalization and intelligentization of orthopedic robot-assisted surgery.
The speech given by Professor Fangwen Zhai from the Intelligent Robot Research Center, Institute for Artificial Intelligence, Tsinghua University, was about “The Future of Orthopedic Robots”. He pointed out that most orthopedic surgical robots, such as spinal surgical robots, joint surgical robots and trauma surgical robots, can perform only relatively simple surgical procedures at present. Therefore, multiple sets of surgical robots must be purchased to operate on different body parts, which increases cost, lengthens the learning curve (LC), and consume more surgical resources. More importantly, the lack of standards and sharing mechanisms among industries and the lack of openness or compatibility of software for various robot systems render it impossible for preoperative planning and robot control software to interact with each other and cause serious data segmentation, which seriously prevents the industry from moving forward. Therefore, it is imperative to develop a unified infrastructure and a common software and hardware platform and to work out various functional modules based on that platform to allow compatibility among surgical modes for different surgeries. Surgery 4.0, launched by Johnson & Johnson, is just one of such unified platforms .
Professor Zhai pointed out that intraoperative registration is a bottleneck for robotic surgery because of high skill requirements on doctors, the radiation exposure during long-time intraoperative imaging and point registration and surface scanning methods that affect the surgical process. Therefore, it is necessary to develop a highly efficient automatic registration mode that offers clear and radiation-free real-time imaging support and fast registration algorithms coupled with more flexible scene perception methods and to establish a registration-free surgical navigation mode that provides preoperative qualitative planning, intraoperative multimodal real-time perception and real-time surgical plan generation. In addition, he emphasized that, at present, surgical robots are still a high-degree-of-freedom locator, lacking real-time environmental perception and complex decision-making ability and having weak force control. In the future, robot designs need to be customized and specialized to make robots more dexterous, gentler and more adaptive to various types of surgery.
From the perspective of a surgeon, Professor Jiying Chen comprehensively answered the question “What kind of robot is needed for joint surgery?”. He focused on the shortcomings of existing robots for joint surgery, such as the lack of data accumulation, a low level of intelligentization and the need for manual assistance to complete the operation. The high demand for wide-scope preoperative radiography and the implantation of the reference frame in robot-assisted hip and knee surgery are likely to cause damage to the patient. The cumbersome intraoperative registration procedure and high failure rate will prolong the operation time. The inability of robots to perceive soft tissue tension makes them unable to provide forecasting factors of the impact and dislocation. In view of this, Professor Chen proposed a vision for the future of joint surgery robots: a focus on improving the function and effectiveness of robots, increasing their 3D accuracy and enhancing the individualization of force lines, positions and angles; continuously incorporating the latest knowledge into preoperative planning and enriching personalized design, e.g., by considering the role of the hip-spine relationship in the hip joint and the roles of developmental deformities and extra-articular deformities in the knee joint.
The clinical benefits and ethical risks of robotic joint surgery are an important research direction that cannot be ignored. The speech made by professor Jin Lin from Peking Union Medical College Hospital was titled “Focus on Clinical Value: Reflections on the Innovation of the TKA Robot, a Chinese Domestic Product”. In his keynote speech, he defined the clinical value from six dimensions, i.e., patient benefits, clinical pain point resolution, doctors’ self-realization, clinical application costs, learning curve (LC), and the payer’s net expenditure. Of these, patient benefits, clinical pain point resolution, and doctors’ self-realization were used as the numerator items, and clinical application costs, doctors’ LC and the payer’s net expenditure as the denominator items. He asserted that if a product can achieve breakthroughs in two of the six dimensions, the product can be called a “great breakthrough”. Furthermore, he stated that the “one-vote veto” should be avoided due to the difficulty in moving forward along certain dimensions. He further pointed out that robotic surgery is a powerful tool for achieving technological breakthroughs and that although it currently has some shortcomings, surgeons should put more trust in the robot-assisted surgery.