Robotics in orthopaedic surgery: why, what and how?

Real-time active constraint generation and enforcement for surgical tools using 3D detection and localisation network

Introduction: Collaborative robots, designed to work alongside humans for manipulating end-effectors, greatly benefit from the implementation of active constraints. This process comprises the definition of a boundary, followed by the enforcement of some control algorithm when the robot tooltip interacts with the generated boundary. Contact with the constraint boundary is communicated to the human operator through various potential forms of feedback. In fields like surgical robotics, where patient safety is paramount, implementing active constraints can prevent the robot from interacting with portions of the patient anatomy that shouldn't be operated on. Despite improvements in orthopaedic surgical robots, however, there exists a gap between bulky systems with haptic feedback capabilities and miniaturised systems that only allow for boundary control, where interaction with the active constraint boundary interrupts robot functions. Generally, active constraint generation relies on optical tracking systems and preoperative imaging techniques. Methods: This paper presents a refined version of the Signature Robot, a three degrees-of-freedom, hands-on collaborative system for orthopaedic surgery. Additionally, it presents a method for generating and enforcing active constraints "on-the-fly" using our previously introduced monocular, RGB, camera-based network, SimPS-Net. The network was deployed in real-time for the purpose of boundary definition. This boundary was subsequently used for constraint enforcement testing. The robot was utilised to test two different active constraints: a safe region and a restricted region. Results: The network success rate, defined as the ratio of correct over total object localisation results, was calculated to be 54.7% ± 5.2%. In the safe region case, haptic feedback resisted tooltip manipulation beyond the active constraint boundary, with a mean distance from the boundary of 2.70 mm ± 0.37 mm and a mean exit duration of 0.76 s ± 0.11 s. For the restricted-zone constraint, the operator was successfully prevented from penetrating the boundary in 100% of attempts. Discussion: This paper showcases the viability of the proposed robotic platform and presents promising results of a versatile constraint generation and enforcement pipeline.

Clinical applications of robotic surgery platforms: a comprehensive review

Robotic surgery has expanded globally across various medical specialties since its inception more than 20 years ago. Accompanying this expansion were significant technological improvements, providing tremendous benefits to patients and allowing the surgeon to perform with more precision and accuracy. This review lists some of the different types of platforms available for use in various clinical applications. We performed a literature review of PubMed and Web of Science databases in May 2023, searching for all available articles describing surgical robotic platforms from January 2000 (the year of the first approved surgical robot, da Vinci® System, by Intuitive Surgical) until May 1st, 2023. All retrieved robotic platforms were then divided according to their clinical application into four distinct groups: soft tissue robotic platforms, orthopedic robotic platforms, neurosurgery and spine platforms, and endoluminal robotic platforms. Robotic surgical technology has undergone a rapid expansion over the last few years. Currently, multiple robotic platforms with specialty-specific applications are entering the market. Many of the fields of surgery are now embracing robotic surgical technology. We review some of the most important systems in clinical practice at this time.

Accuracy of Advanced Active Robot for Total Knee Arthroplasty: A Cadaveric Study

Although the accuracy of other types of robotic systems for total knee arthroplasty (TKA) has been assessed in cadaveric studies, no investigations have been performed to evaluate this newly advanced active robotic system. Therefore, the authors aimed to analyze the accuracy of bone resection in terms of thickness and alignment in a cadaveric study. Three cadaveric specimens (six knees) and an active robotic system (CUVIS Joint, CUREXO) were used in the study. Three surgeons with different experiences in robotic TKAs performed this cadaveric study using the same robotic protocol with two different implant designs. The thickness and angle of bone resection planes obtained from the optical tracking system and the difference between resection planes and the planning data were assessed to determine accuracy. With respect to the overall resection accuracy compared to the plan, the cutting depth accuracy was within 1.0 mm mean of root mean square (RMS), and the resection angle accuracy in terms of sagittal, coronal, and axial planes was within 1.0 degree mean RMS. In contrast, no significant differences were observed between the planned and measured values in terms of the resection angles and cutting thickness. The hip-knee-ankle angle at postoperative evaluation was 0.7 degrees ± 0.7 degrees (RMS 1.0 degrees). This in vivo study suggests that the use of this newly advanced active robotic system for TKA demonstrates a high degree of accuracy in terms of resection thickness and alignment. This finding supports the clinical application of this advanced robotic system. LEVEL OF EVIDENCE:  Cadaveric study, Level V.

The landscape of surgical robotics in orthopedics surgery

Orthopedic surgery is one of the first surgical specialties to apply surgical robotics in clinical practice, which has become an interesting field over the years with promising results. Surgical robotics can facilitate total joint arthroplasty by providing robotic support to accurately prepare the bone, improving the ability to reproduce alignment, and restoring normal kinematics. Various robotic systems are available on the market, each tailored to specific types of surgeries and characterized by a series of features with different requirements and/or modus operandi. Here, a narrative review of the current state of surgical robotic systems for total joint knee arthroplasty is presented, covering the different categories of robots, which are classified based on the operation, requirements, and level of interaction with the surgeon. The different robotic systems include closed/open platform, image-based/imageless, and passive/active/semi-active systems. The main goal of a robotic system is to increase the accuracy and precision of the operation regardless of the type of system. Despite the short history of surgical robots, they have shown clinical effectiveness compared to conventional techniques in orthopedic surgery. When considering which robotic system to use, surgeons should carefully evaluate the different benefits and drawbacks to select the surgical robot that fits their needs the best.

Preliminary study of short-term outcomes and learning curves of robotic-assisted THA: comparison between closed platform robotic system and open platform robotic system

BACKGROUND

Both closed platform and open platform robotic-assisted total hip arthroplasty (THA) have recently been recommended as a viable treatment option for achieving accurate positioning of components. Yet, limited studies paid attention to the differences between the closed platform robotic system and the open platform robotic system. Hence, this study aimed to investigate clinical outcomes, radiographic outcomes, complication rates and learning curve of two systems.

MATERIALS AND METHODS

We retrospectively included 62 patients (31 closed robotic system and 31 open robotic system) who underwent THA between February 2021 and January 2023. The demographics, operating time, cup positioning, complications and hip Harris score were evaluated. Learning curves of operation time was conducted using cumulative sum (CUSUM) analysis.

RESULTS

There were no differences in surgical time (76.7 ± 12.1 min vs. 72.3 ± 14.8 min), estimated blood loss (223.2 ± 13.2 ml vs. 216.9 ± 17 ml) and Harris Hip score (HHS) between closed platform robotic system and the open platform robotic system. The closed robotic system and the open robotic system were associated with a learning curve of 9 cases and 7 cases for surgical time respectively, based on the satisfying rate of Lewinnek's safe zone outliers (1/31, 96.8%) and no occurrence of complication. Both robotic systems had significant reduction in overall surgical time, the duration of acetabulum registration, and estimated blood loss between learning phase and proficiency phase.

CONCLUSION

The authors suggest that the surgical outcomes and safe zone outlier rate of the open robotic-assisted THA were similar to those of the closed robotic-assisted THA. These two robotic-assisted are associated with comparable learning curves and both have the precise positioning of acetabular component. From learning phase to proficiency phase, the rate of positions within the safe zone differed only marginally (88.9-100% vs. 85.7-100%) based on a rather low number of patients. This is not a statistically significant difference. Therefore, we suggest that THA undergoing with the robotic-assisted system is the relatively useful way to achieve planned acetabular cup position so far.

Revolutionizing Orthopedic Healthcare: The Role of Robotics

Integrating robotics into orthopedic healthcare represents a transformative paradigm shift driven by technological advancements. This editorial explores the profound impact of robotics on the diagnosis, treatment, and rehabilitation of musculoskeletal conditions. Robotics redefines precision in orthopedic surgery through advanced imaging and real-time feedback, resulting in minimized disruption to tissues and faster recovery. Personalized treatment plans leverage robotics' capabilities to tailor procedures to individual anatomical characteristics, enhancing outcomes and reducing complications. Minimally invasive procedures, facilitated by robotics, mitigate trauma and expedite patient recovery. This collaboration between surgeons and robotic systems enhances precision without supplanting human expertise. Moreover, robotics extends to postoperative rehabilitation, utilizing exoskeletons and motion-capture systems to optimize mobility and strength recovery. While challenges of cost and training exist, proactive collaborations are shaping the future of robotics in orthopedic care. Ethical considerations underline the importance of balancing human intervention with robotic assistance. As robotics evolves, orthopedic healthcare embraces a future where technology and human expertise synergize, ultimately conquering musculoskeletal conditions.

Intraoperative sensor technology quantifies inter-prosthesis pressure for predicting lower limb alignment after Oxford unicompartmental knee arthroplasty

Purpose: The aim of this study is to quantify inter-prosthetic pressures at different knee angles in Oxford unicompartmental knee arthroplasty (OUKA) and its correlation with postoperative lower limb alignment. Methods: This study included 101 patients (122 knees) who underwent OUKA from March 2022 to July 2022. The previously designed matrix flexible force sensor was used to measure the inter-prosthesis pressure of different knee joint angles during the UKA operation, and the force variation trend and gap balance difference were obtained. The correlation between inter-prosthesis pressure and postoperative lower limb alignment index including hip-knee-ankle angle (HKAA) and posterior tibial slope (PTS) was analyzed. The effect of PTS change (ΔPTS) on the inter-prosthesis pressure and the range of motion (ROM) of the knee joint was analyzed. Radiographic and short-term clinical outcomes of included patients were assessed. Results: The inter-prosthesis pressure of the different knee joint angles during the operation was not consistent. The mean inter-prosthesis pressure and gap balance difference were 73.68.28 ± 41.65N and 36.48 ± 20.58N. The inter-prosthesis pressure at 0° and 20° was positively correlated with postoperative HKAA (p < 0.001). ΔPTS was positively correlated with the pressure at the end of knee extension and negatively correlated with the pressure at the end of knee flexion (p < 0.001). The HKAA, ROM, degree of fixed knee flexion deformity, and knee society score of the included patients were significantly improved compared with those before the operation (p < 0.001). Conclusion: The inter-prosthesis pressure measured at the knee extension position can predict postoperative HKAA to some degree. Changes in PTS will affect the inter-prosthesis pressure at the end of flexion and end of knee extension, but this change is not related to the range of motion of the knee joint.

Intraoperative technology increases operating room times in primary total knee arthroplasty

INTRODUCTION

Optimization of patient outcomes and identification of factors to improve the surgical workflow are increasingly important. Operating room time is one modifiable factor that leads to greater hospital efficiency as well as improved outcomes such as shorter length of stay and fewer infections and readmissions. The aim of this study was to identify factors associated with operative time disparities in total knee arthroplasty (TKA).

METHODS

A retrospective review of 7659 consecutive primary TKA cases was conducted. Patient demographic data, discrete operating room (OR) times, use of technology (i.e. robotic-assisted surgery, computer navigation), surgeon experience and the level of training of the first assistant were collected. Multivariate regression analysis was used to determine the effect of hospital characteristics on operative times. Operative times of five minutes or greater were considered to be clinically significant.

RESULTS

While the use of technology (182.64 ± 39.85 vs 158.70 ± 37.45 min; B = 26.09; p < 0.0001) and greater surgeon experience (162.14 ± 39.87 vs 158.69 ± 33.18 min, B = 3.15, p = 0.002) were found to increase OR times, level of training of the first assist (161.65 vs 156.4 min; Β = - 0.264; p = 0.487) did not. Of the discrete OR times examined, incision time and total time under anesthesia were negatively impacted by the use of technology.

CONCLUSION

Use of technology was the only study variable found to significantly increase OR times. With increased operative times and limited evidence that technology improves long-term patient outcomes, surgeons should carefully consider the benefits and cost of technology in TKA.

How reproducible are clinical measurements in robotic knee surgery?

PURPOSE

Robotic-assisted surgery has been recently introduced to improve biomechanical restoration, and thus better clinical and functional outcomes, after knee joint arthroplasty operations. Robotic-assisted uni-compartmental knee arthroplasty (UKA) aims indeed to improve surgical bone resection and alignment accuracy, optimized component positioning and knee balancing, relying on a series of calibration measurements performed during the surgery. These advantages focus therefore on improving the reproducibility of UKA surgeries, reducing (if not eliminating) eventual differences among high- and low-volume surgeons. The purpose of this study is to investigate and quantify the reproducibility of in-vivo measurements performed with a robotic system: the intra- and inter-observer variability of a series of measurements was therefore analyzed and compared among differently experienced operators.

METHODS

Five patients were analyzed and underwent robotic-assisted UKA using a semi-active robotic system. Three different observers with different experience levels were involved to independently perform the measurements of two parameters of the preoperative knee (Hip-Knee-Ankle angle [HKAa], Internal-External Rotation) at different degrees of knee flexion. Inter-observer and intra-observer comparisons were performed.

RESULTS

The average variability in the measurements obtained from the intra-observer and inter-observer comparisons were always < 0.68° for HKAa and < 2.59° for internal-external rotation, and the ICCs showed excellent agreement (> 0.75) for most cases and good agreement (> 0.60) in the remaining ones.

CONCLUSION

This study demonstrated high reproducibility of the measurements obtainable in clinical environment with the robotic system. The inter-observer results furthermore showed that the level of confidence with the robotic system is not significantly influencing the measurement.

Postoperative regular use of a self-rehabilitation mobile application for more than two weeks reduces extension deficit and cyclop syndrome after anterior cruciate ligament reconstruction

PURPOSE

To investigate the minimum use that correlates with the best outcomes in term of complications associated with self-directed rehabilitation mobile application and to explore the user profile and usage habits.

METHODS

This was a single-center retrospective study of 356 patients who underwent ACL reconstruction surgery between November 2019 and August 2020. Complications were defined as the presence of an extension deficit ≥ 5° after 6 weeks and/or the presence of cyclops syndrome. The demographics, sports competition level and number of connections were collected by the application.

RESULTS

The complication rate was reduced 4.2-fold with at least 2 weeks of use (2.4% (3/123) (with 0.8% (1/123) of cyclops syndrome) versus 10.8% (23/212) (with 3.3% (7/212) cyclops syndrome), p = .04). The mean duration of use was 20 ± 23 days with a frequency of 2.1 ± 2.3 connections per day. The usage rate was 50% in week 1, 35% in week 2, and 24% in week 3. There was one peak in the abandon rate during the first few days of use and a second peak at Day 10 when physiotherapy sessions started. There were two dips in the abandon rate associated with the follow-up visits at Days 21 and 45. Greater use was found in older patients (p = .0001) and female patients (p = .04).

CONCLUSIONS

When using the application for a minimum of 2 weeks, the risk of complications was reduced 4.2-fold. The typical users of a self-directed rehabilitation application after ACL surgery in this study were women and patients over 30 years of age.

LEVEL OF EVIDENCE

IV, retrospective.

Technology and orthopaedic surgeons

Modern and innovative technologies are rapidly penetrating the clinical practices of Orthopaedic Surgeons. The ones that have proved successful for clinical use are Additive Manufacturing/3D printing, Artificial Intelligence, Robotics, Smart sensors, and Orthobiologics. Industry 5.0 revolution has helped provide personalised treatment by integrating machines and human beings. In this special issue, we present a collection of excellent articles on these technologies.

Finite element analysis of malposition in bi-unicompartmental knee arthroplasty

PURPOSE

Bi-unicompartmental knee arthroplasty is a less invasive treatment than a total one, great advantage for the patient but more difficult for the surgeon because of the lower visibility during surgery; this can therefore lead to eventual small errors in cutting angles during the procedure. The aim of this study is to investigate the effects of these slight angle variations in terms of anterior-posterior slope for the lateral tibial tray.

METHODS

The geometries of the bones were acquired and uncemented fixed bearing metal-back UKAs virtually implanted in a finite elements environment. The lateral component was implanted in six different antero-posterior slope configurations (from - 5° to + 5° respect to medial component). Material properties for implant, bones and soft tissues were taken from the literature. A vertical compressive force of 2000 N was applied in full-extended configuration on the femur. Von Mises stress distribution in proximal tibia, load/pressure/contact area repartitions between the medial and lateral compartments was extracted as outputs.

RESULTS

Outcomes for 0° and - 3° configurations are acceptable, but the - 2° of slope configuration achieved the best ones in terms of stress on proximal tibia, load repartition, contact pressure distribution and shear component. Drastically different results are found for the  ± 5° configurations, presenting a level of unbalancing often associated with weak stability and failure over time.

CONCLUSIONS

Slight errors can happen during the surgery: performing the cut aiming to slightly posterior slopes during the surgery helps to minimize the chances of obtaining positive slopes that could lead to an unstable implant.

Where are We Now and What are We Hoping to Achieve with Robotic Total Knee Arthroplasty? A Critical Analysis of the Current Knowledge and Future Perspectives

Robotic-assisted total knee arthroplasty (rTKA) has been developed to improve knee kinematics and functional outcomes, expedite recovery, and improve implants long-term survivorship. Robotic devices are classified into active, semi-active, and passive, based on their degree of freedom. Their capacity to provide increased accuracy in implants positioning with reduced radiographic outliers has been widely proved. However, these early advantages are yet to be associated with long-term survivorship. Moreover, multiple drawbacks are still encountered including a variable learning curve, increased setup and maintenance costs, and potential complications related to the surgical technique. Despite recent technologies applied to TKA have failed to prove substantial improvements, robotic-assisted surgery seems to be here to stay and revolutionize the field of TKA. To support its consistent usage on a daily basis, long-term results are still awaited, and further improvements are necessary to reduce the expenses related to it.

Discussion on the possibility of multi-layer intelligent technologies to achieve the best recover of musculoskeletal injuries: Smart materials, variable structures, and intelligent therapeutic planning

Although intelligent technologies has facilitated the development of precise orthopaedic, simple internal fixation, ligament reconstruction or arthroplasty can only relieve pain of patients in short-term. To achieve the best recover of musculoskeletal injuries, three bottlenecks must be broken through, which includes scientific path planning, bioactive implants and personalized surgical channels building. As scientific surgical path can be planned and built by through AI technology, 4D printing technology can make more bioactive implants be manufactured, and variable structures can establish personalized channels precisely, it is possible to achieve satisfied and effective musculoskeletal injury recovery with the progress of multi-layer intelligent technologies (MLIT).

Custom Massive Allograft in a Case of Pelvic Bone Tumour: Simulation of Processing with Computerised Numerical Control vs. Robotic Machining

The use of massive bone allografts after the resection of bone tumours is still a challenging process. However, to overcome some issues related to the processing procedures and guarantee the best three-dimensional matching between donor and recipient, some tissue banks have developed a virtual tissue database based on the scanning of the available allografts for using their 3D shape during virtual surgical planning (VSP) procedures. To promote the use of future VSP bone-shaping protocols useful for machining applications within a cleanroom environment, in our work, we simulate a massive bone allograft machining with two different machines: a four-axes (computer numerical control, CNC) vs. a five-axes (robot) milling machine. The allograft design was based on a real case of allograft reconstruction after pelvic tumour resection and obtained with 3D Slicer and Rhinoceros software. Machining simulations were performed with RhinoCAM and graphically and mathematically analysed with CloudCompare and R, respectively. In this case, the geometrical differences of the allograft design are not clinically relevant; however, the mathematical analysis showed that the robot performed better than the four-axes machine. The proof-of-concept presented here paves the way towards massive bone allograft cleanroom machining. Nevertheless, further studies, such as the simulation of different types of allografts and real machining on massive bone allografts, are needed.

Multi-Stage Platform for (Semi-)Automatic Planning in Reconstructive Orthopedic Surgery

Intricate lesions of the musculoskeletal system require reconstructive orthopedic surgery to restore the correct biomechanics. Careful pre-operative planning of the surgical steps on 2D image data is an essential tool to increase the precision and safety of these operations. However, the plan’s effectiveness in the intra-operative workflow is challenged by unpredictable patient and device positioning and complex registration protocols. Here, we develop and analyze a multi-stage algorithm that combines deep learning-based anatomical feature detection and geometric post-processing to enable accurate pre- and intra-operative surgery planning on 2D X-ray images. The algorithm allows granular control over each element of the planning geometry, enabling real-time adjustments directly in the operating room (OR). In the method evaluation of three ligament reconstruction tasks effect on the knee joint, we found high spatial precision in drilling point localization (ε<2.9mm) and low angulation errors for k-wire instrumentation (ε<0.75∘) on 38 diagnostic radiographs. Comparable precision was demonstrated in 15 complex intra-operative trauma cases suffering from strong implant overlap and multi-anatomy exposure. Furthermore, we found that the diverse feature detection tasks can be efficiently solved with a multi-task network topology, improving precision over the single-task case. Our platform will help overcome the limitations of current clinical practice and foster surgical plan generation and adjustment directly in the OR, ultimately motivating the development of novel 2D planning guidelines.