Video-based computer navigation in knee arthroscopy for patient-specific ACL reconstruction

Marker-Less Navigation System for Anterior Cruciate Ligament Reconstruction with 3D Femoral Analysis and Arthroscopic Guidance

Accurate femoral tunnel positioning is crucial for successful anterior cruciate ligament reconstruction (ACLR), yet traditional arthroscopic techniques face significant challenges in spatial orientation and precise anatomical localization. This study presents a novel marker-less computer-assisted navigation system that integrates three-dimensional femoral modeling with real-time arthroscopic guidance. The system employs advanced image processing techniques for accurate condyle segmentation and implements the Bernard and Hertel (BH) grid system for standardized positioning. A curvature-based feature extraction approach precisely identifies the capsular line reference (CLR) on the lateral condyle surface, forming the foundation for establishing the BH reference grid. The system's two-stage registration framework, combining SIFT-ICP algorithms, achieves accurate alignment between preoperative models and arthroscopic views. Validation results from expert surgeons demonstrated high precision, with 71.5% of test groups achieving acceptable or excellent performance standards (mean deviation distances: 1.12-1.86 mm). Unlike existing navigation solutions, our system maintains standard surgical workflow without requiring additional surgical instruments or markers, offering an efficient and minimally invasive approach to enhance ACLR precision. This innovation bridges the gap between preoperative planning and intraoperative execution, potentially improving surgical outcomes through standardized tunnel positioning.

Surgical Robots Improve Tunnel Angle and Graft Bending Angle in Anatomic ACL Reconstruction: A Multicenter Study

The anatomic characteristics of the graft and tunnel, i.e., the tunnel position, angle, length, and the graft bending angle, influence knee joint stability and postoperative functional recovery. The purpose of this study was to evaluate the tunnel position, length and angle, as well as graft bending angle after ACL reconstruction assisted by a surgical robot. A total of 70 patients were randomized into two groups: the surgical robot group (robot group, n = 35) and the traditional handheld locator group (control group, n = 35). Postoperative computed tomography (CT) was employed to assess the positions and lengths of the tunnels, as well as the tunnel angle and the graft bending angle. Additionally, the posterior wall distance was measured by determining the minimum vertical distance from the long axis of the tunnel to the posterior wall region. There were no significant differences between the two groups in the mean position or length of the femoral and tibial tunnel (p > 0.05). However, the femoral tunnel angle was significantly larger in the robot group compared to the handheld locator group (p = 0.012). The graft bending angle was significantly less acute in the robot group than in the control group (p = 0.008). Additionally, the posterior wall distance was significantly greater in the robot group compared to the control group (p < 0.001). The results suggest that surgical robot-assisted ACL reconstruction enhances safety in the inclination of the tunnel and graft, helping to avoid potential biomechanical issues such as the wiper effect and the bungee effect, which may lead to tunnel widening and surgical failure.

3D reconstruction from endoscopy images: A survey

Three-dimensional reconstruction of images acquired through endoscopes is playing a vital role in an increasing number of medical applications. Endoscopes used in the clinic are commonly classified as monocular endoscopes and binocular endoscopes. We have reviewed the classification of methods for depth estimation according to the type of endoscope. Basically, depth estimation relies on feature matching of images and multi-view geometry theory. However, these traditional techniques have many problems in the endoscopic environment. With the increasing development of deep learning techniques, there is a growing number of works based on learning methods to address challenges such as inconsistent illumination and texture sparsity. We have reviewed over 170 papers published in the 10 years from 2013 to 2023. The commonly used public datasets and performance metrics are summarized. We also give a taxonomy of methods and analyze the advantages and drawbacks of algorithms. Summary tables and result atlas are listed to facilitate the comparison of qualitative and quantitative performance of different methods in each category. In addition, we summarize commonly used scene representation methods in endoscopy and speculate on the prospects of deep estimation research in medical applications. We also compare the robustness performance, processing time, and scene representation of the methods to facilitate doctors and researchers in selecting appropriate methods based on surgical applications.

Application progress of artificial intelligence and augmented reality in orthopaedic arthroscopy surgery

In today's rapidly developing technological era, the technological revolution triggered by the rapid iteration of artificial intelligence and augmented reality has provided brand-new digital intelligent empowerment for orthopaedic clinical operation. Although traditional arthroscopy has been widely promoted globally due to its advantages such as minimally invasive, safety and early functional exercise, it still has deficiencies in precision and personalization. The assistance of artificial intelligence and augmented reality enables precise positioning and navigation in arthroscopic surgery, as well as personalized operations based on patient conditions, which lifts the objective limitations of traditional sports medicine surgery. The integration of artificial intelligence and augmented reality with orthopaedic arthroscopy surgery is still in infancy, even though there are still some insufficient to be solved, but its prospect is bright.

Navigation in anterior cruciate ligament reconstruction: State of the art

Computer navigation (CN) for anterior cruciate ligament (ACL) surgery has been used mainly for two purposes: to enhance the accuracy of tunnel position and to evaluate the kinematics of the ACL reconstruction (ACLR) and the stability achieved by different surgical techniques. Many studies have shown that navigation may improve the accuracy of anatomical tunnel orientation and position during ACL reconstructive surgery compared with normal arthroscopic tunnel placement, especially regarding the femoral side. At the same time, it has become the gold-standard method for intraoperative knee kinematic assessment, as it permits a quantitative multidirectional knee joint laxity evaluation. CN in ACL surgery has been associated with diverse problems. First, in most optic systems additional skin incisions and drill holes in the femoral bone are required for fixation of a reference frame to the femur. Second, additional radiation exposure and extra medical cost to the patient for preoperative planning are usually needed. Third, CN, due to additional steps, has more opportunities for error during preoperative planning, intraoperative registration, and operation. Fourth, soft tissues, including the skin and subcutaneous tissues, are usually not considered during the preoperative planning, which can be a problem for kinematic and stability assessment. Many studies have concluded that ACLR using a CN system is more expensive than conventional surgery, it adds extra time to the surgery and it is not mitigated by better clinical outcomes. This, combined with costs and invasiveness, has limited the use of CN to research-related cases. Future technology should prioritize less invasive intra-operative surgical navigation.

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.

Feasibility and accuracy of orthopaedic surgical robot system for intraoperative navigation to locate bone tunnel in anterior cruciate ligament reconstruction

BACKGROUND

The combination of navigational system and robotics has the potential to accurately identify and drill bone tunnels in anterior cruciate ligament (ACL) reconstruction. This study explores the feasibility and accuracy of bone tunnel positioning using the TiRobot, an orthopaedic surgical robot.

METHODS

The experiment was divided into two groups. In group A, the bone tunnels were positioned using the TiRobot surgical robot (n = 8). In group B, handheld locators were used for positioning (n = 8).

RESULTS

TiRobot can be used for positioning the ACL bone tunnel. The accuracy of positioning the femoral tunnel in group A and B was 1.00 ± 0.20 and 3.10 ± 0.59 mm, respectively (t = -9.49, P < 0.001). As for tibial tunnel, the accuracy was 1.02 ± 0.20 and 2.64 ± 0.14 mm, respectively (t = -18.54, P < 0.001).

CONCLUSIONS

The bone tunnel drilling precision using TiRobot for ACL reconstruction surgery was more accurate than traditional surgical techniques.

Current and future of anterior cruciate ligament reconstruction techniques

In recent years, anterior cruciate ligament (ACL) reconstruction has generally yielded favorable outcomes. However, ACL reconstruction has not provided satisfactory results in terms of the rate of returning to sports and prevention of osteoarthritis (OA) progression. In this paper, we outline current techniques for ACL reconstruction such as graft materials, double-bundle or single-bundle reconstruction, femoral tunnel drilling, all-inside technique, graft fixation, preservation of remnant, anterolateral ligament reconstruction, ACL repair, revision surgery, treatment for ACL injury with OA and problems, and discuss expected future trends. To enable many more orthopedic surgeons to achieve excellent ACL reconstruction outcomes with less invasive surgery, further studies aimed at improving surgical techniques are warranted. Further development of biological augmentation and robotic surgery technologies for ACL reconstruction is also required.

Influence of femoral tunnel exit on the 3D graft bending angle in anterior cruciate ligament reconstruction

Purpose

To quantify the influence of the femoral tunnel exit (FTE) on the graft bending angle (GBA) and GBA-excursion throughout a full range of motion (ROM) in single-bundle anterior cruciate ligament (ACL) reconstruction.

Methods

Three-dimensional (3D) surface models of five healthy knees were generated from a weight-bearing CT obtained throughout a full ROM (0, 30, 60, 90, 120°) and femoral and tibial ACL insertions were computed. The FTE was simulated for 16 predefined positions, referenced to the Blumensaat's line, for each patient throughout a full ROM (0, 30, 60, 90, 120°) resulting in a total of 400 simulations. 3D GBA was calculated between the 3D directional vector of the ACL and the femoral tunnel, while the intra-articular ACL insertions remained unchanged. For each simulation the 3D GBA, GBA-excursion, tunnel length and posterior tunnel blow-out were analysed.

Results

Overall, mean GBA decreased with increasing knee flexion for each FTE (p < 0.001). A more distal location of the FTE along the Blumensaat's line resulted in an increase of GBA and GBA-excursion of 8.5 ± 0.6° and 17.6 ± 1.1° /cm respectively (p < 0.001), while a more anterior location resulted in a change of GBA and GBA-excursion of -2.3 ± 0.6° /cm (+ 0.6 ± 0.4°/ cm from 0–60° flexion) and 9.8 ± 1.1 /cm respectively (p < 0.001).

Mean tunnel length was 38.5 ± 5.2 mm (range 29.6–50.5). Posterior tunnel blow-out did not occur for any FTE.

Conclusion

Aiming for a more proximal and posterior FTE, with respect to Blumensaat’s line, reliably reduces GBA and GBA-excursion, while preserving adequate tunnel length. This might aid to reduce excessive graft stress at the femoral tunnel aperture, decrease femoral tunnel widening and promote graft-healing.

Level of Evidence

IV