Biomechanical and Finite-Element Analysis of Femoral Pin-Site Fractures Following Navigation-Assisted Total Knee Arthroplasty

Analysis of the learning curve for unilateral biportal endoscopic technique using CUSUM method on fresh frozen cadavers

PURPOSE

This study aims to determine the learning curve for lumbar discectomy and nerve root decompression using the unilateral biportal endoscopic (UBE) technique on fresh frozen cadavers through linear regression and cumulative sum (CUSUM) analyses.

METHODS

The analysis was conducted on three spine surgeons without UBE experience. They performed lumbar discectomy using the unilateral endoscopic technique on fresh frozen cadavers. Each physician performed operations on 40 lumbar spine segments, recording the time it took each physician to complete a segment of lumbar discectomy by UBE. The learning curve was assessed by linear regression and CUSUM analysis using SPSS 27.0 software and GraphPad Prism 8.0 software.

RESULTS

According to the CUSUM analysis of the learning curve, the number of segments required to complete the learning phase for the three surgeons was 20, 16, and 20, respectively. With the increased number of operated segments, the operation time for each lumbar vertebral segment gradually decreased and stabilized.

CONCLUSIONS

In our study, spine surgeons without experience in UBE require 20 segments of surgery to overcome the UBE learning curve. Additionally, fresh frozen cadavers can effectively simulate real surgeries. Whenever possible, we should reasonably use fresh frozen cadavers for early UBE training of doctors, thereby better protecting the health and safety of patients.

Biomechanical analysis of different techniques for residual bone defect from tibial plateau bone cyst in total knee arthroplasty

Background

In patients with tibial plateau bone cysts undergoing total knee arthroplasty (TKA), bone defects commonly occur following tibial plateau resection. Current strategies for addressing these defects include bone grafting, bone cement filling, and the cement-screw technique. However, there remains no consensus on the optimal approach to achieve the best surgical outcomes. This study aims to evaluate the most effective repair method for residual bone defects following tibial plateau bone cyst repair during TKA from a biomechanical perspective.

Methods

The treatment options for tibial plateau bone defects were classified into four categories: no treatment, cancellous bone filling, bone cement filling, and the cement-screw technique. Finite-element analysis (FEA) was employed to evaluate stress distribution and displacement across the models for each treatment group. In addition, static compression mechanical tests were used to assess the displacement of the models within each group.

Results

FEA results indicate that when employing the cement-screw technique to repair tibial plateau bone defects, the maximum stress on the prosthesis and the cement below the prosthesis is minimized, while the maximum stress on the cancellous bone is maximized. And the displacement of each component is minimized. Biomechanical tests results further demonstrate that the displacement of the model is minimized when utilizing the cement-screw technique for tibial plateau bone defects.

Conclusion

Using cement-screw technique in treating residual tibial bone defects due to bone cysts in TKA offers optimal biomechanical advantages.

Robotic-assisted patellofemoral arthroplasty provides excellent implant survivorship and high patient satisfaction at mid-term follow-up

PURPOSE

Robotic adoption in knee surgery has yielded several benefits, but its application in patellofemoral arthroplasty (PFA) remains barely reported. The purpose of this study was to determine implant survival, patient satisfaction, and functional outcomes after robotic-assisted PFA at an intermediate follow-up.

METHODS

This prospective analysis targeted 18 knees of 16 consecutive patients who underwent robot-aided PFA with three-year minimum follow-up (range, 3 to 6 years). Each patient was evaluated collecting pre-operative and post-operative medical record data, including range of motion, radiographic images, and multiple scores, such as VAS, APKS, and OKS.

RESULTS

At surgery, the mean age was 55.4 years ± 14.4 (range, 32 to 78 years), and the mean BMI was 26.8 kg/m² ±5.2 (range, 20 to 36). Etiologies of patellofemoral osteoarthritis included idiopathic degeneration (28%), post-traumatic (33%), and dysplasia (39%). Pre-implantation scores were VAS 7.9 ± 1.4, AKPS 34.6 ± 23.3, and OKS 17.3 ± 10.3. One implant was revised with primary total knee arthroplasty for osteoarthritis progression. Clinical and radiographic follow-up showed no signs of loosening or infection. The maximum flexion reached an average of 131.1°±10.5° (range, 110° to 145°), accompanied by significantly improved score results (P-value < 0.01): VAS 1.1 ± 1.4, AKPS 90.2 ± 8.6, and OKS 46.3 ± 1.8.

CONCLUSIONS

At 3 years after robotic assisted patellofemoral arthroplasty, excellent implant survival and patient satisfaction rates can be expected along with significantly improved functional and pain control outcomes. Although the limitations imposed by the restricted cohort, these findings indicate that robotic assistance in PFA is both safe and effective at intermediate follow-up.

Complications and Learning Curve Associated with an Imageless Burr-Based (CORI) Robotic-Assisted Total Knee Arthroplasty System: Results from First 500 Cases

Background

The use of robotic-assisted total knee arthroplasty (RA-TKA) is gaining traction. There is evidence to suggest that RA-TKA can help to optimize the precision and accuracy of implant positioning and that there may be protective effects on surrounding bony and soft tissues. Yet, there are important differences between the various RA-TKA systems currently on the market. One such newly introduced RA-TKA system uses imageless technology and performs bony cuts with the use of a burr-based device. The learning curve and complications unique to this system have yet to be assessed.

Methods

We evaluated 500 consecutive RA-TKA cases using a newly developed burr-based and imageless system which were done by a single surgeon between the months of October 2021 and February 2023. Operative times were recorded and compared to the previous 150 conventional TKA cases allowing for the learning curve to be calculated using the CUSUM method. Intraoperative and postoperative complications were categorically profiled.

Results

The learning curve of this RA-TKA system was found to be 6 cases. Intraoperative complications included unintended bony over resection (n = 3), soft tissue injury (n = 2), and robotic system hardware (n = 2) or software (n = 2) malfunction. Postoperative complications consisted of superficial pin site infection (n = 1) and periprosthetic fracture near the pin sites (n = 1). There were no identified cases of prosthetic joint infection, instability events, or wound complications.

Conclusions

The learning curve and the complication profile of a newly introduced imageless and burr-based RA-TKA system were described. This information serves to guide surgeons in adopting this technology and can counsel them regarding the potential pitfalls and challenges associated with its integration into practice. The work sheds light on the complexity and learning curve of the recently released imageless burr-based RA-TKA system. This important information is intended to help surgeons accept this cutting-edge technology by providing advice on any errors and difficulties that can occur when integrating it into clinical practice. This information can help surgeons navigate the complexities of integrating this new burr-based robotic technology into knee replacement procedures, enabling them to make well-informed decisions and receive guidance.

Risk of internal fixation treatment in intertrochanteric fracture based on different lateral femoral wall thickness: finite element analysis

OBJECTIVE

The thickness of the lateral femoral wall, which is an important indicator for evaluating the stability and integrity of intertrochanteric fractures, has been widely studied in recent years. However, as a typical representative of internal fixation treatment, there are few reports on the biomechanical comparison between PFNA and DHS + CS. This study focused primarily on the biomechanical effects of different lateral femoral wall thicknesses on two types of internal fixation through finite element analysis.

METHODS

We randomly recruited a healthy adult and collected his femoral CT data to establish a model of femoral intertrochanteric fracture with different lateral femoral wall thicknesses. Following PFNA and DHS + CS fixation, femoral models were simulated, and variations in stress and displacement of the internal fixation and femoral head were recorded under the same physiological load.

RESULTS

First, finite element mechanical analysis revealed that the stress and displacement of the internal fixation and femoral head were lower in the femoral model after PFNA fixation than in the DHS + CS model. Second, as the outer wall thickness decreased, the stress and deformation endured by both types of internal fixation gradually increased.

CONCLUSIONS

Finite element analysis determined that PFNA exhibits significantly better biomechanical stability than DHS + CS when subjected to varying lateral femoral wall thicknesses. Moreover, lateral femoral wall thickness substantially affects the stability of the two internal fixation biomechanical environments. When the thickness of the lateral femoral wall is too small, we do not recommend using extramedullary fixation because there is a significant risk of internal fixation fracture.

Model Properties and Clinical Application in the Finite Element Analysis of Knee Joint: A Review

The knee is the most complex joint in the human body, including bony structures like the femur, tibia, fibula, and patella, and soft tissues like menisci, ligaments, muscles, and tendons. Complex anatomical structures of the knee joint make it difficult to conduct precise biomechanical research and explore the mechanism of movement and injury. The finite element model (FEM), as an important engineering analysis technique, has been widely used in many fields of bioengineering research. The FEM has advantages in the biomechanical analysis of objects with complex structures. Researchers can use this technology to construct a human knee joint model and perform biomechanical analysis on it. At the same time, finite element analysis can effectively evaluate variables such as stress, strain, displacement, and rotation, helping to predict injury mechanisms and optimize surgical techniques, which make up for the shortcomings of traditional biomechanics experimental research. However, few papers introduce what material properties should be selected for each anatomic structure of knee FEM to meet different research purposes. Based on previous finite element studies of the knee joint, this paper summarizes various modeling strategies and applications, serving as a reference for constructing knee joint models and research design.