A novel flexible capacitive load sensor for use in a mobile unicompartmental knee replacement bearing: An in vitro proof of concept study

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.

“Smart Knee Implants: An Overview of Current Technologies and Future Possibilities”

Background

This article focuses on clinical implementation of smart knee implants for total knee replacement and the future development of smart implant technology. With the number of total knee replacements undertaken growing worldwide, smart implants incorporating embedded sensor technology offer opportunity to improve post-operative recovery, reducing implant failure rates, and increasing overall patient satisfaction.

Methods

A literature review on smart implants, historical prototypes, current clinically available smart implants, and the future potential for conventional implant instrumentation with embedded sensors and electronics was undertaken.

Results

The overview of current and future technology describes use cases for various diagnostic and therapeutic treatment solutions.

Conclusion

Smart knee implants are at an early development stage, with the first generation of smart implants being available to patients and with more novel technologies under development.

Can mobile-bearing unicompartmental knee arthroplasty achieve natural gap-balancing? An observational study with a novel pressure sensor

Background

Mobile-bearing unicompartmental knee arthroplasty (MB-UKA) is an effective treatment for anteromedial knee osteoarthritis. Meticulous intraoperative soft tissue balancing remains challenging yet consequential for a successful operation. Currently, surgeons rely mostly on their experience during soft tissue balancing, yielding unreproducible results. The purpose of this study was to quantified measure the soft tissue tension of medial compartment and determine if an optimal "target" tension values with the natural state exists.

Methods

This was an observational study of 24 consecutive patients. All 30 UKAs were performed by a single surgeon. The piezoresistive sensor was custom designed to fit in the medial compartment gap. Contact pressures were measured at 5 angular positions of the knee intraoperatively: 0°, 20°, 45°, 90°, and 110° of flexion. The change in pressure from extension (20° position) and flexion (110° position) was also calculated (E-FPD). Data on age, sex, body mass index, operative side, and bearing size were collected. Outcome measures were measured at baseline and at the 6-month postoperative follow-up; Oxford Knee Score, visual analog scale score, and range of motion were compared to evaluate clinical outcomes.

Results

There was a significant improvement in patients in all measured outcomes at 6 months from baseline (P < 0.05). The E-FPD of 14.9 N (8.9, 24.6) was indicative of appropriate soft tissue balancing throughout the functional range of knee motion. Of 30 knees, 22 were 3-mm bearing and 8 were 4- or 5-mm bearing. The pressure data of the 3-mm bearing group was larger than that of the non-3-mm bearing group for each knee flexion degree, but the difference was not statistically significant (P > 0.05).

Conclusions

Objective data from sensor output may assist surgeons in decreasing loading variability during MB-UKA. The data suggested that MB-UKA could not accurately restore soft tissue tension to the natural state, which was related to the inability of MB-UKA surgical instruments to fine adjust the bone cut and soft tissue release.

Study registration

Chinese Clinical Trial Registry (http://www.chictr.org.cn): ChiCTR1900024146.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-022-03255-6.

Micromachined Tactile Sensor Array for RTSA

This work presents a polymer-based tactile capacitive sensor capable of measuring joint reaction forces of reverse total shoulder arthroplasty (RTSA). The capacitive sensor contains a polydimethylsiloxane (PDMS) dielectric layer with an array of electrodes. The sensor was designed in such a way that four components of glenohumeral contact forces can be quantified to help ensure proper soft tissue tensioning during the procedure. Fabricated using soft lithography, the sensor has a loading time of approximately 400 ms when a 14.13 kPa load is applied and has a sensitivity of 1.24 × 10-3 pF/kPa at a load of 1649 kPa. A replica RTSA prothesis was 3D printed, and the sensor was mounted inside the humeral cap. Four static right shoulder positions were tested, and the results provided an intuitive graphical description of the pressure distribution across four quadrants of the glenohumeral joint contact surface. It may help clinicians choose a right implant size and offset that best fit a patient's anatomy and reduce postoperative biomechanical complications such as dislocation and stress fracture of the scapula.

Computer assisted orthopaedic surgery: Past, present and future

Computer technology is ubiquitous and relied upon in virtually all professional activities including neurosurgery, which is why it is surprising that it is not the case for orthopaedic surgery with fewer than 5% of surgeons using available computer technology in their procedures. In this review, we explore the evolution and background of Computer Assisted Orthopaedic Surgery (CAOS), delving into the basic principles behind the technology and the changes in the discussion on the subject throughout the years and the impact these discussions had on the field. We found evidence that industry had an important role in driving the discussion at least in knee arthroplasty-a leading field of CAOS-with the ratio between patents and publications increased from approximately 1:10 in 2004 to almost 1:3 in 2014. The adoption of CAOS is largely restrained by economics and ergonomics with sceptics challenging the accuracy and precision of navigation during the early years of CAOS moving to patient functional improvements and long term survivorship. Nevertheless, the future of CAOS remains positive with the prospect of new technologies such as improvements in image-guided surgery, enhanced navigation systems, robotics and artificial intelligence.