The Use of Electronic Sensor Device to Augment Ligament Balancing Leads to a Lower Rate of Arthrofibrosis After Total Knee Arthroplasty

Precision soft tissue balancing: grid-assisted pie-crusting in total knee arthroplasty

Introduction

The varus and valgus knee deformities result from imbalance in tension between medial and lateral soft tissue compartments. These conditions need to be addressed during total knee arthroplasty (TKA). However, there is no consensus on optimal soft-tissue release techniques for correcting varus and valgus deformities during TKA. We assessed the efficacy of a novel grid-based pie-crusting technique on soft-tissue release.

Methods

Cadaver knees were dissected, leaving only the femur and tibia connected by an isolated MCL or the femur and fibula connected by an isolated LCL. Bone cuts were made as performed during primary TKA. Mechanical testing was performed using an MTS machine. A 3D-printed 12-hole grid was placed directly over the MCL and LCL. Using an 18-gauge needle, horizontal in-out perforations were made 3 mm apart. Deformation and stiffness of the ligaments were collected after every 2 perforations. Means were calculated, and regression analyses were performed.

Results

A total of 7 MCL and 6 LCL knees were included in our analysis. The mean medial femorotibial (MFT) space increased from 6.018 ± 1.4 mm-7.078 ± 1.414 mm (R2 = 0.937) following 12 perforations. The mean MCL stiffness decreased from 32.15 N/mm-26.57 N/mm (R2 = 0.965). For the LCL group, the mean gap between the femur and fibula increased from 4.287 mm-4.550 mm following 8 perforations. The mean LCL stiffness decreased from 29.955 N/mm-25.851 N/mm. LCL stiffness displayed a strong inverse relationship with the number of holes performed (R2 = 0.988).

Discussion

Our results suggest that using this novel grid for pie-crusting of the MCL and LCL allows for gradual lengthening of the ligaments without sacrificing their structural integrity. Our proposed technique may serve as a valuable piece in the soft-tissue release toolkit for orthopaedic surgeons performing TKA in varus and valgus deformed knees.

Improved Clinical Outcomes With Dynamic, Force-Controlled, Gap-Balancing in Posterior-Stabilized Total Knee Arthroplasty

BACKGROUND

Optimal soft-tissue management in total knee arthroplasty (TKA) may reduce symptomatic instability. We hypothesized that TKA outcomes using a computer-assisted dynamic ligament balancer that acquires medial and lateral gap sizes throughout the motion arc would show improved Knee Society Scores (KSS) compared to TKAs done with a traditional tensioner at 0 and 90°. We also sought to quantify the degree to which the planned femoral rotation chosen to optimize medio-lateral balance throughout the arc of motion deviated from the femoral rotation needed to achieve a rectangular flexion gap at 90° alone.

METHODS

Baseline demographics, clinical outcomes, KSSs, and femoral rotations were compared in 100 consecutive, computer-assisted TKAs done with the balancer (balancer group) to the immediately prior 100 consecutive computer-assisted TKAs done without the balancer (control group). Minimum follow-up was 13 months and all patients had osteoarthritis. Mean knee motion did not differ preoperatively (110.1 ± 13.6° balancer, 110.4 ± 12.5° control, P = .44) or postoperatively (119.1 ± 10.3° balancer, 118.8 ± 10.9° control, P = .42). Tourniquet times did not differ (93.1 ± 13.0 minutes balancer, 90.7 ± 13.0 minutes control, P = .13). Postoperative length of stay differed (40.2 ± 20.9 hours balancer, 49.0 ± 18.3 hours control, P = .0009). There were 14 readmissions (7 balancer, 7 control), 11 adverse events (4 balancer, 7 control), and 3 manipulations (1 balancer, 2 control). The cohorts were compared using Student's t-tests, Shapiro-Wilk normalities, Wilcoxon rank-sums, and multivariable logistic regression analyses.

RESULTS

Postoperative KSS improvements were higher in the balancer group (P < .0001). In multivariable regression analyses, the balancer group experienced 7 ± 2 point improvement in KSS Knee scores (P < .0001) and 4 ± 2 point improvement in KSS Function scores (P = .040) compared to the control group.

CONCLUSIONS

The statistically and clinically significant improvements in postoperative KSS demonstrated in the balancer cohort are likely driven by improved stability throughout the motion arc. Further study is warranted to evaluate replicability by non-design surgeons.

Exploring the Performance of an Artificial Intelligence-Based Load Sensor for Total Knee Replacements

Using tibial sensors in total knee replacements (TKRs) can enhance patient outcomes and reduce early revision surgeries, benefitting hospitals, the National Health Services (NHS), stakeholders, biomedical companies, surgeons, and patients. Having a sensor that is accurate, precise (over the whole surface), and includes a wide range of loads is important to the success of joint force tracking. This research aims to investigate the accuracy of a novel intraoperative load sensor for use in TKRs. This research used a self-developed load sensor and artificial intelligence (AI). The sensor is compatible with Zimmer's Persona Knee System and adaptable to other knee systems. Accuracy and precision were assessed, comparing medial/lateral compartments inside/outside the sensing area and below/within the training load range. Five points were tested on both sides (medial and lateral), inside and outside of the sensing region, and with a range of loads. The average accuracy of the sensor was 83.41% and 84.63% for the load and location predictions, respectively. The highest accuracy, 99.20%, was recorded from inside the sensing area within the training load values, suggesting that expanding the training load range could enhance overall accuracy. The main outcomes were that (1) the load and location predictions were similar in accuracy and precision (p > 0.05) in both compartments, (2) the accuracy and precision of both predictions inside versus outside of the triangular sensing area were comparable (p > 0.05), and (3) there was a significant difference in the accuracy of load and location predictions (p < 0.05) when the load applied was below the training loading range. The intraoperative load sensor demonstrated good accuracy and precision over the whole surface and over a wide range of load values. Minor improvements to the software could greatly improve the results of the sensor. Having a reliable and robust sensor could greatly improve advancements in all joint surgeries.

An electronic force sensor accurately detects increased but not decreased soft tissue tension in total knee arthroplasty

BACKGROUND

Postoperative knee instability is a leading cause of revision total knee arthroplasty (TKA). This study used a commercially available insert-shaped electronic force sensor to measure joint loads and facilitate ligament balance adjustment, and assessed the ability of this sensor to detect increased or decreased soft tissue tension during primary TKA.

METHODS

Changes in medial and lateral tibiofemoral joint loads during knee flexion were evaluated with sensor thicknesses ranging from 10 to 16 mm using six varus osteoarthritis cadaver knees with intact medial collateral ligaments (MCLs), and the measurements were repeated after MCL resection. Correlations between joint loads and maximum knee extension angle were also evaluated. To validate the efficacy of the sensor, the values were compared with those obtained using a conventional tension device.

RESULTS

For MCL-intact knees in extension, the medial joint load increased with sensor thickness. The maximum knee extension angle decreased with sensor thickness (ρ = -0.4), resulting in extension restriction up to -20°. Knee flexion contracture was below 5° when the total tibiofemoral joint load was below a cut-off of 42 lb. After the MCL was resected, medial joint loads remained unchanged at low values, even with increased sensor thickness. In contrast, the tension device clearly detected an increased gap as the degree of tension decreased.

CONCLUSIONS

The electronic sensor identified increased joint loads associated with increased ligament tension, and could predict knee flexion contracture during TKA. However, unlike the tension device, it did not accurately detect excessively decreased ligament tension.

Medial Varus Proximal Tibial Resection is Superior to Pie-Crusting of the Medial Collateral Ligament During Primary Total Knee Arthroplasty

BACKGROUND

Medial varus proximal tibial (MPT) resection or soft tissue releases (STR) of the medial collateral ligament (MCL) in form of pie-crusting can be performed to achieve a balanced knee in a varus deformity. Studies comparing the two modalities have not been addressed within the literature. Therefore, the aims of this study were to assess: 1) compartmental changes between the two methods; and 2) changes in patient-reported outcome measurements (PROMs).

METHODS

Using our institution's total joint arthroplasty registry, patients who underwent primary total knee arthroplasty from January 1, 2017 to December 31, 2019 were identified. The MPT resection and STR patients were 1:1 matched with baseline parameters yielding 196 patients. Outcomes of interest included: changes in compartmental pressures at 10, 45, and 90° degrees and change to the Short-Form 12 (SF-12), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and Forgotten Joint Scores (FJS) at the two-year follow-up period. A P-value less than 0.05 was used as our threshold for statistical difference.

RESULTS

The MPT resection led to significant reductions in compartmental pressures at 10° [43 vs 19 pounds (lbs.), P<0.0001), 45° (43 vs 27 lbs., P<0.0001), and 90° degrees (27 vs. 16 lbs., P<0.0001) compared to STR. MPT resection also had significantly improved SF-12 (47 vs. 38, P<0.0001), WOMAC (9 vs. 21, P<0.0001), and FJS (79 vs. 68, P=0.005).

CONCLUSION

Bone modification was superior to pie-crusting of the MCL in achieving consistent pressure balancing and improved outcomes. The investigation can guide surgeons on the preferred method to achieve a well-balanced knee.

Verasense sensor-assisted total knee arthroplasty showed no difference in range of motion, reoperation rate or functional outcomes when compared to manually balanced total knee arthroplasty: a systematic review

PURPOSE

The aim of this systematic review was to investigate the clinical and functional knee outcomes after Verasense sensor-assisted total knee arthroplasty (VA TKA), and to compare these outcomes, where possible, with those from manually balanced total knee arthroplasty (MB TKA).

METHODS

A systematic literature search following PRISMA guidelines was conducted on PubMed, Embase, Medline and Scopus from the beginning of January 2012 until the end of June 2022, to identify potentially relevant articles for this review. Selection was based on the following inclusion criteria: full text English- or German-language clinical studies, published in peer-reviewed journals, which assessed clinical and functional outcomes following VA TKA. Not original research, preprints, abstract-only papers, protocols, reviews, expert opinion papers, book chapters, surgical technique papers, and studies pertaining only to unicondylar knee arthroplasty (UKA) or patellofemoral arthroplasty (PFA) were excluded. Several scores (Knee Society Score [KSS], Oxford Knee Score [OKS], Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC], Knee injury and Osteoarthritis Outcome Score-4 subscales [KOOS4] and Physical Function-Computerised Adaptive Testing [PF-CAT]), alongside postoperative measurements of range of motion [ROM], reoperation rates and the rate of manipulation under anaesthesia [MUA]) were used to evaluate clinical and functional outcomes. The quality of included papers, except randomised control trials (RCTs), was evaluated using the Methodological Index for Non-Randomised Studies (MINORS). For the assessment of included RCTs, the Jadad Scale was used.

RESULTS

The literature search identified 243 articles. After removing duplicates, 184 papers were included in the initial screening process. Fourteen of them met all the inclusion criteria following the selection process. Mean MINORS for non-comparative studies value was 11.5 (11-12), and for comparative studies 18.2 (13-21). Mean Jadad Scale score was 3.6 (2-5). Outcomes from a total number of 3633 patients were evaluated (mean age at surgery 68.5 years [32-88 years]). In terms of clinical outcomes, the overwhelming majority of studies observed an improvement after VA TKA, but no statistically significant difference in ROM and reoperation rate when compared to MB TKA. On the other hand, lower rates of MUA have been described in the VA TKA group. An increase in postoperative clinical and functional scores values, when compared to the preoperative ones, has been reported in both groups, although no statistically significant difference between them has been observed.

CONCLUSION

The use of Verasense pressure sensors in TKA leads to no significant improvement in ROM, reoperation rate or functional outcomes, when compared to the standard manually balancing technique. However, lower rates of MUA have been described in the VA TKA group. These findings highlight the importance of tools being able to measure ligament stresses or joint pressure for achieving an optimally balanced knee.

LEVEL OF EVIDENCE

III.

Sensor Use in Cruciate-Retaining Total Knee Arthroplasty Compared with Posterior-Stabilized Total Knee Arthroplasty: Load Balancing and Posterior Femoral Rollback

The purpose was to investigate the proportion of severe load imbalance after appropriate conventional gap balancing and analyze the intraoperative kinematics after load balancing in cruciate-retaining (CR) and posterior-stabilized (PS) total knee arthroplasties (TKAs). In total, 45 sensor-assisted CR and 45 PS TKAs using NexGen prosthesis were prospectively evaluated. After appropriate conventional gap balancing, the loads at 10, 45, and 90 degrees of knee flexion were evaluated with a wireless load sensor placed in trial implants. The proportion of severe load imbalance (medial load-lateral load >75 lbs) was investigated. After load balancing, location of the femorotibial contact point was investigated at each flexion angle to analyze femorotibial kinematics. The proportion of the severe load imbalance was significantly higher in CR TKAs at the 10 degrees knee flexion (37.8 vs. 15.6%, p = 0.031). This proportion was higher in CR TKAs than in PS TKAs at the 45 and 90 degrees knee flexion angles, but without statistical significance (31.1 vs. 15.6%, p = 0.134 and 33.3 vs. 15.6%, p = 0.085, respectively). After load balancing, consistent posterior femoral rollback occurred in medial and lateral compartments during 90 degrees flexion in CR TKAs (p < 0.001), but not in PS TKAs. Medial pivot kinematics was not observed in both TKA designs. The sensor was more beneficial in CR TKAs for achieving appropriate load balancing and consistent posterior femoral rollback compared with PS TKAs. Further studies are required to identify target load distribution to restore ideal knee kinematics after TKA. This study shows level of evidence II.

No Benefit to Sensor-guided Balancing Compared With Freehand Balancing in TKA: A Randomized Controlled Trial

BACKGROUND

Soft tissue balancing in TKA has traditionally relied on surgeons' subjective tactile feedback. Although sensor-guided balancing devices have been proposed to provide more objective feedback, it is unclear whether their use improves patient outcomes.

QUESTIONS/PURPOSES

We conducted a randomized controlled trial (RCT) comparing freehand balancing with the use of a sensor-guided balancing device and evaluated (1) knee ROM, (2) patient-reported outcome measures (PROMs) (SF-12, WOMAC, and Knee Society Functional Scores [KSFS]), and (3) various surgical and hospital parameters (such as operative time, length of stay [LOS], and surgical complications) at a minimum of 2 years of follow-up.

METHODS

A total of 152 patients scheduled for primary TKA were recruited and provided informed consent to participate in this this study. Of these, 22 patients were excluded preoperatively, intraoperatively, or postoperatively due to patient request, surgery cancellation, anatomical exclusion criteria determined during surgery, technical issues with the sensor device, or loss to follow-up. After the minimum 2-year follow-up was accounted for, there were 63 sensor-guided and 67 freehand patients, for a total of 130 patients undergoing primary TKA for osteoarthritis. The procedures were performed by one of three fellowship-trained arthroplasty surgeons (RPS, HJC, JAG) and were randomized to either soft tissue balancing via a freehand technique or with a sensor-guided balancing device at one institution from December 2017 to December 2018. There was no difference in the mean age (72 ± 8 years versus 70 ± 9 years, mean difference 2; p = 0.11), BMI (30 ± 6 kg/m 2 versus 29 ± 6 kg/m 2 , mean difference 1; p = 0.83), gender (79% women versus 70% women; p = 0.22), and American Society of Anesthesiology score (2 ± 1 versus 2 ± 1, mean difference 0; p = 0.92) between the sensor-guided and freehand groups, respectively. For both groups, soft tissue balancing was performed after all bony cuts were completed and trial components inserted, with the primary difference in technique being the ability to quantify the intercompartmental balance using the trial tibial insert embedded with a wireless sensor in the sensor-guided cohort. Implant manufacturers were not standardized. Primary outcomes were knee ROM and PROMs at 3 months, 1 year, and 2 years. Secondary outcomes included pain level evaluated by the VAS, opioid consumption, inpatient physical therapy performance, LOS, discharge disposition, surgical complications, and reoperations.

RESULTS

There was no difference in the mean knee ROM at 3 months, 1 year, and 2 years postoperatively between the sensor-guided cohort (113° ± 11°, 119° ± 13°, and 116° ± 12°, respectively) and the freehand cohort (116° ± 13° [p = 0.36], 117° ± 13° [p = 0.41], and 117° ± 12° [p = 0.87], respectively). There was no difference in SF-12 physical, SF-12 mental, WOMAC pain, WOMAC stiffness, WOMAC function, and KSFS scores between the cohorts at 3 months, 1 year, and 2 years postoperatively. The mean operative time in the sensor-guided cohort was longer than that in the freehand cohort (107 ± 0.02 versus 84 ± 0.04 minutes, mean difference = 23 minutes; p = 0.008), but there were no differences in LOS, physical therapy performance, VAS pain scores, opioid consumption, discharge disposition, surgical complications, or percentages of patients in each group who underwent reoperation.

CONCLUSION

This RCT demonstrated that at 2 years postoperatively, the use of a sensor-balancing device for soft tissue balancing in TKA did not confer any additional benefit in terms of knee ROM, PROMs, and clinical outcomes. Given the significantly increased operative time and costs associated with the use of a sensor-balancing device, we recommend against its routine use in clinical practice by experienced surgeons.

LEVEL OF EVIDENCE

Level I, therapeutic study.

Variability between the trial and final implant measurements during the sensor-guided total knee arthroplasty

PURPOSE

Compartmental load-sensing technology has been used in the attempt to achieve optimal soft tissue balance during total knee arthroplasty (TKA). This study was conducted to investigate the validity of such use of intraoperative sensing technology.

METHODS

Ninety-three knees scheduled to undergo total knee arthroplasty for knee osteoarthritis with a tibial sensor were prospectively enrolled. Measurements were divided into three groups according to the three different time points of intraoperative load testing: group Trial (with the trial components), group Final (with the definitive cemented implants and an open joint capsule), and group Closed (with the definitive cemented implants and a closed joint capsule). Load measurements and component rotational alignments were documented at 10°, 30°, 45°, 90°, and 120° of flexion for all three groups, and compared. One year postoperatively, the joint line obliquity angle was obtained radiographically in the valgus and varus stress views at 10° and 30° flexion to evaluate the clinical instability. The Knee Society, Hospital for Special Surgery, and Western Ontario McMaster Universities Osteoarthritis Index scores were used to determine functional outcomes. The correlations of the above outcomes with intraoperative load were evaluated.

RESULTS

There were significant differences in medial and lateral loads at all flexion angles (except at a 120° lateral load) between group Trial and group Final (p < 0.05). Tibial trays were internally rotated to a significantly higher degree in group Final than in group Trial (p = 0.010). The lateral compartmental load significantly decreased after patellar inversion (p = 0.037). There were no correlations of intraoperative load with clinical instability and functional outcomes.

CONCLUSION

Significant variability was observed between the trial and final implant measurements and intraoperative sensing data were not correlated with instability or functional outcomes over a 1-year period. Therefore, intraoperative sensor technology provides limited feedback and clinical efficacy in the adjustment of the soft tissue balance during TKA.

LEVEL OF EVIDENCE

Level II.

Intraoperative pressure sensors improve soft-tissue balance but not clinical outcomes in total knee arthroplasty: a multicentre randomized controlled trial

AIMS

Intraoperative pressure sensors allow surgeons to quantify soft-tissue balance during total knee arthroplasty (TKA). The aim of this study was to determine whether using sensors to achieve soft-tissue balance was more effective than manual balancing in improving outcomes in TKA.

METHODS

A multicentre randomized trial compared the outcomes of sensor balancing (SB) with manual balancing (MB) in 250 patients (285 TKAs). The primary outcome measure was the mean difference in the four Knee injury and Osteoarthritis Outcome Score subscales (ΔKOOS₄) in the two groups, comparing the preoperative and two-year scores. Secondary outcomes included intraoperative balance data, additional patient-reported outcome measures (PROMs), and functional measures.

RESULTS

There was no significant difference in ΔKOOS₄ between the two groups at two years (mean difference 0.4 points (95% confidence interval (CI) -4.6 to 5.4); p = 0.869), and multiple regression found that SB was not associated with a significant ΔKOOS₄ (0.2-point increase (95% CI -5.1 to 4.6); p = 0.924). There were no significant differences between groups in other PROMs. Six-minute walking distance was significantly increased in the SB group (mean difference 29 metres; p = 0.015). Four-times as many TKAs were unbalanced in the MB group (36.8% MB vs 9.4% SB; p < 0.001). Irrespective of group assignment, no differences were found in any PROM when increasing ICPD thresholds defined balance.

CONCLUSION

Despite improved quantitative soft-tissue balance, the use of sensors intraoperatively did not differentially improve the clinical or functional outcomes two years after TKA. These results question whether a more precisely balanced TKA that is guided by sensor data, and often achieved by more balancing interventions, will ultimately have a significant effect on clinical outcomes. Cite this article: Bone Joint J 2022;104-B(5):604-612.

Sensor-guided gap balance versus manual gap balance in primary total knee arthroplasty: a meta-analysis

Background

Despite Vast improvements in technology and surgical technique in total knee arthroplasty (TKA), approximately 15–25% TKAs, have suboptimal subjective clinical outcomes. Our study sought to evaluate if sensor-guided balancing improves postoperative clinical outcomes compared to a conventional gap balancing technique.

Methods

We searched Web of Science, Embase, PubMed, Cochrane Controlled Trials Register, Cochrane Library, Highwire, CBM, CNKI, VIP, and Wanfang database in March 2022 to identify studies involving sensor-guided balancing versus conventional gap balancing technique in TKA. Finally, we identified 2147 knees assessed in nine studies.

Results

Compared with manual gap balancing, Sensor-guided gap balancing resulted in less rate of Manipulation under anesthesia (MUA) (P = 0.02), however more rate of intraoperative additional procedures (P = 0.0003). There were no significant differences in terms of KSS (P = 0.21), KSS Function score (P = 0.36), OKS (P = 0.61), KOOS (P = 0.78), operative time (P = 0.17), Mechanical axis (P = 0.69) and rate of reoperation between two groups.

Conclusion

Compared with conventional manual gap balancing techniques, sensors have more balancing procedures being performed. However, it did result in a reduction in the rate of MUA. More extensive, high-quality RCTs are required to verify our findings further.

The MAKO robotic-arm knee arthroplasty system

INTRODUCTION

The Mako robotic arm knee arthroplasty system was initially indicated in unicompartmental knee arthroplasty followed by bicompartmental and total knee arthroplasty techniques. The system utilizes three elements: (1) Pre-op 3D CT based planning and image based intra-op navigation. (2) Pre-resection implant modifications with integrated alignment, implant position and gap data, and (3) A semi-constrained robotic arm assisted execution of bone resection with "haptic" boundaries, and cemented implants.

MATERIALS AND METHODS

This paper evaluates variable pre-op implant placement, and anatomic reference positioning; data entry with incorporation of alignment, implant congruency through range of motion, and gaps; bone resection with "haptic" boundaries, and final implant evaluation with kinetic sensors.

RESULTS

The Mako system allowed for improved implant placement utilizing CT guidance, bone resection accuracy, flexibility for functional implant placement with gap balancing. When combined with kinetic sensors, there was improved rotation and soft tissue balance.

CONCLUSION

The MAKO robotic system can assist the surgeon with anatomic landmarks, provides the flexibility for independent gap balance through implant and alignment refinement, and three-dimensional soft tissue balancing data to achieve functional stability. Registry data has shown improved outcome survivorship irrespective of the surgeons' volumes and learning curves.

Current role of intraoperative sensing technology in total knee arthroplasty

PURPOSE

Sensors have been introduced within the last 10 years to quantify soft tissue balancing during total knee arthroplasty (TKA) and to give the surgeon objective data. These devices are fairly new and their impact on patient outcome remains uncertain. The aim of this systematic review was to summarize all the relevant surgical and clinical results of sensors for TKA.

METHODS

A PRISMA systematic review was conducted using five databases (PubMed, EMBASE, MEDLINE, GOOGLE SCHOLAR, and the COCHRANE LIBRARY) to identify all available literature that described the surgical and clinical results of sensors for TKA between 2000 and 2021. The main investigated outcome criteria were intraoperative data, postoperative functional and clinical outcome, knee range of motion, complications and revision rates.

RESULTS

Twenty-seven articles were finally included. The maximum reported follow-up was 26 months. A balanced knee with sensor corresponded to a mediolateral difference inferior to 15 lb and a stable posterior drawer test. The standard assessment of knee balance was a poor predictor of the true soft tissue balance when compared to sensor data. At least 60% of TKA needed an additional rebalancing procedure with the sensor, after conventional gap balancing. Achieving a quantitatively balanced knee resulted in a significantly higher patient satisfaction score. But the prospective comparative studies found no demonstrable improvement in clinical outcome, range of motion or complication rate at one year postoperatively for patients undergoing TKA using sensor-guided balancing compared with routine techniques.

CONCLUSION

Even though the use of the intraoperative sensing technology was not related to an improvement in clinical outcome, the current studies showed that using sensors facilitates the reproduction of natural joint stability, and improves the rate of achieving a balanced knee. Sensor use in complex cases could be particularly valuable, but their use in standard practice remains to be defined.

Sensor-Assisted Total Knee Arthroplasty: A Narrative Review

Wireless intraoperative load sensors have been used to improve the quality of soft-tissue balancing during total knee arthroplasty(TKA). Recent studies using the sensors have demonstrated reductions in gap imbalance, as well as early improvement of patient-reported clinical outcomes and low rates of arthrofibrosis. However, well-designed prospective studies are needed to determine whether the application of the sensor technology for TKA will have clinical benefits and improve the survival of prosthesis. Knowledge of the load-sensing technology (advantages and disadvantages, potential pitfalls, and future prediction) is crucial to apply this new TKA technique successfully. Herein, we conduct a narrative review of previous studies on this technique.

How to Quantitatively Balance a Total Knee? A Surgical Algorithm to Assure Balance and Control Alignment

To achieve a balanced total knee, various surgical corrections can be performed, while intra-operative sensors and surgical navigation provide quantitative, patient-specific feedback. To understand the impact of these corrections, this paper evaluates the quantitative impact of both soft tissue releases and bone recuts on knee balance and overall limb alignment. This was achieved by statistically analyzing the alignment and load readings before and after each surgical correction performed on 479 consecutive primary total knees. An average of three surgical corrections were required following the initial bone cuts to achieve a well aligned, balanced total knee. Various surgical corrections, such as an arcuate release or increasing the tibial polyethylene insert thickness, significantly affected the maximum terminal extension. The coronal alignment was significantly impacted by pie-crusting the MCL, adding varus to the tibia, or releasing the arcuate ligament or popliteus tendon. Each surgical correction also had a specific impact on the intra-articular loads in flexion and/or extension. A surgical algorithm is presented that helps achieve a well-balanced knee while maintaining the sagittal and coronal alignment within the desired boundaries. This analysis additionally indicated the significant effect that soft tissue adjustments can have on the limb alignment in both anatomical planes.

Achieving a Balanced Knee in Robotic TKA

Total knee arthroplasty (TKA) surgery with manual instruments provides a quantitatively balanced knee in approximately 50% of cases. This study examined the effect of combining robotics technology with real-time intra-operative sensor feedback on the number of quantitatively balanced cases in a consecutive series of 200 robotic-assisted primary TKAs. The robotics platform was used to plan the implant component position using correctable poses in extension and a manual, centrally pivoting the balancer in flexion, prior to committing to the femoral cuts. During the initial trialing, the quantitative state of balance was assessed using an instrumented tibial tray that measured the intra-articular loads in the medial and lateral compartments. These sensor readings informed a number of surgical corrections, including bone recuts, soft-tissue corrections, and cement adjustments. During initial trialing, a quantitatively balanced knee was achieved in only 65% of cases. After performing the relevant soft-tissue corrections, bone recuts, and cement adjustments, 87% of cases ended balanced through the range of motion. Meanwhile, this resulted in a wide range of coronal alignment conditions, ranging from 6° valgus to 9° varus. It is therefore concluded that gaps derived from robotics navigation are not indicative for a quantitatively balanced knee, which was only consistently achieved when combining the robotics platform with real-time feedback from intra-operative load sensors.

New Technologies in Knee Arthroplasty: Current Concepts

Total knee arthroplasty (TKA) is an effective treatment for severe osteoarthritis. Despite good survival rates, up to 20% of TKA patients remain dissatisfied. Recently, promising new technologies have been developed in knee arthroplasty, and could improve the functional outcomes. The aim of this paper was to present some new technologies in TKA, their current concepts, their advantages, and limitations. The patient-specific instrumentations can allow an improvement of implant positioning and limb alignment, but no difference is found for functional outcomes. The customized implants are conceived to reproduce the native knee anatomy and to reproduce its biomechanics. The sensors have to aim to give objective data on ligaments balancing during TKA. Few studies are published on the results at mid-term of these two devices currently. The accelerometers are smart tools developed to improve the TKA alignment. Their benefits remain yet controversial. The robotic-assisted systems allow an accurate and reproducible bone preparation due to a robotic interface, with a 3D surgical planning, based on preoperative 3D imaging or not. This promising system, nevertheless, has some limits. The new technologies in TKA are very attractive and have constantly evolved. Nevertheless, some limitations persist and could be improved by artificial intelligence and predictive modeling.

Comparison of the contact stress between the sensor and real polyethylene insert in total knee arthroplasty: a finite element analysis

Background

In implants, sensors are made of an acrylic-like plastic, while polyethylene (PE) inserts are made of ultra-high-molecular-weight PE (UHMPE). Thus, the stress distribution on the sensor may be different from that on the PE insert due to variations in material properties. The present study sought to analyze and compare the stress distribution profile between the sensor and PE insert after total knee arthroplasty (TKA).

Methods

Finite element analysis was performed to estimate contact stress between the sensor and PE insert after TKA. The materials of the femoral component, sensor, and PE insert were determined as cobalt-chrome-molybdenum, acryl plastic, and UHMWPE, respectively. The stiffness levels of medial and lateral soft tissue were set at 28.8 N/mm and 18.8 N/mm at knee flexion and 24.7 N/mm and 17.2 N/mm at knee extension, respectively. The average and peak contact stress levels on the sensor and PE were analyzed in knee flexion and extension.

Results

The average amount of contact stress in the medial compartment was 43.4 MPa on the sensor and 31.9 MPa on the PE insert at knee extension. Meanwhile, the medial compartmental peak contact stress levels were 55.2 MPa on the sensor and 48.8 MPa on the PE insert at knee extension. The other values of average and peak contact stress among the two materials were less than 5 MPa.

Conclusions

There was a difference in the contact stress distribution between the sensor and PE insert due to material properties, especially in the medial compartment at knee extension. The development of a sensor composed of a material with properties similar to a PE insert would be useful in the prediction of femorotibial contact stress in real implants.

Load imbalances existed as determined by a sensor after conventional gap balancing with a tensiometer in total knee arthroplasty

PURPOSE

To evaluate intercompartmental load intraoperatively with a sensor after conventional gap balancing with a tensiometer during total knee arthroplasty (TKA).

METHODS

Fifty sensor-assisted TKA procedures were performed prospectively between August and September 2018 with a cruciate-retaining prosthesis. After applying a modified measured resection technique, conventional balancing between resected surfaces was achieved. The equal and rectangular flexion-extension gaps were confirmed using a tensiometer at 90° and 5°-7° (due to posterior tibial slope) of knee flexion. Then, the load distribution was evaluated intraoperatively with a sensor placed on trial implants in the positions of knee flexion (90° flexion) and extension (10° flexion).

RESULTS

The proportion of coronal load imbalance (medial load - lateral load ≥  ± 15 lb) was 56% in extension and 32% in flexion (p = 0.023). The proportion of sagittal load imbalance (extension load - flexion load ≥  ± 15 lb) was 36% in the medial compartment and 4% in the lateral compartment (p < 0.001). An additional procedure for load balancing was performed in 74% of knees.

CONCLUSIONS

Coronal and sagittal load imbalances existed as determined by the sensor even after the achievement of appropriate conventional gap balance. The additional rebalancing procedure was performed for balanced loads in 74% of the knees after conventional balancing. The use of an intraoperative load sensor offers the advantage of direct evaluation of the load on TKA implants.

LEVEL OF EVIDENCE

IV.

Does the sequential addition of accelerometer-based navigation and sensor-guided ligament balancing improve outcomes in TKA?

AIMS

A significant percentage of patients remain dissatisfied after total knee arthroplasty (TKA). The aim of this study was to determine whether the sequential addition of accelerometer-based navigation for femoral component preparation and sensor-guided ligament balancing improved complication rates, radiological alignment, or patient-reported outcomes (PROMs) compared with a historical control group using conventional instrumentation.

METHODS

This retrospective cohort study included 371 TKAs performed by a single surgeon sequentially. A historical control group, with the use of intramedullary guides for distal femoral resection and surgeon-guided ligament balancing, was compared with a group using accelerometer-based navigation for distal femoral resection and surgeon-guided balancing (group 1), and one using navigated femoral resection and sensor-guided balancing (group 2). Primary outcome measures were Patient-Reported Outcomes Measurement Information System (PROMIS) and Knee injury and Osteoarthritis Outcome (KOOS) scores measured preoperatively and at six weeks and 12 months postoperatively. The position of the components and the mechanical axis of the limb were measured postoperatively. The postoperative range of motion (ROM), haematocrit change, and complications were also recorded.

RESULTS

There were 194 patients in the control group, 103 in group 1, and 74 in group 2. There were no significant differences in baseline demographics between the groups. Patients in group 2 had significantly higher baseline mental health subscores than control and group 1 patients (53.2 vs 50.2 vs 50.2, p = 0.041). There were no significant differences in any PROMs at six weeks or 12 months postoperatively (p > 0.05). There was no difference in the rate of manipulation under anaesthesia (MUA), complication rates, postoperative ROM, or blood loss. There were fewer mechanical axis outliers in groups 1 and 2 (25.2%, 14.9% respectively) versus control (28.4%), but this was not statistically significant (p = 0.10).

CONCLUSION

The sequential addition of navigation of the distal femoral cut and sensor-guided ligament balancing did not improve short-term PROMs, radiological outcomes, or complication rates compared with conventional techniques. The costs of these added technologies may not be justified. Cite this article: Bone Joint J 2020;102-B(6 Supple A):24-30.

Interobserver agreement of sensor-derived compartmental pressure measurements in computer-assisted total knee arthroplasty

BACKGROUND

Sensor-guided compartmental pressure measurements are becoming increasingly utilized in total knee arthroplasty (TKA) to objectively confirm intraoperative knee balance. We aimed to determine agreement of pressure measurements between two observers when performing sensor-guided TKA with the use of computer-assisted surgery (CAS).

METHODS

One-hundred and eighteen consecutive patients undergoing 130 TKAs were analysed. Femoral and tibial trial implants were inserted prior to performing knee balancing. We compared the reliability of sensor pressure compartmental measurements between two observers at 10, 45 and 90° of flexion using intraclass correlation coefficient (ICC) estimates and the 95% limits of agreement (Bland-Altman plots).

RESULTS

The interobserver agreement between sensor pressure measurements was excellent at 10° of knee flexion, with ICCs of 0.93 and 0.91 in the medial and lateral compartments, respectively (P < 0.001). At 45°, medial and lateral compartment ICCs were 0.91 and 0.76, respectively (P < 0.001). At 90°, the ICC was 0.88 medially and 0.76 laterally (P < 0.001). Although the agreement decreased at higher knee flexion, it remained good to excellent. The 95% limits of agreement at each angle were all within 20 psi and 11 psi for the medial and lateral compartments, respectively.

CONCLUSIONS

There was excellent interobserver agreement of sensor pressure measurements at 10° of knee flexion with computer-assisted TKA. Interobserver agreement decreased slightly as knee flexion angles increased, particularly in the lateral compartment. It is likely that interobserver agreement and hence reliability of sensor pressure measurements in TKA has some dependence on accurate angular positioning of the knee.

Acquired Idiopathic Stiffness After Total Knee Arthroplasty: A Systematic Review and Meta-Analysis

BACKGROUND

Stiffness is a common reason for suboptimal clinical outcomes after primary total knee arthroplasty (pTKA). There is a lack of consensus regarding its definition, which is often conflated with its histopathologic subcategory-i.e., arthrofibrosis. There is value in refining the definition of acquired idiopathic stiffness in an effort to select for patients with arthrofibrosis. We conducted a systematic review and meta-analysis to establish a consensus definition of acquired idiopathic stiffness, determine its prevalence after pTKA, and identify potential risk factors for its development.

METHODS

MEDLINE, Embase, Cochrane Controlled Register of Trials (CENTRAL), and Scopus databases were searched from 2002 to 2017. Studies that included patients with stiffness after pTKA were screened with strict inclusion and exclusion criteria to isolate the subset of patients with acquired idiopathic stiffness unrelated to known extrinsic or surgical causes. Three authors independently assessed study eligibility and risk of bias and collected data. Outcomes of interest were then analyzed according to age, sex, and body mass index (BMI).

RESULTS

In the 35 included studies (48,873 pTKAs), the mean patient age was 66 years. In 63% of the studies, stiffness was defined as a range of motion of <90° or a flexion contracture of >5° at 6 to 12 weeks postoperatively. The prevalence of acquired idiopathic stiffness after pTKA was 4%, and this did not differ according to age (4%, I = 95%, among patients <65 years old and 5%, I = 96%, among those ≥65 years old; p = 0.238). The prevalence of acquired idiopathic stiffness was significantly lower in males (1%, I = 85%) than females (3%, I = 95%) (p < 0.0001) as well as in patients with a BMI of <30 kg/m (2%, I = 94%) compared with those with a BMI of ≥30 kg/m (5%, I = 97%) (p = 0.027).

CONCLUSIONS

Contemporary literature supports the following definition for acquired idiopathic stiffness: a range of motion of <90° persisting for >12 weeks after pTKA in patients in the absence of complicating factors including preexisting stiffness. The mean prevalence of acquired idiopathic stiffness after pTKA was 4%; females and obese patients were at increased risk.

LEVEL OF EVIDENCE

Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Are Patients More Satisfied With a Balanced Total Knee Arthroplasty?

BACKGROUND

Patient-reported outcome measures are increasingly recognized as an important tool in quantifying the clinical success of arthroplasty surgery. The aim of this study is to measure post-operative joint awareness and satisfaction in patients with and without a quantitatively balanced knee following primary total knee arthroplasty (TKA).

METHODS

In this multi-center study, a total of 318 eligible patients were assigned to one of the 2 patient groups: sensor-guided TKA or surgeon-guided TKA. In the sensor-guided group, quantitative balancing was performed according to intercompartmental tibiofemoral load measurements measured by an instrumented tibial trial component. In contrast, for the surgeon-guided group, the knees were balanced according to the surgeons' standard manual techniques while blinding the surgeon to the sensor measurements. Patients were blinded to their allocation and filled out the validated Forgotten Joint Score and 2011 Knee Society Satisfaction questionnaires at 6 weeks and 6 months. For the purposes of this study, the subjects were pooled and stratified by their state of soft tissue balance, based on the mediolateral load differential through the range of motion.

RESULTS

In the surgeon-guided group, approximately 50% of the cases yielded a quantitatively balanced knee. Significantly more balanced knees were observed in the sensor-guided group (84.0%). More importantly, for both outcome measures, the balanced group of patients reported significantly better outcomes scores.

CONCLUSION

This demonstrates that using sensor feedback during knee arthroplasty surgery results in a more reproducible procedure, resulting in a higher percentage of balanced patients who in turn demonstrate superior clinical outcomes compared to unbalanced patients.

An intraoperative load sensor did not improve the early postoperative results of posterior-stabilized TKA for osteoarthritis with varus deformities

PURPOSE

In the present study, the early results of sensor-assisted versus manually balanced posterior-stabilized total knee arthroplasty (TKA) for osteoarthritis with varus deformities were prospectively compared.

METHODS

Fifty patients undergoing sensor-assisted TKA (group S) and 50 patients receiving manually balanced TKA (group M) were prospectively compared. The groups did not differ in terms of demographics, preoperative clinical status, or severity of deformity. The knee and function scores (KS and FS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and range of motion (ROM) were evaluated clinically. The mechanical axes and positions of components were assessed radiographically. In sensor-assisted TKA, the medial and lateral compartment loads were compared based on the patellar positions of inversion and eversion.

RESULTS

There was no between-group difference in the postoperative KS or FS (n.s., respectively). The average postoperative WOMAC score was 17.0 in group S and 18.0 in group M (n.s.). The ROM was 131.2° in group S and 130.8° in group M (n.s.). Neither the postoperative alignment of the mechanical axis nor the component positioning differed between the groups (n.s.). In sensor-assisted TKA, the difference between the medial and lateral compartment loads was less than 15 lbs (6.8 kg) in each knee. The lateral compartment load increased after patellar eversion (p < 0.001).

CONCLUSION

There are concerns about the cost-benefit ratio of the intraoperative load sensor, despite its advantage of more precisely assessing ligament balance without patellar eversion, which resulted in a smaller lateral gap. A long-term follow-up study with a large cohort is required.

LEVEL OF EVIDENCE

II.

Smart implants in orthopedic surgery, improving patient outcomes: a review

Smart implants are implantable devices that provide not only therapeutic benefits but also have diagnostic capabilities. The integration of smart implants into daily clinical practice has the potential for massive cost savings to the health care system. Applications for smart orthopedic implants have been identified for knee arthroplasty, hip arthroplasty, spine fusion, fracture fixation and others. To date, smart orthopedic implants have been used to measure physical parameters from inside the body, including pressure, force, strain, displacement, proximity and temperature. The measurement of physical stimuli is achieved through integration of application-specific technology with the implant. Data from smart implants have led to refinements in implant design, surgical technique and strategies for postoperative care and rehabilitation. In spite of decades of research, with very few exceptions, smart implants have not yet become a part of daily clinical practice. This is largely because integration of current sensor technology necessitates significant modification to the implants. While the technology underlying smart implants has matured significantly over the last several decades, there are still significant technical challenges that need to be overcome before smart implants become part of mainstream health care. Sensors for next-generation smart implants will be small, simple, robust and inexpensive and will necessitate little to no modification to existing implant designs. With rapidly advancing technology, the widespread implementation of smart implants is near. New sensor technology that minimizes modifications to existing implants is the key to enabling smart implants into daily clinical practice.