Improved sizing with image-based robotic-assisted system compared to image-free and conventional techniques in medial unicompartmental knee arthroplasty

Enhancing robotic precision in medial UKA: Image-based robot-assisted system had higher accuracy in implant positioning than imageless robot-assisted system across 292 knees

PURPOSE

The objective of this study was to compare the degree of accuracy in implant positioning and limb alignment offered by two robot-assisted (RA) systems: an image-based robot-assisted (IBRA) versus an imageless robot-assisted (ILRA) system for the treatment of medial knee osteoarthritis with unicompartmental knee arthroplasty (UKA).

METHODS

This retrospective radiographic study included medial UKAs performed between 2011 and 2023. Radiographic measurements taken preoperatively and at 1-year postoperative control visit focusing on hip-knee-ankle angle (HKA), posterior tibial slope (PTS), tibial component coronal alignment relative to Cartier's angle and restoration of proper joint line (JL) height were analyzed. Outliers for postoperative measurements were defined as follows: HKA <175° or >180°, PTS <2° or >8°, >3° or <-3° alterations in Cartier's angle and ±2 mm changes in the height of the joint line.

RESULTS

The final sample consisted of 292 medial UKAs: 95 (32.5%) with an IBRA system and 197 (67.5%) with an ILRA system. Implant positioning and limb alignment were more accurate in the group of patients treated with IBRA, HKA (77.9% vs. 67.5%, p = 0.07), PTS (93.7% vs. 82.7%, p = 0.01), restoration of tibial varus relative to Cartier's angle (87.4% vs. 65%, p < 0.001) and restoration of JL height (81.1% vs. 69.5%, p = 0.04).

CONCLUSION

Medial UKA surgery using an IBRA system was associated with a higher degree of accuracy in implant positioning and postoperative limb alignment as compared to an ILRA system. This is a valuable contribution to help communicate the advantages of using this surgical technique and improve its reproducibility.

LEVEL OF EVIDENCE

Level III, Retrospective cohort study.

Valgus stress knee radiographs accurately anticipate the bone resection in medial unicompartmental knee arthroplasty: Protocol validation using an image-based robotic system

PURPOSE

The objective of this study was to describe a planning method for medial unicompartmental knee arthroplasty (UKA) implantation using preoperative stress radiographs to measure the thickness of tibial and femoral bone resections and to validate this method with data from an image-based robotic surgery system. Having such method for preoperative planning would be of interest for surgeons performing UKA in order to anticipate optimal bone resection on both tibia and femoral sides.

METHODS

A new planning method for medial UKA based on valgus stress knee radiographs validated it with an image-based robotic surgery system (Restoris MCK, MAKO®, Stryker Corporation) was proposed. This retrospective study involved radiographic measurements of 76 patients who underwent image-based robotic medial UKA between April 2022 and February 2023. Preoperative anteroposterior stress radiographs of the knee were used to simulate UKA implantation. The UKA technique was based on Cartier's angle and aimed at restoring the joint line. The total dimension measured was 14 mm (8 mm for minimal tibial component and polyethylene insert + 4 mm for femoral component + 2 mm for safety laxity). Bone resections were measured in the preoperative valgus stress radiographs and then against the intraoperative bone resection data provided by the robotic system. Inter- and intra-observer reliability was assessed using 25 measurements.

RESULTS

The mean planned tibial resection measured in the radiographs was 4.3 ± 0.4 [2.9-5.8], while the mean robotic resection was 4.2 ± 0.5 [2.7-5.8] (mean difference = 0.15 mm, 95% confidence interval [CI] [-0.27 to 0.57]). There was a strong correlation between these two values (Pearson's rank R = 0.79, p < 0.001). Intra- and inter-observer reliability were also very strong (Pearson's rank R = 0.91, p < 0.001, and Pearson's rank R = 0.82, p < 0.001, respectively). The mean planned femoral bone resection measured in the radiographs was 2.7 ± 0.7 mm [1-4.5], while the mean robotic resection was 2.5 ± 0.9 [1-5] (mean difference = 0.21 mm, 95% CI [-0.66 to 1.08]). There was a strong correlation between these two values (Pearson's rank R = 0.82, p < 0.001). Intra- and inter-observer reliability were also strong (Pearson's rank R = 0.88, p < 0.001, and Pearson's rank R = 0.84, p < 0.001, respectively).

CONCLUSION

This study describes and validates with robotic information a simple and reproducible preoperative planning method to determine femoral and tibial bone resection for medial UKA implantation using antero-posterior valgus stress knee radiographs, leaving a medial safety laxity of 2 mm. It represents a very valuable contribution to the understanding of UKA principles, which can serve to extend its indications and increase reproducibility of the surgical technique.

LEVEL OF EVIDENCE

III. Retrospective cohort study.

A morphometric medial compartment-specific unicompartmental knee system: 5 years follow up results from a pilot center

BACKGROUND

Unicompartmental Knee Arthroplasty (UKA) is a valuable solution for the treatment of medial osteoarthritis of the knee. New implants feature designs for the elective substitution of a specific compartment. Aim of this study was to assess the survivorship and functional outcomes at minimum 4 years of the first 60 implanted patients in a pilot center of a new medial UKA as the evolution of a well performing long lasting fixed bearing implant.

METHODS

Between June 2017 and the end of 2018, 60 medial UKA were implanted in 58 patients. All patients were available for the last follow up and were analyzed prospectively. 37 were females and 21 were males with a mean age of 67 years (SD 10,71) and a mean of BMI 27.16 (SD 3.94) for the male population and of 26.73 (SD 4.05) for the female population.

RESULTS

At final follow up the mean Oxford Knee Score (OKS) was 44,02 (SD 3,1) and the mean Forgotten Joint Score (FJS) 78,6 (SD 7,9). The Knee Society Score (KSS) score was 95,2 for the "knee" score and 89.8 for the "function" score. No patients were revised. Kaplan-Meyer survival estimate showed a 100% survivorship at final follow up. No progressive radiolucent lines were found and no direct or indirect signs of polyethylene wear were registered on the final radiographs.

CONCLUSIONS

This new implant demonstrated promising clinical results with an excellent survival rate at short to midterm follow- up. Further follow up is needed to confirm this trend at longer term.

Robotic trials in arthroplasty surgery

Total hip and knee arthroplasty (THA, TKA) are largely successful procedures; however, both have variable outcomes, resulting in some patients being dissatisfied with the outcome. Surgeons are turning to technologies such as robotic-assisted surgery in an attempt to improve outcomes. Robust studies are needed to find out if these innovations are really benefitting patients. The Robotic Arthroplasty Clinical and Cost Effectiveness Randomised Controlled Trials (RACER) trials are multicentre, patient-blinded randomized controlled trials. The patients have primary osteoarthritis of the hip or knee. The operation is Mako-assisted THA or TKA and the control groups have operations using conventional instruments. The primary clinical outcome is the Forgotten Joint Score at 12 months, and there is a built-in analysis of cost-effectiveness. Secondary outcomes include early pain, the alignment of the components, and medium- to long-term outcomes. This annotation outlines the need to assess these technologies and discusses the design and challenges when conducting such trials, including surgical workflows, isolating the effect of the operation, blinding, and assessing the learning curve. Finally, the future of robotic surgery is discussed, including the need to contemporaneously introduce and evaluate such technologies.

Restoration of preoperative tibial alignment improves functional results after medial unicompartmental knee arthroplasty

PURPOSE

The alignment obtained after unicompartmental knee arthroplasty (UKA) influences the risk of failure. Kinematic alignment after UKA based on Cartier angle restauration is likely to improve clinical outcomes compared with mechanical alignment. The purpose of this study is to analyze the influence of implant alignment and native knee restoration after UKA using the conventional techniques on clinical outcomes.

METHODS

This retrospective study included 144 medial UKA patients from 2015 to 2020. Radiographic measurements were performed pre- and postoperatively. Outliers were defined as follows: Δ Cartier > 3° (difference between the preoperative and postoperative Cartier angle); Δ MPTA (Medial Proximal Tibial angle) and postoperative TCA (Tibial Coronal component Angle) > 3° (difference between the positioning of the tibial implant and the preoperative proximal tibial deformity). The Knee injury and Osteoarthritis Outcome Score (KOOS), the International Knee Society (IKS) Function and Knee score, the Forgotten Joint Score (FJS), and the Subjective Knee Value (SKV) were evaluated. A Student t test or a non-parametric Wilcoxon test was used for non-normal data to compare pre- and postoperative values for functional scores and angular measurements. The correlation of postoperative angles with functional outcomes was assessed by the Spearman's rank correlation coefficient.

RESULTS

During the inclusion period, 214 patients underwent medial UKA, 71 patients were excluded, and 19 were lost to follow-up leaving 124 patients with 144 knees (20 bilateral UKA) included for analysis with a mean follow-up of 54.7 months ± 22.1 (24-95). The Δ Cartier was significantly correlated with IKS function (R2 = 0.06, p < 0.001) and FJS (R2 = 0.05, p < 0.01) scores. The Δ preoperative MPTA-TCA was significantly correlated (p < 0.001) with KOOS (R2 = 0.38), IKS Knee (R2 = 0.17), IKS function (R2 = 0.34), SKV (R2 = 0.08), and FJS (R2 = 0.37) scores. In subgroup analysis, non-outliers (< 3°) for Δ preoperative MPTA-TCA had better KOOS score (Δ = 23.5, p < 0.001) and IKS Function (Δ = 17.7, p < 0.001) compared to outliers (> 3°) patients.

CONCLUSION

Functional results after medial UKA can be influenced by implant alignment in the coronal plane with slight clinical improvement when positioning the tibial implant close to the preoperative tibial deformity, rather than by restoring the Cartier angle. This series suggests the interest of a more personalized alignment strategy, but these results will have to be confirmed by other controlled studies.

LEVEL OF EVIDENCE

IV, retrospective case series.

Patellofemoral Arthroplasty Is an Efficient Strategy for Isolated Patellofemoral Osteoarthritis with or without Robotic-Assisted System

There is relative paucity in the literature concerning outcomes after robotic-assisted Patellofemoral Arthroplasty (PFA). The aims were (1) to evaluate outcomes in patients undergoing PFA with inlay or onlay components, with or without robotic arm assistance and (2) to identify risk factors of poor outcomes after PFA. This retrospective study included 77 PFA for isolated patellofemoral joint osteoarthritis, assigned to three groups (18 conventional technique, 17 image-free robotic-assisted system and 42 image-based robotic-assisted system). The demographic data were comparable between the three groups. The clinical outcomes assessed were: Visual Analogue Scale, Knee Society Score, Kujala score and satisfaction rate. The radiological measures were: Caton Deschamps index, patellar tilt and frontal alignment of the trochlea. Functional outcomes, satisfaction rate and residual pain were comparable between the three groups. Patellar tilt improvement was superior when a robotic device was used (either image-based or image-free) compared to the conventional technique. There were three revisions (3.9%) at the last follow-up related to femorotibial osteoarthritis progression. Multivariate analysis found no significant risk factors for poor outcomes, with respect to the surgical technique or implant design. Functional outcomes and revisions rate after PFA were comparable between the surgical techniques and implants. Robotic-assisted systems were associated with a superior improvement of the patellar tilt compared to the conventional technique.

Robotic-arm assisted unicompartmental knee arthroplasty system has a learning curve of 11 cases and increased operating time

PURPOSE

UKA has higher revision risk, particularly for lower volume surgeons. While robotic-arm assisted systems allow for increased accuracy, introduction of new systems has been associated with learning curves. The aim of this study was to determine the learning curve of a UKA robotic-arm assisted system. The hypothesis was that this may affect operative times, patient outcomes, limb alignment, and component placement.

METHODS

Between 2017 and 2021, five surgeons performed 152 consecutive robotic-arm assisted primary medial UKA, and measurements of interest were recorded. Patient outcomes were measured with Oxford Knee Score, EuroQol-5D, and Forgotten Joint Score at 6 weeks, 1 year, and 2 years. Surgeons were grouped into 'low' and 'high' usage groups based on total UKA (manual and robotic) performed per year.

RESULTS

A learning curve of 11 cases was found with operative time (p < 0.01), femoral rotation (p = 0.02), and insert sizing (p = 0.03), which highlighted areas that require care during the learning phase. Despite decreased 6-week EQ-5D-5L VAS in the proficiency group (77 cf. 85, p < 0.01), no difference was found with implant survival (98.2%) between phases (p = 0.15), or between 'high' and 'low' usage surgeons (p = 0.23) at 36 months. This suggested that the learning curve did not lead to early adverse effects in this patient cohort.

CONCLUSION

Introduction of a UKA robotic-arm assisted system showed learning curves for operative times and insert sizing but not for implant survival at early follow-up. The short learning curve regardless of UKA usage indicated that robotic-arm assisted UKA may be particularly useful for low-usage surgeons.

LEVEL OF EVIDENCE

Level III, Retrospective cohort study.

Better accuracy and implant survival in medial imageless robotic-assisted unicompartmental knee arthroplasty compared to conventional unicompartmental knee arthroplasty: two- to eleven-year follow-up of three hundred fifty-six consecutive knees

PURPOSE

Implant malpositioning, joint line (JL) lowering, and malalignment have been identified as risk factors for implant failure in unicompartmental knee arthroplasty (UKA). The aims of this study were to compare the accuracy of implant positioning in robotic-assisted UKA versus conventional UKA in a large cohort and examine the correlation with implant survival at mid-term follow-up.

METHODS

This retrospective study included 356 medial UKAs from 2011 to 2019. The radiological measurements performed were coronal positioning of tibial implant according to Cartier angle (Δ Cartier), posterior tibial slope (PTS), residual hip-knee-ankle (HKA), and JL restoration. Outliers were defined as follows: post-operative HKA < 175° or > 180°, Δ Cartier > 3° or <  - 3°, JL change ≥ 2 mm, and PTS < 2° or > 8°. The survival probability was reported at the last follow-up.

RESULTS

Out of the 356 knees included, 159 underwent conventional UKA (44.5%) and 197 (55.5%) robotic-assisted UKA. The mean follow-up was 61.3 months ± 24.0. Robotic UKA was associated with better accuracy compared to conventional UKA in relation to HKA (67% vs 56%, p = 0.023), JL restoration (70% vs 44%, p < 0.0001), PTS (83% vs 55%, p < 0.0001), and tibial varus restoration (65% vs 55%, p = 0.049). Implant survival in the robotic group was found to be superior at the last follow-up (96.4% versus 87.3% at 9 years, p = 0.004).

CONCLUSION

Robotic assistance in patients undergoing medial UKA was associated with better accuracy compared to conventional UKA with respect to tibial implant positioning, post-operative limb alignment, and JL restoration. This was translated in improved survival at mid-term follow-up favouring the robotic group.

How long does image based robotic total knee arthroplasty take during the learning phase? Analysis of the key steps from the first fifty cases

INTRODUCTION

Robotically assisted total knee arthroplasty (RA-TKA) is an emerging surgical tool. The purpose of this study was to analyze the length of time taken to perform the key steps of a RA-TKA for a surgeon and centre new to the MAKO robotic system.

METHOD

This was a prospective cohort study of the first 50 patients undergoing TKA using a robotic platform (Mako, Stryker, Kalamazoo, MI, USA) performed by a single surgeon. Each key surgical step was recorded. The first 50 patients were chronologically allocated into five groups of ten and compared.

RESULTS

Mean operation length was 59.4 ± 7.4 min with significant improvement after 30 cases. A significant effect on certain steps of the surgery also occurred over 50 cases: after 30 cases for pre-operative planning (3.8 min in group 1 versus 1.2 min in group 4, p < 0.005), ten cases for registration time (5.2 min in group 1 versus 3.8 in group 2, p = 0.039) and ten cases for tibial cutting time (1.6 min in group 1 versus 1.3 in group 2, p < 0.005). Nurse setup, femur cutting, and intraoperative planning did not demonstrate a significant improvement in time over 50 cases.

CONCLUSION

A significant decrease in total operating length occurred after the 30th case. Anatomical registration and tibial cutting time demonstrated the largest improvements. MAKO image-based robotically assisted TKA is not a time-intensive intervention for both the surgeon and scrub nursing staff, and significant improvements in total surgical time occurs early in the learning phase.

Image-based robot assisted bicompartmental knee arthroplasty versus total knee arthroplasty

OBJECTIVE

To evaluate the short-term clinical outcomes of image-based robot-assisted bicruciate retaining bicompartmental knee arthroplasty and compare it to robot-assisted total knee arthroplasty in the Indian population.

METHODS

Between December 2018 and November 2019, five patients (six knees) underwent robot-assisted bicompartmental knee arthroplasty (BCKA). These patients were demographically matched with five patients (six knees) who underwent robot-assisted total knee arthroplasty (TKA) during the same period. Clinical outcomes of these twelve knees were assessed in the form of knee society score (KSS) score, Oxford knee score (OKS), and forgotten joint score (FJS) after a minimum follow-up period of 25 months. The data between the two cohorts were compared and analyzed.

RESULTS

Scores obtained from both cohorts were subjected to statistical analysis. SPSS software was utilized and the Mann Whitney U-test was utilized to compare the two groups. There was no statistically significant difference found between the two groups in terms of functional outcome.

CONCLUSION

Image-based robot-assisted BCKA is a bone stock preserving and more physiological procedure which can be a promising alternative to patients presenting with isolated arthritis of only two compartments of the knee. Although long-term, larger trials are warranted to establish it as an alternative, our pilot study shows an equally favorable outcome as TKA, making it an exciting new avenue in the field of arthroplasty.

Robotic-arm assisted total knee arthroplasty has a learning curve of 16 cases and increased operative time of 12 min

BACKGROUND

Robotic-arm assisted systems are increasingly used for knee arthroplasty, however introduction of new systems can involve a learning curve. We aimed to define the learning curve in terms of operative time and component placement/sizing of a robotic system for total knee arthroplasty (TKA) in a team of experienced surgeons, and to investigate mid-term patient outcomes.

METHODS

A total of 101 consecutive patients underwent primary robotic-arm assisted TKA by three surgeons (mean 2 year follow-up). Operative times, component placement, implant sizing and reoperations were recorded. Cumulative Summation (CUSUM) was used to analyse learning curves. Patient outcomes were compared between learning and proficiency phases.

RESULTS

The learning curve was 16 cases, with a 12-min increase in operative time (P < 0.01). Once proficiency was achieved, the greatest time reductions were seen for navigation registration (P = 0.003) and bone preparation (P < 0.0001). A learning curve was found with polyethylene (PE) insert sizing (P = 0.01). No differences were found between learning and proficiency groups in terms of implant survival (100% and 97%, respectively, NS) or patient-reported outcome measures at 2 years (NS).

CONCLUSION

Introduction of a robotic-arm assisted system for TKA led to increased operative times for navigation registration and bone preparation, and a learning curve with PE insert sizing. No difference in patient outcomes between learning and proficiency groups at 2 years was found. These findings can inform surgeons' expectations when starting to use robotic-assisted systems.

Artificial intelligence in knee arthroplasty: current concept of the available clinical applications

Background

Artificial intelligence (AI) is defined as the study of algorithms that allow machines to reason and perform cognitive functions such as problem-solving, objects, images, word recognition, and decision-making. This study aimed to review the published articles and the comprehensive clinical relevance of AI-based tools used before, during, and after knee arthroplasty.

Methods

The search was conducted through PubMed, EMBASE, and MEDLINE databases from 2000 to 2021 using the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA).

Results

A total of 731 potential articles were reviewed, and 132 were included based on the inclusion criteria and exclusion criteria. Some steps of the knee arthroplasty procedure were assisted and improved by using AI-based tools. Before surgery, machine learning was used to aid surgeons in optimizing decision-making. During surgery, the robotic-assisted systems improved the accuracy of knee alignment, implant positioning, and ligamentous balance. After surgery, remote patient monitoring platforms helped to capture patients’ functional data.

Conclusion

In knee arthroplasty, the AI-based tools improve the decision-making process, surgical planning, accuracy, and repeatability of surgical procedures.

Predicting robotic-assisted total knee arthroplasty operating time

Aims

No predictive model has been published to forecast operating time for total knee arthroplasty (TKA). The aims of this study were to design and validate a predictive model to estimate operating time for robotic-assisted TKA based on demographic data, and evaluate the added predictive power of CT scan-based predictors and their impact on the accuracy of the predictive model.

Methods

A retrospective study was conducted on 1,061 TKAs performed from January 2016 to December 2019 with an image-based robotic-assisted system. Demographic data included age, sex, height, and weight. The femoral and tibial mechanical axis and the osteophyte volume were calculated from CT scans. These inputs were used to develop a predictive model aimed to predict operating time based on demographic data only, and demographic and 3D patient anatomy data.

Results

The key factors for predicting operating time were the surgeon and patient weight, followed by 12 anatomical parameters derived from CT scans. The predictive model based only on demographic data showed that 90% of predictions were within 15 minutes of actual operating time, with 73% within ten minutes. The predictive model including demographic data and CT scans showed that 94% of predictions were within 15 minutes of actual operating time and 88% within ten minutes.

Conclusion

The primary factors for predicting robotic-assisted TKA operating time were surgeon, patient weight, and osteophyte volume. This study demonstrates that incorporating 3D patient-specific data can improve operating time predictions models, which may lead to improved operating room planning and efficiency.

Cite this article: Bone Jt Open 2022;3(5):383–389.

Health economic value of CT scan based robotic assisted UKA: a systematic review of comparative studies

PURPOSE

The aim of this systematic review was to compare relevant health economic consequences of the CT-based robotic-arm-assisted system versus conventional Uni-compartmental Knee Arthroplasty (UKA).

METHODS

In November 2020, A PRISMA systematic review was conducted using four databases (Pubmed, Scopus, Cochrane and Google Scholar) to identify all comparative studies reporting health economic assessments, such as robotic system costs, consumable costs, surgical revision rate, operating time, length of stay, and inpatient care costs.

RESULTS

A total of nine comparative studies published between 2014 and 2020 were included in this systematic review. There was a moderate risk of bias as assessed using the ROBINS-I Tool. The CT-based robotic-arm-assisted system seemed to be associated with a lower risk of revision, decreased analgesia requirements during hospitalization, a shorter length of stay, and lower inpatient care costs compared to a conventional technique.

CONCLUSION

CT-based robotic-arm-assisted system for UKA appears to be an economically viable solution with a positive health economic impact as it tends to decrease revision rate compared to conventional UKA, improve post-operative rehabilitation and analgesia management. Post-operative inpatient care costs seem lower with the robotic-assisted system but depend on institutional case volume and differ among health systems. More studies are needed to confirm cost-effectiveness of CT-based robotic-arm-assisted system based on different health systems.

LEVEL OF EVIDENCE

Systematic review, Level IV.