Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic-assisted total knee arthroplasty.

PURPOSE: Predictive models help determine predictive factors necessary to improve functional outcomes after total knee arthroplasty (TKA). However, no study has assessed predictive models for functional outcomes after TKA based on the new concepts of personalised surgery and new technologies. This study aimed to develop and evaluate predictive modelling approaches to predict the achievement of minimal clinically important difference (MCID) in patient-reported outcome measures (PROMs) 1 year after TKA. METHODS: Four hundred thirty robotic-assisted TKAs were analysed in this retrospective study. The mean age was 67.9 ± 7.9 years; the mean body mass index (BMI) was 32.0 ± 6.8 kg/m2. The following PROMs were collected preoperatively and 1-year postoperatively: knee injury and osteoarthritis outcome score for joint replacement, Western Ontario and McMaster Universities osteoarthritis index (WOMAC) Function, WOMAC Pain. Demographic data, preoperative CT scan, implant size, implant position on the robotic system and characteristics of the joint replacement procedure were selected as predictive variables. Four machine learning algorithms were trained to predict the MCID status at 1-year post-TKA for each PROM survey. 'No MCID' was chosen as the target. Models were evaluated by class discrimination (F1-score) and area under the receiver operating characteristic curve (ROC-AUC). RESULTS: The best-performing model was ridge logistic regression for WOMAC Function (area under the curve [AUC] = 0.80, F1 = 0.48, sensitivity = 0.79, specificity = 0.62). Variables most strongly contributing to not achieving MCID status were preoperative PROMs, high BMI and femoral resection depth (posterior and distal), supporting functional positioning principles. Conversely, variables contributing to a positive outcome (achieving MCID) were medial/lateral alignment of the tibial component, whether the procedure was an outpatient surgery and whether the patient received managed Medicare insurance. CONCLUSION: The most predictive variables included preoperative PROMs, BMI and surgical planning. The surgical predictive variables were valgus femoral alignment and femoral rotation, reflecting the benefits of personalised surgery. Including surgical variables in predictive models for functional outcomes after TKA should guide clinical and surgical decision-making for every patient. LEVEL OF EVIDENCE: Level III.

Three-dimensional-based native alignment phenotype classification system: Description for use in planning for deformities during total knee arthroplasty.

Introduction: Total knee arthroplasty (TKA) is a complex surgical procedure that traditionally relies on two-dimensional radiographs for pre-operative planning. These radiographs may not capture the intricate details of individual knee anatomy, potentially limiting the precision of surgical interventions. With advancements in imaging technology, there is an opportunity to refine TKA outcomes. This study introduces the Native Alignment Phenotype classification system that is based on pre-operative 3-dimensional computed tomography (CT) scans, aiming to provide a more detailed understanding of knee deformities and their influence on characterizing knee osteoarthritis and planning for TKA procedures. Methods: There were 1406 pre-operative non-weight-bearing CT scans analyzed by a single surgeon experienced with robotically-assisted total knee arthroplasties. These scans were converted into three-dimensional models, focusing on the coronal and sagittal planes. Intraoperatively, the robotic system was used to capture native coronal and sagittal deformities for each patient. These values were captured with the patient's leg held in a non-stress, extension pose. A new classification system, 'The Native Alignment Phenotype', was developed to categorize the specific differences between individual knees. Results: There were four primary knee malalignments identified: varus deformity; valgus deformity; and two deformities in the sagittal plane. These malalignments were further categorized based on the degrees of deviation, creating groups with 5° coronal and sagittal ranges. A total of 77 phenotypic alignment patterns were found based on the analyzed cohort. In the coronal plane, varus HKA deformity between 6 and 10° was the most common, with 36.9% of the cases, followed by varus HKA alignment, which was between 0 and 5°, representing 34.3% of the cases. In the sagittal plane, neutral and flexion contracture deformities between 0 and 5° were the most common, with 32.6% of the cases, followed by a fixed flexion contracture alignment, which was between 6 and 10°, representing 28.7% of the cases. When combining coronal and sagittal planes, the most common alignment was the varus between 0 and 5° with a flexion contracture between 0 and 5° (12.5% of cases), closely followed by the varus between 6 and 10° with a flexion contracture between 6 and 10° (12.4% of cases). Conclusion: The Native Alignment Phenotype classification system offers a nuanced understanding of knee deformities based on three-dimensional (CT scan) assessments, potentially leading to improved surgical outcomes in TKA. By leveraging the detailed data from the CT scans, this system provides a more comprehensive view of the knee's anatomy, emphasizing the importance of individualized, data-driven approaches in knee surgery.

Patient-reported and radiographic outcomes of a porous-coated acetabular cup in robotic assisted total hip arthroplasty at 2-year follow up.

Introduction: Several implant manufacturers have developed ultra-porous metal substrate acetabular components recently. Despite this, data on clinical and radiographic outcomes remain limited. Our study evaluated postoperative patient-reported outcome measures (PROMs) and radiographic analyses in patients fitted with a novel acetabular porous-coated component. Methods: A total of 152 consecutive patients underwent a total hip arthroplasty by a single orthopaedic surgeon. All patients underwent surgery utilizing the same CT-scan based robotic-assisted device with the same porous cementless acetabular shell. They received standardized postoperative physical therapy, rehabilitation, and pain protocols. Preoperatively, first postoperative visit, 6-months, 1-year, and 2-years, patients were evaluated based on Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain, physical function, and total scores; 2) Patient-Reported Outcomes Measurement Information System (PROMIS)-10 physical and mental scores; 3) Hip Disability and Osteoarthritis Outcome Score (HOOS)-Jr scores; as well as 4) acetabular component positions and 5) evidence of acetabular component loosening. Results: Significant improvements were observed by 6 months in WOMAC pain, physical function, and total scores (p < 0.05), maintained at 1 and 2 years. PROMIS-10 physical scores also improved significantly from preoperative to 6 months postoperative and remained so at 1 and 2 years postoperative (p < 0.05). No significant changes were found in PROMIS-10 mental scores. HOOS-Jr scores significantly improved from preoperative to 6 months postoperative and remained so through 2 years (p < 0.05). At 6 months, slight changes were noted in abduction angle and horizontal and vertical offset. Radiolucencies, initially found in 3 shells, reduced to 1 shell with 2 new radiolucencies by 6 months, and remained stable with no subsequent operative interventions. At 1 year and 2 years, no radiographic abnormalities were noted, including complete resolution of prior radiolucencies as well as stable components. Conclusion: This porous cementless acetabular shell, implanted with CT-scan-based robotic-assisted techniques, demonstrated excellent postoperative PROMs at 2 years. Stable radiolucencies suggest good component stability. The early stable clinical and radiographic results suggest promising long-term outcomes with this device. Level of evidence: III (retrospective cohort study).

Clinical Outcomes after Computed Tomography-Based Total Knee Arthroplasty: A Minimum 3-Year Analyses.

Computed tomography (CT) scan-based three-dimensional (3D) modeling operative technology has been shown to improve upon results of manual total knee arthroplasties (TKAs). Although there are many reports on superior precision of this CT-based technology, there has been continuing interest regarding extended clinical outcomes. The purpose of this study was to compare their clinical outcomes with manual TKAs at approximately 3-year follow-up. Specifically, we analyzed: (1) survivorship, (2) functional outcomes, (3) complications, and (4) radiographic outcomes (i.e., alignment, progressive radiolucencies). A total of 210 patients receiving CT-based TKAs performed by a single surgeon at a single center between July 1, 2016, and February 16, 2018, were compared with 210 manual TKAs completed by the same surgeon immediately preceding implementation of the CT-based technology. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) surveys were collected at ∼3 years postoperatively. Subgroup analyses of pain and physical function scores were performed. Follow-up radiographs were evaluated for alignment, loosening, and/or progressive radiolucencies. There was 100% survivorship at final follow-up. The postoperative mean pain scores for the CT-based cohort and manual cohort were 1 ± 2 (range, 0-14) and 2 ± 3 (range, 0-17), respectively (p < 0.05). The postoperative mean physical function scores for the CT-based cohort and manual cohort were 3 ± 4 (range, 0-18) and 5 ± 5 (range, 0-19), respectively (p < 0.05). The postoperative mean total WOMAC scores for the CT-based cohort and manual cohort were 5 ± 4 (range, 0-32) and 7 ± 8 (range, 0-35), respectively (p < 0.05). There were low numbers of postoperative complications at final follow-up in either cohort. None exhibited progressive radiolucencies by final follow-up. The 3-year postoperative clinical outcomes support excellent survivorship and radiographic outcomes, low complication rates, as well as improved pain, physical function, and total WOMAC scores for CT-based TKAs. Therefore, patients who undergo CT-based 3D modeling TKAs should expect to have superior long-term clinical outcomes.

Results of Robotic-Assisted Versus Manual Total Knee Arthroplasty at 2-Year Follow-up.

Robotic-assisted technology has been developed to optimize the consistency and accuracy of bony cuts, implant placements, and knee alignments for total knee arthroplasty (TKA). With recently developed designs, there is a need for the reporting longer than initial patient outcomes. Therefore, the purpose of this study was to compare manual and robotic-assisted TKA at 2-year minimum for: (1) aseptic survivorship; (2) reduced Western Ontario and McMaster Universities Osteoarthritis Index (r-WOMAC) pain, physical function, and total scores; (3) surgical and medical complications; and (4) radiographic assessments for progressive radiolucencies. We compared 80 consecutive cementless robotic-assisted to 80 consecutive cementless manual TKAs. Patient preoperative r-WOMAC and demographics (e.g., age, sex, and body mass index) were not found to be statistically different. Surgical data and medical records were reviewed for aseptic survivorship, medical, and surgical complications. Patients were administered an r-WOMAC survey preoperatively and at 2-year postoperatively. Mean r-WOMAC pain, physical function, and total scores were tabulated and compared using Student's t-tests. Radiographs were reviewed serially throughout patient's postoperative follow-up. A p < 0.05 was considered significant. The aseptic failure rates were 1.25 and 5.0% for the robotic-assisted and manual cohorts, respectively. Patients in the robotic-assisted cohort had significantly improved 2-year postoperative r-WOMAC mean pain (1 ± 2 vs. 2 ± 3 points, p = 0.02), mean physical function (2 ± 3 vs. 4 ± 5 points, p = 0.009), and mean total scores (4 ± 5 vs, 6 ± 7 points, p = 0.009) compared with the manual TKA. Surgical and medical complications were similar in the two cohorts. Only one patient in the manual cohort had progressive radiolucencies on radiographic assessment. Robotic-assisted TKA patients demonstrated improved 2-year postoperative outcomes when compared with manual patients. Further studies could include multiple surgeons and centers to increase the generalizability of these results. The results of this study indicate that patients who undergo robotic-assisted TKA may have improved 2-year postoperative outcomes.

Time-Based Learning Curve for Robotic-Assisted Total Knee Arthroplasty: A Multicenter Study.

Robotic-assisted total knee arthroplasty (RA-TKA) has been shown to improve the accuracy of bone resection, reduce radiographic outliers, and decrease iatrogenic injury. However, it has also been shown that RA-TKA surgical times can be longer than manual surgery during adoption. The purpose of this article was to investigate (1) the characteristics of the operative time curves and trends, noting the amount of surgeons who improved, for those who performed at least 12 cases (based on initial modeling); (2) the proportion of RA surgeons who achieved the same operative times for RA-TKA as compared with manual TKAs; and (3) the number of RA-TKA cases until a steady-state operative time was achieved. TKA operative times were collected from 30 hospitals for 146 surgeons between January 1, 2016, and December 31, 2019. A hierarchical Bayesian model was used to estimate the difference between the mean RA-TKA times by case interval and the weighted baseline for manual times. The learning curve was observed at the 12th case. Therefore, operative times were analyzed for each surgeon who performed at least 12 RA-TKA cases to determine the percentage of these surgeons who trended toward a decrease or increase in their times. These surgeons were further analyzed to determine the proportion who achieved the same operating times as manual TKAs. A further hierarchical Bayesian model was used to determine when these surgeons achieved steady-state operative times. There were 60 surgeons (82%) who had decreasing surgical times over the first 12 RA-TKA cases. The remaining 13 (18%) had increasing surgical times (mean increase of 0.59 minutes/case). Approximately two-thirds of the surgeons (64%) achieved the same operating times as manual cases. The steady-state time neutrality occurred between 15 and 20 cases and beyond. This study demonstrated the learning curve for a large cohort of RA-TKAs. This model demonstrated a learning curve between 15 and 20 cases and beyond. These are important findings for this innovative technology.

The Association of Patient and Procedural Factors on Improved Outcomes: A Cluster Analysis on 853 Total Knee Arthroplasty Patients.

Many studies involving robotic-assisted total knee arthroplasty (RATKA) have demonstrated superiority regarding soft tissue balance and consistency with alignment target achievement. However, studies investigating whether RATKA is associated with improved patient outcomes regarding physical function and pain are also important. Therefore, we performed a cluster analysis and examined factors that contributed to differences in patient-reported outcome measures (PROMs). Specifically, we analyzed: (1) reduced WOMAC (rWOMAC) scores regarding pain and function; (2) usage of RATKA; (3) common patient comorbidities; as well as (4) patient demographic factors. The rWOMAC score is an abbreviated PROM that includes pain and physical function domains. This study analyzed 853 patients (95 conventional and 758 robotic-assisted) who had completed preoperative, 6-month, and 1-year postoperative rWOMAC surveys. Two clusters were constructed using rWOMAC pain and function scores at 1 year. Cluster 1 included 753 patients who had better outcomes at 1 year (mean rWOMAC pain = 0.9, mean rWOMAC function = 1.4), and cluster 2 included 100 patients who had worse outcomes at 1 year (mean rWOMAC pain = 7.7, mean rWOMAC function = 10.4). The clusters were compared to determine (1) how scores improved and (2) what patient characteristics were significantly different between clusters. Cluster 1 demonstrated greater improvement from preoperative to 6 months or 1 year (p = 0.0013 for pain preoperative to 6 months, p< 0.0001 for other measures) and 6 months to 1 year (p< 0.0001). Comparisons demonstrated that cluster 1 had older patients (67 vs. 65 years, p = 0.0479) who had lower body mass index or BMIs (31.8 vs. 33.9 kg/m2, p = 0.0042) and no significant differences in sex (p = 0.7849). Cluster 1 also had a significantly higher percentage of RATKA patients (90 vs. 79%, p< 0.001). Cluster analyses provided differentiating factors which were associated with improved postoperative rWOMAC pain and function scores at 1 year. Patients undergoing robotic-assisted TKA were associated with better rWOMAC pain and function scores from preoperative to 6 months and 1 year.

Learning Curve of Robotic-Assisted Total Knee Arthroplasty for a High-Volume Surgeon.

The learning curve has been established for robotic-assisted total knee arthroplasty (RATKA) during the first month of use; however, there have been no studies evaluating this on a longer term. Therefore, the purpose of this study was to compare operative times for three cohorts during the first year following adoption of RATKA (initial, 6 months, and 1 year) and a prior cohort of manual TKA. We investigated both mean operative times and the variability of operative time in each cohort. This is a learning curve study comparing a single surgeon's experience using RAKTA. The study groups were made up of two cohorts of 60 cementless RATKAs performed at ∼6 months and 1 year of use. A learning curve was created based on the mean operative times and individual operative times were stratified into different cohorts for comparison. Study groups were compared with the surgeon's initial group of 20 cemented RATKAs and 60 cementless manual cases. Descriptive numbers were compiled and mean operative times were compared using Student's t-tests for significant differences with a p-value of < 0.05. The mean surgical times continued to decrease after 6 months of RATKA. In 1 year, the surgeon was performing 88% of the RATKA between 50 and 69 minutes. The initial cohort and 1-year robotic-assisted mean operative times were 81 and 62 minutes, respectively (p < 0.00001). Mean 6-month robotic-assisted operative times were similar to manual times (p = 0.12). A significant lower time was found between the mean operative times for the 1-year robotic-assisted and manual (p = 0.008) TKAs. The data show continued improvement of operative times at 6 months and 1 year when using this new technology. The results of this study are important because they demonstrate how the complexity of a technology which initially increases operative time can be overcome and become more time-effective than conventional techniques.

The Accuracy of Computed Tomography-Based, Three-Dimensional Implant Planning in Robotic-Assisted Total Knee Arthroplasty.

Advanced imaging used in robotic-assisted total knee arthroplasty (TKA), such as computed tomography (CT)-based three-dimensional (3D) planning, may provide an accurate means of implant sizing preoperatively. The purpose of this study was to examine preoperative CT-based implant planning accuracy for robotic-assisted TKA in patients who have (1) varus deformities, (2) valgus deformities, (3) neutral alignment, and (4) retained hardware. A total of 393 patients underwent a robotic-assisted TKA by a single surgeon received preoperative CT scans. The surgeon reviewed the CT-based model preoperatively and recorded the expected size of the components. The final implants used in each case were recorded and compared with the surgeon's preoperative plan. In all groups of patients, the surgeon's CT-based implant plan was within one size of the implant utilized 100% of the time for both the tibiae and femora. Overall, the surgeon was exactly matched in 319 (81%) and 315 (80%) cases for the femoral and tibial components, respectively. For the femoral component, the mean age for patients in whom the original plan was exactly matched was younger than those whose implants were upsized and older than patients those implants were downsized (p = 0.024). Other patient demographics and preoperative knee alignment were not associated with predictive accuracy for femoral or tibial components. Our results demonstrate how preoperative CT-based, 3D planning for robotic-assisted TKA is accurate to within one size of the components in every case (100%), and exactly matched in 80%. The results of this study are important because they demonstrate how CT-based preoperative implant planning for TKA is reliable and accurate across all native knee alignments and other patient-specific factors. In addition, they build on a previous study by the same single surgeon, demonstrating that predictive ability can improve over time. This may be important as we move toward more outpatient surgery with less ability for prostheses inventory at ambulatory sites.

Surgical Tray Optimization and Efficiency: The Impact of a Novel Sealed Sterile Container and Instrument Tray Technology.

INTRODUCTION: As bundle payments have begun focusing on orthopaedic procedures, particularly total knee arthroplasties (TKAs), surgeons and hospitals have evaluated methods for improving efficiency. Few studies have investigated the impact of novel, sealed-container and instrument-tray technology on turnover and costs. Therefore, the purpose of this study was to compare traditional and sealed container-sterilized TKA surgical trays by: 1) investigating the setup and clean-down time in the operating room (OR); 2) examining trays processing time in central sterile supply (CS); and 3) estimating OR and CS costs and waste produced. MATERIALS AND METHODS: An interdisciplinary team determined points throughout a TKA tray single-case life cycle that could cause variations in turnover time. The times were recorded for two different TKA tray configurations. Process A utilized instruments housed in vendor trays that were "blue" wrap sterilized, while Process B employed optimized trays that were sealed container-sterilized. Times were recorded during preoperative setup and postoperative clean down in the OR and CS. Reductions in mean OR or CS times were used to estimate cost savings. Wastes were analyzed for each method. Statistical analyses using Student t-tests were used to determine statistical differences and a p-value of less than 0.05 was considered significant. RESULTS: Overall, the use of optimized trays and sealed sterilization containers reduced the turnover time by 57 minutes and the number of trays by a mean of three. OR and CS processing yearly savings were estimated to be $249,245. Waste disposal was an estimated 10,590 ounces and 450 ounces for traditional and sealed containers, respectively. CONCLUSION: Novel sealed sterilization containers demonstrated increased efficiency in the total turnover time of TKA trays. This is important for surgeons participating in bundle payments who perform surgery in a hospital and ambulatory surgery center. Reduced turnover time could potentially increase case load and decrease the need for extra instrumentation or loaner trays. This simple means of increasing efficiency could be used as a model for surgeons wishing to streamline surgical trays and reduce costs.

Estimation of Femoral Version During Total Hip Arthroplasty: Surgeon Visual Assessment versus Robotic-Arm Assisted Technology.

INTRODUCTION: Malposition of THA implants can lead to many complications, some of which may necessitate reoperation. Thus, proper implant placement is critical for optimizing patient outcomes. In addition, intraoperative visual estimation of stem position has been shown to be unreliable. Therefore, the purpose of this study was to compare a surgeon's visual estimation of femoral version to the actual version captured using a three-dimensional robotic-arm assisted platform. MATERIALS AND METHODS: A prospective study of 25 THAs performed by a single surgeon was performed. The mean version, as estimated by intraoperative visual assessment, was compared to that measured by the robotic-arm assisted technology software using a two-sided t-test. Outliers were evaluated for the following intervals: 1 to 5°, 6 to 10°, and greater than 10°. A separate analysis was performed for anteverted versus retroverted stems. RESULTS: The mean version, as estimated by intraoperative visual assessment, was 9.16 ± 4.02° (range, 3 to 18°) compared to 3.52 ± 8.66° (range, -12 to 19) as measured by the robotic-arm assisted software (P=0.005). The surgeon's estimates of broach version and those measured by the robotic-arm assisted software were identical in three cases (12%). The evaluation methods differed by 1 to 5° in six cases (24%), 6 to 10° in 10 cases (40%), and greater than 10° in six cases (24%). Larger differences between methods were noted for cases in which the stem was found to be in anteversion by the robotic-arm assisted software. CONCLUSIONS: Visual estimation of femoral implant version differed significantly from measurements captured by three-dimensional robotic-arm assisted imaging. This suggests that estimating stem position intraoperatively by eye is not reliable, even when done by an experienced surgeon. The use of robotic-arm assisted technology may be recommended for determining femoral stem version intraoperatively.

One-Year Patient Outcomes for Robotic-Arm-Assisted versus Manual Total Knee Arthroplasty.

Although there are many studies on the alignment advantages when using the robotic arm-assisted (RAA) system for total knee arthroplasty (TKA), there have been questions regarding patient-reported outcomes. Therefore, the purpose of this study was to use this index to compare: (1) total, (2) physical function, and (3) pain scores for manual versus RAA patients. We compared 53 consecutive RAA to 53 consecutive manual TKAs. No differences in preoperative scores were found between the cohorts. Patients were administered a modified Western Ontario and McMaster Universities Osteoarthritis Index satisfaction survey preoperatively and at 1-year postoperatively. The results were broken down to: (1) total, (2) physical function, and (3) pain scores. Univariate analysis with independent samples t-tests was used to compare 1-year postoperative scores. Multivariate models with stepwise backward linear regression were utilized to evaluate the associations between scores and surgical technique, age, sex, as well as body mass index (BMI). Statistical analyses were performed with a p < 0.05 to determine significance. The RAA cohort had significantly improved mean total (6 ± 6 vs. 9 ± 8 points, p = 0.03) and physical function scores (4 ± 4 vs. 6 ± 5 points, p = 0.02) when compared with the manual cohort. The mean pain score for the RAA cohort (2 ± 3 points [range, 0-14 points]) was also lower than that for the manual cohort (3 ± 4 points [range, 0-11 points]) (p = 0.06). On backward linear regression analyses, RAA was found to be significantly associated with more improved total (ß coefficient [ß] -0.208, standard error [SE] 1.401, p < 0.05), function (ß = 0.216, SE = 0.829, p < 0.05), and pain scores (ß -0.181, SE = 0.623, p = 0.063). The RAA technique was found to have the strongest association with improved scores when compared with age, gender, and BMI. This study suggests that RAA patients may have short-term improvements at minimum 1-year postoperatively. However, longer term follow-up with greater sample sizes is needed to further validate these results.

Robotic-Assisted Total Knee Arthroplasty in the Presence of Extra-Articular Deformity.

INTRODUCTION: Tibial or femoral extra-articular deformities complicate the goal achieving optimal mechanical axis alignment for successful total knee arthroplasty (TKA) outcomes. In the presence of these extra-articular deformities, standard operative techniques and instruments may not be reliable. Robotic-arm assisted technology was developed to help achieve a well-aligned and balanced knee in a variety of clinical scenarios. Although prior case series have reported on the use of robotic-arm assisted devices for cases with severe angular deformity, there is a lack of data concerning the use of the robotic device for patients with other potentially complex surgical factors. Therefore, the purpose of this series was to present cases in which the robotic-arm assisted TKA application was used in the setting of extra-articular deformities to educate the surgeon community on this potentially useful method to address these complex cases. MATERIALS AND METHODS: Three cases of patients who underwent robotic-arm assisted TKA in the setting of preoperative extra-articular deformities were identified. These included one with femoral and tibial fracture malunion, another with a proximal tibial fracture nonunion, and another with a healed tibial plateau fracture. Patient clinical histories, intraoperative surgical techniques, and postoperative outcomes were obtained. Specific focus was placed on the surgical management of the patient's pre-existing deformity. RESULTS: These three case reports are discussed in detail, with emphasis on preoperative planning and intraoperative techniques. The robotic software was able to appropriately consider the extra-articular deformity in the preoperative and real-time updated intraoperative plans. Doing so, the surgeon was able to achieve balanced and aligned TKA in each case. All three patients underwent robotic-assisted total knee arthroplasty with no intraoperative or postoperative complications. For all patients, their anteroposterior and lateral radiographs demonstrated well fixed and aligned femoral and tibial components with no signs of loosening or osteolysis. On physical exam, all patients had excellent range-of-motion with mean flexion of 122° (range: 120 to 125° of flexion) at final follow up. DISCUSSION: The decision on how to best approach TKA in patients with extra-articular deformity should be based on an extensive patient history, physical examination, and thorough evaluation of the magnitude and proximity of the deformity to the knee joint. Utilizing preoperative CT-scans with a 3D plan for robotic-arm assisted surgery allowed for appropriate assessment of the deformity preoperatively and execution of a plan for a balanced and aligned total knee arthroplasty. We have demonstrated excellent results utilizing robotic-arm assisted TKA in these complex cases.

Survivorship and Radiographic Analysis of Highly Porous Acetabular Cups Designed for Improved Osseointegration Potential.

INTRODUCTION: A variety of highly porous materials have been used to obtain biological acetabular fixation after total hip arthroplasty (THA). Due to their improved surface-coated properties, new highly porous titanium metal implants have shown potential to promote prosthesis osseointegration. Therefore, the purpose of this multicenter study was to evaluate: 1) overall acetabular cup survivorship; 2) postoperative complications; and 3) radiographic signs of loosening and radiolucencies in patients who received a new highly porous titanium metal cup. MATERIALS AND METHODS: A total of 81 patients who underwent primary THA and received a new porous acetabular cup between May 16, 2013 and January 27, 2016 at three academic centers were included for analysis. There were 40 women (49%) and 41 men (51%) who had a mean age of 65 years (range, 38 to 95 years) and a mean body mass index (BMI) of 28 kg/m2 (range, 16 to 43 kg/m2). The minimum follow up time was two years and seven months (range, 2 to 4 years). The cup was engineered with fully interconnected porosity designed for potential long-term biologic fixation. Medical records were reviewed to assess for any revision surgeries and postoperative complications, and the most recent radiographs were reviewed for signs of loosening or radiolucencies. RESULTS: Overall, acetabular component survivorship, free of fixation failure or aseptic loosening, was 100%. Two patients underwent revision due to dislocations; however, revisions were performed because no constrained or dual mobility liners were available for the shell at the time. Both patients had successful outcomes and were doing well at final follow up with no further episodes of dislocation. There was one open reduction internal fixation for a periprosthetic femoral fracture, and three polyethylene revisions were performed for instability. In all of these cases, the acetabular cup was retained. On radiographic evaluation of antero-posterior pelvis radiographs, there was one patient who had radiolucencies of <1mm in Zone 1 and Zone 2 at 15 months after surgery, and another patient demonstrated radiolucencies of <1mm in Zone 2 and 3 at one-year follow up. At a minimum of two-year follow up, both patients had non-progressive and stable findings. CONCLUSION: The results of this study demonstrated excellent survivorship, and there were no radiographic failures of this acetabular cup in primary total hip arthroplasty patients. Although two patients were found to have minimal (<1mm) radiolucencies, these were not progressive. Longer follow-up studies are needed to further assess the survivorship and outcomes of this new acetabular cup; however, based on the results of this study, these are expected to be favorable.

Does the Robotic Arm and Preoperative CT Planning Help with 3D Intraoperative Total Knee Arthroplasty Planning?

Although several studies highlight the advantages of robotic arm-assisted total knee arthroplasty (RA-TKA), few investigate its intraoperative outcome. Therefore, the purpose of this study was to analyze the RA-TKA's ability to assist with intraoperative correction of: (1) flexion and (2) extension gaps, as well as its ability to (3) accurately predict implant sizes. Additionally, in this RA-TKA cohort, length of stay, complications, and readmissions were assessed. A total of 335 patients who underwent RA-TKA were included. The robotic software virtually measured the intraoperative prebone cut extension and flexion gaps. Differences in medial versus lateral prebone cut extension and flexion gaps were calculated. A total of 155 patients (46%) had an extension gap difference of between -2 and 2 mm (mean, -0.3 mm), while 119 patients (36%) had a flexion gap difference of between -2 and 2 mm (mean, -0.6 mm). Postbone cut differences in medial versus lateral flexion and extension gaps were measured. Balanced knees were considered to have a medial and lateral flexion gap difference within 2 mm. The robot-predicted implant size was also compared with the final implant size. Additionally, lengths of stay, complications, and readmissions were assessed. All patients achieved a postbone cut extension gap difference between -1 and 1 mm (mean, -0.1 mm). A total of 332 patients (99%) achieved a postbone cut flexion gap difference of between -2 and 2 mm (mean, 0 mm). For 98% of prostheses, the robotic software predicted within 1 implant size the actual tibial or femoral implant size used.The mean length of stay was found to be 2 days. No patients suffered from superficial skin infection, pin site infections or fractures, soft tissue damage, and no robotic cases were converted to manual TKA due to intraoperative complications. A total of 8 patients (2.2%) were readmitted; however, none were directly related to robotic use. The robotic software and use of a preoperative computed tomography (CT) substantially helped with intraoperative planning and accurate prediction of implant sizes. Therefore, based on the results of this study, the RA-TKA device does, in fact, provide considerable intraoperative assistance.

Difficult Cases in Robotic Arm-Assisted Total Knee Arthroplasty: A Case Series.

Sagittal deformity of the knee is commonly corrected to neutral biomechanical axis (±3 degrees) during total knee arthroplasty (TKA), which is a widely accepted goal. Recent advances in surgical technology have made it possible to accurately plan and fulfill these goals. One of these is robotic-assisted TKA, which has been noted to help increase accuracy and precision of restoring a neutral mechanical axis. While there are data confirming the ability of robotic devices to better correct knee alignment than the manual technique, there is a lack of data concerning the use of the robotic devices in more complex cases, such as those in patients with severe varus or valgus deformity, as well as in flexion contractures. Therefore, the purpose of this case study is to present three cases in which the robotic-assisted TKA device was used to correct a severe varus and severe valgus deformities. Based on this case series, it should be noted that the robotic device can also help correct severe varus/valgus deformities and flexion contractures.

The Learning Curve Associated with Robotic Total Knee Arthroplasty.

As with most new surgical technologies, there is an associated learning curve with robotic-assisted total knee arthroplasty (TKA) before surgeons can expect ease of use to be similar to that of manual cases. Therefore, the purpose of this study was to (1) assess robotic-assisted versus manual operative times of two joint reconstructive surgeons separately as well as (2) find an overall learning curve. A total of 240 robotic-assisted TKAs performed by two board-certified surgeons were analyzed. The cases were sequentially grouped into 20 cases and a learning curve was created based on mean operative times. For each surgeon, mean operative times for their first 20 and last 20 robotic-assisted cases were compared with 20 randomly selected manual cases performed by that surgeon as controls prior to the initiation of the robotic-assisted cases. Each of the surgeons first 20 robotic assisted, last 20 robotic assisted, and 20 controls were then combined to create 3 cohorts of 40 cases for analysis. Surgeon 1: First and last robotic cohort operative times were 81 and 70 minutes (p < 0.05). Mean operative times for the first 20 robotic-assisted cases and manual cases were 81 versus 68 minutes (p < 0.05). Mean operative times for the last 20 robotic-assisted cases and manual cases were 70 versus 68 minutes (p > 0.05). Surgeon 2: First and last robotic cohort operative times were 117 and 98 minutes (p < 0.05). Mean operative times for the first 20 robotic-assisted cases and manual cases were 117 versus 95 (p < 0.05). Mean operative times for the last 20 robotic-cohort cases and manual cases were 98 versus 95 (p > 0.05). A similar trend occurred when the times of two surgeons were combined. The data from this study effectively create a learning curve for the use of robotic-assisted TKA. As both surgeons completed their total cases numbers within similar time frames, these data imply that within a few months, a board-certified orthopaedic joint arthroplasty surgeon should be able to adequately perform robotic TKA without adding any operative times.

Coronal Correction for Severe Deformity Using Robotic-Assisted Total Knee Arthroplasty.

Although robotic-assisted total knee arthroplasty (TKA) has the potential to accurately reproduce neutral alignment, it is still unclear if this correction is attainable in patients who have severe varus or valgus deformities. Therefore, the purpose of this study was to assess a single surgeon's experience with correcting coronal deformities using the robotic-assisted TKA device. Specifically, we looked at correction of varying degrees of varus and valgus deformity in patients who underwent robotic arm-assisted TKA. A total of 330 robotic-assisted TKA cases performed by a single surgeon were analyzed. Preoperative CT scans were registered to the robotic-assisted software to create a three-dimensional rendering from which coronal alignment was measured. Postoperative coronal alignment measurements were taken in the operating room using the robotic-assisted device after trial component placement. The robotic-assisted device uses optical tracking from navigation probes placed on the distal femur and proximal tibia. The robotic-assisted software can register these probes as bony landmarks to measure coronal alignment in the distal plane of the femoral component and proximal plane of the tibial component. A total of 261 cases were of varus knees, 46 cases were of valgus knees, and 23 cases had 0° preoperative alignment. Severe deformity was defined as 7° or greater deformity. Preoperative neutral alignment was defined as 0°, while postoperative neutral alignment was defined as 0° ± 3°. There were 129 patients with and initial severe varus and 7 patients with an initial severe valgus deformity of 7° or greater. Patients were divided into varus or valgus cohorts, and analysis was performed on the overall cohort, as well as nonsevere (<7°) and severe (7° or greater) deformity cohorts.All 132 knees with initial varus deformity of less than 7° were corrected to neutral (mean 1°, range -1-3°). A total of 82 knees (64%) with 7° or greater varus deformity were corrected to neutral (mean 2°, range 0-3°). However, roughly 30% of patients with severe deformity who were not corrected to neutral were still corrected within a couple of degrees of neutral. There were seven knees with 7° or greater valgus deformity, and all were corrected to neutral (mean 2°, range 0-3°). This study demonstrated that all knees were corrected in the appropriate direction within a few degrees of neutral, and no knees were overcorrected. The implication of this ability to achieve alignment goals on clinical outcomes will need to be evaluated in future studies. The results from this study demonstrate the potential for the robotic-assisted device during TKA in helping surgeons achieve a preoperatively planned desired neutral alignment.