Excessive posterior pelvic tilt (PT) may increase the risk of anterior instability after total hip arthroplasty (THA). The aim of this study was to investigate the changes in PT occurring from the preoperative supine to postoperative standing position following THA, and identify factors associated with significant changes in PT. Supine PT was measured on preoperative CT scans and standing PT was measured on preoperative and one-year postoperative standing lateral radiographs in 933 patients who underwent primary THA. Negative values indicate posterior PT. Patients with > 13° of posterior PT from preoperative supine to postoperative standing (ΔPT ≤ -13°) radiographs, which corresponds to approximately a 10° increase in functional anteversion of the acetabular component, were compared with patients with less change (ΔPT > -13°). Logistic regression analysis was used to assess preoperative demographic and spinopelvic parameters predictive of PT changes of ≤ -13°. The area under receiver operating characteristic curve (AUC) determined the diagnostic accuracy of the predictive factors.Aims
Methods
Acetabular component positioning is commonly referenced with the pelvis in the supine position in direct anterior approach THA. Changes in pelvic tilt (PT) from the pre-operative supine to the post-operative standing positions have not been well investigated and may have relevance to optimal acetabular component targeting for reduced risk of impingement and instability. The aims of this study were therefore to determine the change in PT that occurs from pre-operative supine to post-operative standing, and whether any factors are associated with significant changes in tilt ≥13° in posterior direction. 13° in a posterior direction was chosen as that amount of posterior rotation creates an increase in functional anteversion of the acetabular component of 10°. 1097 THA patients with pre-operative supine CT and standing lateral radiographic imaging and 1 year post-operative standing lateral radiographs (interquartile range 12–13 months) were reviewed. Pre-operative supine PT was measured from CT as the angle between the anterior pelvic plane (APP) and the horizontal plane of the CT device. Standing PT was measured on standing lateral x-rays as the angle between the APP and the vertical line. Patients with ≥13° change from supine pre-op to standing post-op (corresponding to a 10° change in cup anteversion) were grouped and compared to those with a <13° change using unpaired student's t-tests. Mean pre-operative supine PT (3.8±6.0°) was significantly different from mean post-operative standing PT (−3.5±7.1°, p<0.001), ie mean change of −7.3±4.6°. 10.4% (114/1097) of patients had posterior PT changes ≥13° supine pre-op to standing post-op. A significant number of patients, ie 1 in 10, undergo a clinically significant change in PT and functional anteversion from supine pre-op to standing post-op. Surgeons should be aware of these changes when planning component placement in THA.
Smartphone-based apps that measure step-count and patient reported outcomes (PROMs) are being increasingly used to quantify recovery in total hip arthroplasty (THA). However, optimum patient-specific activity level before and during THA early-recovery is not well characterised. This study investigated 1) correlations between step-count and PROMs and 2) how patient demographics impact step-count preoperatively and during early postoperative recovery. Smartphone step-count and PROM data from 554 THA patients was retrospectively reviewed. Mean age was 64±10yr, BMI was 29±13kg/m2, 56% were female. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and HOOS12 Function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<2500steps/day), medium (2500-5500steps/day), and high (>5500steps/day). Age >65years, BMI >30, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). HOOS12 Function correlated with step-count preoperatively and at 6wk (p<0.01). High vs low step count individuals had improved UCLA scores preoperatively (∆1.8,p<0.001), at 6wk (∆1.1,p<0.05), and 12wk (∆1.6,p<0.01), and improved HOOS12 Function scores preoperatively (∆8.4,p<0.05) and at 6wk (∆8.8,p<0.001). Younger patients had greater step-count preoperatively (4.1±3.0k vs 3.0±2.5k, p<0.01) and at 12wk (5.1±3.3k vs 3.6±2.9k, p<0.01). Males had greater step-count preoperatively (4.1±3.0k vs. 3.0±2.7k, p<0.001), at 6wk (4.5±3.2k vs 2.6±2.5k, p<0.001), and at 12wk (5.2±3.6k vs. 3.4±2.5k, p<0.001). Low BMI patients had greater step-count at 6wk (4.3±3.3k vs. 2.6±2.7k, p<0.01) and 12wk (5.0±3.6k vs. 3.6±2.6k, p<0.05). Daily step-count is significantly impacted by patient demographics and correlates with PROMs, where patients with high step count exhibit improved PROMs. Generic recovery profiles may therefore not be appropriate for benchmarking across diverse populations.
Inverse Kinematic Alignment (iKA) and Gap Balancing (GB) aim to achieve a balanced TKA via component alignment. However, iKA aims to recreate the native joint line versus resecting the tibia perpendicular to the mechanical axis. This study aims to compare how two alignment methods impact 1) gap balance and laxity throughout flexion and 2) the coronal plane alignment of the knee (CPAK). Two surgeons performed 75 robotic assisted iKA TKA's using a cruciate retaining implant. An anatomic tibial resection restored the native joint line. A digital joint tensioner measured laxity throughout flexion prior to femoral resection. Femoral component position was adjusted using predictive planning to optimize balance. After femoral resection, final joint laxity was collected. Planned GB (pGB) was simulated for all cases posthoc using a neutral tibial resection and adjusting femoral position to optimize balance. Differences in ML balance, laxity, and CPAK were compared between planned iKA (piKA) and pGB. ML balance and laxity were also compared between piKA and final (fiKA). piKA and pGB had similar ML balance and laxity, with mean differences <0.4mm. piKA more closely replicated native MPTA (Native=86.9±2.8°, piKA=87.8±1.8°, pGB=90±0°) and native LDFA (Native=87.5±2.7°, piKA=88.9±3°, pGB=90.8±3.5°). piKA planned for a more native CPAK distribution, with the most common types being II (22.7%), I (20%), III (18.7%), IV (18.7%) and V (18.7%). Most pGB knees were type V (28.4%), VII (37.8%), and III (16.2). fiKA and piKA had similar ML balance and laxity, however fiKA was more variable in midflexion and flexion (p<0.01). Although ML balance and laxity were similar between piKA and pGB, piKA better restored native joint line and CPAK type. The bulk of pGB knees were moved into types V, VII, and III due to the neutral tibial cut. Surgeons should be cognizant of how these differing alignment strategies affect knee phenotype.
Evaluation of patient specific spinopelvic mobility requires the detection of bony landmarks in lateral functional radiographs. Current manual landmarking methods are inefficient, and subjective. This study proposes a deep learning model to automate landmark detection and derivation of spinopelvic measurements (SPM). A deep learning model was developed using an international multicenter imaging database of 26,109 landmarked preoperative, and postoperative, lateral functional radiographs (HREC: Bellberry: 2020-08-764-A-2). Three functional positions were analysed: 1) standing, 2) contralateral step-up and 3) flexed seated. Landmarks were manually captured and independently verified by qualified engineers during pre-operative planning with additional assistance of 3D computed tomography derived landmarks. Pelvic tilt (PT), sacral slope (SS), and lumbar lordotic angle (LLA) were derived from the predicted landmark coordinates. Interobserver variability was explored in a pilot study, consisting of 9 qualified engineers, annotating three functional images, while blinded to additional 3D information. The dataset was subdivided into 70:20:10 for training, validation, and testing. The model produced a mean absolute error (MAE), for PT, SS, and LLA of 1.7°±3.1°, 3.4°±3.8°, 4.9°±4.5°, respectively. PT MAE values were dependent on functional position: standing 1.2°±1.3°, step 1.7°±4.0°, and seated 2.4°±3.3°, p< 0.001. The mean model prediction time was 0.7 seconds per image. The interobserver 95% confidence interval (CI) for engineer measured PT, SS and LLA (1.9°, 1.9°, 3.1°, respectively) was comparable to the MAE values generated by the model. The model MAE reported comparable performance to the gold standard when blinded to additional 3D information. LLA prediction produced the lowest SPM accuracy potentially due to error propagation from the SS and L1 landmarks. Reduced PT accuracy in step and seated functional positions may be attributed to an increased occlusion of the pubic-symphysis landmark. Our model shows excellent performance when compared against the current gold standard manual annotation process.
The Coronal Plane Alignment of the Knee (CPAK) is a recent method for classifying knees using the hip-knee-ankle angle and joint line obliquity to assist surgeons in selection of an optimal alignment philosophy in total knee arthroplasty (TKA)1. It is unclear, however, how CPAK classification impacts pre-operative joint balance. Our objective was to characterise joint balance differences between CPAK categories. A retrospective review of TKA's using the OMNIBotics platform and BalanceBot (Corin, UK) using a tibia first workflow was performed. Lateral distal femoral angle (LDFA) and medial proximal tibial angle (MPTA) were landmarked intra-operatively and corrected for wear. Joint gaps were measured under a load of 70–90N after the tibial resection. Resection thicknesses were validated to recreate the pre-tibial resection joint balance. Knees were subdivided into 9 categories as described by MacDessi et al.1 Differences in balance at 10°, 40° and 90° were determined using a one-way 2-tailed ANOVA test with a critical p-value of 0.05. 1124 knees satisfied inclusion criteria. The highest proportion of knees (60.7%) are CPAK I with a varus aHKA and Distal Apex JLO, 79.8% report a Distal Apex JLO and 69.3% report a varus aHKA. Greater medial gaps are observed in varus (I, IV, VII) compared to neutral (II, V, VIII) and valgus knees (III, VI, IX) (p<0.05 in all cases) as well as in the Distal Apex (I, II, III) compared to Neutral groups (IV, V, VI) (p<0.05 in all cases). Comparisons could not be made with the Proximal Apex groups due to low frequency (≤2.5%). Significant differences in joint balance were observed between and within CPAK groups. Although both hip-knee-ankle angle and joint line orientation are associated with joint balance, boney anatomy alone is not sufficient to fully characterize the knee.
Preoperative ligament laxity can be characterized intraoperatively using digital robotic tensioners. Understanding how preoperative knee joint laxity affects preoperative and early post-operative patient reported outcomes (PROMs) may aid surgeons in tailoring intra-operative balance and laxity to optimize outcomes for specific patients. This study aims to determine if preoperative ligament laxity is associated with PROMs, and if laxity thresholds impact PROMs during early post-operative recovery. 106 patients were retrospectively reviewed. BMI was 31±7kg/m2. Mean age was 67±8 years. 69% were female. Medial and lateral knee joint laxity was measured intraoperatively using a digital robotic ligament tensioning device after a preliminary tibial resection. Linear regressions between laxity and KOOS12-function were performed in extension (10°), midflexion (45°), and flexion (90°) at preoperative, 6-week, and 3-month time points. Patients were separated into two laxity groups: ≥7 mm laxity and <7 mm laxity. Student's Correlations were found between preoperative KOOS12-function and medial laxity in midflexion (p<0.001) and flexion (p<0.01). Patients with <7 mm of medial laxity had greater preoperative KOOS12-function scores compared to patients with ≥7 mm of medial laxity in extension (46.8±18.2 vs. 29.5±15.6, p<0.05), midflexion (48.4±17.8 vs. 32±16.1, p<0.001), and flexion (47.7±18.3 vs. 32.6±14.7, p<0.01). No differences in KOOS12-function scores were observed between medial laxity groups at 6-weeks or 3-months. All knees had <5 mm of medial laxity postoperatively. No correlations were found between lateral laxity and KOOS12-function. Patients with preoperative medial laxity ≥7 mm had lower preoperative PROMs scores compared to patients with <7 mm of medial laxity. No differences in PROMs were observed between laxity groups at 6 weeks or 3 months. Patients with excessive preoperative joint laxity achieve similar PROMs scores to those without excessive laxity after undergoing gap balancing TKA.
Passive smartphone-based apps are becoming more common for measuring patient progress after total knee arthroplasty (TKA). Optimum activity levels during early TKA recovery haven't been well documented. This study investigated correlations between step-count and patient reported outcome measures (PROMs) and how demographics impact step-count preoperatively and during early post-operative recovery. Smartphone capture step-count data from 357 TKA patients was retrospectively reviewed. Mean age was 68±8years. 61% were female. Mean BMI was 31±6kg/m2. Mean daily step count was calculated over three time-windows: 60 days prior to surgery (preop), 5-6 weeks postop (6wk), and 11-12 weeks postop (12wk). Linear correlations between step-count and KOOS12-function and UCLA activity scores were performed. Patients were separated into three step-count levels: low (<1500steps/day), medium (1500-4000steps/day), and high (>4000steps/day). Age >65years, BMI >30kg/m2, and sex were used for demographic comparisons. Student's t-tests determined significant differences in mean step-counts between demographic groups, and in mean PROMs between step-count groups. UCLA correlated with step-count at all time-windows (p<0.01). KOOS12-Function correlated with step-count at 6wk and 12wk (p<0.05). High step-count individuals had improved PROMs compared to low step-count individuals preoperatively (UCLA: ∆1.4 [p<0.001], KOOS12-Function: ∆7.3 [p<0.05]), at 6wk (UCLA: ∆1 [p<0.01], KOOS12-Function: ∆7 [p<0.05]), and at 12wk (UCLA: ∆0.8 [p<0.05], KOOS12-Function: ∆6.5 [p<0.05]). Younger patients had greater step-count preoperatively (3.8±3.0k vs. 2.5±2.3k, p<0.01), at 6wk (3.1±2.9k vs. 2.2±2.3k, p<0.05) and at 12wk (3.9±2.6k vs. 2.8±2.6k, p<0.01). Males had greater step-count preoperatively (3.7±2.6k vs. 2.5±2.6k, p<0.001), at 6wk (3.6±2.6k vs. 1.9±2.4k, p<0.001), and at 12wk (3.9±2.3 vs. 2.8±2.8k, p<0.01). No differences in step-count were observed between low and high BMI patients at any timepoint. High step count led to improved PROMs scores compared to low step-count. Early post-operative step-count was significantly impacted by age and sex. Generic recovery profiles may not be appropriate across a diverse population.
Neither a surgeon’s intraoperative impression nor the parameters of computer navigation have been shown to be predictive of the outcomes following total knee arthroplasty (TKA). The aim of this study was to determine whether a surgeon, with robotic assistance, can predict the outcome as assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS) for pain (KPS), one year postoperatively, and establish what factors correlate with poor KOOS scores in a well-aligned and balanced TKA. A total of 134 consecutive patients who underwent TKA using a dynamic ligament tensioning robotic system with a tibia first resection technique and a cruciate sacrificing ultracongruent TKA system were enrolled into a prospective study. Each TKA was graded based on the final mediolateral ligament balance at 10° and 90° of flexion: 1) < 1 mm difference in the thickness of the tibial insert and that which was planned (n = 75); 2) < 1 mm difference (n = 26); 3) between 1 mm to 2 mm difference (n = 26); and 4) > 2 mm difference (n = 7). The mean one-year KPS score for each grade of TKA was compared and the likelihood of achieving an KPS score of > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high-grade TKA (grade A and B) were analyzed.Aims
Methods
Achieving a balanced joint with neutral alignment is not always possible in total knee arthroplasty (TKA). Intra-operative compromises such as accepting some joint imbalance, non-neutral alignment or soft-tissue release may result in worse patient outcomes, however, it is unclear which compromise will most impact outcome. In this study we investigate the impact of post-operative soft tissue balance and component alignment on postoperative pain. 135 patients were prospectively enrolled in robot assisted TKA with a digital joint tensioning tool (OMNIBotics with BalanceBot, Corin USA) (57% female; 67.0 ± 8.1 y/o; BMI: 31.9 ± 4.8 kg/m2). All surgeries were performed with a PCL sacrificing tibia or femur first techniques technique, using CR femoral components and a deep dish tibial insert (APEX, Corin USA). Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the tensioning tool inserted in place of the tibial trial. Component alignment parameters and post-operative joint gaps throughout flexion were recorded. Patients completed 1-year KOOS pain questionnaires. Spearman correlations and Mann-Whitney-U tests were used to investigate continuous and categorical data respectively. All analysis performed in R 3.5.3.Introduction
Methods
Neither a surgeon's intraoperative impression or computer navigation parameters have been shown to be predictive of postoperative outcomes following TKA. The purpose of this study is to determine 1) whether a surgeon and a robot can predict the 1-year KOOS pain score (KPS) and 2) determine what factors correlate with poor KOOS scores in well aligned and balanced TKA. The data of 131 consecutive patients enrolled in a prospective trial was reviewed. All TKAs were performed using a dynamic ligament tensioning robotic system with a tibial first resection technique and a cruciate sacrificing ultracongruent knee implant. Each TKA was graded based on the final recorded mediolateral ligament balance at 10° and 90°: A) <1mm with an implanted insert thickness equal to planned (n=74); B) <1mm (n=25); C) <2mm (n=26); D) >2mm (n=6) (Table-1). The 1-year KPS for each knee grade were compared and the likelihood of achieving an KPS > 90 was calculated. Finally, the factors associated with lower KPS despite achieving a high grade TKA (A/B) was performed. The Mann-Whitney U test and Chi-squared analysis was performed.Introduction
Methods
Soft-tissue balancing methods in TKA have evolved from surgeon feel to digital load-sensing tools. Such techniques allow surgeons to assess the soft-tissue envelope after bone cuts, however, these approaches are ‘after-the-fact’ and require soft-tissue release or bony re-cuts to achieve final balance. Recently, a robotic ligament tensioning device has been deployed which characterizes the soft tissue envelope through a continuous range-of-motion after just the initial tibial cut, allowing for virtual femoral resection planning to achieve a targeted gap profile throughout the range of flexion (figure-1). This study reports the first early clinical results and patient reported outcomes (PROMs) associated with this new technique and compares the outcomes with registry data. Since November 2017, 314 patients were prospectively enrolled and underwent robotic-assisted TKA using this surgical technique (mean age: 66.2 ±8.1; females: 173; BMI: 31.4±5.3). KOOS/WOMAC, UCLA, and HSS-Patient Satisfaction scores were collected pre- and post-operatively. Three, six, and twelve-month assessments were completed by 202, 141, and 63 patients, respectively, and compared to registry data from the Shared Ortech Aggregated Repository (SOAR). SOAR is a TJA PROM repository run by Ortech, an independent clinical data collection entity, and it includes data from thousands of TKAs from a diverse cross-section of participating hospitals, teaching institutions and clinics across the United States and Canada who collect outcomes data. PROMs were compared using a two-tailed t-test for non-equal variance.Introduction
Methods
Soft tissue releases are often required to correct deformity and achieve gap balance in total knee arthroplasty (TKA). However, the process of releasing soft tissues can be subjective and highly variable and is often perceived as an ‘art’ in TKA surgery. Releasing soft tissues also increases the risk of iatrogenic injury and may be detrimental to the mechanically sensitive afferent nerve fibers which participate in the regulation of knee joint stability. Measured resection TKA approaches typically rely on making bone cuts based off of generic alignment strategies and then releasing soft tissue afterwards to balance gaps. Conversely, gap-balancing techniques allow for pre-emptive adjustment of bone resections to achieve knee balance thereby potentially reducing the amount of ligament releases required. No study to our knowledge has compared the rates of soft tissue release in these two techniques, however. The objective of this study was, therefore, to compare the rates of soft tissue releases required to achieve a balanced knee in tibial-first gap-balancing versus femur-first measured-resection techniques in robotic assisted TKA, and to compare with release rates reported in the literature for conventional, measured resection TKA [1]. The number and type of soft tissue releases were documented and reviewed in 615 robotic-assisted gap-balancing and 76 robotic-assisted measured-resection TKAs as part of a multicenter study. In the robotic-assisted gap balancing group, a robotic tensioner was inserted into the knee after the tibial resection and the soft tissue envelope was characterized throughout flexion under computer-controlled tension (fig-1). Femoral bone resections were then planned using predictive ligament balance gap profiles throughout the range of motion (fig-2), and executed with a miniature robotic cutting-guide. Soft tissue releases were stratified as a function of the coronal deformity relative to the mechanical axis (varus knees: >1° varus; valgus knees: >1°). Rates of releases were compared between the two groups and to the literature data using the Fischer's exact test.Introduction
Methods
Achieving good ligament balance in total knee arthroplasty (TKA) is essential to prevent early failure and revision surgery. Poor balance and instability are well-defined, however, an ideal ligament balance target across all patients is not well-understood. In this study we investigate the achieved ligament balance using an imageless, intra-operative dynamic balancing tool and its relation to patient reported outcomes. A prospective, multi-surgeon, multi-center study investigated the use of a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform using the APEX knee (OMNI-Corin, Raynham MA). After all resections, the femoral trial and a computer-controlled tensioning device in place of the tibial tray was inserted into the knee joint. The difference in medial and lateral (ML) gaps when balancing the knee under constant load at extension (10°), mid-flexion (30°) and flexion (90°) was captured. Patients completed the KOOS questionnaire at 3 months ± 2 weeks post-surgery and considered the past 7 days as a timeframe for responses. Pearson's correlation was used to determine linear correlations between factors and ANOVA tests were used to determine differences in categorical data.Background
Methods
Achieving a well-balanced midflexion and flexion soft tissue envelope is a major goal in Total Knee Arthroplasty (TKA). The definition of soft tissue balance that results in optimal outcomes, however, is not well understood. Studies have investigated the native soft tissue envelope in cadaveric specimen and have shown loosening of the knee in flexion, particularly on the lateral side. These methods however do not reflect the post TKA environment, are invasive, and not appropriate for intra-operative use. This study utilizes a digital gap measuring tool to investigate the impact of soft tissue balance in midflexion and flexion on post-operative pain. A prospective multicenter multi-surgeon study was performed in which patients underwent TKA with a dynamic ligament-balancing tool in combination with a robotic-assisted navigation platform. All surgeries were performed with APEX implants (Corin Ltd., USA) using a variety of tibia and femur first techniques. Gap measurements were acquired under load (average 80 N) throughout the range of motion during trialing with the balancing tool inserted in place of the tibial trial. Patients completed KOOS pain questionnaires at 3months±2weeks post-op. Linear correlations were investigated between KOOS pain and coronal gap measurements in midflexion (30°–60°) and flexion (>70°). T-tests were used to compare outcomes between categorical data.Introduction
Methods
Current CMS reimbursement policy for total joint replacement is aligned with more cost effective, higher quality care. Upon implementation of a standardized evidenced-based care pathway, we evaluated overall procedural costs and clinical outcomes over the 90-day episode of care period for patients undergoing TKA with either conventional (Conv.) or robotic-assisted (RAS) instrumentation. In a retrospective review of the first seven consecutive quarters of Bundled Payment for Care Improvement (BPCI) Model 2 participation beginning January 2014, we compared 90-day readmission rates, Length of Stay (LOS), discharge disposition, gains per episode in relation to target prices and overall episode costs for surgeons who performed either RAS-TKA (3 surgeons, 147 patients) or Conv. TKA (3 surgeons, 85 patients) at a single institution. All Medicare patients from all surgeons performing more than two TKA's within the study period were included. An evidence-based clinical care pathway was implemented prior to the start of the study that standardized pre-operative patient education, anesthesia, pain management, blood management, and physical/occupational therapy throughout the LOS for all patients. Physician specific target prices were established from institutional historical payment data over a prior three year period.Introduction
Methods
Robotic systems have been used in TKA to add precision, although few studies have evaluated clinical outcomes. We report on early clinical results evaluating patient reported outcomes (PROs) on a series of robotic-assisted TKA (RAS-TKA) patients, and compare scores to those reported in the literature. We prospectively consented and enrolled 106 patients undergoing RAS-TKA by a single surgeon performing a measured-resection femur-first technique using a miniature bone-mounted robotic system. Patients completed a KOOS, New Knee Society Score (2011 KSS) and a Veterans RAND-12 (VR-12) pre-operatively and at 3, 6 and 12 months (M) post- operatively. At the time of publication 104, 101, and 78 patients had completed 3M, 6M, and 12M PROs, respectively. Changes in the five KOOS subscales (Pain, Symptoms, Activities of Daily Living (ADL), Sport and recreation function (Sport/Rec) and Knee-related Quality of Life (QOL)) were compared to available literature data from FORCE – TJR, a large, prospective, national cohort of TJR patients enrolled from diverse high-volume centers and community orthopaedic practices in the U.S, as well as to individual studies reporting on conventional (CON-TKA) and computer-assisted (CAS- TKA) at 3M, and on conventional TKA at 6M. The 2011 KSS is a validated method for quantifying patient's expectations and satisfaction with their TKA procedure. Improvements in the 2011 KSS were compared with literature data at 6M post-operatively.Introduction
Methods
Gap balancing technique aims to achieve equal and symmetric gap at full extension and in flexion; however, little is known about the connection between the native and the replaced knee gaps. In this study, a novel robotic assisted ligament tensioning tool was used to measure the pre- and post- operative gaps to better understand their relationship when aiming for balance gaps in flexion and extension. The accuracy of a prediction algorithm for the post-operative gaps based on the native gap and implant alignment was evaluated in this study. The medial and lateral gap were smallest at full extension. The native gaps increase with flexion until 30 degrees where they plateaued for the remaining flexion range. The native lateral gap was larger than the medial gap throughout the flexion range. Planning for equal gaps at extension and flexion resulted with tightest gaps at these angle; however, the gaps in mid-flexion were 3–4 mm larger. Good agreement was observed between the post-operative results and the predicted gas from the software algorithm. The results showed that the native gaps are neither symmetric nor equal. In addition, aiming for equal gaps reduces the variation at these angles but could result in mid- flexion laxity. Advanced robotics-assisted instrumentation can aid in evaluation of soft-tissue and help in surgical planning of TKA. This allows the surgeon to achieve the targeted outcome as well as record the final implant tension to correlate with clinical outcomes.
We introduce a novel active tensioning system that can be used for dynamic gap-based implant planning as well as for assessment of final soft tissue balance during implant trialing. We report on the concept development and preliminary findings observed during early feasibility testing in cadavers with two prototype systems. The active spacer (fig 1) consists of a motorized actuator unit with integrated force sensors, independently actuated medial and lateral upper arms, and a set of modular attachments for replicating the range of tibial baseplate and insert trial sizes. The spacer can be controlled in either force or position (gap) control and is integrated into the OMNIBoticsTM Robotic-assisted TKA platform (OMNI, MA, USA). Two design iterations were evaluated on eleven cadaver specimens by seven orthopaedic surgeons in three separate cadaver labs. The active spacer was used in a tibial-first technique to apply loads and measure gaps prior to and after femoral resections. To determine the range of forces applied on the spacer during a varus/valgus assessment procedure, each surgeon performed a varus/valgus stress test and peak medial and lateral forces were measured. Surgeons also rated the feel of the stability of the knee at 50N and 80N of preload using the following scale: 1 – too loose; 2 – slightly loose; 3 – ideal; 4 slightly tight; 5 – too tight. Final balanced was assessed with the spacer and with manual trial components.System description
Cadaver Study
Knee instability, stiffness, and soft-tissue imbalance are causes of aseptic revision and patient dissatisfaction following total knee arthroplasty (TKA). Surgical techniques that ensure optimal ligament balance throughout the range of motion may help reduce TKA revision for instability and improve outcomes. We evaluated a novel tibial-cut first gap balancing technique where a computer-controlled tensioner is used to dynamically apply a varying degree of distraction force in real-time as the knee is taken through a range of motion. Femoral bone cuts can then be planned while visualizing the predicted knee implant laxity throughout the arc of flexion. After registering the mechanical axes and morphology of the tibia and femur using computer navigation, the tibial resection was performed and a robotic tensioning tool was inserted into the knee prior to cutting the femur. The tool was programmed to apply equal loads in the medial and lateral compartments of the knee, but to dynamically vary the distraction force in each compartment as the knee is flexed with a higher force being applied in extension and a progressively lower force applied though mid-flexion up to 90° of flexion. The tension and predictive femoral gaps between the tibial cut and the femoral component in real-time was determined based on the planned 3D position and size of the femoral implant and the acquired pre-resection gaps (figure 1). Femoral resections were then performed using a robotic cutting guide and the trial components were inserted.Introduction
Surgical Technique Description
Arthrofibrosis remains a dominant post-operative complication and reason for returning to the OR following total knee arthroplasty. Trauma induced by ligament releases during TKA soft tissue balancing and soft tissue imbalance are thought to be contributing factors to arthrofibrosis, which is commonly treated by manipulation under anesthesia (MUA). We hypothesized that a robotic-assisted ligament balancing technique where the femoral component position is planned in 3D based on ligament gap data would result in lower MUA rates than a measured resection technique where the implants are planned based solely on boney alignment data and ligaments are released afterwards to achieve balance. We also aimed to determine the degree of mechanical axis deviation from neutral that resulted from the ligament balancing technique. We retrospectively reviewed 301 consecutive primary TKA cases performed by a single surgeon. The first 102 consecutive cases were performed with a femur-first measured resection technique using computer navigation. The femoral component was positioned in neutral mechanical alignment and at 3° of external rotation relative to the posterior condylar axis. The tibia was resected perpendicular to the mechanical axis and ligaments were released as required until the soft tissues were sufficiently balanced. The subsequent 199 consecutive cases were performed with a tibia-first ligament balancing technique using a robotic-assisted TKA system. The tibia was resected perpendicular to the mechanical axis, and the relative positions of the femur and tibia were recorded in extension and flexion by inserting a spacer block of appropriate height in the medial and lateral compartments. The position, rotation, and size of the femoral component was then planned in all planes such that the ligament gaps were symmetric and balanced to within 1mm (Figure 1). Bone resection values were used to define acceptable limits of implant rotation: Femoral component alignment was adjusted to within 2° of varus or valgus, and within 0–3° of external rotation relative to the posterior condyles. Component flexion, anteroposterior and proximal-distal positioning were also adjusted to achieve balance in the sagittal plane. A robotic-assisted femoral cutting guide was then used to resect the femur according to the plan (Figure 2). CPT billing codes were reviewed to determine how many patients in each group underwent post-operative MUA. Post-operative mechanical alignment was measured in a subset of 50 consecutive patients in the ligament balancing group on standing long-leg radiographs by an independent observer. Post-operative MUA rates were significantly lower in the ligament balancing group (0.5%; 1/199) than in the measured resection group (3.9%; 4/102), p=0.051. 91.3% (42/46) of knees were within 3° and 100% (46/46) were within 4° of neutral alignment to the mechanical axis post-operatively in the ligament balancing group.Methods
Results
There is increasing pressure on healthcare providers to demonstrate competitiveness in quality, patient outcomes and cost. Robotic and computer-assisted total knee arthroplasty (TKA) have been shown to be more accurate than conventional TKA, thereby potentially improving quality and outcomes, however these technologies are usually associated with longer procedural times and higher costs for hospitals. The aim of this study was to determine the surgical efficiency, learning curve and early patient satisfaction of robotic-assisted TKA with a contemporary imageless system. The first 29 robotic-assisted TKA cases performed by a single surgeon having no prior experience with computer or robotic-assisted TKA were reviewed. System time stamps were extracted from computer surgical reports to determine the time taken from the first step in the anatomical registration process, the hip center acquisition, to the end of the last bone resection, the validation of the proximal tibial resection. Additional time metrics included: a) array attachment, b) anatomical registration, c) robotic-assisted femoral resection, d) tibial resection, e) trailing, f) implant insertion, and skin-to-skin time. The Residual Time was also calculated as the skin-to-skin time minus the time taken for steps a) to f), representing the time spent on all other steps of the procedure. Patients completed surveys at 3 months to determine their overall satisfaction with their surgical joint.Introduction
Methods
Computer-assisted surgery (CAS) aims to improve component positioning and mechanical alignment in Total Knee Arthroplasty (TKA). Robotic cutting-guides have been integrated into CAS systems with the intent to improve bone-cutting precision and reduce navigation time by precisely automating the placement of the cutting-guide. The objectives of this study were to compare the intra-operative efficiency and accuracy of a robotic-assisted TKA procedure to a conventional computer-assisted TKA procedure where fixed sequential cutting-blocks are navigated free-hand. This was a retrospective study comparing two distinct cohorts: the control group consisted of patients undergoing TKA with conventional CAS (Stryker Universal Knee Navigation v3.1, Stryker Orthopaedics, MI) from May 2006 to September 2007; the study group consisted of patients undergoing TKA with a robotic cutting-guide (Apex Robotic Technology, ART, OMNIlife Science, MA) from October 2010 to May 2012. Exclusion of patients with preexisting hardware in the joint or an absence of navigation data resulted in a total of 29 patients in the control group and 52 patients in the study group. Both groups were similar with respect to BMI, age, gender, and pre-operative alignment. All patients were operated on by a single surgeon at a single institution. The navigation log files were analyzed to determine the total navigation time for each case, which was defined as the time from the start of the acquisition of the hip center to the end of the final alignment analysis for both systems. The intraoperative final mechanical axis was also recorded. The tourniquet time (time of inflation prior to incision to deflation immediately after cement hardening) and hospitalization length were compared. Linear regression analysis was performed using R statistical software v2.12.1.Introduction:
Methods:
Intimate bone-implant contact is a requirement for achieving stable component fixation and osseo-integration of porous-coated implants in TKA. However, consistently attaining a press-fit and a tight-fitting femoral component can be problematic when using conventional instrumentation. We present a new robotic cutting-guide system that permits intra-operative adjustment of the femoral resections such that a specified amount of press-fit can be consistently attained. System Description: A.R.T. (Apex Robotic Technology) employs a miniature bone-mounted robotic cutting-guide and flexible software that permits the surgeon to adjust the anterior and posterior femoral resections in increments of 0.25 mm per resection, allowing a maximum of 1.5mm of total added press in the AP dimension. The accuracy of guide-positioning and bone-cutting with A.R.T. was assessed in bench testing on synthetic bones (SAWBONES®) using an optical comparator. The individual guide locations for 16 femoral cut positioning sequences (80 guide positions in total) were measured. Femoral resections were performed with A.R.T. on eight sawbones (two per fit-adjustment setting) and the anterior-posterior dimensions of the final cut surfaces were also measured. Eight sawbones were prepared using conventional instrumentation (jigs) as controls: four with a 0 mm press-fit block and four with a +0.5 mm specially manufactured press-fit block.Introduction
Methods
We evaluated the utility of imageless computer-navigation coupled with a miniature robotic-cutting guide for managing large deformities in TKA. We asked what effect did severe pre-operative deformities have on post-operative alignment and surgery time using the system. We also report on the early functional outcomes of this group of patients. This was a retrospective cohort study of 128 TKA's performed by a single surgeon (mean age: 71y/o [range 53–93], BMI: 31.1 [20–44.3], 48males). Patients were stratified into three groups according to their pre-operative coronal plane deformity: Neutral or mild deformity <10((baseline group); Severe varus ≥10(; severe valgus ≥10(; and according to the degree of flexion contracture: Neutral or mild flexion from −5(hyperextension to 10(flexion (baseline group); hyperextension ≤−5(, and severe flexion ≥10. (The degree of deformity and final postoperative alignment achieved was measured using computer navigation in all patients and analysed using multivariate regression. The APEX CR/Ultra Knee System (OMNIlife Science, Inc.) was used with the PRAXIM Navigation system in all cases. A students t-test was used to compare pre- and post-operative (3–6 months) Knee Society Scores (KSS) and Knee Functional Scores (KSSF) for all patients.Introduction
Methods
The aim of this study was to quantify mid-flexion laxity in a total knee arthroplasty with an elevated joint line, as compared to a native knee and a TKA with joint line maintained. Our hypothesis was joint line elevation of 4mm would increase coronal plane laxity throughout mid-flexion in a pattern distinct from the preoperative knee or in a TKA with native joint line. Six fresh-frozen cadaver legs from hip-to-toe underwent TKA with a posterior stabilised implant (APEX PS, OMNIlife Science, Inc.) using a computer navigation system equipped with a robotic cutting-guide, in this controlled laboratory cadaveric study. After the initial tibial and femoral resections were performed, the flexion and extension gaps were balanced using navigation, and a 4mm recut was made in the distal femur. The remaining femoral cuts were made, the femoral component was downsized by resecting an additional 4mm of bone off the posterior condyles, and the polyethylene was increased by 4mm to create a situation of a well-balanced knee with an elevated joint line. The navigation system was used to measure overall coronal plane laxity by measuring the mechanical alignment angle at maximum extension, 30, 45, 60 and 90(of flexion, when applying a standardised varus/valgus load of 9.8Nm across the knee using a 4kg spring-load located at 25cm distal to the knee joint line. Laxity was also measured in the native knee, as well as the native knee after a standard approach during TKA which included a medial release. Coronal plane laxity was defined as the absolute difference (in degrees) between the mean mechanical alignment angle obtained from applying a standardised varus and valgus stress at 0, 30, 45, 60 and 90(.Introduction
Methods
The aim of this study was to quantitatively analyze the amount coronal plane laxity in mid-flexion that occurs in a well-balanced knee with an elevated joint line of 4 mm. In the setting an elevated joint line, we hypothesized that we would observe an increased varus and/or valgus laxity throughout mid flexion. After obtaining IRB approval, nine fresh-frozen cadaver legs from hip-to-toe underwent TKA with a posterior stabilized implant (APEX PS, OMNIlife Science, Inc.) using a computer navigation system equipped with a robotic cutting-guide, in this controlled laboratory cadaveric study. After the initial tibial and femoral resections were performed, the flexion and extension gaps were balanced using navigation, and a 4 mm recut was made in the distal femur. The remaining femoral cuts were made, the femoral component was downsized by resecting an additional 4 mm of bone off the posterior condyles, and the polyethylene was increased by 4 mm to create a situation of a well-balanced knee with an elevated joint line. Real implants were used in the study to eliminate any inherent error or laxity in the trials. The navigation system was used to measure overall coronal plane laxity by measuring the mechanical alignment angle at maximum extension, 30, 45, 60 and 90 degrees of flexion, when applying a standardized varus/valgus load of 9.8 [Nm] across the knee using a 4 kg spring-load located at 25 cm distal to the knee joint line (Figure 1). Coronal plane laxity was defined as the absolute difference (in degrees) between the mean mechanical alignment angle obtained from applying a standardized varus and valgus stress at 0, 30, 45, 60 and 90 degrees. Each measurement was performed three separate times. Two tailed student t-tests were performed to analyze whether there was difference in the mean mechanical alignment angle at 0°, 30°, 45°, 60°, and 90° between the well balanced scenario and following a 4 mm joint line elevation with an otherwise well balanced knee.Introduction
Methods
The aim of this study was to quantitatively analyze the amount coronal plane laxity in mid-flexion that occurs with a loose extension gap in TKA. In the setting of a loose extension gap, we hypothesized that although full extension is achieved, a loose extension gap will ultimately lead to increased varus and/or valgus laxity throughout mid flexion. After obtaining IRB approval, six fresh-frozen cadaver legs from hip-to-toe underwent TKA with a posterior stabilized implant (APEX PS OMNIlife Science, Inc.) using a computer navigation system equipped with a robotic cutting-guide, in this controlled laboratory cadaveric study. After the initial tibial and femoral resections were performed, and the flexion and extension gaps were balanced using navigation, a 4 mm distal recut was made in the distal femur to create a loose extension gap (using the same thickness of polyethylene as the well-balanced case). Real implants were used in the study to eliminate error in any laxity inherent to the trials. The navigation system was used to measure overall coronal plane laxity by measuring the mechanical alignment angle at maximum extension, 30, 45, 60 and 90 degrees of flexion, when applying a standardized varus/valgus load of 9.8 [Nm] across the knee using a 4 kg spring-load located at 25 cm distal to the knee joint line. (Figure 1). Coronal plane laxity was defined as the absolute difference (in degrees) between the mean mechanical alignment angle obtained from applying a standardized varus and valgus stress at 0, 30, 45, 60 and 90 degrees. Each measurement was performed three separate times. Two tailed student t-tests were performed to analyze whether there was difference in the mean mechanical alignment angle at 0°, 30°, 45°, 60°, and 90° between the well balanced scenario and following a 4 mm recut in the distal femur creating a loose extension gap.Introduction
Methods
Severe angular deformities in total knee arthroplasty require specific attention to bone resections and soft tissue balancing. This can add technical complexity and time, with some authors reporting an increase of approximately 20 minutes in mean surgery time when managing large deformities with conventional instrumentation [1]. We evaluate the utility of computer-navigation with imageless BoneMorphing® and Apex Robotic Technology, or A.R.T.® for managing large deformities in TKA. BoneMorphing® allows for real-time visualization of virtual bone resection contours, limb alignment and soft-tissue balance during TKA. A.R.T. permits accurate cutting and recutting of the distal femur in 1 mm increments. We asked what effects do severe pre-operative deformities have on post-operative alignment and surgery time in comparison to knees with only mild deformities when using this system. This was a retrospective cohort study of 128 consecutive A.R.T. TKA's performed by a single surgeon (mean age: 71 y/o [range 53–93], BMI: 31.1 [20–44.3], 48 males). Patients were stratified into three groups according to their pre-operative coronal plane deformity: Neutral or mild deformity <10° (baseline group); Severe varus ≥10°; and Severe valgus ≥10°; and according to the degree of flexion contracture: Neutral or mild flexion from −5° hyperextension to 10° flexion (baseline group); Hyperextension ≤−5°, and Severe flexion ≥10°. The degree of deformity and final postoperative alignment achieved was measured using computer navigation in all patients and analyzed using multivariate regression. The APEX CR/Ultra Knee System (OMNIlife Science, Inc.) was used in all cases.Introduction
Methods
Long-term implant survivorship in total knee arthroplasty (TKA) depends on the alignment of the tibial and femoral components, as well as on the mechanical alignment of the leg. Computer navigation improves component and limb alignment in TKA compared to the manual technique. However, its use is often associated with an increase in surgical time. We aimed to evaluate the use of adjustable cutting blocks (ACB) in navigated TKA. We hypothesised that the use of ACB would (1) improve tibial and femoral component positioning; (2) improve postoperative mechanical leg alignment; and (3) decrease tourniquet time, when compared to conventional cutting blocks (CCB). This was a retrospective cohort study of 94 navigated primary TKA. Patients were classified into two groups according to whether the surgery had been performed using ACB or CCB. There were sixty-four patients in the CCB group and 30 patients in the ACB group. Charts were reviewed to obtain the following data: age, gender, body mass index (BMI), tourniquet time and operated side. Pre- and postoperative standing full-leg radiographs and lateral radiographs were reviewed. Mean coronal femoral alignment for the CCB group was 0.8® varus (SD = 1.95®) and for the ACB group it was 1.1® varus (SD = 1.5®) (P = 0.12). Mean coronal tibial alignment for the CCB group was 0.1® valgus (SD = 1.3®) and for the ACB group it was 0.5® varus (SD = 1.01) (P = 0.15). Sagittal tibial alignment was a mean 0.5® of anterior slope (SD = 2.9®) for the CCB group and 0.7® anterior slope (SD = 2.5®) for the ACB group (P = 0.38). Preoperatively, the CCB group had a mean mechanical alignment of 1.8® varus (SD = 9.6®), while the ACB group had a mean 1.8® varus (SD = 9.37®) (P = 0.88). After surgery, mechanical leg alignment for the CCB group improved to a mean 0.7® varus (SD = 2.7®) (P = 0.0001), while the ACB group improved to 1.8® varus (SD = 1.7®) (P<0.0001). There was significantly less variability in postoperative mechanical alignment in the ACB group (P = 0.0091). Mean tourniquet time for the CCB group was 91 minutes (SD = 17.7 minutes). The ACB group a mean tourniquet time of 76 minutes (SD = 16.7 minutes) (P = 0.01). In the multiple linear regression model, the use of an ACB reduced tourniquet time by 16.8 minutes (P = 0.001). Adjustable cutting blocks for TKA significantly reduced postoperative mechanical alignment variability and tourniquet time compared to conventional navigated instrumentation, while providing equal or better component alignment.
Accurate and reliable registration of the ankle center is a necessary requirement in computer-assisted TKR. There is debate among surgeons over which registration procedure more accurately reflects the true center of the ankle joint. The aim of this study was to compare two different ankle registration landmarks on radiographs and determine how much they differed from the anatomic center of the talus in the frontal plane. Specifically, we asked what the average deviation in tibial mechanical axis registration would be when registering the ankle center using: A) the extreme medial and lateral points; and B) the most distal points, of the respective malleoli. A second question was whether or not BMI had any significant effect on mechanical axis registration error. We reviewed the preoperative hip-to-ankle radiographs of 40 patients who underwent navigated TKR at our institution. The patient cohort was composed of 32 females and 7 males, with a mean age of 69 years (range, 45–84 years) and a mean BMI of 29.9 (range, 14.7–43.3). All radiographs were stored in and reviewed using PACS. No clinically significant divergence from the anatomic center of the ankle was seen when using the Extremes Midpoint technique (mean divergence = 0.2® lateral; SD = 0.5®; 95% CI = −0.3®, −0.1®) or the Distal Midpoint technique (mean divergence = 0.2® lateral; SD = 0.6®; 95% CI = −0.39®, 0®). The mean difference between both techniques was 0.02® (SD = 0.3®; 95% CI = −0.1®, 0.1®; P = 0.68). BMI had no significant effect on the divergence from the true ankle center for either the Extremes Midpoint (R2 = 0.002; P = 0.78) or the Distal Midpoint techniques (R2 = 0.004; P = 0.90).(Figure 2) The center of the ankle, as determined by using the Extremes Midpoint technique, lied 1.1 mm (SD = 2.6 mm; 95% CI = −1.9 mm to −0.3 mm) from the anatomic axis of the tibia. When determined using the Distal Midpoint technique, the center of the ankle lied 1.7 mm (SD = 2.3 mm; 95% CI = −2.5 mm to −0.98 mm) from the anatomic axis. Although statistically significant (P = 0.028), this difference was not clinically relevant (<3 mm). BMI had no significant effect on these differences (R2 = 0.07; P = 0.11; R2 = 0.02, P = 0.38).(Figure 3) There is no significant difference between ankle registration using the Extremes Midpoint or the Distal Midpoint techniques and the anatomic center of the ankle. Patients' BMI does not seem to affect the registration of the ankle center with either technique.
Robotic-guided arthroplasty procedures are becoming increasingly common. We introduced a new computer-navigated TKA system with a robotic cutting-guide into a community-based hospital and characterized the accuracy and efficiency of the technique. We retrospectively reviewed our first 100 cases following IRB approval. Tourniquet time, intraoperative bone-cut accuracy and final limb alignment as measured by the computer were collected and divided into consecutive quartiles: Groups I, II, III, and IV; 25 cases per group. All resections were planned neutral to the mechanical axis. Postoperative component alignment and overall mechanical axis limb alignment were also measured on standing long-leg radiographs by two independent observers at minimum six weeks follow-up. Radiographic alignment was available for 62 cases.
Imageless computer-navigated TKA with a robotic cutting guide allowed one surgeon to make bone resections within 3° of neutral in 98% of cases. Radiographic limb alignment was less precise, which is consistent with the known limitations inherent to this measurement technique. Surgeons can expect this procedure to take 15 additional minutes during the first ten cases and five additional minutes during the second ten cases on average, without compromising accuracy.
The aims of this study were: 1) to quantitatively analyse the amount of knee extension that is achieved with +2mm incremental increases in the amount of distal femoral bone that is resected during TKA in the setting of a flexion contracture, 2) to quantify the amount of coronal plane laxity that occurs with each 2mm increase in the amount of distal femur resected. In the setting of a soft tissue flexion contracture, we hypothesized that although resecting more distal femur will reliably improve maximal knee extension, it will ultimately lead to increased varus and/or valgus laxity throughout mid-flexion. Seven fresh-frozen cadaver legs from hip-to-toe underwent TKA with a posterior stabilized implant using a measured resection technique with computer navigation system equipped with a robotic cutting-guide, in this IRB approved, controlled laboratory study. After the initial tibial and femoral resections were performed, the posterior joint capsule was sutured (imbricated) through the joint space under direct visualization until a 10° flexion contracture was obtained with the trial components in place, as confirmed by computer navigation. Two distal femoral recuts of +2mm each where then subsequently made and after the remaining femoral cuts were made, the trail implants were reinserted. The navigation system was used to measure overall coronal plane laxity by measuring the mechanical alignment angle at maximum extension, 30°, 60° and 90° of flexion, when applying a standardized varus/valgus load of 9.8 [Nm] across the knee using a 4kg spring-load located at 25cm distal to the knee joint line.(Figure 1) Coronal plane laxity was defined as the absolute difference (in °) between the mean mechanical alignment angle obtained from applying a standardized varus and valgus stress at 0°, 30, 60° and 90°. Each measurement was performed three separate times and averaged. The maximal extension angle achieved following each 2mm distal recut was also recorded. Two-tailed student's t-tests were performed to analyze whether there was difference in the mean laxity at each angle and if there was a significant improvement in maximal extension with each recut. P-values < 0.05 were considered significant.Aims/Hypothesis
Methods
Robotic-guided arthroplasty procedures are becoming increasingly common, though to our knowledge there are no published studies on robotic cutting guides in TKA. We introduced a new computer-navigated TKA system with a robotic cutting-guide into a community-based hospital and characterized the accuracy and efficiency of the technique with respect to bone cutting, component alignment and final limb alignment, and tourniquet time. The first 100 cases from a single-surgeon were retrospectively reviewed following IRB approval. Intra-operative bone-cut accuracy and overall limb alignment as measured by the computer were collected and divided into consecutive quartiles: Group I, cases 1–25; Group II, cases 26–50; Group III, cases 51–74; Group IV, cases 75–100. All resections were planned neutral to the mechanical axis. Postoperative component alignment and the overall mechanical axis limb alignment in the coronal plane were also measured on standing long-leg AP radiographs by two independent observers at a minimum six weeks post-op. This mechanical radiographic alignment was available for 62 cases. Tourniquet time (the time prior to incision until after cementation) and robotic cutting guide use time were also analyzed.Introduction
Methods
Our aim was to compare the passive kinematics and coronal plane stability throughout flexion in the native and the replaced knee, using three different TKA designs: posterior stabilized (PS), bi-cruciate substituting (BCS), and ultracongruent (UC). Our hypotheses were: 1.) a guided motion knee replacement (BCS) offers the closest replication of native knee kinematics in terms of femoral rollback 2.) the replaced knee will be significantly more stable in the coronal plane than the native knee; 3.) No difference exists in coronal plane stability between the 3 implants/designs throughout flexion. After IRB approval, two cadaveric specimens were used for a pilot study to determine sample size. Five fresh-frozen hip-to-toe cadaveric specimens then underwent TKA using an anatomic measured resection technique with a computer-navigated robotic femoral cutting-guide. The PS, BCS, and UC TKA designs were implanted in each knee using the same distal and posterior femoral cuts to standardize the position of the implants. Computer navigation was then utilized to record the varus/valgus laxity of each implant at 0°, 30°, 60° and 90° of flexion while applying a standardized 9.8Nm moment. Passive tibiofemoral kinematics were measured in a continuous passive motion machine from 10° to 110°. Femoral rollback on the tibia was calculated for the native and replaced knees by measuring the closest point (CP) on the femoral condyle to a transverse plane perpendicular to the mechanical axis of the tibia at each flexion angle.Purpose
Methods
the mean medial gap was 1.5–2.5mm smaller than the mean lateral gap for all scenarios and forces tested (p<
0.05); everting the patella decreased the medial and lateral gaps by 1mm and 1.3mm with an intact PCL, and by 1mm and 2.7mm with the PCL resected, respectively; PCL resection resulted in increased flexion gap heights of ~1–2mm for both sides. During knee flexion from 30° to 90°, the PCL tended to squeeze the medial compartment by 1–2mm (p<
0.05). Increasing the force from 50N to 100N per side resulted in a mean gap increase of 0.5mm throughout the range of flexion.
