Aims. The surgical target for optimal implant positioning in robotic-assisted total knee arthroplasty remains the subject of ongoing discussion. One of the proposed targets is to recreate the knee’s functional behaviour as per its pre-diseased state. The aim of this study was to optimize implant positioning, starting from mechanical alignment (MA), toward restoring the pre-diseased status, including ligament strain and kinematic patterns, in a patient population. Methods. We used an active appearance model-based approach to segment the preoperative CT of 21 osteoarthritic patients, which identified the osteophyte-free surfaces and estimated cartilage from the segmented bones; these geometries were used to construct patient-specific musculoskeletal models of the pre-diseased knee. Subsequently, implantations were simulated using the MA method, and a previously developed optimization technique was employed to find the optimal implant position that minimized the root mean square deviation between pre-diseased and postoperative ligament strains and kinematics. Results. There were evident biomechanical differences between the simulated patient models, but also trends that appeared reproducible at the population level. Optimizing the implant position significantly reduced the maximum observed strain root mean square deviations within the cohort from 36.5% to below 5.3% for all but the anterolateral ligament; and concomitantly reduced the kinematic deviations from 3.8 mm (SD 1.7) and 4.7° (SD 1.9°) with MA to 2.7 mm (SD 1.4) and 3.7° (SD 1.9°) relative to the pre-diseased state. To achieve this, the femoral component consistently required translational adjustments in the anterior, lateral, and proximal directions, while the tibial component required a more posterior slope and varus rotation in most cases. Conclusion. These findings confirm that MA-induced biomechanical alterations relative to the pre-diseased state can be reduced by optimizing the implant position, and may have implications to further advance pre-planning in robotic-assisted surgery in order to restore pre-diseased knee function. Cite this article: Bone Joint J 2024;106-B(11):1231–1239

Abstract. Rehabilitation exercise is critical for patients’ recovery after knee injury or post-surgery. Unfortunately, adherence to exercise is low due to a lack of positive feedback and poor self-motivation. Therefore, it is crucial to monitor their progress and provide supervision. Inertial measurement unit (IMUs) based sensing technology can provide remote patient monitoring functions. However, most current solutions only measure the range of knee motion in one degree of freedom. The current IMUs estimate the orientation-angle based on the integrated raw data, which might lack accuracy in measuring knee motion. This study aims to develop an IMU-based sensing system using the absolute measured orientation-angle to provide more accurate comprehensive monitoring by measuring the knee rotational angles. An IMU sensing system monitoring the knee joint angles, flexion/extension (FE), adduction/abduction (AA), and internal/external (IE) was developed. The accuracy and reliability of FE measurements were validated in human participants during squat exercise using measures including root mean square error (RMSE) and correlation coefficient. The RMSE of the three knee angles (FE, AA, and IE) were 0.82°, 0.26°, and 0.11°, which are acceptable for assessing knee motion. The FE measurement was validated in human participants and showed excellent accuracy (correlation coefficient of 0.99°). Further validation of AA and IE in human participants is underway. The sensing system showed the capability to estimate three knee rotation angles (FE, AA, and IE). It showed the potential to provide comprehensive continuous monitoring for knee rehabilitation exercises, which can also be used as a clinical assessment tool

Aims. The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Methods. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC. Results. Within the imputed datasets, the LOS (RMSE 1.161) and PROMs models (RMSE 15.775, 11.056, 21.680 for KOOS pain, function, and QOL, respectively) demonstrated good accuracy. For all models, the accuracy of predicting outcomes in a new set of patients were consistent with the cross-validation accuracy overall. Upon validation with a new patient dataset, the LOS and readmission models demonstrated high accuracy (71.5% and 65.0%, respectively). Similarly, the one-year PROMs improvement models demonstrated high accuracy in predicting ten-point improvements in KOOS pain (72.1%), function (72.9%), and QOL (70.8%) scores. Conclusion. The data-driven models developed in this study offer scalable predictive tools that can accurately estimate the likelihood of improved pain, function, and quality of life one year after knee arthroplasty as well as LOS and 90 day readmission. Cite this article: Bone Joint J 2020;102-B(9):1183–1193

Introduction. Existing studies report more accurate implant placement with robotic-assisted unicompartmental knee arthroplasty (UKA); however, surgeon experience has not always been accounted for. The purpose of this study was to compare the accuracy of an experienced, high-volume surgeon to published data on robotic-assisted UKA tibial component alignment. Methods. One hundred thirty-one consecutive manual UKAs performed by a single surgeon using a cemented, fixed bearing implant were radiographically reviewed by an independent reviewer to avoid surgeon bias. Native and tibial implant slope and coronal alignment were measured on pre- and postoperative lateral and anteroposterior radiographs, respectively. Manual targets were set within 2° of native tibial slope and 0 to 2° varus tibial component alignment. Deviations from target were calculated as root mean square (RMS) errors and were compared to robotic-assisted UKA data. Results. One hundred twenty-eight UKAs were analyzed. The proportion of manual UKAs within the target for tibial component alignment (66%) exceeded published values comparing robotic (58%) to manual (41%) UKA. RMS error for tibial component alignment (1.5°) was less than published RMS error rates in robotic UKAs (range 1.8 to 5°). Fifty-eight percent of study UKAs were within the surgeon's preoperative goal for tibial slope, closer to published findings of 80% for robotic UKAs vs. 22% of manual UKAs. RMS error for tibial slope in study UKAs (1.5°) was smaller than RMS error rates for tibial slope in robotic UKAs (range 1.6 to 1.9°). Conclusion. These data demonstrate that an experienced, high-volume surgeon's accuracy in manual UKA can meet or exceed robotic-assisted UKA. Therefore, a surgeon's experience and aptitude should be taken into account when determining the value of robotics in knee arthroplasty. Further, the relationship between implant position and patient outcomes, and consensus on ideal surgical targets for optimal survivorship need further elucidation

Introduction. SPECT/CT might be a promising diagnostic modality in patients with painful total knee arthroplasty. It was the purpose of our study to introduce a novel standardised SPECT/CT algorithm for assessing patients with painful primary total knee arthroplasty and to evaluate its clinical applicability and inter- and intra-observer variation and reliability. Methods. A novel SPECT/CT localisation scheme, which consists of 9 tibial, 9 femoral and 4 patellar regions on standardised transverse, coronal, and sagittal slices was introduced. It was assessed in 18 consecutive patients with painful knees after total knee arthroplasty. The localisation and level of the tracer uptake on SPECT/CT were noted using a color coded 10 steps graded scale (0-100). The inter and intra-observer reliability were assessed. The femoral and tibial prosthetic component position was assessed in the CT images after 3D reconstruction and aligning them to standardised frames of reference. The average root mean square difference±standard deviations and ranges of these measured angles are presented along with the intraclass correlation coefficients for inter- and intraobserver reliability. Results. The localisation scheme was useful and easily applicable in all 18 cases. The novel classification using the SPECT/CT for the femoral, the tibial and patellar region was reliable. The measurements of component position in SPECT/CT images were highly reliable and feasible in all cases with sufficient visibility of the landmarks. The mean intra-observer difference between the rotational alignment measurements of tibial and femoral components was less than 2° (2SD 1°). The intra-observer variability for these measurements was less than 1 degree (2SD 1°). Conclusions. The introduced algorithm using SPECT/CT in patients after total knee arthroplasty, which combines mechanical (assessment of 3D rotational alignment of the prosthesis in the inherent CT data) and metabolic data (SPECT/CT localisation scheme), was highly reliable and useful. We propose its use in larger scaled clinical studies to investigate its clinical value

Aims

To map the Oxford Knee Score (OKS) and High Activity Arthroplasty Score (HAAS) items to a common scale, and to investigate the psychometric properties of this new scale for the measurement of knee health.

Aims

Distal femoral resection in conventional total knee arthroplasty (TKA) utilizes an intramedullary guide to determine coronal alignment, commonly planned for 5° of valgus. However, a standard 5° resection angle may contribute to malalignment in patients with variability in the femoral anatomical and mechanical axis angle. The purpose of the study was to leverage deep learning (DL) to measure the femoral mechanical-anatomical axis angle (FMAA) in a heterogeneous cohort.

Aims

The goal was to evaluate tibiofemoral knee joint kinematics during stair descent, by simulating the full stair descent motion in vitro. The knee joint kinematics were evaluated for two types of knee implants: bi-cruciate retaining and bi-cruciate stabilized. It was hypothesized that the bi-cruciate retaining implant better approximates native kinematics.

Aims

The primary aim of this study was to compare the postoperative systemic inflammatory response in conventional jig-based total knee arthroplasty (conventional TKA) versus robotic-arm assisted total knee arthroplasty (robotic TKA). Secondary aims were to compare the macroscopic soft tissue injury, femoral and tibial bone trauma, localized thermal response, and the accuracy of component positioning between the two treatment groups.

Aims

The objective of this study is to assess the use of ultrasound (US) as a radiation-free imaging modality to reconstruct 3D anatomy of the knee for use in preoperative templating in knee arthroplasty.

Aims

Robotic-assisted unicompartmental knee arthroplasty (UKA) promises accurate implant placement with the potential of improved survival and functional outcomes. The aim of this study was to present the current evidence for robotic-assisted UKA and describe the outcome in terms of implant positioning, range of movement (ROM), function and survival, and the types of robot and implants that are currently used.

Objectives

The aim of this study was to investigate the biomechanical effect of the anterolateral ligament (ALL), anterior cruciate ligament (ACL), or both ALL and ACL on kinematics under dynamic loading conditions using dynamic simulation subject-specific knee models.

Aims

In Asia and the Middle-East, people often flex their knees deeply in order to perform activities of daily living. The purpose of this study was to investigate the 3D kinematics of normal knees during high-flexion activities. Our hypothesis was that the femorotibial rotation, varus-valgus angle, translations, and kinematic pathway of normal knees during high-flexion activities, varied according to activity.

Objectives

Unicompartmental knee arthroplasty (UKA) is one surgical option for treating symptomatic medial osteoarthritis. Clinical studies have shown the functional benefits of UKA; however, the optimal alignment of the tibial component is still debated. The purpose of this study was to evaluate the effects of tibial coronal and sagittal plane alignment in UKA on knee kinematics and cruciate ligament tension, using a musculoskeletal computer simulation.

Objectives

An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry.

Aims

The primary aim of this study was to determine the surgical team’s learning curve for introducing robotic-arm assisted unicompartmental knee arthroplasty (UKA) into routine surgical practice. The secondary objective was to compare accuracy of implant positioning in conventional jig-based UKA versus robotic-arm assisted UKA.

Objectives

The aim of the current study was to analyse the effects of posterior cruciate ligament (PCL) deficiency on forces of the posterolateral corner structure and on tibiofemoral (TF) and patellofemoral (PF) contact force under dynamic-loading conditions.

Pre-operative variables are increasingly being used to determine eligibility for total knee replacement (TKR). This study was undertaken to evaluate the relationships, interactions and predictive capacity of variables available pre- and post-operatively on patient satisfaction following TKR. Using nationally collected patient reported outcome measures and data from the National Joint Registry for England and Wales, we identified 22 798 patients who underwent TKR for osteoarthritis between August 2008 and September 2010. The ability of specific covariates to predict satisfaction was assessed using ordinal logistic regression and structural equational modelling. Only 4959 (22%) of 22 278 patients rated the results of their TKR as ‘excellent’, despite the majority (71%, n = 15 882) perceiving their knee symptoms to be much improved. The strongest predictors of satisfaction were post-operative variables. Satisfaction was significantly and positively related to the perception of symptom improvement (operative success) and the post-operative EuroQol-5D score. While also significant within the models pre-operative variables were less important and had a minimal influence upon post-operative satisfaction. The most robust predictions of satisfaction occurred only when both pre- and post-operative variables were considered together. These findings question the appropriateness of restricting access to care based on arbitrary pre-operative thresholds as these factors have little bearing on post-operative satisfaction.

Cite this article: Bone Joint J 2013;95-B:1359–65.

The primary aim of this study was to develop a patient-reported Activity & Participation Questionnaire (the OKS-APQ) to supplement the Oxford knee score, in order to assess higher levels of activity and participation. The generation of items for the questionnaire involved interviews with 26 patients. Psychometric analysis (exploratory and confirmatory factor analysis and Rasch analysis) guided the reduction of items and the generation of a scale within a prospective study of 122 relatively young patients (mean age 61.5 years (42 to 71)) prior to knee replacement. A total of 99, completed pre-operative and six month post-operative assessments (new items, OKS, Short-Form 36 and American Knee Society Score).

The eight-item OKS-APQ scale is unidimensional, reliable (Cronbach’s alpha 0.85; intraclass correlation coefficient (ICC) 0.79; or 0.92 when one outlier was excluded), valid (r >  0.5 with related scales) and responsive (effect size 4.16).

We recommend that it is used with the OKS with adults of all ages when further detail regarding the levels of activity and participation of a patient is required.

Cite this article: Bone Joint J 2014;96-B:332–8.