Estimating Total Knee Arthroplasty Joint Loads from Kinematics

Transcription

1 Estimating Total Knee Arthroplasty Joint Loads from Kinematics Clare K. Fitzpatrick, Paul Rullkoetter. University of Denver, Denver, CO, USA. Disclosures: C.K. Fitzpatrick: None. P. Rullkoetter: 5; DePuy Synthes. Introduction: There is a wealth of clinical data available from total knee arthroplasty (TKA) patients that assess the kinematic performance of TKA. Joint kinematics are frequently measured using motion capture analysis in the gait laboratory, typically using markers attached to the skin to estimate joint motion during activity. Video fluoroscopy tracks the bone or implant geometry with improved accuracy over motion capture systems; single plane systems have reported measurement of joint motions with accuracy of 1 mm or 1.5, with increased accuracy from bi-plane fluoroscopy systems [1, 2]. Kinematic information provides valuable insight into the performance of different TKA component designs, but does not describe the entire mechanics of the joint. Loads acting at the joint affect wear and micromotion of the components, influencing the longevity of these devices. However, collection of in vivo joint loads is difficult and has been accomplished with relatively few TKA patients [3].The purpose of this study was to investigate how accurately joint loads could be predicted from more easily obtained joint kinematics. Accurate prediction of joint loads would facilitate improved prediction of wear when comparing component designs, in addition to providing valuable information for experimental and computational testing of components under physiological loading conditions. Methods: A set of TKA components, for which published telemetric tibiofemoral (TF) joint loading data was available [3], was incorporated into a TF finite element (FE) model. The model consisted of femoral and tibial bones, telemetric implant geometry, and nine primary ligaments crossing the TF joint (Figure 1) [4]. A dynamic squat simulation was initially performed such that the measured six-degree-of-freedom (6-DOF) telemetric loads at the TF joint were reproduced for a deep knee bend cycle. The resulting internal-external (I-E) and anterior-posterior (A-P) TF joint kinematics during the cycle were recorded. The analysis was subsequently run by applying only compressive joint force and reproducing I-E and A-P joint motions. To evaluate the consistency of joint load ratio predictions, further analysis was performed by reproducing the same I-E and A-P motions, with a variety of compressive force profiles. Specifically, compressive force profiles at consistent 500 N, 1000 N and 2000 N through the cycle were evaluated. All other DOFs were unconstrained. Joint load ratios (A-P force and I-E torque to compressive force (AP:C and IE:C)) were compared for different compressive force analyses. Results: When comparing the initial simulation which reproduced telemetric joint loads, with the subsequent kinematic simulations which reproduced I-E and A-P joint motions under the same compressive load, A-P joint force was faithfully reproduced, while some differences in I-E torque were observed, particularly in early flexion (< 30 ). Upon altering the compressive load profile to consistent 500 N, 1000 N, and 2000 N forces throughout flexion, absolute magnitude of the A-P and I-E loads were altered, but joint load ratios (AP:C and IE:C) were consistent with predictions from the variable compressive load analysis (Figures 2 and 3). Discussion: Initial results demonstrate the potential applicability of using kinematic data to predict joint load ratios. While compressive load may be difficult to measure in vivo, if population-based range of joint loads are of interest for evaluating component performance throughout the population, computational models can evaluate implants over a range of compressive force profiles and corresponding A-P forces and I-E torques can be predicted. Unlike telemetric TKA patient data, for which only a limited number of datasets are available, the prevalence of kinematic data facilitates that this study can be used to determine the span of joint loads across a wide spectrum of TKA patients. Differences in IE:C ratio predictions between the 6-DOF load simulation and the kinematic simulation was due to differences in valgus-varus (V-V) torque, which were applied in the 6-DOF simulation, but unconstrained in subsequent simulations. Availability of high-accuracy kinematic data, which could be obtained from bi-plane fluoroscopy systems, would allow V-V motions to be applied in the same manner as I-E and A-P motions, and would likely improve joint load ratio predictions. As is, computational simulations can be performed under a range of V-V profiles to ensure that population variability is appropriately captured in scope of the model loading conditions. Further work will investigate the sensitivity of experimental measurement error in prediction of joint load ratios. Significance: This preliminary study demonstrates the potential applicability and accuracy of using kinematic data to predict joint load ratios in the TKA knee. This data can be used in experimental simulators and computational analyses to ensure that prospective implant designs are evaluated under physiological loading conditions. Acknowledgments: The work was supported in part by DePuy Synthes, Inc References: [1] Mahfouz et al., IEEE Trans Med Imaging 22, [2] Torry et al., Knee Surg Sports Traumatol Arthrosc 19, [3] Kutzner et al., J Biomech 43, [4] Fitzpatrick et al., J Biomech 45, 2092-

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4 ORS 2014 Annual Meeting Poster No: 1701

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