Abstract

In total knee arthroplasty (TKA), one common metric used to evaluate innovations in component designs, methods of component alignment, and surgical techniques aimed at decreasing the high rate of patient-reported dissatisfaction is tibiofemoral contact kinematics. Tibiofemoral contact kinematics are determined based on the movement of the contact locations in the medial and lateral compartments of the tibia during knee flexion. A tibial force sensor is a useful instrument to determine the contact locations, because it can simultaneously determine contact forces and contact locations. Previous reports of tibial force sensors have neither characterized nor corrected errors in the computed contact location (i.e., center of pressure) between the femoral and tibial components in TKA that, based on a static analysis, are caused by the curved articular surface of the tibial component. The objectives were to experimentally characterize these errors and to develop and validate an error correction algorithm. The errors were characterized by calculating the difference between the errors in the computed contact locations when forces were applied normal to the tibial articular surface and those when forces were applied normal to the tibial baseplate. The algorithm generated error correction functions to minimize these errors and was validated by determining how much the error correction functions reduced the errors in the computed contact location caused by the curved articular surface. The curved articular surface primarily caused bias (i.e., average or systematic error) which ranged from 1.0 to 2.7 mm in regions of high curvature. The error correction functions reduced the bias in these regions to negligible levels ranging from 0.0 to 0.6 mm (p < 0.001). Bias in the computed contact locations caused by the curved articular surface of the tibial component as small as 1 mm needs to be accounted for, because it might inflate the computed internal-external rotation and anterior-posterior translation of femur on the tibia leading to false identifications of clinically undesirable contact kinematics (e.g., internal rotation and anterior translation during flexion). Our novel error correction algorithm is an effective method to account for this bias to more accurately compute contact kinematics.

Highlights

  • Clinicians along with engineers from both academia and industry are working to innovate component designs, methods of aligning the components, and surgical techniques to increase patient-reported satisfaction after total knee arthroplasty (TKA)

  • The compartmental root-mean-square error (RMSE) for the AP and ML coordinates caused by the curved articular surface in each compartment over all regions ranged from 1.4 to 2.6 mm and from 1.9 to 2.5 mm, respectively (Table 3)

  • Posterior, and inner regions of the insert where the magnitudes of the orientation of the surface normals were greater than 5 deg (Fig. 7), the regional RMSE was due primarily to bias caused by the curved articular surface and ranged in magnitude from 1.0 to 2.7 mm (Fig. 8; Table 4)

Read more

Summary

Introduction

Clinicians along with engineers from both academia and industry are working to innovate component designs, methods of aligning the components, and surgical techniques to increase patient-reported satisfaction after total knee arthroplasty (TKA). 18–25% of patients are not satisfied following TKA [1,2,3]. With the projection that 3.5 Â 106 TKAs will be performed annually in the United States alone by 2030 [4], up to 875,000 patients will not be satisfied per year. It is important that all innovations are objectively evaluated so that iterations can be made efficiently to more rapidly increase patient satisfaction. One metric that is often used to evaluate innovations is tibiofemoral contact kinematics [1,2,3,4]. Abnormal contact kinematics, which include external rotation of the tibia on the femur and anterior translation of the femur on the tibia during knee flexion, are associated with accelerated wear [6], limited flexion [7,8], and decreased function [9]

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call