Improper soft-tissue balancing can result in postoperative complications after total knee arthroplasty (TKA) and may lead to early revision. A single-use tibial insert trial with embedded sensor technology (VERASENSE from OrthoSensor Inc., Dania Beach, FL) was designed to provide feedback to the surgeon intraoperatively, with the goal to achieve a “well-balanced” knee throughout the range of motion (Roche et al. 2014). The purpose of this study was to quantify the effects of common soft-tissue releases as they related to sensor measured joint reactions and kinematics. Robotic testing was performed using four fresh-frozen cadaveric knee specimens implanted with appropriately sized instrumented trial implants (geometry based on a currently available TKA system). Sensor outputs included the locations and magnitudes of medial and lateral reaction forces. As a measure of tibiofemoral joint kinematics, medial and lateral reaction locations were resolved to femoral anterior-posterior displacement and internal-external tibial rotation (Fig 1.). Laxity style joint loading included discrete applications of ± 100 N A-P, ± 3 N/m I-E and ± 5 N/m varus-valgus (V-V) loads, each applied at 10, 45, and 90° of flexion. All tests included 20 N of compressive force. Laxity tests were performed before and after a specified series of soft-tissue releases, which included complete transection of the posterior cruciate ligament (PCL), superficial medial collateral ligament (sMCL), and the popliteus ligament (Table 1). Sensor outputs were recorded for each quasi-static test. Statistical results were quantified using regression formulas that related sensor outputs (reaction loads and kinematics) as a function of tissue release across all loading conditions. Significance was set for p-values ≤ 0.05.Introduction
Methods
Understanding the relationship between knee specific tissue behavior and joint contact mechanics remains an area of focus. Seminal work from 1990's established the possibility to optimize tissue properties for recreation of laxity driven kinematics (Mommersteeg et al., 1996). Yet, the uniqueness and validity of such predictions could be strengthened, especially as they relate to joint contact conditions. Understanding this interplay has implications for the long term performance of joint replacements. Development of instrumented knee implants, highlighted by a single use tibial insert trial with embedded sensor technology (VERASENSE, Orthosensor Inc.), may offer an avenue to establish the relationship between tissue state and joint mechanics. Utilization of related data also has the potential to confirm computational predictions, where both rigid body motions and associated reactions are explicitly accounted for. Hence, the goal of this work was to evaluate an approach for optimization of ligament properties using joint mechanics data from an instrumented implant during laxity style testing. Such a framework could be used to inform joint balancing techniques, improve long term implant performance, and alternatively, qualify factors that may lead to poor outcomes
The INTRODUCTION
METHODS
Experimental testing reproducing activity specific joint-level loading has the potential to quantify structure-function relationships, evaluate intervention possibilities, perform device analysis, and quantify joint kinematics. Many recent technological advancements have been made in this field and inspire this study's aim to present a framework for the application of activity dependent tibiofemoral loading in a specific custom developed 6 degree of freedom (DOF) robotic test frame. This study demonstrates a pipeline wherein kinetic and kinematic data from subjects were collected in a gait lab, analyzed through musculoskeletal modeling techniques, and applied to cadaveric specimens in the robotic testing system in a real-time manner. This pipeline (Figure 1 blue dotted region) fits into a framework for synergistic development and refinement of arthroplasty techniques and devices. Gait lab kinetic and kinematic data for walking was collected from 5 subjects. Subject-specific musculoskeletal modeling was performed to determine 6 DOF active component joint loading (OpenSim version 2.4, Introduction
Methods
The acetabular labrum is an essential stabilizer of the hip joint, imparting its greatest effect in extreme joint positions where the femoral head is disposed to subluxation and dislocation. However, its stabilizing value has proved difficult to quantify. The objective of the present study was to assess the contribution of the entire acetabular labrum to mechanical joint stability. We introduce a novel “dislocation potential test” that utilizes a dynamic, cadaveric, robotic model that functions in real-time under load-control parameters to map the joint space for low-displacement determination of stability, and quantify using the “stability index”. Five fresh-frozen human cadaveric hips without labral tears were mounted to a six-degree-of-freedom robotic manipulator and studied in 2 distinct joint positions provocative for either anterior or posterior dislocation. Dislocation potential tests were run in 15° intervals, or sweep planes, about the face of the acetabulum. For each interval, a 100 N force vector was applied medially and swept laterally until dislocation occurred. Three-dimensional kinematic data from conditions with and without labrum were quantified using the stability index, which is the percentage of all directions a constant force can be applied within a given sweep plane while maintaining a stable joint.Background
Methods
