Methods

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.

METHODS

Experimentation was performed on a 52 year old male, left, cadaveric specimen. Joint arthroplasty was performed using standard practice by an experienced orthopedic surgeon. To mimic passive intraoperative loading, laxity loading at 10°, 45° and 90° flexion, which consisted of discrete application of anterior-posterior (± 100N), varus-valgus (± 5 Nm) and internal-external (± 3 Nm) loads at each angle, was performed using a simVITROTM robotic musculoskeletal simulator (Cleveland Clinic, Cleveland, OH). Experimental results included relative tibiofemoral kinematics and sensor measured metrics (Fig 1).

The finite element model was developed from specimen-specific MRIs and solved using Abaqus/Explicit. The model included the rigid bones, appropriately placed implants and relevant soft-tissue structures (Fig. 1). Ligament stiffness values were adopted from the literature and included a 6% strain toe region. Sets of nonlinear springs, defined using MR imaging, comprised each ligament/bundle. Optimization was performed, which minimized the root mean squared difference between VERASENSE measured tibiofemoral mechanics and the model predicted values. Ligament slack lengths were the control variables and the objective included each loading state and all contact metrics (θ, AFD, ML, and LL).

Methods

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, simtk.org). Kinetic profiles of the stance phase of gait were estimated and experimentally prescribed in a clinically relevant joint coordinate frame (as a function of time). Of note, knee flexion angle was the only kinematically applied DOF in the robotic testing system. Six fresh-frozen left cadaveric knee specimens (3 male, 3 female, age 49–70) were acquired. The specimens were rigidly secured to the robotic Universal Musculoskeletal Simulator (UMS) custom testing apparatus [1], which controlled joint loads with a real-time force feedback controller. Joint loads were scaled to 40% of predicted loads determined through modeling, because of system load capacity limitations and to prevent joint soft tissue damage potentially caused by additional loads without active muscle constraints. The loading profile for the walking activity was applied to each of the knees and the resulting kinematics were recorded. In addition, the force feedback controller performance was evaluated by calculating the root-mean-square (RMS) error between the desired and actual loads throughout these dynamic loading profiles.

Methods

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.