Methods

Alignment specific physiological loading was determined using telemetric tibial implant data from Orthoload [2] and applying it to a validated finite element lower limb model developed by the University of Denver [3]. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the lower limb model, hip and ankle external boundary conditions were applied to the ATTUNE^® knee system for both MA and AA techniques. The 6 degree of freedom kinetics and kinematics for each activity were then extracted from the model for each alignment type. Mechanical alignment (MA) was considered to be neutral alignment (0° Hip Knee Ankle Angle (HKA), 0° Joint Line (JL)) and AA was chosen to be 3° varus HKA, 5° JL. It is important not to exceed the limits of safety when using AA as such it is noted that DePuy Synthes recommends staying within 3º varus HKA and 3º JL. The use of 5º JL was used in this study to account for surgical variation [Depuy-Synthes surgical technique DSUS/JRC/0617/2179].

Following a similar method described by Maag et al [1] ATTUNE tibial implants were cemented into a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. Tibial implant constructs were then subjected to intra-operative ROM/stability evaluation, followed by a hyperextension activity until 15 minutes of cement curing time, and finally 3 additional ROM/stability evaluations were performed using an AMTI VIVO simulator. The alignment specific loading parameters were then applied to the tibial implants using an AMTI VIVO simulator. Each sample was subjected to 50,000 DKB cycles and 120,000 SD cycles at 0.8 Hz in series; approximating 2 years of physiological activity. After physiological loading the samples were tested for fixation failure load by axial pull off.

METHODS

Two sets of three ATTUNE^® size 5 right leg CR RP TKRs (DePuy Synthes, Warsaw, IN) were used in a study to evaluate ADL implant wear. Implant specific loading profiles were produced via a validated finite element lower limb model [1] that uses activity data such as gait (K1L_110108_1_86p), SD (K1L_240309_2_144p), and DKB (K9P_2239_0_9_I1) from the Orthoload database [2] to produce external boundary conditions. Each set of components were tested using a VIVO joint simulator (AMTI, Watertown, MA, Figure 1) for a total of 4.5 million cycles (Mcyc). All cycles were conducted at 0.8Hz in force-control with flexion driven in displacement control. Bovine calf serum lubricant was prepared to a total protein concentration of 18g/L and maintained at 37°±2°C. Wear of the tibial inserts was quantified via gravimetric methods per ISO14243–2:2009(E). Polyethylene tibial insert weights were taken prior to testing and every 0.5Mcyc there after which corresponded to serum exchange intervals. The multi-activity test intervals were split into10 loops of 1,250 DKB, 3,000 SD, and 45,750 gait cycles in series. Based on activity data presented by Wimmer et al. the number of cycles per activity and activities used is sufficient for a person that is considered active [3]. A loaded soak control was used to compensate for fluid absorption in wear rate calculations. Wear rates were calculated using linear regression.

Methods

Three commercially available fixed bearing tibial implant designs were investigated in this study: ATTUNE^®, PFC SIGMA^® CoCr, ATTUNE^® S+. The implant designs were first prepared using a LMI implantation process. Following the method described by Maag et al tibial implants were cemented in a bone analog with 2 mL of bone marrow in the distal cavity and an additional reservoir of lipid adjacent to the posterior edge of the implant. The samples were subjected to intra- operative range of motion (ROM)/stability evaluation using an AMTI VIVO simulator, then a hyperextension activity until 15 minutes of cement cure time, and finally 3 additional ROM/stability evaluations were performed.

Implant specific physiological loading was determined using telemetric tibial implant data from Orthoload and applying it to a validated FE lower limb model developed by the University of Denver. Two high demand activities were selected for the loading section of this study: step down (SD) and deep knee bend (DKB). Using the above model, 6 degree of freedom kinetics and kinematics for each activity was determined for each posterior stabilized implant design.

Prior to loading, the 3-D motion between tibial implant and bone analog (micromotion) was measured using an ARAMIS Digital Image Correlation (DIC) system. Measurement was taken during the simulated DKB at 0.25Hz using an AMTI VIVO simulator while the DIC system captured images at a frame rate of 10Hz. The GOM software calculated the distance between reference point markers applied to the posterior implant and foam bone. A Matlab program calculated maximum micromotion within each DKB cycle and averaged that value across five cycles.

The implant specific loading parameters were then applied to the three tibial implant designs. Using an AMTI VIVO simulator each sample was subjected to 50,000 DKB and 120,000 SD cycles at 0.8Hz in series; equating to approximately 2 years of physiological activity. Following loading, micromotion was measured using the same method as above.

Methods

Three-dimensional tibial models were created from CT scans of 22 healthy Japanese knees (M7:F15, Age 31.0±12.6 years) using Mimics (Materialise NV, Leuven, Belgium).

The mid-sagittal plane of the tibia was defined by medial margin of the tibial tuberosity, origin of the PCL and center of the foot joint. The tibial plateau (or joint line plane) was determined by following three points; a dwell point of aligned femur on lateral tibial articular surface, and two points at anterior and posterior rim of medial tibial articular surface defined within sagittal plane that coincide with dwell point of femur on medial tibia. All measurements were made with respect to the mid-sagittal plane.

The shape of the tibial growth plate (GP) was extracted using Livewire function and mask editing tools of Mimics. To determine 3D orientation of the GP, moment of inertia axes were calculated for the 3D model. The inertia axes were also determined for medial and lateral half of the GP (Figure 1).

Methods

CT scans of sixteen healthy Japanese knees (M6:F10, Age 31.9±13.9 years) were studied. Three-dimensional reconstruction models were created using Mimics 17 (Materialise, Leuven, Belgium). First, a mid-sagittal tibial reference plane, for comparing the varus/valgus orientation of the tibial plateau to that of the growth plate, was defined by the medial margin of the tibial tuberosity, origin of the PCL and center of the foot joint. The tibial plateau (or joint line plane) was determined from three points; dwell point of femur (aligned in extension) on lateral tibial articular surface, and two points at anterior and posterior rim of medial tibial articular surface sampled in the sagittal view and coinciding with dwell point of femur on medial tibia.

Then, a three-dimensional model of the tibial growth plate was extracted using the Livewire function and mask editing tools in Mimics. To determine 3D orientation of the growth plate (GP), the vertical mass moment of inertia axis was calculated for the 3D model. The inertia axes were also determined for medial and lateral half of the GP (Figure 1).

Methods:

Pre-operative computed-tomography scans were collected from 14,791 TKR patients. The tibia and femur were segmented and anatomic landmarks identified: tibial mechanical axis, medial third and medial border of the tibial tubercle, PCL attachment site, and the surgical ECA of the femur. Virtual surgery was performed with an 8-mm resection (referencing the high side) made perpendicular to the tibial mechanical axis in the frontal plane, with 3° posterior slope, and transversely aligned with three different landmarks: the ECA, the medial border, and medial third of the tubercle. In each of these rotational alignments, the relative asymmetry of the medial and lateral plateaus was calculated (Medial AP/Lateral AP) (Fig. 1).

Methods

Wear testing was conducted on midsized Attune and Sigma fixed bearing cruciate substituting TKR components (DePuy Synthes). The two systems differ in many aspects; notably, Attune employs antioxidant-stabilized moderately-crosslinked polyethylene and a gradually changing sagittal femoral curvature while Sigma uses remelted moderately-crosslinked polyethylene and a mulit-radius femoral design. Wear was evaluated across a wide range of medial/lateral (M/L) load splits: 10/90, 60/40, and 90/10 using an AMTI six-station knee simulator (Figure 1). Simulation was conducted for 3 million cycles using at 1 Hz using previously described methods [4] with ‘High Kinematic’ displacement controlled inputs in 25% bovine calf serum (Hyclone) at 37 ± 2°C supplemented with sodium azide and EDTA. Polyethylene wear was determined gravimetrically with load soak compensation every 0.5 Mcyc.