Total Hip Arthroplasty (THA) devices are now increasingly subjected to a progressively greater range of kinematic and loading regimes from substantially younger and more active patients. In the interest of ensuring adequate THA solutions for all patient groups, THA polyethylene acetabular liner (PE Liner) wear representative of younger, heavier, and more active patients (referred to as HA in this study) warrants further understanding. Previous studies have investigated HA joint related morbidity [1]. Current or past rugby players are more likely to report osteoarthritis, osteoporosis, and joint replacement than a general population. This investigation aimed to provide a preliminary understanding of HA patient specific PE liner tribological performance during Standard Walking (SW) gait in comparison to IS0:14242-1:2014 standardized testing. Nine healthy male subjects volunteered for a gait lab-based study to collect kinematics and loading profiles. Owing to limitations in subject selection, five subjects wore a weighted jacket to increase Body Mass Index ≥30 (BMI). An induced increase in Bodyweight was capped (<30%BW) to avoid significantly effecting gait [3] (mean=11%BW). Six subjects identified as HA per BMI≥30, but with anthropometric ratios indicative of lower body fat as previously detailed by the author [2] (Waist-to-hip circumference ratio and waist circumference-to-height ratio). Three subjects identified as Normal (BMI<25). Instrumented force plate loading profiles were scaled (≈270%BW) in agreement with instrumented hip force data [4]. A previously verified THA (Pinnacle® Marathon® 36×56mm, DePuy Synthes) Finite Element Analysis wear model based on Archard's law and modified time hardening model [5] was used to predict geometrical changes due to wear and deformation, respectively (Figure 1). Subject dependent kinematic and loading conditions were sampled to generate, for both legs, 19 SW simulation runs using a central composite design of response surface method.Introduction
Materials and Methods
Implant wear testing is traditionally undertaken using standardized inputs set out by ISO or ASTM. These inputs are based on a single individual performing a single activity with a specific implant. Standardization helps ensure that implants are tested to a known set of parameters from which comparisons may be drawn but it has limitations as patients perform varied activities, with different implant sizes and designs that produce different kinematics/kinetics. In this study, wear performance has been evaluated using gait implant specific loading/kinematics and comparing to a combination deep knee bend (DKB), step down (SD) and gait implant specific loading on cruciate retaining (CR) rotating platform (RP) total knee replacements (TKR). This combination activity profile better replicates patient activities of daily living (ADL). 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.INTRODUCTION
METHODS
