Introduction

An understanding of anatomic variability can help guide the surgeon on intervention strategies. Well-functioning thumb metacarpophalangeal joints (MCPJ) are essential for carrying out typical daily activities. However, current options for arthroplasty are limited. This is further hindered by the lack of a precise understanding of the geometric variation present in the population. In this paper, we offer new insight into the major modes of geometric variation in the thumb MCP using Statistical Shape Modelling.

Introduction

Unicompartmental Knee Replacement Arthroplasty (UKA) is a treatment option for early knee OA that appears under-utilised, partly because of a lack of clear guidance on how to best restore lasting knee function using such devices. Computational tools can help consider inherent uncertainty in patient anatomy, implant positioning and loading when predicting the performance of any implant. In the present research an approach for creating patient-specific finite element models (FEM) incorporating joint and muscle loads was developed to assess the response of the underlying bone to UKA implantation.

Polymer foams have been extensively used in the testing and development of orthopaedic devices and computational models. Often these foams are used in preference to cadaver and animal models due to being relatively inexpensive and their consistent material properties. Successful validation of such models requires accurate material/mechanical data. The assumed range of compressive moduli, provided in the sawbones technical sheet, is 16 MPa to 1.15 GPa depending on the density of foam. In this investigation, we apply two non-contact measurement techniques (digital volume correlation (DVC) and optical surface extensometry/point-tracking) to assess the validity of these reported values. It is thought that such non-contact methods remove mechanical extensometer errors (slippage, misalignment) and are less sensitive to test-machine end-artifacts (friction, non-uniform loading, platen flexibility). This is because measurement is taken directly from the sample, and hence material property assessment should be more accurate. Use of DVC is advantageous as full field strain measurement is possible, however test time and cost is significantly higher than extensometry. Hence, the study also sought to assess the viability of optical extensometry for characterising porous materials.

Testing was conducted on five 20 mm cubic samples of 0.32g/cc (20 pcf) solid rigid polyurethane foam (SAWBONESTM). The strain behaviour was characterised by incremental loading via an in situ loading rig. Loading was performed in 0.1 mm increments for 8 load steps with scans between loading steps. Full field strain measurement was performed on one sample by micro focus tomography (muvis centre, Southampton) and subsequent DVC (DaVis, Lavision). Average strains in each direction were then calculated to enable modulus and Poisson's ratio calculation. These results were subsequently corroborated by use of optical point-tracking (MatchID). To account for heterogeneities, axial strain measurements were averaged from six points on the front and rear surfaces (fig.2). In each test compressive displacement was applied to 900N (∼2MPa) to remain within the linear elastic region.

Significant variability of individual strain measurements were observed from point couples on the same sample, indicating non-uniform loading did occur in all samples. However, by averaging across multiple points, linear loading profiles were ascertained (fig.2). For all non-contact methods the calculated elastic moduli were found to range between 331–428 MPa whilst the approximated modulus based on cross head displacement was ∼210 MPa, similar to the manufacturer's quoted value (220MPa). The point-tracking gave a significantly higher modulus (p = 0.047) than the DVC results as only surface measurements were made. It is thought that a correction factor may be ascertained from the finite element method to correct this. Both the DVC and point-tracking results (p = 0.001) indicated a substantially higher compressive modulus than the manufacturer provided properties.

This study demonstrates that methods of measuring displacement data on cellular foams must be carefully considered, as artefacts can lead to errors of up to 70% compared to optical and x-ray based techniques.

Increased incidence of obesity and longer life expectancies will place increased demands on load bearing joints. In the present work, a method of pre-clinical evaluation to assess the condition of the joint and potentially inform on cases of joint deterioration, is described. Acoustic emission (AE) is a non-destructive test methodology that has been used extensively in engineering for condition monitoring of machinery and structures. It is a passive technique that uses piezoelectric sensors to detect energy released from internal structural defects as they deform and grow. The technique has been used with some success in the past to identify characteristic signals generated from the knee joint during activities such as standing and sitting, in candidate arthroplasty patients (1,2). In this study, 40 asymptomatic subjects had AE data generated from their knee joints analysed. Subject characteristics such as age, gender, and lifestyle were disclosed and evaluated against the AE data.

Each subject was invited to take a seated position and a piezoelectric AE sensor (Pancom P15, 150kHz resonance, 19mm diameter) was attached to the subject's knee using a wax couplant and tape as close to the articulating surface and on a bony prominence to avoid signal attenuation in the soft tissue.

Subjects were invited to sit and stand 3 times. AE data were collected and processed using an AMSY5 AE processor (Vallen, Germany). Tests were repeated on a separate occasion and selected subjects were invited to participate on a third occasion. The AE data of particular interest were the peak amplitudes and the frequency power spectrum of the waveform.

Post-test inspection of subject characteristics allowed them to be separated into three broad categories: no previous history (group A), some instances of pain in the knee (group B), and those who have had previous minor surgery on the knee (group C). The corresponding AE results were grouped separately. It was found that groups A and B demonstrated similar signal amplitude characteristics while group C produced much higher, significantly different (p<0.05) amplitudes and amplitude distributions. Typical results are shown in figure 1.

At present, broad trends could be identified and relationships emerged between the data and subject history (prior surgery, typical daily activity). Further work will continue with asymptomatic subjects and the work will be extended to pre-operative patients to identify whether certain trends are amplified in this population.

Introduction

Periprosthetic bone remodelling after Total Knee Arthroplasty (TKA) may be attributed to local changes in the mechanical strain field of the bone as a result of the stiffness mismatch between high modulus metallic implant materials and the supporting bone. This can lead to significant loss of periprosthetic bone density, which may promote implant loosening, and complicate revision surgery. A novel polyetheretherketone (PEEK) implant with a modulus similar to bone has the potential to reduce stress shielding whilst eliminating metal ion release. Numerical modelling can estimate the remodelling stimulus but rigorous validation is required for use as a predictive tool. In this study, a finite element (FE) model investigating the local biomechanical changes with different TKA materials was verified experimentally using Digital Image Correlation (DIC). DIC is increasingly used in biomechanics for strain measurement on complex, heterogeneous anisotropic material structures.

There is a large variability associated with hip stem designs, patient anatomy, bone mechanical property, surgical procedure, loading, etc. Designers and orthopaedists aim at improving the performance of hip stems and reducing their sensitivity to this variability. This study focuses on the primary stability of a cementless short stem across the spectrum of patient morphology using a total of 109 femoral reconstructions, based on segmentation of patient CT scan data. A statistical approach is proposed for assessing the variability in bone shape and density [Blanc, 2012]. For each gender, a thousand new femur geometries were generated using a subset of principal components required to capture 95% of the variance in both female and male training datasets [Bah, 2013]. A computational tool (Figure 1) is then developed that automatically selects and positions the most suitable implant (distal diameter 6–17 mm, low and high offset, 126° and 133° CCD angle) to best match each CT-based 3D femur model (75 males and 34 females), following detailed measurements of key anatomical parameters. Finite Element contact models of reconstructed hips, subjected to physiologically-based boundary constraints and peak loads of walking mode [Speirs, 2007] were simulated using a coefficient of fricition of 0.4 and an interference-fit of 50μm [Abdul-Kadir, 2008]. Results showed that the maximum and average implant micromotions across the subpopulation were 100±7μm and 7±5μm with ranges [15μm, 350μm] and [1μm, 25μm], respectively. The computed percentage of implant area with micromotions greater than reported critical values of 50μm, 100μm and 150μm never exceeded 14%, 8% and 7%, respectively. To explore the possible correlations between anatomy and implant performance, response surface models for micromotion metrics were constructed using the so-called Kriging regression methodology, based on Gaussian processes. A clear nonlinear decreasing trend was revealed between implant average micromotion and the metaphyseal canal flare indexes (MCFI) measured in the medial-lateral (ML), anterio-posterior (AP) and femoral neck-oriented directions but also the average bone density in each Gruen zone. In contrast, no clear influence of the remaining clinically important parameters (neck length and offsets, femoral anteversion and CCD angle, standard canal flares, patient BMI and weight or stem size) to implant average micromotion was found. In conclusion, the present study demonstrates that the primary stability and tolerance of the short stem to variability in patient anatomy were high, suggesting no need for patient stratification. The developed methodology, based on detailed morphological analysis, accurate implant selection and positioning, prediction of implant micromotion and primary stability, is a novel and valuable tool to support implant design and planning of femoral reconstructive surgery.

This work was motivated by the need to capture the spectrum of anatomical shape variability rather than relying on analyses of single bones. A novel tool was developed that combines image-based modelling with statistical shape analysis to automatically generate new femur geometries and measure anatomical parameters to capture the variability across the population. To demonstrate the feasibility of the approach, the study used data from 62 Caucasian subjects (31 female and 31 male) aged between 43 and 106 years, with CT voxel size ranging 0.488 × 0.488 × 1.5 mm to 0.7422 × 0.7422 × 0.97 mm.

The scans were divided into female and male subgroups and high-quality subject-specific tetrahedral finite element (FE) meshes resulting from segmented femurs formed the so-called training samples. A source mesh of a segmented femur (25580 nodes, 51156 triangles) from the Visible Human dataset [Spitzer, 1996] was used for elastic surface registration of each considered target male and female subjects, followed by applying a mesh morphing strategy.

To represent the variations in bone morphology across the population, gender-based Statistical Shape Models (SSM) were developed, using Principal Component Analysis. These were then sampled using the principal components required to capture 95% of the variance in each training dataset to generate 1000 new anatomical shapes [Bryan, 2010; Blanc, 2012] and to automatically measure key anatomical parameters known to critically influence the biomechanics after hip replacement (Figure 1).

Analysis of the female and male training datasets revealed the following data for the five considered anatomical parameters: anteversion angle (12.6 ± 6.4° vs. 6.2 ± 7.5°), CCD angle (124.8 ± 4.7° vs. 126.3 ± 4.6°), femoral neck length (48.7 ± 3.8 mm vs. 52 ± 5 mm), femoral head radius (21.5 ± 1.3 mm vs. 24.9 ± 1.5 mm) and femur length (431.0 ± 17.6 mm vs. 474.5 ± 26.3 mm). However, using the SSM generated pool of 1000 femurs, the following data were computed for females against males: anteversion angle (10.5 ± 14.3° vs. 7.6 ± 7.2°), CCD angle (123.9 ± 5.8° vs. 126.7 ± 4°), femoral neck length (46.7 ± 7.7 mm vs. 51.5 ± 4.4 mm), femoral head radius (21.4 ± 1.2 mm vs. 24.9 ± 1.4 mm) and femur length (430.2 ± 16.1 mm vs. 473.9 ± 25.9 mm).

The highest variability was found in the anteversion of the females where the standard deviation in the SSM-based sample was increased to 14.3° from 6.4° in the original training dataset (Figures 2 & 3). The mean values for both females (10.5°) and males (7.6 °) were found close to the values of 10° and 7° reported in [Mishra, 2009] in 31 females and 112 males with a [2°, 25°] and [2°, 35°] range, respectively.

Femoral neck length of the female (male) subjects was 47.3 ± 6.2 mm (51.8 ± 4.1 mm) compared to 48.7 ± 3.8 mm (52 ± 5 mm) in the training dataset and 63.65 ± 5.15 mm in [Blanc, 2012] with n = 142, 54% female, 46% male and a [50.32–75.50 mm] range. For the measured CCD angle in both female (123.9 ± 5.8°) and male (126.7 ± 4°) subjects, a good correlation was found with reported values of 128.4 ± 4.75° [Atilla, 2007], 124.7 ± 7.4° [Noble, 1988] and 129.82 + 5.37° [Blanc, 2012].

In conclusion, the present study demonstrates that the proposed methodology based on gender-specific statistical shape modelling can be a valuable tool for automatically generating a large specific population of femurs to support implant design and planning of femoral reconstructive surgery.

Introduction

Implant-cement debonding at the knee has been reported previously [1]. The strength of the mechanical interlock of bone cement on to an implant surface can be associated with both bone cement and implant related factors. In addition to implant surface profile, sub-optimal mixing temperatures and waiting times prior to cement application may weaken the strength of the interlock.

Introduction

Fatigue and wear at the head/stem modular junction of large diameter total hip replacements can be exacerbated as a result of the increase in frictional torque. In vivo, a “toggling,” anterior-posterior (A-P) movement of the head taper on the trunnion may facilitate corrosion in the presence of physiological fluids, leading to increased metal ion release. Clinically, metal ion release has been linked to the formation of pseudo tumours and tissue necrosis [1].

Introduction:

Novel biomaterials may offer alternatives to metal arthroplasty bearings. To employ these materials in thin, bone conserving implants would require direct fixation to bone, using Titanium/HA coatings. Standard tests are used to evaluate the adhesion strength of coatings to metal substrates [1], versus FDA pass criteria [2]. In tensile adhesion testing, a disc is coated and uniform, uniaxial tension is exerted upon the coating-substrate interface; the strength is calculated from the failure load and surface area. Rapid failure occurs when the peak interface stress exceeds the adhesion strength, as local failure will propagate into an increasing tensile stress field.

Ceramics and reinforced polymers (e.g. carbon-fibre-reinforced PEEK), have considerably different stiffness (E) and Poisson's Ratio (ν) from the coating and implant metals. We hypothesised that this substrate-coating stiffness mismatch would produce stress concentrations at the interface edge, well in excess of the uniform stress experienced with coatings on similar stiffness metals.

Representative pre-clinical analysis is essential to ensure that novel prosthesis concepts offer an improvement over the state-of-the-art. Proposed designs must, fundamentally, be assessed against cyclic loads representing common daily activities [Bergmann 2001] to ensure that they will withstand conceivable in-vivo loading conditions. Fatigue assessment involves:

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cyclic mechanical testing, representing worst-case peak loads encountered in-vivo, typically for 10 million cycles, or

Cyclic stresses from gait loading are super-imposed upon residual assembly stresses. In thick walled devices, the residual component is small in comparison to the cyclic component, but in thin section, bone preserving devices, residual assembly stresses may be a multiple of the cyclic stresses, so a different approach to fatigue assessment is required.

Modular devices provide intraoperative flexibility with minimal inventories. Components are assembled in surgery with taper interfaces, but resulting residual stresses are variable due to differing assembly forces and potential misalignment or interface contamination. Incorrect assembly can lead to incomplete seating and dissociation [Langdown 2007], or fracture due to excessive press-fit stress or point loading [Hamilton 2010]. Pre-assembly in clean conditions, with reproducible force and alignment, gives close control of assembly stresses. Clinical results indicate that this is only a concern with thick sectioned devices in a small percentage of cases [Hamilton 2010], but it may be critical for thin walled devices.

A pre-clinical analysis method is proposed for this new scenario, with a case study example: a thin modular cup featuring a ceramic bearing insert and a Ti-6Al-4V shell (Fig. 1). The design was assessed using FE predictions, and manufacturing variability from tolerances, surface finish effects and residual stresses was assessed, in addition to loading variability, to ensure physical testing is performed at worst case:

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assembly loads were applied, predicting assembly residual stress, verified by strain gauging, and a range of service loads were superimposed.

The predicted worst-case stress conditions were analysed against three ‘constant life’ limits [Gerber, 1874, Goodman 1899, Soderberg 1930], a common aerospace approach, giving predicted safety factors. Finally, equivalent fatigue tests were conducted on ten prototype implants.

Taking a worst-case size (thinnest-walled 48 mm inner/58 mm outer), under assembly loading the peak tensile stress in the titanium shell was 274 MPa (Fig. 2). With 5kN superimposed jogging loading, at an extreme 75° inclination, 29 MPa additional tensile stress was predicted. This gave mean fatigue stress of 288.5 MPa and stress amplitude of 14.5 MPa (R=0.9). Against the most conservative infinite life limit (Soderberg), the predicted safety factor was 2.40 for machined material, and 2.03 for forged material, or if a stress-concentrating surface scratch occurs during manufacturing or implantation (Fig. 3). All cups survived 10,000,000 fatigue cycles.

This study employed computational modelling and physical testing to verify the strength of a joint prosthesis concept, under worst case static and fatigue loading conditions. The analysis technique represents an improvement in the state of the art where testing standards refer to conventional prostheses; similar methods could be applied to a wide range of novel prosthesis designs.

INTRODUCTION

Resurfacing prostheses are implanted by impaction onto the prepared femoral head. Ceramic resurfacings can be proposed as an alternative to metal implants, combining bone conservation with mitigation of sensitivity reaction risks. With low wall-thickness required for bone conservation, their strength must be verified. This study aimed to assess a ceramic resurfacing prosthesis' strength under surgical loads using a computational model, tuned and verified with physical tests.