INTRODUCTION

Component impingement in total hip arthroplasty (THA) can cause implant damage or dislocation. Dual mobility (DM) implants are thought to reduce dislocation risk, but impingement on metal acetabular bearings may cause femoral component notching. We studied the prevalence of (and risk factors for) femoral notching with DM across two institutions.

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.

There is a critical need for safe innovation in total joint replacements to address the demands of an ageing yet increasingly active population. The development of robust implant designs requires consideration of uncertainties including patient related factors such as bone morphology but also activity related loads and the variability in the surgical procedure itself. Here we present an integrated framework considering these sources of variability and its application to assess the performance of the femoral component of a total hip replacement (THR).

The framework offers four key features. To consider variability in bone properties, an automated workflow for establishing statistical shape and intensity models (SSIM) was developed. Here, the inherent relationship between shape and bone density is captured and new meshes of the target bone structures are generated with specific morphology and density distributions. The second key feature is a virtual implantation capability including implant positioning, and bone resection. Implant positioning is performed using automatically identified bone features and flexibly defined rules reflecting surgical variability. Bone resection is performed according to manufacturer guidelines. Virtual implantation then occurs through Boolean operations to remove bone elements contained within the implant's volume. The third feature is the automatic application of loads at muscle attachment points or on the joint contact surfaces defined on the SSIM. The magnitude and orientation of the forces are derived from models of similar morphology for a range of activities from a database of musculoskeletal (MS) loads. The connection to this MS loading model allows the intricate link between morphology and muscle forces to be captured. Importantly, this model of the internal forces provides access to the spectrum of loading conditions across a patient population rather than just typical or average values. The final feature is an environment that allows finite element simulations to be run to assess the mechanics of the bone-implant construct and extract results for e.g. bone strains, interface mechanics and implant stresses. Results are automatically processed and mapped in an anatomically consistent manner and can be further exploited to establish surrogate models for efficient subsequent design optimization. To demonstrate the capability of the framework, it has been applied to the femoral component of a THR.

An SSIM was created from 102 segmented femurs capturing the heterogeneous bone density distributions. Cementless femoral stems were positioned such that for the optimal implantation the proximal shaft axis of the femurs coincided with the distal stem axis and the position of the native femoral head centre was restored. Here, the resection did not affect the greater trochanter and the implantations were clinically acceptable for 10000 virtual implantations performed to simulate variability in patient morphology and surgical variation. The MS database was established from musculoskeletal analyses run for a cohort of 17 THR subjects obtaining over 100,000 individual samples of 3D muscle and joint forces. An initial analysis of the mechanical performance in 7 bone-implant constructs showed levels of bone strains and implant stresses in general agreement with the literature.

Inter-subject variability is inherently present in patient anatomy and is apparent in differences in shape, size and relative alignment of the bony structures. Understanding the variability in patient anatomy is useful for distinguishing between pathologies and to assist in surgical planning. With the aim of supporting the development of stratified orthopaedic interventions, this work introduces an Articulated Statistical Shape Model (ASSM) of the lower limb. The model captures inter-subject variability and allows reconstructing ‘virtual’ knee joints of the lower limb shape while considering pose.

A training dataset consisting of 173 lower limbs from CT scans of 110 subjects (77 male, 33 female) was used to construct the ASSM of the lower limb. Each bone of the lower limb was segmented using ScanIP (Simpleware Ltd., UK), reconstructed into 3D surface meshes, and a SSM of each bone was created. A series of sizing and positioning procedures were carried out to ensure all the lower limbs were in full extension, had the same femoral length and that the femora were aligned with a coincident centre. All articulated lower limbs were represented as: (femur scale factor) × (full extension articulated lower limb + relative transformation of tibia, fibula and patella to femur). Articulated lower limbs were in full extension were used to construct a statistical shape model, representing the variance of lower limb morphology. Relative transformations of the tibia, fibula and patella versus the femur were used to form a statistical pose model. Principal component analysis (PCA) was used to extract the modes of changes in the model.

The first 30 modes of the shape model covered 90% of the variance in shape and the first 10 modes of the pose model covered 90% of the pose variance. The first mode captures changes of the femoral CCD angle and the varus/valgus alignment of the knee. The second mode represents the changes in the ratio of femur to tibia length. The third mode reflects change of femoral shaft diameter and patella size. The first mode characterising pose captures the medial/lateral translation between femur and tibia. The second mode represents variation in knee flexion. The third mode reflects variation in tibio-femoral joint space.

An articulated statistical modelling approach was developed to characterize inter-subject variability in lower limb morphology for a set of training specimens. This model can generate large sets of lower limbs to systematically study the effect of anatomical variability on joint replacement performance. Moreover, if a series of images of the lower limb during a dynamic activity are used as training data, this method can be applied to analyse variance of lower limb motion across a population.

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.

Summary Statement

A population based finite element study that accounts for subject-specific morphology, density and load variations, suggests that osteoporosis does not markedly lower the mechanical compliance of the proximal femur to routine loads.

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:

Acetabular retroversion has been implicated as a risk factor for the development of early hip osteoarthritis. In clinical practice standard osseous signs such as the cross-over sign (COS) and the posterior wall sign (PWS) are widely used to establish the diagnosis of acetabular retroversion on plain radiographs. Despite standardized radiological evaluation protocols, an increased pelvic tilt can lead to a misdiagnosis of acetabular retroversion in AP radiographs and 2D MR or CT scans. Previous studies have shown that the elimination of observer bias using a standardized methodology based on 3D-CT models and the anterior pelvic plane (APP) for the assessment of COS and PWS results in greater diagnostic accuracy. Using this method a prevalence of 28% for COS and 24% for PWS has been found in a cohort of patients with symptoms indicative of FAI, however the prevalence of both signs in asymptomatic adults remains unknown. This study therefore sought to establish the prevalence of the COS and PWS in relation to the APP in an asymptomatic population using a reliable and accurate 3 D-CT based assessment.

The hypothesis of the current study was that the loading of the proximal femur is altered significantly by the surgical approach. The change in long-term periprosthetic bone mineral density in relation to the alteration of the musculature after the anterolateral (Group A) and transgluteal approaches (Group B) has been compared. Group A comprised 35 hip joints (30 patients) and Group B 47 hip joints (37 patients). No significant differences were seen between groups in respect to age, gender, or diaphyseal BMD distribution and in respect to average stem size in a Wilcoxon test. Measurement of BMD in femoral Gruen Zones I, II, VI, and VII revealed a significant bone loss in Group B compared with Group A; however the functional outcome showed no significant differences between the two groups postoperatively. Analysis of proximal femoral loading by means of a validated musculoskeletal model showed a considerable redistribution of the musculoskeletal loading across the hip during walking and stair climbing after a transgluteal compared with an anterolateral surgical approach. The muscular damage caused by the surgical approach seems to have a significant influence on the long-term bone loss and the initial postoperative loading of the proximal femur.

We studied the sensitivity and specificity of magnetic resonance arthrography (MRa) for the diagnosis of lesions of the acetabular labrum in 20 cadaver hips. The MRa results were compared with macroscopic and histological findings.

We found that the labrum could be satisfactorily delineated by MRa and that large detachments could be identified satisfactorily. The diagnosis of small detachments and degeneration of the labrum was less reliable.

Failure of fixation is a major complication of the treatment of unstable intertrochanteric fractures. A retrospective review was performed of 54 such fractures treated with a sliding screw-plate device. Linear and angular displacements were calculated from radiographs taken at operation and serially until healing was complete. Linear displacement was related to fracture instability, but the neck-shaft angle was relatively constant during healing. Complications were often due to failure of the sliding mechanism of the implant. We conclude that a sliding screw-plate allows controlled collapse of the major fragments but maintains the neck-shaft angle even in unstable fractures.