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. We identified 37 patients with minimum 1-year radiographic follow-up after primary (19), revision (16), or conversion (2) THA with 3 distinct DM devices between 2012 and 2017. Indications for DM included osteonecrosis, femoral neck fracture, concomitant spinal or neurologic pathology, revision or conversion surgery, and history of prosthetic hip dislocation. Most recent radiographs were reviewed and assessed for notching. Acetabular anteversion and abduction were calculated as per Widmer (2004). Records were reviewed for dislocations and reoperations.INTRODUCTION
METHODS
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. As a basis for future uncertainty modelling of UKA performance, the geometriesof 173 lower limbs weregenerated from clinical CT scans. These were segmented (ScanIP, Simpleware Ltd, UK) to reconstruct the 3D surfaces of the femur, tibia, patella and fibula. The appropriate UKA prosthesis (DePuy, U.S.) size was automatically selected according to tibial plateau size and virtually positioned (Figure 1). Boolean operations and mesh generation were accomplished with ScanIP. A patient-specific musculoskeletal model was generated in open-source software OpenSim (Delp et al. 2007) based on the Gait2392 model. The model was scaled to a specific size and muscle insertion points were modified to corresponding points on lower limb of patient. Hip joint load, muscle forces and lower limb posture during gait cycle were calculated from the musculoskeletal model. The FE meshes of lower limb bones were transformed to the corresponding posture at each time point of a gait cycle and FE analyses were performed (Ansys, Inc. U.S) to evaluate the strain distribution on the tibial plateau in the implanted condition.Introduction
Methods
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.
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. A large pool of consecutive CT scans of the pelvis undertaken in our department for conditions unrelated to disorders of the hip was available for analysis. Scans in subjects with a Harris hip score of less than 90 points were excluded leaving a sample of 100 asymptomatic subjects (200 hips) for this study. A previously established 3D analysis method designed to eliminate errors resulting from variations in the position and orientation of the pelvis during CT imaging was applied to determine in order to assess the prevalence of the COS and PWS in relation to the APP. Here, the acetabuli were defined as retroverted if either the COS, PWS or both were positive.INTRODUCTION:
METHODS:
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.
