Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model.

This paper is motivated by the need to accurately and efficiently measure key periosteal and endosteal parameters of the femur, known to critically influence hip biomechanics following arthroplasty. The proposed approach uses statistical shape and intensity models (SSIMs) to represent the variability across a wide range of patients, in terms of femoral shape and bone density. The approach feasibility is demonstrated by using a training dataset of computer tomography scans from British subjects aged 25-106 years (75 male and 34 female). For each gender, a thousand new virtual femur geometries were generated using a subset of principal components required to capture 95% of the variance in both female and male training datasets. Significant differences were found in basic anatomic parameters between females and males: anteversion, CCD angle, femur and neck lengths, head offsets and radius, cortical thickness, densities in both Gruen and neck zones. The measured anteversion for female subjects was found to be twice as high as that for male subjects: 13 ± 6.4° vs. 6.3 ± 7.8° using the training datasets compared to 12.96 ± 6.68 vs. 5.83 ± 9.2 using the thousand virtual femurs. No significant differences were found in canal flare indexes. The proposed methodology is a valuable tool for automatically generating a large specific population of femurs, targeting specific patients, supporting implant design and femoral reconstructive surgery.

Inter-subject variability effects on the primary stability of a short cementless femoral stem.

This paper is concerned with the primary stability of the Furlong Evolution(®) cementless short stem across a spectrum of patient morphology. A computational tool is developed that automatically selects and positions the most suitable stem from an implant system made of a total of 48 collarless stems to best match a 3D model based on a library of CT femur scans (75 males and 34 females). Finite Element contact models of reconstructed hips, subjected to physiologically-based boundary constraints and peak loads of walking mode, were simulated using a coefficient of friction of 0.4 and an interference-fit of 50 µm. Maximum and average implant micromotions across the subpopulation were predicted to be 100±7 µm and 7±5 µm with ranges [15 µm, 350 µm] and [1 µm, 25 µm], respectively. The computed percentage of implant area with micromotions greater than reported critical values of 50 µm, 100 µm and 150 µm 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. Detailed morphological analyses were conducted and a clear nonlinear decreasing trend was observed between implant average micromotion and both the metaphyseal canal flare indices and average densities in Gruen zones. The present study demonstrates that the primary stability and tolerance of the short stem to variability in patient anatomy were high, reducing the need for patient stratification. In addition, the developed tool could be utilised to support implant design and planning of femoral reconstructive surgery.

Efficient computational method for assessing the effects of implant positioning in cementless total hip replacements.

The present work describes a statistical investigation into the effects of implant positioning on the initial stability of a cementless total hip replacement (THR). Mesh morphing was combined with design of computer experiments to automatically construct Finite Element (FE) meshes for a range of pre-defined femur-implant configurations and to predict implant micromotions under joint contact and muscle loading. Computed micromotions, in turn, are postprocessed using a Bayesian approach to: (a) compute the main effects of implant orientation angles, (b) predict the sensitivities of the considered implant performance metrics with respect to implant ante-retroversion, varus-valgus and antero-posterior orientation angles and (c) identify implant positions that maximise and minimise each metric. It is found that the percentage of implant area with micromotion greater than 50 µm, average and maximum micromotions are all more sensitive to antero-posterior orientation than ante-retroversion and varus-valgus orientation. Sensitivities, combined with the main effect results, suggest that bone is less likely to grow if the implant is increasingly moved from the neutral position towards the anterior part of the femur, where the highest micromotions occur. The computed implant best position leads to a percentage of implant area with micromotion greater than 50 µm of 1.14 when using this metric compared to 14.6 and 5.95 in the worst and neutrally positioned implant cases. In contrast, when the implant average/maximum micromotion is used to assess the THR performance, the implant best position corresponds to average/maximum micromotion of 9 µm/59 µm, compared to 20 µm/114 µm and 13 µm/71 µm in the worst and neutral positions, respectively. The proposed computational framework can be extended further to study the effects of uncertainty and variability in anatomy, bone mechanical properties, loading or bone-implant interface contact conditions.

Mesh morphing for finite element analysis of implant positioning in cementless total hip replacements.

Finite element (FE) analysis of the effect of implant positioning on the performance of cementless total hip replacements (THRs) requires the generation of multiple meshes to account for positioning variability. This process can be labour intensive and time consuming as CAD operations are needed each time a specific orientation is to be analysed. In the present work, a mesh morphing technique is developed to automate the model generation process. The volume mesh of a baseline femur with the implant in a nominal position is deformed as the prosthesis location is varied. A virtual deformation field, obtained by solving a linear elasticity problem with appropriate boundary conditions, is applied. The effectiveness of the technique is evaluated using two metrics: the percentages of morphed elements exceeding an aspect ratio of 20 and an angle of 165 degrees between the adjacent edges of each tetrahedron. Results show that for 100 different implant positions, the first and second metrics never exceed 3% and 3.5%, respectively. To further validate the proposed technique, FE contact analyses are conducted using three selected morphed models to predict the strain distribution in the bone and the implant micromotion under joint and muscle loading. The entire bone strain distribution is well captured and both percentages of bone volume with strain exceeding 0.7% and bone average strains are accurately computed. The results generated from the morphed mesh models correlate well with those for models generated from scratch, increasing confidence in the methodology. This morphing technique forms an accurate and efficient basis for FE based implant orientation and stability analysis of cementless hip replacements.

Effect of geometrical uncertainty on cemented hip implant structural integrity.

A large number of parameters such as material properties, geometry, and structural strength are involved in the design and analysis of cemented hip implants. Uncertainties in these parameters have a potential to compromise the structural performance and lifetime of implants. Statistical analyses are well suited to investigating this type of problem as they can estimate the influence of these uncertainties on the incidence of failure. Recent investigations have focused on the effect of uncertainty in cement properties and loading condition on the integrity of the construct. The present study hypothesizes that geometrical uncertainties will play a role in cement mantle failure. Finite element input parameters were simulated as random variables and different modes of failure were investigated using a response surface method (RSM). The magnitude of random von Mises stresses varied up to 8 MPa, compared with a maximum nominal value of 2.38 MPa. Results obtained using RSM are shown to match well with a benchmark direct Monte Carlo simulation method. The resulting probability that the maximum cement stress will exceed the nominal stress is 62%. The load and the bone and prosthesis geometries were found to be the parameters most likely to influence the magnitude of the cement stresses and therefore to contribute most to the probability of failure.