Robust optimization of total joint replacements incorporating environmental variables

Physicomechanical, morphological and tribo-deformation characteristics of lightweight WC/AZ31B Mg-matrix biocomposites for hip joint applications

Exploring high strength materials with a higher concentration of reinforcements in the alloy proves to be a challenging task. This research has explored magnesium-based composites (AZ31B alloy) with tungsten carbide reinforcements, enhancing strength for medical joint replacements via league championship optimisation. The primary objective is to enhance medical joint replacement biomaterials employing magnesium-based composites, emphasising the AZ31B alloy with tungsten carbide reinforcements. The stir casting method is utilised in the manufacture of magnesium matrix composites (MMCs), including varied percentages of tungsten carbide (WC). The mechanical characteristics, such as micro-hardness, tensile strength, and yield strength, have been assessed and compared with computational simulations. The wear studies have been carried out to analyse the tribological behaviour of the composites. Additionally, this study investigates the prediction of stress and the distribution of forces inside bone and joint structures, therefore offering significant contributions to the field of biomedical research. This research contemplates the use of magnesium-based MMCs for the discovery of biomaterials suitable for medical joint replacement. The study focuses on the magnesium alloy AZ31B, with particles ranging in size from 40 to 60 microns used as the matrix material. Moreover, the outcomes have revealed that when combined with MMCs based on AZ31B-magnesium matrix, the WC particle emerges as highly effective reinforcements for the fabrication of lightweight, high-strength biomedical composites. This study uses the league championship optimisation (LCO) approach to identify critical variables impacting the synthesis of Mg MMCs from an AZ31B-based magnesium alloy. The scanning electron microscopy (SEM) images are meticulously analysed to depict the dispersion of WC particulates and the interface among the magnesium (Mg) matrix and WC reinforcement. The SEM analysis has explored the mechanisms underlying particle pull-out, the characteristics of inter-particle zones, and the influence of the AZ31B matrix on the enhancement of the mechanical characteristics of the composites. The application of finite element analysis (FEA) is being used in order to make predictions regarding the distribution of stress and the interactions of forces within the model of the hip joint. This study has compared the physico-mechanical and tribological characteristics of WC to distinct combinations of 0%, 5%, 10% and 15%, and its impact on the performance improvements. SEM analysis has confirmed the findings' improved strength and hardness, particularly when 10%-15% of WC was incorporated. Following the incorporation of 10% of WC particles within Mg-alloy matrix, the outcomes of the study has exhibited enhanced strength and hardness, which furthermore has been evident by utilising SEM analysis. Using ANSYS, structural deformation and stress levels are predicted, along with strength characteristics such as additional hardness of 71 HRC, tensile strength of 140-150 MPa, and yield strength closer to 100-110 MPa. The simulations yield significant insights into the behaviour of the joint under various loading conditions, thus enhancing the study's significance in biomedical environments.

Application of finite element analysis to tissue differentiation and bone remodelling approaches and their use in design optimization of orthopaedic implants: A review

Post-operative bone growth and long-term bone adaptation around the orthopaedic implants are simulated using the mechanoregulation based tissue-differentiation and adaptive bone remodelling algorithms, respectively. The primary objective of these algorithms was to assess biomechanical feasibility and reliability of orthopaedic implants. This article aims to offer a comprehensive review of the developments in mathematical models of tissue-differentiation and bone adaptation and their applications in studies involving design optimization of orthopaedic implants over three decades. Despite the different mechanoregulatory models developed, existing literature confirm that none of the models can be highly regarded or completely disregarded over each other. Not much development in mathematical formulations has been observed from the current state of knowledge due to the lack of in vivo studies involving clinically relevant animal models, which further retarded the development of such models to use in translational research at a fast pace. Future investigations involving artificial intelligence (AI), soft-computing techniques and combined tissue-differentiation and bone-adaptation studies involving animal subjects for model verification are needed to formulate more sophisticated mathematical models to enhance the accuracy of pre-clinical testing of orthopaedic implants.

Surrogate articular contact models for computationally efficient multibody dynamic simulations

Contact occurs in a wide variety of multibody dynamic systems, including the human musculoskeletal system. However, sensitivity and optimization studies of such systems have been limited by the high computational cost of repeated contact analyses. This study presents a novel surrogate modeling approach for performing computationally efficient three-dimensional elastic contact analyses within multibody dynamic simulations. The approach fits a computationally cheap surrogate contact model to data points sampled from a computationally expensive elastic contact model (e.g., a finite element or elastic foundation model) and resolves several unique challenges involved in applying surrogate modeling techniques to elastic contact problems. As an example application, we performed multibody dynamic simulations of a Stanmore wear simulator machine using surrogate and elastic foundation (EF) contact models of a total knee replacement. Accuracy was assessed by performing eleven dynamic simulations with both types of contact models utilizing large variations in motion and load inputs to the machine. Wear volumes predicted with the surrogate contact models were within 1.5% of those predicted with the EF contact models. Computational speed was assessed by performing five Monte Carlo analyses (over 1000 dynamic simulations each) with surrogate contact models utilizing realistic variations in motion and load inputs. Computation time was reduced from an estimated 284 h per analysis with the EF contact models to 1.4 h with the surrogate contact models (i.e., 17 min vs. 5 s per simulation), with higher wear sensitivity observed for motion variations than for load variations. The proposed surrogate modeling approach can significantly improve the computational speed of multibody dynamic simulations incorporating three-dimensional elastic contact models with general surface geometry.

Two-Dimensional Surrogate Contact Modeling for Computationally Efficient Dynamic Simulation of Total Knee Replacements

Computational speed is a major limiting factor for performing design sensitivity and optimization studies of total knee replacements. Much of this limitation arises from extensive geometry calculations required by contact analyses. This study presents a novel surrogate contact modeling approach to address this limitation. The approach involves fitting contact forces from a computationally expensive contact model (e.g., a finite element model) as a function of the relative pose between the contacting bodies. Because contact forces are much more sensitive to displacements in some directions than others, standard surrogate sampling and modeling techniques do not work well, necessitating the development of special techniques for contact problems. We present a computational evaluation and practical application of the approach using dynamic wear simulation of a total knee replacement constrained to planar motion in a Stanmore machine. The sample points needed for surrogate model fitting were generated by an elastic foundation (EF) contact model. For the computational evaluation, we performed nine different dynamic wear simulations with both the surrogate contact model and the EF contact model. In all cases, the surrogate contact model accurately reproduced the contact force, motion, and wear volume results from the EF model, with computation time being reduced from 13minto13s. For the practical application, we performed a series of Monte Carlo analyses to determine the sensitivity of predicted wear volume to Stanmore machine setup issues. Wear volume was highly sensitive to small variations in motion and load inputs, especially femoral flexion angle, but not to small variations in component placements. Computational speed was reduced from an estimated 230hto4h per analysis. Surrogate contact modeling can significantly improve the computational speed of dynamic contact and wear simulations of total knee replacements and is appropriate for use in design sensitivity and optimization studies.

What design factors influence wear behavior at the bearing surfaces in total joint replacements?

Bearing surface wear in total joint replacements arises from local stresses that exceed the mechanical strength of the articulating materials. Because both the tensile/compressive principal stresses and maximum shear stress near the bearing surface increase when contact stresses increase, minimizing contact stresses has been a central design goal, especially in total knees. Wear rates increase with factors such as increased sliding distance in metal-on-polyethylene bearings, or suboptimal fluid film lubrication in the case of hard-on-hard total hip implants. These factors in turn depend directly on implant design. Advanced preclinical assessment technologies such as laboratory physical simulators and finite element analyses have provided means by which the dependence of wear rate on mechanical design factors can be quantified. However, untoward complexities occurring in vivo, such as impingement or third-body challenge, can appreciably compromise wear performance even for implants that are well-designed in terms of bearing surface stress minimization.

The effect of three-dimensional shape optimization on the probabilistic response of a cemented femoral hip prosthesis

Probabilistic analyses allow the effect of uncertainty in system parameters on predicted model performance measures to be determined. Furthermore, using performance functions to describe a failure event, the probability of failure can be quantified. The effect of three-dimensional prosthesis shape optimization on the probabilistic response and failure probability of a cemented hip prosthesis system is investigated. Random variables include joint and muscle loading, cortical and cancellous bone and PMMA bone cement elastic properties, and strength parameters describing failure of the bone cement and the prosthesis-bone cement interface. Several performance functions describing the bone cement and prosthesis-cement interface are used to compute the probability of failure. When evaluated deterministically, most performance functions indicated a safe design, with the exception of interface tensile failure. However, when evaluated probabilistically, finite probabilities of failure were computed, some significant. The most likely mode of failure before shape optimization was prosthesis-bone cement interface tensile failure with a predicted probability of failure of 97.9%. Deterministic prosthesis shape optimization reduced the probability of failure for all performance functions and reduced prosthesis-bone cement interface tensile failure by 31.7%. Probability sensitivity factors indicate that the uncertainty in the joint loading, cement strength, and implant-cement interface strength have the greatest effect on the computed probability of failure. Implant shape optimization results in a more robust implant design that is less sensitive to uncertainties in joint loading, which cannot be easily controlled, and more sensitive to cement and interface properties, which are easier to modify.

Acetabular Cup Geometry and Bone-Implant Interference have More Influence on Initial Periprosthetic Joint Space than Joint Loading and Surgical Cup Insertion

Environmental variations in patient-dependent and surgical factors were modeled using robust optimization with a finite element acetabular cup-pelvis model. A previously developed statistical optimization scheme was used to: (1) determine the cup geometry and the optimal cup-bone interference that maximized bone-implant contact areas and minimized changes in the gap volume between the implant and bone surface during gait loading and unloading; and (2) determine the relative contributions of design, patient-dependent, and surgical factors to variations in bone-implant contact areas and a change in gap volume. The statistical analyses indicated that the design variables, namely the equatorial diameter and eccentricity, explained most of the variations in the performance measures. Further, the hemispherical designs performed better than the nonhemispherical designs. The 58mm hemispherical cup, with 2mm diametral interferences, minimized the change in gap volume and attained 82% and 81% of the maximum predicted total and rim contact areas, respectively. The equatorial diameter and eccentricity, not the patient-dependent and surgical factors, explained most of the variations in the performance measures. Perfect surface apposition was not attained with any of the cup designs.

Design optimization of cementless femoral hip prostheses using finite element analysis

Implant separation from bone tissue, resulting in the necessity for revision surgery, is a serious drawback of cementless total joint replacement. Unnatural stress distribution around the implant is considered the main reason for the failure. Optimization of the implant properties, especially its geometric parameters, is believed to be the right way to improve reliability of joint prosthetics. An efficient numerical model of thefemur-implant system is presented in the paper, including the finite element formulation featuring computation of sensitivity gradients, parametric mesh generator, and a gradient-based optimization scheme. Numerical examples show results of shape optimization of an implant for two sets of design parameters and for the initial stability criterion taken as the optimization goal. The optimum shape appears to be relatively long and proximally porous-coated on about half of its length. The method can be flexibly adjusted to various implant types, stress- and displacement-based optimum criteria, and geometric design parameters.

Design and analysis of robust total joint replacements: finite element model experiments with environmental variables

Computer simulation of orthopaedic devices can be prohibitively time consuming, particularly when assessing multiple design and environmental factors. Chang et al. (1999) address these computational challenges using an efficient statistical predictor to optimize a flexible hip implant, defined by a midstem reduction, subjected to multiple environmental conditions. Here, we extend this methodology by: (1) explicitly considering constraint equations in the optimization formulation, (2) showing that the optimal design for one environmental distribution is robust to alternate distributions, and (3) illustrating a sensitivity analysis technique to determine influential design and environmental factors. A thin midstem diameter with a short stabilizing distal tip minimized the bone remodeling signal while maintaining satisfactory stability. Hip joint force orientation was more influential than the effect of the controllable design variables on bone remodeling and the cancellous bone elastic modulus had the most influence on relative motion, both results indicating the importance of including uncontrollable environmental factors. The optimal search indicated that only 16 to 22 computer simulations were necessary to predict the optimal design, a significant savings over traditional search techniques.