Use of a genetic algorithm for multiobjective design optimization of the femoral stem of a cemented total hip arthroplasty

Towards an optimal design of a functionally graded porous uncemented acetabular component using genetic algorithm

Generation of polyethylene wear debris and peri‑prosthetic bone resorption have been identified as potential causes of acetabular component loosening in Total Hip Arthroplasty. This study was aimed at optimization of a functionally graded porous acetabular component to minimize peri‑prosthetic bone resorption and polyethylene liner wear. Porosity levels (porosity values at acetabular rim, and dome) and functional gradation exponents (radial and polar) were considered as the design parameters. The relationship between porosity and elastic properties were obtained from numerical homogenization. The multi-objective optimization was carried out using a non-dominated sorting genetic algorithm integrated with finite element analysis of the hemipelvises subject to various loading conditions of common daily activities. The optimal functionally graded porous designs (OFGPs -1, -2, -3, -4, -5) exhibited less strain-shielding in cancellous bone compared to solid metal-backing. Maximum bone-implant interfacial micromotions (63-68 μm) for OFGPs were found to be close to that of solid metal-backing (66 μm), which might facilitate bone ingrowth. However, OFGPs exhibited an increase in volumetric wear (3-10 %) compared to solid metal-backing. The objective functions were found to be more sensitive to changes in polar gradation exponent than radial gradation exponent, based on the Sobol' method. Considering the common failure mechanisms, OFGP-1, having highly porous acetabular rim and less porous dome, appears to be a better alternative to the solid metal-backing.

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents

In vehicle-pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle-pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms-nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)-were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions.

In Silico Optimization of Femoral Fixator Position and Configuration by Parametric CAD Model

Structural analysis, based on the finite element method, and structural optimization, can help surgery planning or decrease the probability of fixator failure during bone healing. Structural optimization implies the creation of many finite element model instances, usually built using a computer-aided design (CAD) model of the bone-fixator assembly. The three most important features of such CAD models are: parameterization, robustness and bidirectional associativity with finite elements (FE) models. Their significance increases with the increase in the complexity of the modeled fixator. The aim of this study was to define an automated procedure for the configuration and placement of fixators used in the treatment of long bone fractures. Automated and robust positioning of the selfdynamisable internal fixator on the femur was achieved and sensitivity analysis of fixator stress on the change of major design parameters was performed. The application of the proposed methodology is considered to be beneficial in the preparation of CAD models for automated structural optimization procedures used in long bone fixation.

Optimization of a Functionally Graded Material Stem in the Femoral Component of a Cemented Hip Arthroplasty: Influence of Dimensionality of FGM

The longevity of hip prostheses is contingent on the stability of the implant within the cavity of the femur bone. The cemented fixation was mostly adopted owing to offering the immediate stability from cement-stem and cement-bone bonding interfaces after implant surgery. Yet cement damage and stress shielding of the bone were proven to adversely affect the lifelong stability of the implant, especially among younger subjects who tend to have an active lifestyle. The geometry and material distribution of the implant can be optimized more efficiently with a three-dimensional realistic design of a functionally graded material (FGM). We report an efficient numerical technique for achieving this objective, for maximum performance stress shielding and the rate of early accumulation of cement damage were concurrently minimized. Results indicated less stress shielding and similar cement damage rates with a 2D-FGM implant compared to 1D-FGM and Titanium alloy implants.

Minimizing Stress Shielding and Cement Damage in Cemented Femoral Component of a Hip Prosthesis through Computational Design Optimization

The average life expectancy of many people undergoing total hip replacement (THR) exceeds twenty-five years and the demand for implants that increase the load-bearing capability of the bone without affecting the short- or long-term stability of the prosthesis is high. Mechanical failure owing to cement damage and stress shielding of the bone are the main factors affecting the long-term survival of cemented hip prostheses and implant design must realistically adjust to balance between these two conflicting effects. In the following analysis we introduce a novel methodology to achieve this objective, the numerical technique combines automatic and realistic modeling of the implant and embedding medium, and finite element analysis to assess the levels of stress shielding and cement damage and, finally, global optimization, using orthogonal arrays and probabilistic restarts, were used. Applications to implants, fabricated using a homogeneous material and a functionally graded material, were presented.

The Applications of Genetic Algorithms in Medicine

A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.].

A Genetic Algorithm Based Multi-Objective Shape Optimization Scheme for Cementless Femoral Implant

The shape and geometry of femoral implant influence implant-induced periprosthetic bone resorption and implant-bone interface stresses, which are potential causes of aseptic loosening in cementless total hip arthroplasty (THA). Development of a shape optimization scheme is necessary to achieve a trade-off between these two conflicting objectives. The objective of this study was to develop a novel multi-objective custom-based shape optimization scheme for cementless femoral implant by integrating finite element (FE) analysis and a multi-objective genetic algorithm (GA). The FE model of a proximal femur was based on a subject-specific CT-scan dataset. Eighteen parameters describing the nature of four key sections of the implant were identified as design variables. Two objective functions, one based on implant-bone interface failure criterion, and the other based on resorbed proximal bone mass fraction (BMF), were formulated. The results predicted by the two objective functions were found to be contradictory; a reduction in the proximal bone resorption was accompanied by a greater chance of interface failure. The resorbed proximal BMF was found to be between 23% and 27% for the trade-off geometries as compared to ∼39% for a generic implant. Moreover, the overall chances of interface failure have been minimized for the optimal designs, compared to the generic implant. The adaptive bone remodeling was also found to be minimal for the optimally designed implants and, further with remodeling, the chances of interface debonding increased only marginally.

Three-dimensional shape optimization of a cemented hip stem and experimental validations

This study proposes novel optimized stem geometry with low stress values in the cement using a finite element (FE) analysis combined with an optimization procedure and experimental measurements of cement stress in vitro. We first optimized an existing stem geometry using a three-dimensional FE analysis combined with a shape optimization technique. One of the most important factors in the cemented stem design is to reduce stress in the cement. Hence, in the optimization study, we minimized the largest tensile principal stress in the cement mantle under a physiological loading condition by changing the stem geometry. As the next step, the optimized stem and the existing stem were manufactured to validate the usefulness of the numerical models and the results of the optimization in vitro. In the experimental study, strain gauges were embedded in the cement mantle to measure the strain in the cement mantle adjacent to the stems. The overall trend of the experimental study was in good agreement with the results of the numerical study, and we were able to reduce the largest stress by more than 50% in both shape optimization and strain gauge measurements. Thus, we could validate the usefulness of the numerical models and the results of the optimization using the experimental models. The optimization employed in this study is a useful approach for developing new stem designs.

Artificial organs 2011: a year in review

In this Editor's Review, articles published in 2011 are organized by category and briefly summarized. As the official journal of The International Federation for Artificial Organs, The International Faculty for Artificial Organs, and the International Society for Rotary Blood Pumps, Artificial Organs continues in the original mission of its founders "to foster communications in the field of artificial organs on an international level."Artificial Organs continues to publish developments and clinical applications of artificial organ technologies in this broad and expanding field of organ replacement, recovery, and regeneration from all over the world. We take this time also to express our gratitude to our authors for offering their work to this journal. We offer our very special thanks to our reviewers who give so generously of time and expertise to review, critique, and especially provide meaningful suggestions to the author's work whether eventually accepted or rejected. Without these excellent and dedicated reviewers, the quality expected from such a journal would not be possible. We also express our special thanks to our Publisher, Wiley-Blackwell, for their expert attention and support in the production and marketing of Artificial Organs. In this Editor's Review, that historically has been widely well-received by our readership, we aim to provide a brief reflection of the currently available worldwide knowledge that is intended to advance and better human life while providing insight for continued application of technologies and methods of organ replacement, recovery, and regeneration. We look forward to recording further advances in the coming years.