Abstract
Today, different implant designs exist in the market; however, there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. Therefore, the aim of this project was to investigate if the geometry of a commercial short stem hip prosthesis can be further optimized to reduce stress shielding effects and achieve better short-stemmed implant performance. To reach this aim, the potential of machine learning techniques combined with parametric Finite Element analysis was used. The selected implant geometrical parameters were: total stem length (L), thickness in the lateral (R1) and medial (R2) and the distance between the implant neck and the central stem surface (D). The results show that the total stem length was not the only parameter playing a role in stress shielding. An optimized implant should aim for a decreased stem length and a reduced length of the surface in contact with the bone. The two radiuses that characterize the stem width at the distal cross-section in contact with the bone were less influential in the reduction of stress shielding compared with the other two parameters; but they also play a role where thinner stems present better results.
Highlights
The importance of a medical treatment is reflected by the number of procedures carried out per year in a population
We investigated whether the geometry of a short stem hip implant can be further optimized to reduce stress shielding at the proximal femur
Finite Element (FE) analyses were combined with Machine Learning Techniques (MLT) and search pattern minimization algorithms
Summary
The importance of a medical treatment is reflected by the number of procedures carried out per year in a population. One million of hip fractures occur worldwide every year. The rate of hip replacements increased by about 25% between 2000 and 2009 [1], and this trend is expected to continue in the decades due to the ageing population, improving medical care in developing countries and decreasing average age at the first operation [2]. Children and young people, whose life expectancy largely surpasses the mean lifetime of an implant, and they often requiring a revision surgery [2], represent a portion of these patients.
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