OPTIMISATION OF A FUNCTIONALLY GRADED HIP STEM MADE OF POROUS METALLIC MATERIAL
Notice bibliographique
Résumé
Introduction After arthroplasty, stress shielding and high shear stresses at the bone-implant interface are common problems of load bearing implants (e.g. hip prostheses). Stiff implants cause stress shielding, which is thought to contribute to bone resorption 1 . High shear stresses, originated by low-stiffness implants, have been related to pain and interfacial micro-movements², prohibiting adequate implant initial fixation. A non-homogeneous distribution of mechanical properties within the implant could reduce the stress shielding and interfacial shear stresses 3 . Such an implant is called “functionally graded implant” (FGI). FGI require porous materials with well-controlled micro-architecture, which can now be obtained with new additive manufacturing technologies (e.g. Electron Beam Melting). Finite element (FE) simulations in ANSYS-v14.5 are used to develop an optimization methodology to design a hip FGI. Methodology A coronal cut was performed on a femur model (Sawbones®) with an implanted Profemur®TL (Wright Medical Inc.) stem to obtain the 2D-geometry for FE simulations. The central part of the FGI stem was made porous, the neck and inferior tip were solid. Ti6Al4V elastic material was assumed (E=120 GPa, v=0.3). Three bone qualities were considered for the optimization: poor (E=6GPa; v=0.3); good (E=12GPa; v=0.3); excellent (E=30GPa; v=0.3). The structure of bone evolves to maintain a reasonable level of the strains. Similarly in the proposed algorithm, the strut sections of the porous material evolve to keep stresses (proportional to strains) at a reasonable level. Starting with a very small strut section, resulting in an almost zero-rigidity stem, strut sections are increased or decreased as a function of the stresses they support. This is done incrementally, until force values corresponding to normal walking of an 80 kg person (1867 N) 4 are reached. Force direction was vertical and no action of the abductors was considered, to analyze the worst case scenario. The optimized FGI microstructure is defined by the strut diameter distributions. Since the distance between struts remain constant, variations in strut diameters result in variations in density. Optimized FGI porous structure was compared for the three bone qualities considered and with a solid stem in terms of bone stresses. Results Different bone qualities result in slightly different strut diameter distribution (Fig.1). An excellent bone quality (E=30 GPa) results in a less dense porous structure, where some dense zones are substituted by a thick strut surrounded by a low density area. As can be expected, a poor bone quality (E=6 GPa) results in a denser porous structure. Compared with the solid stem, in general the FGI stem produced higher bone stresses. Locally, the stresses augmented proximally, while diminished distally (Fig.2). This is expected to result in a smaller influence of stress shielding, and better load transfer. Conclusion The presented algorithm succeeded obtaining an optimal strut diameter distribution from low rigidity struts, using a strategy similar to bone remodelling (i.e. maintaining certain stress level within the struts). Optimized diameter distribution was obtained with little computational cost.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».