Effect of the initial implant fitting on the predicted secondary stability of a cementless stem

Abstract

A numerical model able to investigate the influence of biomechanical factors on the long-term secondary stability of implants would be extremely useful for the design of new cementless prosthetic devices. A purely biomechanical model of osseo-integration has been developed, formulated as a rule-based adaptation scheme. Due to its complexity, the problem was divided into three steps: preliminary implementation of the model (proof of concept); implementation of the complete model and investigation of the model solution; and model validation. The paper describes the first of these three steps. The model was implemented as a discrete-states machine, and the few parameters required were derived from the literature. It was then applied to a real clinical case. The study was conducted using the frictional contact finite element model of a human femur implanted with a cementless anatomical stem. A stable solution was achieved after between three and 15 iterations for all initial positions considered. Similar initial conditions yielded similar final configurations. The model predicted all initial configurations, with the exception of a partial osseo-integration, ranging between 62% (distal fit) and 78% (proximal fit) of the viable interface. This is in good agreement with the values reported in the literature that never exceed 75%, even in the best conditions, and report better clinical results for proximal fit. For the varus configuration, which lacks cortical support, the algorithm predicted a completed loosening.

Searching for Smart Durable Coatings to Promote Bone Marrow Stromal Cell Growth While Preventing Biofilm Formation

“…There have been dramatic improvements in the quality and lifespan of such implants with a corresponding decreased incidence of complications. Typically, in regards to orthopedic devices, the primary concerns are wear [2] infection [3,4], and failure of biointegration [5,6]. Wear of the plastic component produces micro particles that cause an immunological response and adjacent bone resorption [2].…”

“…Infection, although less common, is devastating to the patient and costly to the health care system [3,4]. Failure of osseointegration of the prosthesis prevents long-term stability which contributes to pain [6], implant loosening [6], and infection [5] that usually necessitates revision. To prevent these complications, prostheses of the future must optimize the material composition of components.…”

Bone Implant Design Using Optimization Methods

“…However, this parameter is not considered as a requirement in the design model described in this chapter since its relevance is relative. In fact, even with a gap of 150 µm between the bone and stem, osseointegration can occur [31].…”

“…To take into account the mechanical factors mentioned above, an algorithm based on previous ingrowth models [12,31,47,48] is used. In this algorithm there are five levels for the interface stiffness, from 0 to 30 N mm −1 , as shown in Table 10.7.…”

In silico clinical trials: how computer simulation will transform the biomedical industry

“…[3][4][5][6][7][8][9][10] In the early 2000s, the computational ecology community started to debate the virtues of individual-based models for population ecology. 11 Soon after, in silico medicine research also began to use the first patient-specific models [12][13][14][15][16][17] and some analysts started to suggest that such approaches could be useful in the development of new medical products. 18 In 2007, a group of experts published "seeding the EuroPhysiome: a roadmap to the virtual physiological human".…”