The two major goals of this study were to develop a murine model of osseointegration and to determine whether removing surface contaminants enhances osseointegration. The novel murine model of osseointegration is based on a previous established rat model [41
]. Titanium alloy implants were implanted into a unicortical pilot hole in the mid-diaphysis of the femur and osseointegration was measured over a 5 week time course. Histology, backscatter scanning electron microscopy and x-ray energy dispersive spectroscopy showed areas of bone in intimate physical contact with the implant, confirming osseointegration. Histomorphometric measures of BIC and peri-implant bone and biomechanical measures of ultimate force, stiffness and work to failure increased significantly over time, also demonstrating successful osseointegration. This model was then used to determine whether removing contaminants, such as bacterial debris or manufacturing residues, remaining on orthopaedic implants after sterilization enhances osseointegration. We found that a rigorous cleaning procedure [30
] significantly enhances osseointegration compared with implants that were autoclaved, as recommended by the manufacturer. The most likely interpretation of these results is that surface contaminants inhibit osseointegration.
Our murine model of osseointegration will provide two major benefits compared with current larger animal models [50
]. First, it will allow the use of knock-out and transgenic mice to test the role of specific genes and molecular pathways in osseointegration. Second, it will allow for cost effective screening of potential countermeasures for impaired osseointegration prior to testing in larger animals. Two laboratories reported preliminary osseointegration studies in mice in the mid-1990s [51
]. Recently, osseointegration studies in mice have demonstrated that molecular pathways known to regulate bone turnover also affect osseointegration. Colnot and colleagues used in situ hybridization to show that integration around titanium alloy implants involves molecular markers of bone remodeling [54
]. Studies utilizing knock-out mice demonstrated that cyclooxygenase-2 and fibroblast growth factor receptor-3 play important roles in osseointegration [55
]. Other investigators found that osseointegration is enhanced with local administration of retroviruses encoding osterix or by pre-coating titanium implants with fibronectin [27
]. The performance of stainless steel and poly-lactide implants have also been examined in murine models [58
]. However, osteoblasts do not form bone directly on these materials, which limits their usefulness in the study of osseointegration. Lastly, titanium ring implants were studied in murine calvaria [60
]. However, this study was focused on vertical bone growth around the ring implants, rather than integration. None of these previous studies examined clinically relevant implants or included biomechanical testing to fully characterize murine osseointegration. Biomechanical testing is necessary to evaluate the ability of an implant to sustain a load, an essential component of osseointegration. Our model includes a time course, appropriate sample size, quantitative analysis, clinically relevant implants and biomechanical testing. This is the first murine osseointegration study we know of that has included all of these parameters.
One limitation of our model is that it requires the use of young mice, since increased muscle size in older mice makes exposure of the femur prior to implantation extremely difficult without inducing extensive soft tissue damage. Young mice differ from older mice, most notably in their potential for bone regeneration [61
]. In addition, mice have lower mechanical loads supporting their bones and a higher potential for bone regeneration than larger animals such as humans. The implant in our model is under non-loading conditions. However, non-loading models are useful to examine materials, coatings, or the effects of surface modifications on osseointegration before testing in a loading model [50
]. Another limitation of our model is that because of the implant’s small size, it is only possible to obtain one central histological section of the implant per mouse. Moreover, biomechanical testing can only be performed at time points up to 3 weeks following implantation because bone growth around the neck of the implant prevents gripping of the implant to perform testing. Despite these limitations, a murine model of osseointegration provides significant advantages as discussed in the previous paragraph and is appropriate for examining certain types of questions, such as whether surface contaminants inhibit osseointegration.
In our model, osseointegration occurs rapidly between 1 and 2 weeks (), most likely because of the high potential for bone regeneration in young mice [61
]. After 2 weeks, further osseointegration is modest, and bone remodeling is most likely occuring after this time point. Both histomorphometric and biomechanical measures increase in parallel (), similar to the rat model of osseointegration described by Gabet and colleagues [41
]. The forces that are measured by biomechanical pullout testing arise from the new bone in contact with the implant (BIC) as well as the bone in between the implant threads (peri-implant bone). Therefore, the three parameters of ultimate force, stiffness and work to failure that are generated from biomechanical testing, provide information about the mineralized tissue in the BIC and/or peri-implant bone [62
]. Ultimate force is a measure of the failure of the mineralized tissue within the threads and is therefore dominated by the peri-implant bone. Stiffness is the immediate resistance of the mineralized tissue on the implant surface to deformation and is therefore dominated by the BIC. Work to failure is a measure of the energy that can be absorbed by the mineralized tissue and is the area under the force versus displacement curve. Therefore, work to failure is influenced by both the stiffness (BIC) and ultimate force (peri-implant bone)
We found that contaminants remaining on the implant surface after sterilization significantly inhibits osseointegration as assessed by measurements of BIC and biomechanical pullout testing ( & ). Autoclaved implants had higher levels of LPS, derived from Gram-negative bacteria, when compared to the rigorously cleaned implants that have enhanced osseointegration. Because soluble LPS inhibits osteoblast cell differentiation on tissue culture plastic [63
], it is likely that adherent LPS on the surface of implants can inhibit osteoblast differentiation and thereby inhibit osseointegration. Our results do not however demonstrate that adherent LPS caused the impaired osseointegration since we can not exclude the possibility that other contaminants on the autoclaved implants may also impair osseointegration.
In this study, surface contaminants inhibited BIC and biomechanical pullout testing without affecting either peri-implant bone or the neo-cortex formation ( & ). These results are reminiscent of the finding that surface roughness enhanced BIC and biomechanical parameters in a rabbit osseointegration model but had no affect on peri-implant bone formation [23
]. Thus, both surface contaminants and surface topography primarily effect bone formation on the implant surface (BIC) and have less effect on more distant bone formation (peri-implant bone). In contrast, we would predict that stimulation of bone formation in general would increase both BIC and peri-implant bone as has been shown with systemic parathyroid hormone (PTH) treatment [42
]. In the PTH study, biomechanical pullout testing results primarily correlated with the amount of peri-implant bone formation rather than with BIC as we observed. This is likely due to the different spatial pattern of effects induced by implant surface modifications and systemic treatments.
In this study we developed a novel osseointegration model that provides quantitative and reproducible measurements of osseointegration in mice. Using this model, we found that contaminants on orthopaedic implants inhibit osseointegration as measured by histomorphometry and biomechanical pullout testing. The results of this study justify the need for the development of better detection and removal techniques for contaminants on orthopaedic implants and other medical devices.
- Developed a novel murine model of ossointegration
- Osseointegration characterized by histomorphometry, back-scatter SEM, XEDS, and biomechanical pullout testing
- Surface contaminants inhibited bone-to-implant contact and biomechanical pullout testing