Synchrotron-Based Analysis of Conical Implant–Abutment Connections Under Mechanical Load: How Embedding Materials Influence the Microgap and Implant Shoulder Deformation

Abstract

Objectives: Dental implants have become a reliable solution for oral rehabilitation, but their long-term success can be compromised by factors such as mechanical overload. To ensure the mechanical durability of implants, standardized testing in accordance with the DIN EN ISO 14801 is conducted, in which titanium implants (Young's modulus of approximately 100 GPa) are embedded in brass, a material with similarly high stiffness. However, the mechanical properties of brass differ significantly from those of alveolar bone, potentially affecting test outcomes. This study examines how different embedding materials affect the mechanical behavior of dental implants, specifically microgap changes and deformation at the IAC under load. Materials and Methods: Two conical dental implants were embedded in either methyl methacrylate-based adhesive (PMMA) or brass. A 250 N load was applied at a 45° angle to the implants. Synchrotron-based microcomputed tomography (µCT) was used to assess microgap formation and 3D deformation at the implant shoulder before and under load application. Deformation was analyzed using Avizo Fire software to estimate volumetric changes at the implant shoulder. Results: The results showed that implants embedded in brass exhibited larger microgap changes (53 μm) and greater deformation at the implant shoulder (32 μm) compared to those embedded in PMMA (microgap: 40 μm). Conclusion: The findings suggest that brass, with higher stiffness than PMMA or bone, does not accurately replicate the mechanical conditions of bone, leading to a difference in microgap behavior and deformation at the implant shoulder, suggesting a difference in the wear mechanism and stress-strain distribution in the surrounding bone. These results question the use of brass in mechanical implant testing and highlight the need for more realistic embedding materials to improve the predictive value of implant testing.