Experimental validation of a micro-CT finite element model of a human cadaveric mandible rehabilitated with short-implant-supported partial dentures

PURPOSE: This study aimed to address the predictive value of a micro-computed tomography (μCT)-based finite element (μFE) model of a human cadaveric edentulous posterior mandible, rehabilitated by short dental implants. Hereby, three different prosthetic/implant configurations of fixed partial dentures ("Sp"-3 splinted crowns on 3 implants, "Br" - Bridge: 3 splinted crowns on 2 implants, and "Si"- 3 single crowns) were analysed by comparing the computational predictions of the global stiffness with experimental data. METHODS: Experimental displacement of the bone/implant/prosthesis system was measured under axial and oblique loads of 100 N using an optical deformation system (GOM Aramis) and the overall movement of the testing machine (Zwick Z030). Together with the measured machine force, an "Aramis" (optical markers) and "Zwick" (test machine) stiffness were calculated. FE models were created based on μCT-scans of the cadaveric mandible sample (n = 1) before and after implantation and using stl-files of the crowns. The same load tests and boundary conditions were simulated on the models and the μFE-results were compared to experimental data using linear regression analysis. RESULTS: of 0.80, but the FEA-stiffness was 7.2 times higher. The factor was highly dependent on the test configuration. Sp-configuration showed the largest stiffness followed by Br-configuration (17% difference in experiment and 21% in FEA). CONCLUSIONS: The current study showed good qualitative agreement between the experimental and predicted global stiffness of different short implant configurations. It could be deduced that 1:1 splinting of the short implants by the crowns is most favorable for the stiffness of the implant/prosthesis system. However, in the clinical context, the absolute in silico readings must be interpreted cautiously, as the FEA showed a considerable overestimation of the values.