Numerical Simulation of Functional Evaluation for Implant-Supported Complete Maxillary Denture with an Efficient CT Image Segmentation and Mesh Creation Technique

Objective: This study aims to create twelve numerical models of implant-supported attachment-retained complete maxillary dentures by an efficient CT image segmentation and mesh creation technique, as well as evaluate mechanical characteristics of Model 1. Methods: Masks were first created after identifying regions of interest on CT scan images of maxillary prosthesis, then integrated with CAD models of implant, and finally meshed by extended volumetric marching cubes (EVoMaC) approach. Von Mises stress of edentulous maxilla restored with six anterior implants and resilient attachments placed distal to canines (Model 1) were determined under oblique, vertical and horizontal forces, respectively. Results: Twelve complete maxillary denture meshed models were successfully developed, which could be imported directly into the finite element package and analyzed without any manual correction. As to Model 1, maximum von Mises stress values of peri-implant bone were observed on the mesial cervical area around loaded side canine implant under different loads. Furthermore, there were no significant differences between maximum stress values of loaded side canine implant and those of central incisor implant, both of which were more than those of lateral incisor implant under all loads. Conclusion: The pioneering image segmentation and mesh development approach used in current study is an effective and successful technique in numerical simulation of functional evaluation for dental prosthesis design optimization, and can be applicable to visualization and simulation of other human bones and prostheses with complex internal architectures. In addition, simulated results imply that bone quality before healing and bone loss after treatment in canine region are of particular importance to the long-term success of Model 1.