Prediction of dental implant treatment using computer Simulation
Prof. Ho Beom Kwon, Dr. Mi-El Kim, Dr. Mary Delia Z Bondoc, Dr. Ji-Yeon Kim
Seoul National University School of Dentistry
Objectives
This study aims to utilize computer simulation on patient-specific models to predict dental implant treatment outcomes.
Materials and Methods
Three-dimensional models of the implant-bone interface were created using CT scans of a patient who underwent mandibulectomy and received surgical reconstruction for the treatment of SCC. The patient presented with functional and aesthetic concerns, urgently seeking restoration of mastication function. Anatomic data and prosthetic components were separately modeled using dental CAD software. A screw-retained type prosthesis was designed, with simulated cement layers between custom abutments and the mesostructure, and between the mesostructure and prosthesis. Contact surfaces were simulated at the mating surfaces between the abutment and the top of the implant, screw head and abutment, and abutment screw and implant inner part. Attachment areas for jaw closing muscles, including the masseter, temporal, internal pterygoid, and upper part of the condyle, were constrained. Preloads of 500N were applied to the abutment screw to mimic clinical conditions. Oblique loadings were applied to the left and right sides of the posterior teeth, simulating biting on hard food. Von Mises stress analysis and displacement analysis were performed to assess biomechanical behavior and predict treatment prognosis.
Results
The FEA simulations accurately predicted stress distribution, strain patterns, and component displacement under different loading scenarios. Von Mises stress analysis identified critical areas of stress concentration, while displacement analysis revealed implant stability and micromotion relative to surrounding bone and tissues. Sensitivity analyses allowed for the optimization of treatment plans to minimize risks and improve long-term prognosis.
Conclusions
Patient-specific finite element analysis offered a powerful tool for predicting dental implant treatment outcomes. By integrating anatomical data and biomechanical analysis, clinicians can optimize treatment planning, assess implant stability, and predict treatment prognosis with greater accuracy and precision. This approach holds significant promise for enhancing clinical decision-making and improving patient care in implant dentistry.