IADR Abstract Archives
Occlusion: a key Parameter in the Construction of Patient-Specific Models
Objectives: Understand the mechanical behaviour of teeth is decisive to improve the long-term survival of our treatments. This has traditionally been analysed using finite element models and more recently by patient-specific modelling to consider individual variability and predict more precisely outcomes. Following the growth in computer science, heterogenous parameters have been used to develop these predictive models however without clear evidence on the exact influence of each parameter value and potential clinical implications. The aim of this study was to compare the influence of major simulation parameters on stress distribution using sensitivity analysis.
Methods: The finite element model of a maxillary arch was constructed using a previously reported protocol. Following a full factorial design of experiments, sixteen four models were then generated to evaluate all combinations of the six following parameters axis of loading (axial/lateral force), intensity of loading (150/300 N), dentin elasticity (15/18.6 GPa), length of arch (3 teeth/ half full arch) element size (100/300 micron) ligament (absence/presence). For each model, the root von Mises stresses of the right first premolar were extracted and analysed using analysis of variance (ANOVA).
Results: The stress distribution was similar for all models except for models with lateral force that present highest stresses on the peripheral parts of the root. Results of ANOVA analysis revealed that axis and intensity of loading were the most influent factors, explaining 40 % of the mechanical values.
Conclusions: Define precisely the occlusion of the patient appeared essential to construct a predictive model as a small error on this parameter could greatly influence the biomechanical analysis and potentially lead to therapeutical choices poorly adapted to the patient. However, further investigations are required to evaluate if such an influence is present independently from other clinical parameters such tooth type or substance loss.
Methods: The finite element model of a maxillary arch was constructed using a previously reported protocol. Following a full factorial design of experiments, sixteen four models were then generated to evaluate all combinations of the six following parameters axis of loading (axial/lateral force), intensity of loading (150/300 N), dentin elasticity (15/18.6 GPa), length of arch (3 teeth/ half full arch) element size (100/300 micron) ligament (absence/presence). For each model, the root von Mises stresses of the right first premolar were extracted and analysed using analysis of variance (ANOVA).
Results: The stress distribution was similar for all models except for models with lateral force that present highest stresses on the peripheral parts of the root. Results of ANOVA analysis revealed that axis and intensity of loading were the most influent factors, explaining 40 % of the mechanical values.
Conclusions: Define precisely the occlusion of the patient appeared essential to construct a predictive model as a small error on this parameter could greatly influence the biomechanical analysis and potentially lead to therapeutical choices poorly adapted to the patient. However, further investigations are required to evaluate if such an influence is present independently from other clinical parameters such tooth type or substance loss.