Dynamic modelling of tooth deformation using occlusal kinematics and finite element analysis

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Abstract

Background: Dental biomechanics based on finite element (FE) analysis is attracting enormous interest in dentistry, biology, anthropology and palaeontology. Nonetheless, several shortcomings in FE modeling exist, mainly due to unrealistic loading conditions. In this contribution we used kinematics information recorded in a virtual environment derived from occlusal contact detection between high resolution models of an upper and lower human first molar pair (M1 and M1, respectively) to run a non-linear dynamic FE crash colliding test. Methodology: MicroCT image data of a modern human skull were segmented to reconstruct digital models of the antagonistic right M1 and M1 and the dental supporting structures. We used the Occlusal Fingerprint Analyser software to reconstruct the individual occlusal pathway trajectory during the power stroke of the chewing cycle, which was applied in a FE simulation to guide the M1 3D-path for the crash colliding test. Results: FE analysis results showed that the stress pattern changes considerably during the power stroke, demonstrating that knowledge about chewing kinematics in conjunction with a morphologically detailed FE model is crucial for understanding tooth form and function under physiological conditions. Conclusions/Significance: Results from such advanced dynamic approaches will be applicable to evaluate and avoid mechanical failure in prosthodontics/endodontic treatments, and to test material behavior for modern tooth restoration in dentistry. This approach will also allow us to improve our knowledge in chewing-related biomechanics for functional diagnosis and therapy, and it will help paleoanthropologists to illuminate dental adaptive processes and morphological modifications in human evolution.

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CITATION STYLE

APA

Benazzi, S., Nguyen, H. N., Kullmer, O., & Kupczik, K. (2016). Dynamic modelling of tooth deformation using occlusal kinematics and finite element analysis. PLoS ONE, 11(3). https://doi.org/10.1371/journal.pone.0152663

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