Numerical Simulation of Mechanically Adaptive Bone Remodeling Around Teeth and Implants: A Comparison with Clinical Images

• Published in: JOM (1989) Vol. 74; no. 12; pp. 4640 - 4651
• Main Authors: Su, Kangning, Gao, Chengyao, Qiu, Guoxian, Yuan, Li, Yang, Jie, Du, Jing
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2022; Springer Nature B.V
• Subjects: Algorithms; Bone density; Boundary conditions; Calibration; Chemistry/Food Science; Computed tomography; Computer simulation; Density distribution; Dental implants; Earth Sciences; Electrons; Energy; Engineering; Environment; Equilibrium; Finite element analysis; Finite element method; Human subjects; Image analysis; Interactions between Biomaterials and Biological Tissues and Cells; Mathematical models; Physics; Regression analysis; Roots; Scanners; Simulation; Spatial distribution; Strain energy; Teeth; Tomography; United States > US
• ISSN: 1047-4838; 1543-1851
• DOI: 10.1007/s11837-022-05533-4

The results of numerical simulation of mechanically adaptive bone remodeling have been compared with clinical images. Cone beam computed tomography (CBCT) images of multiple human subjects were superimposed to obtain a continuous bone density spatial distribution map inside the mandible supporting the lateral incisor. Strain energy density in the bone under normal chewing and biting forces was computed using finite element analysis. A bone remodeling algorithm was implemented to compute the bone density distribution at equilibrium. Linear regression analysis was performed between the bone density computed by numerical simulation and that obtained from image analysis, for every trabecular bone element. The results exhibited close agreement with a coefficient of correlation of 0.8499. The bite forces were transmitted through tooth roots to the surrounding bone, thus stimulating high trabecular bone density near the roots. The bending and torsion moments on the sagittal section of the mandible resulted in lower bone density near the center than those towards the edge of the mandible. The results provide a new method to compare the results of adaptive bone remodeling simulation with experimental data, and also provide model parameters to predict the bone density distribution surrounding a dental implant that replaced the tooth.