Real-time Simulation of the Transplanted Tooth Using Model Order Reduction

Overview

Journal Front Bioeng Biotechnol

Date 2023 Jul 17

PMID 37456726

Authors

Pierre Lahoud

Arif Badrou

Maxime Ducret

Jean-Christophe Farges

Reinhilde Jacobs

Aline Bel-Brunon

Mostafa EzEldeen

Nawfal Blal

Raphael Richert

Affiliations

Soon will be listed here.

Abstract

The biomechanics of transplanted teeth remain poorly understood due to a lack of models. In this context, finite element (FE) analysis has been used to evaluate the influence of occlusal morphology and root form on the biomechanical behavior of the transplanted tooth, but the construction of a FE model is extremely time-consuming. Model order reduction (MOR) techniques have been used in the medical field to reduce computing time, and the present study aimed to develop a reduced model of a transplanted tooth using the higher-order proper generalized decomposition method. The FE model of a previous study was used to learn von Mises root stress, and axial and lateral forces were used to simulate different occlusions between 75 and 175N. The error of the reduced model varied between 0.1% and 5.9% according to the subdomain, and was the highest for the highest lateral forces. The time for the FE simulation varied between 2.3 and 7.2 h. In comparison, the reduced model was built in 17s and interpolation of new results took approximately 2.10s. The use of MOR reduced the time for delivering the root stresses by a mean 5.9 h. The biomechanical behavior of a transplanted tooth simulated by FE models was accurately captured with a significant decrease of computing time. Future studies could include using jaw tracking devices for clinical use and the development of more realistic real-time simulations of tooth autotransplantation surgery.

Citing Articles

Influence of augmented reality technique on the accuracy of autotransplanted teeth in surgically created sockets.

Marhuenda Ramos M, Faus-Matoses I, Zubizarreta-Macho A, Riad Deglow E, Lobo Galindo A, Abella Sans F BMC Oral Health. 2024; 24(1):415.

PMID: 38575886 PMC: 10996197. DOI: 10.1186/s12903-024-04173-1.

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