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Open AccessArticle

A Hybrid Model for Predicting Bone Healing around Dental Implants

Department of Materials Science and Engineering, National Chiao Tung University, Ta Hsueh Road, Hsinchu 300, Taiwan
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Materials 2020, 13(12), 2858; https://doi.org/10.3390/ma13122858
Received: 24 May 2020 / Revised: 22 June 2020 / Accepted: 23 June 2020 / Published: 25 June 2020
(This article belongs to the Special Issue Dental Implant Materials 2019)
Background: The effect of the short-term bone healing process is typically neglected in numerical models of bone remodeling for dental implants. In this study, a hybrid two-step algorithm was proposed to enable a more accurate prediction for the performance of dental implants. Methods: A mechano-regulation algorithm was firstly used to simulate the tissue differentiation around a dental implant during the short-term bone healing. Then, the result was used as the initial state of the bone remodeling model to simulate the long-term healing of the bones. The algorithm was implemented by a 3D finite element model. Results: The current hybrid model reproduced several features which were discovered in the experiments, such as stress shielding effect, high strength bone connective tissue bands, and marginal bone loss. A reasonable location of bone resorptions and the stability of the dental implant is predicted, compared with those predicted by the conventional bone remodeling model. Conclusions: The hybrid model developed here predicted bone healing processes around dental implants more accurately. It can be used to study bone healing before implantation surgery and assist in the customization of dental implants. View Full-Text
Keywords: dental implant; tissue differentiation; bone remodeling; mechano-regulation theory; short-term healing; long-term healing dental implant; tissue differentiation; bone remodeling; mechano-regulation theory; short-term healing; long-term healing
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Kung, P.-C.; Chien, S.-S.; Tsou, N.-T. A Hybrid Model for Predicting Bone Healing around Dental Implants. Materials 2020, 13, 2858.

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