[A study on the predictive model of porous hyperelastic properties of human alveolar bone based on computed tomography imaging].

Alveolar bone reconstruction simulation is an effective means for quantifying orthodontics, but currently, it is not possible to directly obtain human alveolar bone material models for simulation. This study introduces a prediction method for the equivalent shear modulus of three-dimensional random porous materials, integrating the first-order Ogden hyperelastic model to construct a computed tomography (CT) based porous hyperelastic Ogden model (CT-PHO) for human alveolar bone. Model parameters are derived by combining results from micro-CT, nanoindentation experiments, and uniaxial compression tests. Compared to previous predictive models, the CT-PHO model shows a lower root mean square error (RMSE) under all bone density conditions. Simulation results using the CT-PHO model parameters in uniaxial compression experiments demonstrate more accurate prediction of the mechanical behavior of alveolar bone under compression. Further prediction and validation with different individual human alveolar bone samples yield accurate results, confirming the generality of the CT-PHO model. The study suggests that the CT-PHO model proposed in this paper can estimate the material properties of human alveolar bone and may eventually be used for bone reconstruction simulations to guide clinical treatment.

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Publication Details

Journal
PubMed
Published
2025-04-25
DOI
https://doi.org/10.7507/1001-5515.202408014
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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[A study on the predictive model of porous hyperelastic properties of human alveolar bone based on computed tomography imaging].

Bin Wu, Mingna Li, Fan Yang, Leyuan Ma et al.
PubMed
Radiomics and Machine Learning in Medical Imaging
article

[A study on the predictive model of porous hyperelastic properties of human alveolar bone based on computed tomography imaging].

Bin Wu, Mingna Li, Fan Yang, Leyuan Ma, Yi Lu, Di Jiang, Bin Yan, Yang Yi
article en

Abstract

Alveolar bone reconstruction simulation is an effective means for quantifying orthodontics, but currently, it is not possible to directly obtain human alveolar bone material models for simulation. This study introduces a prediction method for the equivalent shear modulus of three-dimensional random porous materials, integrating the first-order Ogden hyperelastic model to construct a computed tomography (CT) based porous hyperelastic Ogden model (CT-PHO) for human alveolar bone. Model parameters are derived by combining results from micro-CT, nanoindentation experiments, and uniaxial compression tests. Compared to previous predictive models, the CT-PHO model shows a lower root mean square error (RMSE) under all bone density conditions. Simulation results using the CT-PHO model parameters in uniaxial compression experiments demonstrate more accurate prediction of the mechanical behavior of alveolar bone under compression. Further prediction and validation with different individual human alveolar bone samples yield accurate results, confirming the generality of the CT-PHO model. The study suggests that the CT-PHO model proposed in this paper can estimate the material properties of human alveolar bone and may eventually be used for bone reconstruction simulations to guide clinical treatment.

PubMedVol. 42(2)
Nanjing Forestry University (CN)
Radiomics and Machine Learning in Medical Imaging
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