Literature DB >> 34121532

Prediction of biomechanical responses of human lumbar discs - a stochastic finite element model analysis.

Wei Wang1,2,3, Chaochao Zhou1,2, Runsheng Guo1,2,4, Thomas Cha1,2, Guoan Li1.   

Abstract

BACKGROUND: Accurate biomechanical investigation of human intervertebral discs (IVDs) is difficult because of their complicated structural and material features. AIM: To investigate probabilistic distributions of the biomechanical responses of the IVD by considering varying nonlinear structural and material properties using a stochastic finite element (FE) model.
METHODS: A FE model of a L3-4 disc was reconstructed, including the nucleus pulposus (NP), annular matrix and fibers. A Monte Carlo method was used to randomly generate 500 sets of the nonlinear material properties and fiber orientations of the disc that were implemented into the FE model. The FE model was analyzed under seven loading conditions: a 500 N compressive force, a 7.5Nm moment simulating flexion, extension, left-right lateral bending, and left-right axial rotation, respectively. The distributions of the ranges of motion (ROMs), intradiscal pressures (IDP), fiber stresses and matrix strains of the disc were analyzed.
RESULTS: Under the compressive load, the displacement varied between 0.29 mm and 0.76 mm. Under the 7.5Nm moment, the ROMs varied between 3.0° and 6.0° in primary rotations. The IDPs varied within 0.3 MPa under all the loading conditions. The maximal fiber stress (3.22 ± 0.64 MPa) and matrix strain (0.27 ± 0.12%) were observed under the flexion and extension moments, respectively.
CONCLUSION: The IVD biomechanics could be dramatically affected by the structural and material parameters used to construct the FE model. The stochastic FE model that includes the probabilistic distributions of the structural and material parameters provides a useful approach to analyze the statistical ranges of the biomechanical responses of the IVDs.

Entities:  

Keywords:  Finite element; Intervertebral disc; Lumbar biomechanics; Probabilistic analysis; Stochastic model

Mesh:

Year:  2021        PMID: 34121532     DOI: 10.1080/10255842.2021.1914023

Source DB:  PubMed          Journal:  Comput Methods Biomech Biomed Engin        ISSN: 1025-5842            Impact factor:   1.763


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