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Disc measurement and nucleus calibration in a smoothened lumbar model increases the accuracy and efficiency of in-silico study
BACKGROUNDS: Finite element analysis (FEA) is an important tool during the spinal biomechanical study. Irregular surfaces in FEA models directly reconstructed based on imaging data may increase the computational burden and decrease the computational credibility. Definitions of the relative nucleus p...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8362282/ https://www.ncbi.nlm.nih.gov/pubmed/34389025 http://dx.doi.org/10.1186/s13018-021-02655-4 |
Sumario: | BACKGROUNDS: Finite element analysis (FEA) is an important tool during the spinal biomechanical study. Irregular surfaces in FEA models directly reconstructed based on imaging data may increase the computational burden and decrease the computational credibility. Definitions of the relative nucleus position and its cross-sectional area ratio do not conform to a uniform standard in FEA. METHODS: To increase the accuracy and efficiency of FEA, nucleus position and cross-sectional area ratio were measured from imaging data. A FEA model with smoothened surfaces was constructed using measured values. Nucleus position was calibrated by estimating the differences in the range of motion (RoM) between the FEA model and that of an in-vitro study. Then, the differences were re-estimated by comparing the RoM, the intradiscal pressure, the facet contact force, and the disc compression to validate the measured and calibrated indicators. The computational time in different models was also recorded to evaluate the efficiency. RESULTS: Computational results indicated that 99% of accuracy was attained when measured and calibrated indicators were set in the FEA model, with a model validation of greater than 90% attained under almost all of the loading conditions. Computational time decreased by around 70% in the fitted model with smoothened surfaces compared with that of the reconstructed model. CONCLUSIONS: The computational accuracy and efficiency of in-silico study can be improved in the lumbar FEA model constructed using smoothened surfaces with measured and calibrated relative nucleus position and its cross-sectional area ratio. |
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