Lumbar spine finite element model for healthy subjects: development and validation

Area of Science:

• Biomechanics
• Computational modeling
• Spinal research

Background:

• The finite element (FE) method is valuable for studying human lumbar spine biomechanics.
• Single deterministic FE models face accuracy limitations due to inter-subject variability in spinal geometry and material properties.
• Ensemble predictions from multiple FE models offer improved accuracy for human lumbar spine behavior.

Purpose of the Study:

• To develop and validate an ensemble of five finite element (FE) models of the human lumbar spine (L1-L5).
• To assess the consistency and predictive power of these models under identical loading and boundary conditions.
• To establish a validated modeling methodology for future studies on spinal pathologies.

Main Methods:

• Development of five distinct FE models of the human lumbar spine (L1-L5) based on five healthy living subjects.
• Application of an identical modeling methodology across all five subjects.
• Extensive validation using existing experimental and computational data, including mesh convergence and material sensitivity analyses.

Main Results:

• The results from the five developed FE models demonstrated consistency with established experimental data and literature simulation results.
• The ensemble approach showed improved predictive capability compared to single deterministic models.
• The validated modeling method proved reliable for simulating human lumbar spine biomechanics.

Conclusions:

• The ensemble of validated FE models provides a more accurate prediction of human lumbar spine behavior.
• The established modeling methodology is suitable for future investigations into dysfunctional spines, including disc degeneration and scoliosis.
• This approach enhances the reliability of computational biomechanics in spinal research.