C4-C5 segment finite element model development, validation, and load-sharing investigation.

Area of Science:

• Biomechanics
• Computational modeling
• Spinal research

Background:

• Accurate cervical spine models are crucial for understanding injury mechanisms and predicting occupant responses in automotive crashes.
• Existing models lack the necessary detail for precise response prediction under various loading conditions.

Purpose of the Study:

• To develop a high-fidelity C4-C5 finite element model with detailed tissue representation.
• To incorporate advanced material data and nonlinear constitutive models for accurate response prediction.
• To validate the model against experimental data across diverse loading scenarios.

Main Methods:

• Developed a C4-C5 finite element model with an increased element count for enhanced resolution.
• Integrated state-of-the-art material data using nonlinear constitutive models.
• Validated the model against experimental data for axial rotation, flexion, extension, lateral bending, and translation at various load levels.

Main Results:

• The model accurately predicted cervical spine responses within a single standard deviation of experimental data across multiple loading conditions and levels.
• Demonstrated that detailed mesh refinement, tissue-level representation, and advanced material properties yield accurate predictions without model calibration.
• Identified dominant load-bearing structures (disc, ligaments, facet joints) correlating with known injury patterns for different loading modes.

Conclusions:

• The developed C4-C5 finite element model provides a validated and accurate tool for analyzing cervical spine biomechanics.
• This model advances the understanding of injury mechanisms and occupant response in automotive impacts.
• It serves as a foundation for developing a comprehensive finite element model of the entire cervical spine for future injury prediction studies.