A data-driven framework for developing a unified density-modulus relationship for the human lumbar vertebral body

Area of Science:

• Biomechanics
• Materials Science
• Orthopedic Research

Background:

• Bone stiffness depends on density, but unified relationships for cancellous and cortical bone are lacking.
• Existing methods often assess bone compartments separately, limiting understanding of transitional regions.

Purpose of the Study:

• Develop a unified density-modulus relationship for the entire human lumbar vertebral body.
• Integrate experimental testing and numerical modeling to overcome limitations of separate compartment analysis.

Main Methods:

• A data-driven framework using an energy balance criterion was applied to 25 human lumbar vertebrae.
• Digital volume correlation quantified deformation during axial compression, with microcomputed tomography (micro-CT) imaging.
• Finite element models were constructed from quantitative CT (qCT) images and validated against experimental displacement fields.

Main Results:

• Unified density-modulus relationships (exponential and polynomial) were determined, accurately recovering microscale bone tissue modulus.
• Compressive stiffness moderately correlated with bone mineral density (BMD) at the macroscale.
• Bending stiffness showed a strong correlation with bone mineral content (BMC) at the macroscale.

Conclusions:

• The developed relationships accurately describe vertebral body mechanics, unifying density-modulus correlations.
• The framework has potential for extending to other properties like vertebral strength and toughness.
• This approach offers a more comprehensive understanding of vertebral structure-property relationships.