Multiscale stiffness characterisation of both healthy and osteoporotic bone tissue using subject-specific data

Area of Science:

• Biomaterials Science
• Computational Mechanics
• Orthopedic Engineering

Background:

• Internal fixations for severe bone fractures can fail in osteoporotic patients due to stress concentrations from material stiffness mismatches.
• Direct measurement of bone mechanical properties is impractical, hindering the design of implants that match native bone stiffness.

Purpose of the Study:

• To develop a multiscale methodology for predicting the anisotropic stiffness of bone based on readily measurable parameters like porosity and mineral fraction.
• To create a database of bone stiffness tensors for various bone health conditions to inform implant design.

Main Methods:

• A multistage homogenization technique was employed to predict bone's anisotropic stiffness.
• Incorporated nanoscale mineral phase morphology, microscale osteon geometry, and mesoscale trabecular and cortical bone geometries.
• Utilized microscopy and microCT data for geometric definitions across scales.

Main Results:

• The developed methodology accurately predicts bone stiffness, showing favorable agreement with existing experimental data and modeling works.
• Generated a database of anisotropic stiffness tensors applicable to a wide range of bone mineral fractions and porosities.
• The approach accounts for complex bone structures from nanoscale to mesoscale.

Conclusions:

• The methodology provides a practical approach to evaluate bone mechanical properties non-invasively.
• This work contributes to the design of more robust and patient-specific bone implants, improving fixation in challenging cases.
• Accurate prediction of bone stiffness is vital for reducing stress shielding and preventing secondary fractures.