Advancing HR-pQCT-based homogenised FE models with smooth structured hexahedral meshes

Area of Science:

• Biomechanics
• Medical Imaging
• Computational Modeling

Background:

• Nonlinear homogenized finite element (hFE) models predict bone stiffness and strength from HR-pQCT images.
• Current voxel-based meshes simplify geometry, limiting strain localization prediction.
• A need exists for improved meshing techniques for accurate bone mechanical analysis.

Purpose of the Study:

• To develop and validate a fully automated pipeline for generating smooth, structured hexahedral meshes from HR-pQCT scans.
• To enhance the prediction accuracy of bone stiffness and strength in distal radius and tibia.
• To assess the computational performance and repeatability of the new meshing approach.

Main Methods:

• Developed an automated pipeline for structured hexahedral mesh generation from HR-pQCT data.
• Validated the pipeline using ex vivo and in vivo HR-pQCT datasets of human radii and tibiae.
• Performed mesh sensitivity analysis and assessed mesh quality using Dice similarity coefficients and element quality metrics.

Main Results:

• Achieved high accuracy in predicting bone stiffness (R²=0.88-0.94) and yield force (R²=0.93-0.95).
• Demonstrated excellent mesh-image similarity (Dice >0.98) and good element quality.
• Showcased improved computational efficiency compared to previous methods.

Conclusions:

• The automated structured hexahedral meshing pipeline accurately predicts bone mechanical properties from HR-pQCT.
• The approach enhances geometric representation and computational performance for skeletal analysis.
• This method offers improved clinical insights for patient-specific bone assessments and longitudinal studies.