How bending causes distal radius fracture: Evidence from 6dof load measurement and digital image correlation.
biomechanical · Level V
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- Record sourced from PubMed, PMID 42034150.
- Also identified by DOI 10.1016/j.bone.2026.117904.
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Abstract
Distal radius fractures, specifically Colles-type injuries, are highly prevalent in older females and typically result from falls on an outstretched hand. Clinically, these fractures appear to originate on the volar side of the distal radius due to a substantial dorsiflexion bending moment, yet most biomechanical and finite element (FE) studies rely on simplified axial loading assumptions that fail to reproduce the tensile strain gradients responsible for these fractures. This study quantified the full six-degree-of-freedom (6DOF) force and moment components acting on the distal radius during loading in a dorsiflexed posture, while simultaneously measuring volar cortical strain using full-field digital image correlation (DIC). Twenty cadaveric forearms from ten female donors underwent quantitative CT imaging to obtain specimen-specific geometry and density distributions. Each radius was then loaded against a 30° inclined plate at 0.1 mm/s until failure. Two distinct fracture patterns emerged: distal volar fractures consistent with Colles injuries (n = 10) and proximal diaphyseal fractures (n = 10). Colles-type fractures were associated with lower metaphyseal bone density and exhibited elevated distal tensile strains that exceeded the cortical ultimate tensile strain threshold (~19,000 με). In contrast, diaphyseal fractures were characterised by higher bone density, larger displacements, and higher proximal tensile strains. Across all specimens, peak dorsiflexion moments averaged 20.0 ± 5.5 Nm, confirming that bending-rather than pure compression-is the primary driver of failure. These findings provide a comprehensive multicomponent experimental characterisation of distal radius loading under realistic fall conditions, highlighting the central role of bending in fracture initiation and offering high-fidelity data for validating FE models to improve clinical fracture risk prediction.