Collagen-Related Viscoelasticity as a Metric for Fracture Assessment in Cortical Bone

The mechanical competence of bone relies on both elastic stiffness and viscous damping; however, existing assessments have primarily involved stiffness quantification using bone mineral density but lack a collagen matrix-focused metric to predict fracture risk. This study introduces an experimentally anchored, time-resolved analysis framework for quantifying cortical bone matrix viscoelasticity and evaluating fracture susceptibility arising from collagen organization defects. It further proposes a collagen-related viscoelasticity metric for bone assessment.

Using murine diabetic femoral cortical bone specimens, a time-resolved viscoelastic analysis based on nanoindentation-based creep testing was performed to quantify cortical bone matrix behavior. Polarization-resolved second-harmonic generation (pSHG) microscopy was employed to characterize collagen alignment and orientation at the ultrastructural level. Finite-element simulations incorporating experimentally derived viscoelastic parameters were used to evaluate crack propagation behavior and fracture susceptibility.

Nanoindentation revealed a pronounced reduction in the long-term viscoelastic retardation time ( ${\tau }_2$ ) in diabetic bone; therefore, it can be considered a potential biomechanical indicator of matrix dysfunction. pSHG imaging demonstrated progressive collagen disorganization, attributed to weakened mineral-collagen interfacial coupling and reduced energy dissipation. Computational modeling demonstrated that ${\tau }_2$ reduction promotes crack propagation, compromising structural integrity.

These multimodal findings propose ${\tau }_2$ as a quantitative, informative, collagen-related viscoelastic metric linking collagen degradation and ultrastructure to fracture susceptibility. This study provides the foundation for the development of strategies for next-generation bone collagen assessment, which complement densitometry-centric assessment, particularly in metabolic disorders like diabetes, where mineral changes alone are insufficient to predict fracture risks.