Does lumbar vertebra bone microstructure relate to combined loading fracture tolerance and inform fracture initiation site?

Tushak, Sophia K; Chernyavskiy, Pavel; Gates, Bay; George, Christina; Kerrigan, Jason R · Bone · 2026

biomechanical · Level V

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Abstract

Lumbar vertebrae bone microstructure has been shown to correlate to compressive mechanical properties and display regional variability. However, properties quantified using bone samples may be dissimilar to those of the entire vertebra and sensitive to test methods. Additionally, significant differences in bone quantity across regions of lumbar vertebrae may assist in identifying fracture initiation sites. Further, most studies consider uniaxial compressive loading, whereas the in vivo spine experiences combined loading. The goal of the study was to quantify the relationship between human lumbar vertebrae microstructure and its fracture tolerance to combined compression and flexion. A second goal was to assess if significant regional variation of microstructure within the vertebral body could suggest a location for fracture initiation, given the relationship between microstructure and fracture tolerance. Human three-vertebra spine sections were exposed to dynamic compression-flexion loading, and then the center vertebral bodies were isolated and imaged via micro-computed tomography. Commercial evaluation software was used to quantify bone volume fraction (BV/TV) and cortical thickness (Ct.Th). Bayesian statistical analyses were performed to relate bone microstructure to fracture tolerance with age as a covariate and to quantify microstructural regional variation. BV/TV was significantly associated with fracture tolerance. For the typical donor at the average age, both BV/TV and Ct.Th were positively correlated to fracture tolerance. Ct.Th was region-dependent, while BV/TV was homogeneous. Further efforts may include identifying correlates for bone microstructure that can be measured from common clinical imaging modalities to aid in developing a practical predictive model.

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