A numerical study of dehydration induced fracture toughness degradation in human cortical bone

J Mech Behav Biomed Mater. 2024 May:153:106468. doi: 10.1016/j.jmbbm.2024.106468. Epub 2024 Feb 16.

Abstract

A 2D plane strain extended finite element method (XFEM) model was developed to simulate three-point bending fracture toughness tests for human bone conducted in hydrated and dehydrated conditions. Bone microstructures and crack paths observed by micro-CT imaging were simulated using an XFEM damage model. Critical damage strains for the osteons, matrix, and cement lines were deduced for both hydrated and dehydrated conditions and it was found that dehydration decreases the critical damage strains by about 50%. Subsequent parametric studies using the various microstructural models were performed to understand the impact of individual critical damage strain variations on the fracture behavior. The study revealed the significant impact of the cement line critical damage strains on the crack paths and fracture toughness during the early stages of crack growth. Furthermore, a significant sensitivity of crack growth resistance and crack paths on critical strain values of the cement lines was found to exist for the hydrated environments where a small change in critical strain values of the cement lines can alter the crack path to give a significant reduction in fracture resistance. In contrast, in the dehydrated state where toughness is low, the sensitivity to changes in critical strain values of the cement lines is low. Overall, our XFEM model was able to provide new insights into how dehydration affects the micromechanisms of fracture in bone and this approach could be further extended to study the effects of aging, disease, and medical therapies on bone fracture.

Keywords: Bone; Cement line; Crack resistance curve behavior; Deformation and fracture toughness; Mechanical characterization; Microstructure.

MeSH terms

  • Bone and Bones
  • Cortical Bone / diagnostic imaging
  • Dehydration*
  • Fractures, Bone* / diagnostic imaging
  • Humans
  • Models, Biological