Interrelationship of trabecular mechanical and microstructural properties

E. Mittra, W. Lin, C. Rubin, Y. X. Qin

Research output: Contribution to journalConference article

Abstract

Noticeable changes in bone density are often first evident in trabecular bone. Moreover, qualities beyond density are important is identifying fracture risk. This study seeks to identify the degree to which the variability in trabecular material properties can be explained by using micro-CT (μCT) imaging. The material properties studied include stiffness, yield strength, and ultimate strength, while the μCT parameters analyzed include bone volume fraction, mean intercept length analysis, and degree of anisotropy. Trabecular bone was harvested from both the medial and lateral condyle of the left distal femur of 38 female sheep. The maximum correlation was found by combing all the μCT properties to explain approximately majority of the variability in modulus, yield, and ultimate strength (r2=0.87). In the principal loading direction, a lower amount of the variability in modulus is explained (r2=0.83), which is slightly less than the mediolateral direction but more than the anteroposterior direction. As the goal is to identify changes and potential fracture risk at the earliest possible time, the remaining variability should be identified. Further work with nano-indentation, fractals, and finite element modeling may yield the desired specificity.

Original languageEnglish (US)
Pages (from-to)419-420
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
StatePublished - Dec 1 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

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Keywords

  • Anisotropy
  • Bone volume fraction
  • Mean intercept length
  • Mechanical properties
  • Micro CT
  • Trabecular bone

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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