Specimen-specific vertebral fracture modeling: a feasibility study using the extended finite element method

Hugo Giambini, Xiaoliang Qin, Dan Dragomir-Daescu, Kai Nan An, Ahmad Nassr

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

Osteoporotic vertebral body fractures are an increasing clinical problem among the aging population. Specimen-specific finite element models, derived from quantitative computed tomography (QCT), have the potential to more accurately predict failure loads in the vertebra. Additionally, the use of extended finite element modeling (X-FEM) allows for a detailed analysis of crack initiation and propagation in various materials. Our aim was to study the feasibility of QCT/X-FEM analysis to predict fracture properties of vertebral bodies. Three cadaveric specimens were obtained, and the L3 vertebrae were excised. The vertebrae were CT scanned to develop computational models and mechanically tested in compression to measure failure load, stiffness and to observe crack location. One vertebra was used for calibration of the material properties from experimental results and CT gray-scale values. The two additional specimens were used to assess the model prediction. The resulting QCT/X-FEM model of the specimen used for calibration had 2 and 4 % errors in stiffness and failure load, respectively, compared with the experiment. The predicted failure loads of the additional two vertebrae were larger by about 41–44 % when compared to the measured values, while the stiffness differed by 129 and 40 %. The predicted fracture patterns matched fairly well with the visually observed experimental cracks. Our feasibility study indicated that the QCT/X-FEM method used to predict vertebral compression fractures is a promising tool to consider in future applications for improving vertebral fracture risk prediction in the elderly.

Original languageEnglish
Pages (from-to)583-593
Number of pages11
JournalMedical and Biological Engineering and Computing
Volume54
Issue number4
DOIs
Publication statusPublished - 2016 Apr 1

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Computer Science Applications

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