Prediction of Human Vertebral Compressive Strength Using Quantitative Computed Tomography Based Nonlinear Finite Element Method

Document Type : Original Paper


1 Ph.D. Student in Medical Physics, Tarbiat Modares University, Tehran, Iran

2 Associate Professor, Medical Physics Dept., Tarbiat Modares University, Tehran, Iran

3 Associate Professor, Radiology Dept., Faculty of Medicine, Tehran University, Tehran, Iran

4 Associate Professor, Mechanical Engineering Dept., Tarbiat Modares University, Tehran, Iran

5 M.Sc. Student in Mechanical Engineering, Tarbiat Modares University, Tehran, Iran


Introduction: Because of the importance of vertebral compressive fracture (VCF) role in increasing the patients’ death rate and reducing their quality of life, many studies have been conducted for a noninvasive prediction of vertebral compressive strength based on bone mineral density (BMD) determination and recently finite element analysis. In this study, QCT-voxel based nonlinear finite element method is used for predicting vertebral compressive strength.
Material and Methods: Four thoracolumbar vertebrae were excised from 3 cadavers with an average age of 42 years. They were then put in a water phantom and were scanned using the QCT. Using a computer program prepared in MATLAB, detailed voxel based geometry and mechanical characteristics of the vertebra were extracted from the CT images. The three dimensional finite element models of the samples were created using ANSYS computer program. The compressive strength of each vertebra body was calculated based on a linearly elastic-linearly plastic model and large deformation analysis in ANSYS and was compared to the value measured experimentally for that sample.
Results: Based on the obtained results the QCT-voxel based nonlinear finite element method (FEM) can predict vertebral compressive strength more effectively and accurately than the common QCT-voxel based linear FEM. The difference between the predicted strength values using this method and the measured ones was less than 1 kN for all the samples.
Discussion and Conclusion: It seems that the QCT-voxel based nonlinear FEM used in this study can predict more effectively and accurately the vertebral strengths based on every vertebrae specification by considering their detailed geometric and densitometric characteristics.


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