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Material properties assignment to finite element models of bone structures: a new method.

C Zannoni¹, R Mantovani, M Viceconti

¹Department of Electronics Computer Science and Systems, University of Bologna, Italy.

Medical Engineering & Physics

|May 1, 1999

Summary

A new program assigns material properties to finite element analysis (FEA) models of bone based on computed tomography (CT) scan data. This method significantly impacts strain energy density (SED) calculations in bone mechanical behavior studies.

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Area of Science:

Biomechanics
Medical Imaging
Computational Engineering

Background:

Finite element analysis (FEA) is crucial for understanding bone mechanical behavior.
Computed tomography (CT) data is commonly used to create FE models of bone.
CT images provide accurate bone morphology and tissue density information when calibrated.

Purpose of the Study:

Develop a program to map bone material properties from CT data to FEA mesh elements.
Assign material properties based on bone tissue density at each element's location.
Evaluate the impact of discrete material property assignment on FEA results.

Main Methods:

A specialized program was developed to read CT datasets and associated FEA meshes.
Material properties were assigned to FEA elements based on bone tissue density derived from CT data.

Related Experiment Videos

A 3D FE model of a distal femur was generated from a 16-bit CT dataset.

Strain energy density (SED) was calculated for model elements with varying complexity.

Main Results:

The developed program successfully assigned material properties based on CT-derived bone density.
Computed strain energy density (SED) values were highly sensitive to the material mapping strategy.
Increasing model complexity (number of material cards) influenced SED outcomes.

Conclusions:

The material mapping strategy significantly affects the accuracy of FEA in bone biomechanics.
Accurate assignment of material properties derived from CT data is essential for reliable bone mechanical analysis.
This approach enhances the evaluation of discrete bone material properties in FEA.