Studying The Biomechanical Behavior Of Brain Tissue Comparing Elastic And Hyperelastic Models

Abstract:

Two different types of computer modeling, i.e., the elastic and hyperelastic plane strain models were employed and compared with each other. Using finite element analysis, we determined a suitable model for describing the biomechanical behavior of the brain, especially the deformation and displacement of the brain ventricles. The CT-Scan of an epidural hematoma patient was modeled using both approaches. Then, by varying the mechanical parameters of the tissue (i.e., C10, C01, E, and v) and the internal ventricular pressure, the displacement rate of the corresponding points in the ventricles was simulated. Finally, the results of the simulation were compared with those of the actual ventricles, and then, the data set with the least amount of error was identified. For various types of loadings and with different pressure gradients, the results of the simulation show that if the effect of an increase in the internal pressure of the ventricles is neglected, it will lead to unrealistic results. Particularly, in unidirectional strain loading with a pressure gradient of zero (AP= 0), the walls of the ventricle adjacent to the hematoma will collapse completely. The best results were obtained for the elastic model where ΔP = 9.4 mmHg (1.25 kPa) and for the hyperelastic model where ΔP = 7.5 mmHg (1.00 kPa). These findings are consistent with the clinical conditions of the patient. In the plane strain biomechanical modeling, for unidirectional strain loading (conditions which are similar to the application of navigation systems in surgeries), neglecting the geometry and the variation of the internal pressure of the ventricles will not lead to acceptable results. Taking into account the above­mentioned parameters in describing the mechanical behavior of the brain (for epidural hematoma lesions), the elastic model (88.7% average relative accuracy) brings about better results compared with those of the hyperclastic model (86.9% average relative accuracy).

Language:
Persian
Published:
Iranian Journal of Biomedical Engineering, Volume:1 Issue: 4, 2008
Page:
281
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