Citation

Khanuja T, Unni HN. Proc. Inst. Mech. Eng. Pt. H J. Eng. Med. 2019; ePub(ePub): ePub.

Affiliation

Biomicrofluidics and Biomechanics Lab, Department of Biomedical Engineering, Indian Institute of Technology Hyderabad, Hyderabad, India.

Copyright

(Copyright © 2019, Institution of Mechanical Engineers, Publisher SAGE Publishing)

DOI

10.1177/0954411919881526

PMID

31630604

Abstract

Traumatic brain injuries are life-threatening injuries that can lead to long-term incapacitation and death. Over the years, numerous finite element human head models have been developed to understand the injury mechanisms of traumatic brain injuries. Many of these models are erroneous and used ellipsoidal or spherical geometries to represent brain. This work is focused on the development of high-quality, comprehensive three-dimensional finite element human head model with accurate representation of cerebral sulci and gyri structures in order to study traumatic brain injury mechanisms. Present geometry, predicated on magnetic resonance imaging data consist of three rudimentary components, that is, skull, cerebrospinal fluid with the ventricular system, and the soft tissues comprising the cerebrum, cerebellum, and brain stem. The brain is modeled as a hyperviscoelastic material. Meshed model with 10 nodes modified tetrahedral type element (C3D10M) is validated against two cadaver-based impact experiments by comparing the intracranial pressures at different locations of the head. Our results indicate a better agreement with cadaver results, specifically for the case of frontal and parietal intracranial pressure values. Existing literature focuses mostly on intracranial pressure validation, while the effects of von Mises stress on brain injury are not analyzed in detail. In this work, a detailed interpretation of neurological damage resulting from impact injury is performed by analyzing von Mises stress and intracranial pressure distribution across numerous segments of the brain. A reasonably good correlation with experimental data signifies the robustness of the model for predicting injury mechanisms based on clinical predictions of injury tolerance criteria.

Language: en

Keywords

Traumatic brain injury; finite element model; hyperviscoelastic; intracranial pressure; magnetic resonance imaging; von Mises stress