Computational Modeling of Blunt Impact to Head and Correlation of Biomechanical Measures With Medical Images

2018 ◽  
Author(s):  
X. Gary Tan ◽  
Maria M. D’Souza ◽  
Subhash Khushu ◽  
Raj K. Gupta ◽  
Virginia G. DeGiorgi ◽  
...  
Keyword(s):  
Brain Injury ◽  
High Resolution ◽  
Computational Modeling ◽  
Diffusion Tensor ◽  
Medical Images ◽  
Human Head ◽  
Biological Tissues ◽  
Brain Morphology ◽  
Head Model ◽  
Human Head Model

Mild traumatic brain injury (TBI) is a very common injury to service members in recent conflicts. Computational models can offer insights in understanding the underlying mechanism of brain injury, which can aid in the development of effective personal protective equipment. This paper attempts to correlate simulation results with clinical data from advanced techniques such as magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), MR spectroscopy and susceptibility weighted imaging (SWI), to identify TBI related subtle alterations in brain morphology, function and metabolism. High-resolution image data were obtained from the MRI scan of a young adult male, from a concussive head injury caused by a road traffic accident. The falling accident of human was modeled by combing high-resolution human head model with an articulated human body model. This mixed, multi-fidelity computational modeling approach can efficiently investigate such accident-related TBI. A high-fidelity computational head model was used to accurately reproduce the complex structures of the head. For most soft materials, the hyper-viscoelastic model was used to captures the strain rate dependence and finite strain nonlinearity. Stiffer materials, such as bony structure were simulated using an elasto-plastic material model to capture the permanent deformation. We used the enhanced linear tetrahedral elements to remove the parasitic locking problem in modeling such incompressible biological tissues. The bio-fidelity of human head model was validated from human cadaver tests. The accidental fall was reconstructed using such multi-fidelity models. The localized large deformation in the head was simulated and compared with the MRI images. The shear stress and shear strain were used to correlate with the post-accident medical images with respect to the injury location and severity in the brain. The correspondence between model results and MRI findings further validates the human head models and enhances our understanding of the mechanism, extent and impact of TBI.

Recent Advances in Brain Injury Research: A New Human Head Model Development and Validation

2001 ◽  
Author(s):  
Liying Zhang ◽  
King H. Yang ◽  
Ramesh Dwarampudi ◽  
Kiyoshi Omori ◽  
Tieliang Li ◽  
...  
Keyword(s):  
Brain Injury ◽  
Model Development ◽  
Human Head ◽  
Head Model ◽  
Recent Advances ◽  
Human Head Model ◽  
Injury Research ◽  
Development And Validation

Computational Modeling of Blunt Impact to Head and Correlation of Biomechanical Measures With Medical Images

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
X. Gary Tan ◽  
Maria M. D'Souza ◽  
Subhash Khushu ◽  
Raj K. Gupta ◽  
Virginia G. DeGiorgi ◽  
...  
Keyword(s):  
Clinical Data ◽  
Bone Structure ◽  
Road Traffic ◽  
Medical Images ◽  
Imaging Techniques ◽  
Computational Simulation ◽  
Viscoelastic Model ◽  
Human Head ◽  
Brain Morphology ◽  
Head Model

Abstract Mild traumatic brain injury (TBI) is a common injury to service members in recent conflicts. We attempt to correlate simulation results with clinical data from advanced imaging techniques to identify TBI-related subtle alterations in brain morphology, function, and metabolism. Magnetic resonance image (MRI) data were obtained for a young adult male, after a concussive head injury caused by a road traffic accident. A similar fall of a pedestrian using an articulated human body biodynamics model was integrated with the finite element (FE) analysis using a high-resolution human head model to investigate TBI from an accident. The hyper-viscoelastic model was used to represent the strain rate dependence in brain tissues. The bone structure was simulated using an elastoplastic model to capture the focal permanent deformation. Enhanced tetrahedral elements were used in modeling nearly incompressible tissues. The localized large deformation in the head was simulated and compared with those from the MRI images. Biomechanical measures, such as stresses and strains, were correlated with postaccident medical images with respect to injury location and severity in the brain. The correspondence between model results and MRI findings shows a new way to relate computational simulation response of human head to blunt impacts with clinical data from such incidents and thus enhances our understanding of the mechanism, extent, and effects of TBI.

Biomechanical Assessment of the Bridging Vein Rupture of Blast-Induced Traumatic Brain Injury Using the Finite Element Human Head Model

2012 ◽  
Author(s):  
Chenzhi Wang ◽  
Jae Bum Pahk ◽  
Carey D. Balaban ◽  
Joseph Muthu ◽  
David A. Vorp ◽  
...  
Keyword(s):  
Shock Wave ◽  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Mechanical Response ◽  
Human Head ◽  
Head Model ◽  
Fe Model ◽  
Bridging Vein ◽  
Human Head Model

The incidence of the blast-induced traumatic brain injury (bTBI) among American troops in battle environments is dramatically high in recent years. Shock wave, a production of detonation, is a brief and acute overpressure wave that travels supersonically with a magnitude which can be several times higher than atmospheric pressure. Primary bTBI means that human exposure to shock wave itself without any other impact of solid objects can still result in the impairment of cerebral tissues. The mechanism of this type of brain injury is different from that of the conventional TBI, and has not been fully understood. So far, it is believed that the shock wave transmitted through skull and into cerebral tissues may induce specific injury patterns. This study is trying to develop a methodology to numerically investigate the mechanism of the blast-induced subdural hematoma (bSDH), which is caused by bridging vein rupture. The effort of this study can be divided to three major parts: first, a finite element (FE) model of human head is developed from the magnetic resonance imaging (MRI) of a real human head to contain skull, CSF and brain. Numerically simulated shock waves transmits through the human head model whose mechanical responses are recorded; second, in order to obtain the mechanical properties of human bridging vein, an standard inflation test of blood vessels is conducted on a real human bridging vein sample gained from autopsy. Material parameters are found by fitting the experimental data to an anisotropic hyperelastic constitutive model for blood vessel (Gerhard A. Holzapfel 2000); third, The bridging vein rupture in bTBI is evaluated by the finite element analysis of a separate human bridging vein model under the external loadings in terms of the internal pressure and relative skull-brain motion which are extracted from the mechanical response of the subarachnoid space of the head in the blast-head simulation of the first part.

Computational Study on the Bridging Vein Rupture of Blast-Induced Traumatic Brain Injury Using a Numerical Human Head Model

2011 ◽  
Author(s):  
Chenzhi Wang ◽  
Jae Bum Pahk ◽  
Carey D. Balaban ◽  
Jeffrey S. Vipperman
Keyword(s):  
Shock Wave ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Subdural Hematoma ◽  
Human Head ◽  
Head Model ◽  
Cerebral Contusion ◽  
Injury Threshold ◽  
Bridging Vein ◽  
Human Head Model

The occurrence of blast-induced traumatic brain injury (bTBI) in people serving in battle environments is dramatically high. The blast front, or leading edge of the shock wave is a brief, acute overpressure wave that travels supersonically with a magnitude that is several times higher than that of ambient. The shock wave propagates through the human head and injures intracranial tissues. Classical neuropathologic signs of bTBI include cerebral contusion, diffuse axonal injury, subdural hematoma (SDH) and subarachnoid hematoma, of which subdural hematoma is the most dominating sign of bTBI. Here, computational finite element (FE) modeling is used to investigate the mechanical process of bTBI. The overall goal of the present study is to find the injury threshold of the SDH injury due to bTBI, by investigating the biomechanical response of the bridging veins in the human brain under shock wave loading that originates from detonation. This research mainly develops a basic FE human head model which consists of skull and parts of the brain. The geometric models of skull and brain are developed from segmentations of magnetic resonance imaging (MRI) files of a real human head. The boundary conditions on the neck and head are modeled as a displacement-fixed condition. The numerically simulated blast waves are applied on the human head model as external loading conditions. The internal response in the subarachnoid space is used as loadings on the bridging vein submodel. The maximum principal stress of the bridging vein is used to determine the whether there is failure of the bridging vein, thus estimating the “injury threshold” of SDH in bTBI. Results show that 150g TNT blast of 1 meter away from the head can result in a high possibility of SDH occurrence.

Efficient Electromagnetic Analysis of a Dispersive Head Model Due to Smart Glasses Embedded Antennas at Wi-Fi and 5G Frequencies

2021 ◽  
Vol 36 (2) ◽  
pp. 159-167
Author(s):  
Fatih Kaburcuk ◽  
Atef Elsherbeni
Keyword(s):  
Numerical Study ◽  
Computation Time ◽  
Human Head ◽  
Head Model ◽  
Computer Memory ◽  
Large Computer ◽  
Smart Glasses ◽  
Embedded Antennas ◽  
Human Head Model ◽  
Difference Time

Numerical study of electromagnetic interaction between an adjacent antenna and a human head model requires long computation time and large computer memory. In this paper, two speeding up techniques for a dispersive algorithm based on finite-difference time-domain method are used to reduce the required computation time and computer memory. In order to evaluate the validity of these two speeding up techniques, specific absorption rate (SAR) and temperature rise distributions in a dispersive human head model due to radiation from an antenna integrated into a pair of smart glasses are investigated. The antenna integrated into the pair of smart glasses have wireless connectivity at 2.4 GHz and 5th generation (5G) cellular connectivity at 4.9 GHz. Two different positions for the antenna integrated into the frame are considered in this investigation. These techniques provide remarkable reduction in computation time and computer memory.

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