Development and validation of an advanced anisotropic visco-hyperelastic human brain FE model

Sahoo, Debasis; Deck, Caroline; Willinger, Rémy

doi:10.1016/j.jmbbm.2013.08.022

Cited by 106 publications

(80 citation statements)

References 34 publications

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“…For example, Sahoo and associates 26 used isotropic 1 mm DTI voxels and 5320 brain elements of size 1.14-7.73 mm. In comparison, the KTH model coupled voxels of size 2 mm · 2 mm · 3.6 mm with 7128 brain elements, whose information on FE element size appears not available (albeit, anticipated to be comparable to the earlier example).…”

Section: Limitationsmentioning

confidence: 99%

“…While these studies suggest the importance of WM structural anisotropy, 25 continued development along this line of research by incorporating whole-brain tractography derived from diffusion tensor imaging (DTI) for e n evaluation may improve the injury prediction performance even further. The reason is that tractography potentially allows more accurate estimation of fiber orientations at each individual high resolution sampling point (e.g., every 1 mm along fibers or ''streamlines'') than those ''averaged'' at coarse FE elements or voxels (e.g., element size up to 7.73 mm, 26 or DTI voxel size of 2 mm ·2 mm ·3.6 mm 27 ). For example, Chatelin and associates 18 used weighted directions averaged from 70-4096 DTI voxels for each element.…”

Section: Introductionmentioning

confidence: 99%

“…Both Cloots and coworkers 17 and Wright and Ramesh 19 employed a multiscale approach to couple a macroscale three dimensional (3D) or two dimensional (2D) head model, respectively, with a microscale element embedding a single axon. Work from Wright and colleagues, 21 Kraft and associates, 20 Sahoo and coworkers, 26 , and Giordano and Kleiven 27 assigned average FA values and fiber directions to each element from coregistered DTI for strain evaluation. Instead of averaging on elements, Ji and associates 22 evaluated fiber strain at each DTI voxel transformed into the corresponding FE model space using strain tensors from the closest FE element on a subject-specific basis.…”

Section: Introductionmentioning

confidence: 99%

“…It does not yet incorporate material property heterogeneity 74 or WM material anisotropy (vs. structural anisotropy) resulting from fiber reinforcement. 26,27 While more sophisticated material properties for the brain may further enhance the model predictive power, we chose not to incorporate them in our current work for several practical reasons.…”

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confidence: 99%

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White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography

Zhao

Ford

Flashman

et al. 2016

Journal of Neurotrauma

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Microscale brain injury studies suggest axonal elongation as a potential mechanism for diffuse axonal injury (DAI). Recent studies have begun to incorporate white matter (WM) structural anisotropy in injury analysis, with initial evidence suggesting improved injury prediction performance. In this study, we further develop a tractography-based approach to analyze fiber strains along the entire lengths of fibers from voxel-or anatomically constrained whole-brain tractography. This technique potentially extends previous element-or voxel-based methods that instead utilize WM fiber orientations averaged from typically coarse elements or voxels. Perhaps more importantly, incorporating tractography-based axonal structural information enables assessment of the overall injury risks to functionally important neural pathways and the anatomical regions they connect, which is not possible with previous methods. A DAI susceptibility index was also established to quantify voxel-wise WM local structural integrity and tract-wise damage of individual neural pathways. This ''graded'' injury susceptibility potentially extends the commonly employed treatment of injury as a simple binary condition. As an illustration, we evaluate the DAI susceptibilities of WM voxels and transcallosal fiber tracts in three idealized head impacts. Findings suggest the potential importance of the tractography-based approach for injury prediction. These efforts may enable future studies to correlate WM mechanical responses with neuroimaging, cognitive alteration, and concussion, and to reveal the relative vulnerabilities of neural pathways and identify the most vulnerable ones in real-world head impacts.

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Section: Limitationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography

Zhao

Ford

Flashman

et al. 2016

Journal of Neurotrauma

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“…Richter et al [10] studied mechanisms of brain injury in helmeted motorcyclists, and Liu et al [11] and Abbas et al [12] showed that helmets can reduce the severity of brain injuries. Other researchers have developed computational models of brain injury and used them to study the protection offered by helmets [13][14][15]. Computational models of helmets have also been developed and used to improve helmet design [16,17], to understand the performance of helmets in realistic impact conditions [18] and to investigate the effects of the head/neck interaction on impact performance of the helmet and head [18,19].…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Chin Bar of a Composite-Shell Helmet to Mitigate the Upper Neck Force

2016

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The chin bar of motorcycle full-face helmets is the most likely region of the helmet to sustain impacts during accidents, with a large percentage of these impacts leading to basilar skull fracture. Currently, helmet chin bars are designed to mitigate the peak acceleration at the centre of gravity of isolated headforms, as required by standards, but they are not designed to mitigate the neck force, which is probably the cause of basilar skull fracture, a type of head injury that can lead to fatalities. Here we test whether it is possible to increase the protection of helmet chin bars while meeting standard requirements. Fibre-reinforced composite shells are commonly used in helmets due to their lightweight and energy absorption characteristics. We optimize the ply orientation of a chin bar made of fibre-reinforced composite layers for reduction of the neck force in a dummy model using a computational approach. We use the finite element model of a human head/neck surrogate and measure the neck axial force, which has been shown to be correlated with the risk of basilar skull fracture. The results show that by varying the orientation of the chin bar plies, thus keeping the helmet mass constant, the neck axial force can be reduced by approximately 30% while ensuring that the helmet complies with the impact attenuation requirements prescribed in helmet standards. KeywordsHelmet, chin bar, upper neck force.

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A multi‐GPU finite element computation and hybrid collision handling process framework for brain deformation simulation

Tian

Shen

2018

Computer Animation & Virtual

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This paper offers a fast multi‐graphics processing unit (GPU) parallel simulation framework to the problem of real‐time and nonlinear finite element computation of brain deformation. A load balancing strategy is proposed to ensure the efficient distribution of nonlinear finite element computation on multi‐GPU. A data storage structure is designed to minimize the amount of data transfer and make full use of the overlay technique of GPU to reduce the transferring latency between multi‐GPUs. We further present a fast central processing unit (CPU)–GPU parallel continuous collision detection and response method, which not only can deal with the collision between the brain and skull but also can handle the self‐collision of the brain. Our method can make full use of CPU and GPU to implement a parallel computation about deformation and collision detection. Our experimental results show that our method is able to handle a brain geometric model with high detail gyrus composed of more than 40,000 tetrahedron elements. This can facilitate the fidelity of the current virtual brain surgery simulator. We evaluate our approach qualitatively and quantitatively and compare it with related works.

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Development and validation of an advanced anisotropic visco-hyperelastic human brain FE model

Cited by 106 publications

References 34 publications

White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography

White Matter Injury Susceptibility via Fiber Strain Evaluation Using Whole-Brain Tractography

Optimization of the Chin Bar of a Composite-Shell Helmet to Mitigate the Upper Neck Force

A multi‐GPU finite element computation and hybrid collision handling process framework for brain deformation simulation

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