Embedded finite elements for modeling axonal injury

Garimella, Teja; Menghani, Ritika; Gerber, Jesse; Sridhar, Srikumar; Kraft, Reuben H.

doi:10.31224/osf.io/2dx5e

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…Moreover, as the peak coup pressures for the inclined frontal impact (147.9 kPa) and the normal frontal impact (87.5 kPa) were higher than the systolic arterial blood pressure (12.0 kPa) [53] by 1133% and 629%, respectively, we do not believe that the inclusion of blood pressure would significantly change the model-predicted ICP values. Fourth, the embedded element method could potentially add mass to the model [65]. However, based on our calculations, the additional mass resulting from the vasculature was only 0.06% of the total mass of the human head, implying that the potential effect of the added mass was insignificant.…”

Section: Study Limitationsmentioning

confidence: 83%

The importance of modeling the human cerebral vasculature in blunt trauma

et al. 2021

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Background Multiple studies describing human head finite element (FE) models have established the importance of including the major cerebral vasculature to improve the accuracy of the model predictions. However, a more detailed network of cerebral vasculature, including the major veins and arteries as well as their branch vessels, can further enhance the model-predicted biomechanical responses and help identify correlates to observed blunt-induced brain injury. Methods We used an anatomically accurate three-dimensional geometry of a 50th percentile U.S. male head that included the skin, eyes, sinuses, spine, skull, brain, meninges, and a detailed network of cerebral vasculature to develop a high-fidelity model. We performed blunt trauma simulations and determined the intracranial pressure (ICP), the relative displacement (RD), the von Mises stress, and the maximum principal strain. We validated our detailed-vasculature model by comparing the model-predicted ICP and RD values with experimental measurements. To quantify the influence of including a more comprehensive network of brain vessels, we compared the biomechanical responses of our detailed-vasculature model with those of a reduced-vasculature model and a no-vasculature model. Results For an inclined frontal impact, the predicted ICP matched well with the experimental results in the fossa, frontal, parietal, and occipital lobes, with peak-pressure differences ranging from 2.4% to 9.4%. For a normal frontal impact, the predicted ICP matched the experimental results in the frontal lobe and lateral ventricle, with peak-pressure discrepancies equivalent to 1.9% and 22.3%, respectively. For an offset parietal impact, the model-predicted RD matched well with the experimental measurements, with peak RD differences of 27% and 24% in the right and left cerebral hemispheres, respectively. Incorporating the detailed cerebral vasculature did not influence the ICP but redistributed the brain-tissue stresses and strains by as much as 30%. In addition, our detailed-vasculature model predicted strain reductions by as much as 28% when compared to current reduced-vasculature FE models that only include the major cerebral vessels. Conclusions Our study highlights the importance of including a detailed representation of the cerebral vasculature in FE models to more accurately estimate the biomechanical responses of the human brain to blunt impact.

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Section: Study Limitationsmentioning

confidence: 83%

The importance of modeling the human cerebral vasculature in blunt trauma

et al. 2021

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“…Compared with the voxel-wise approach proposed in the current study, another promising alternative that could largely leverage the DTI-delineated orientation information is to embed the whole fiber tractography with continuous trajectories into FE models (Garimella, 2017; Hajiaghamemar and Margulies, 2021; Hajiaghamemar et al, 2020; Wu et al, 2019; Zhao et al, 2016). Despite its great potential, this approach conforms to multiple challenges associated with tractography reconstruction (Maier-Hein et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Fiber orientation downsampling compromises the computation of white matter tract-related deformation

Zhou

Wang

2021

Preprint

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Incorporating neuroimaging-revealed structural details into finite element (FE) head models opens vast opportunities to understand brain injury mechanisms. Recently, growing efforts have been made to integrate the fiber orientation from diffusion tensor imaging into the FE models to compute white matter (WM) tract-related deformation. Commonly used approaches often downsample the spatially enriched fiber orientation to match the resolution of FE meshes, resulting in an element-wise orientation implementation. However, the validity of downsampling and the consequences on the computed tract-related strains remain elusive. To address this problem, the current study proposed a new voxel-wise approach to integrate fiber orientation into FE models without downsampling. By setting the voxel-wise orientation responses as the reference, we then evaluated the reliability of two existing downsampling approaches on tract-related strains using two FE models with varying element sizes. The results showed that, for a model with a large mesh-image resolution dismatch, the downsampling orientation exhibited an absolute difference over 30 degree across the WM/gray matter interface and pons regions and further negatively affects the computation of tract-related strains with the normalized root-mean-square error up to 20% and peaking tract-related strains underestimated by 5%. This downsampling-induced effect was lower in FE models with finer meshes. Thus, this study yields insights on integrating neuroimaging-revealed fiber orientation into FE models and may better inform the computation of WM tract-related deformation, which are crucial for advancing the etiological understanding and computational predictability of brain injury.

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“…37 It is a useful modeling approach for the numerical analyses under the assumption of no slip between the fiber and matrix. 38 In this method, the fibers (embedded elements) are embedded inside the matrix (host elements), which are schematically represented in Figure 5. The translational degrees of freedom (DOFs) of the embedded element nodes are constrained to the interpolated DOFs of the neighboring host element nodes N. However, rotational DOFs are not constrained.…”

Section: Embedded Element Methodsmentioning

confidence: 99%

Effect of single-fiber properties and fiber volume fraction on the mechanical properties of Ioncell fiber composites

Karakoç

Bulota

Hummel

et al. 2021

Journal of Reinforced Plastics and Composites

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The present study concentrates on a series of experiments and numerical analyses for understanding the effects of fiber volume fraction ( VF) and draw ratio ( DR) on the effective elastic properties of unidirectional composites made from an epoxy resin matrix with a continuous fiber reinforcement. Lyocell-type regenerated cellulose filaments (Ioncell) spun with DRs of 3, 6, and 9 were used. In accordance with the specimens in situ, the fibers were modeled as slender solid elements, for which the ratio between the diameter and length was taken to be much less than unity and deposited inside the matrix with the random sequential adsorption algorithm. The embedded element method was thereafter used in the numerical framework due to its computational advantages and reasonable predictions for continuous fiber reinforced composites. Experiments and numerical investigations were carried out, the results of which were compared, and positive trends for both fiber VFs and DRs on the effective properties were observed. The presented experimental and numerical results and models herein are believed to advance the state of the art in the mechanical characterization of composites with continuous fiber reinforcement.

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Embedded finite elements for modeling axonal injury

Cited by 7 publications

References 21 publications

The importance of modeling the human cerebral vasculature in blunt trauma

The importance of modeling the human cerebral vasculature in blunt trauma

Fiber orientation downsampling compromises the computation of white matter tract-related deformation

Effect of single-fiber properties and fiber volume fraction on the mechanical properties of Ioncell fiber composites

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