Simulating cerebral edema and delayed fatality after traumatic brain injury using triphasic swelling biomechanics

Basilio, Andrew V.; Xu, Peng; Takahashi, Yukou; Yanaoka, Toshiyuki; Sugaya, Hisaki; Ateshian, Gerard A.; Morrison, Barclay

doi:10.1080/15389588.2019.1663347

Cited by 12 publications

(10 citation statements)

References 15 publications

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“…Because fatality due to brain injury would be highly associated with brain stem herniation subsequent to cerebral swelling, with the exception of direct loading to the brain stem, simulation of brain swelling would significantly enhance prediction of fatality due to brain injury. To the best of the authors' knowledge, this study and the relevant study by Basilio et al (2019) are the first attempts to address this issue.…”

Section: Discussionmentioning

confidence: 96%

“…A triphasic (solid, fluid, and ions) simulation was used to predict ICP increase due to the intracellular fixed charge density exposed by cell death. A subsequent increase in ICP due to ischemia via cell death (fixed charge density) was also modeled as an additional pathological change in delayed insult (Basilio et al 2019).…”

Section: Prediction Of Fatality Ratementioning

confidence: 99%

“…A novel approach to estimate fatality rate due to brain injury has been developed by Basilio et al (2019). The procedure combines prediction of brain deformation due to head translational and rotational acceleration with prediction of ICP after sustaining such brain deformation using the software FEBio (Ateshian et al 2013;Maas et al 2012).…”

Section: Introductionmentioning

confidence: 99%

“…By using precoded constitutive models and special algorithms to robustly handle incompressible materials, FEBio simulates ICP increase due to cell death caused by brain deformation from head impact and subsequent ICP increase due to further cell death caused by ischemia. Details of prediction of ICP increase using FEBio can be found in Basilio et al (2019). By combining prediction of the delayed insult represented by ICP increase with the prediction of primary brain injury, fatality rate may be more accurately estimated than the prediction of primary brain injury alone, because significant brain swelling leads to cerebral ischemia and brain stem compression that determine fatality risk.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of probability of fatality due to brain injury in traffic accidents

Takahashi

Yanaoka

Sugaya

et al. 2019

Traffic Injury Prevention

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Objective: Fatal brain injuries result from physiological changes in brain tissues, subsequent to primary damage caused by head impact. Although efforts have been made in past studies to estimate the probability of brain injury, none of them involved prediction of such physiological changes. The goal of this study was to evaluate the fatality prediction capability of a novel approach that predicts an increase in intracranial pressure (ICP) due to primary head injury to estimate the fatality rate using clinical data that correlate ICP with fatality rate. Methods: A total of 12 sets of head acceleration time histories were used to represent no, severe, and fatal brain injury. They were obtained from the literature presenting head kinematics data in noninjurious volunteer sled tests or from accident reconstruction for severe and fatal injury cases. These were first applied to a Global Human Body Models Consortium (GHBMC) head-brain model to predict nodal displacement time histories of the brain, which were then fed into FEBio to predict ICP. A Weibull distribution was applied to the data for the relationship between fatality rate and ICP obtained from a clinical paper to estimate fatality rate from ICP (procedure A). Fatality rate was also estimated by applying the temporal and spatial maximum value of maximum principal strain (MPS max ) obtained from the GHBMC simulation to an injury probability function for MPS max (procedure B). Estimated fatality rates were compared between the 2 procedures. Results: Both procedures estimated higher average fatality rate for higher injury severity. The average fatality rate for procedure A without ischemia representation and procedure B was 72.4 and 51.0% for the fatal injury group and 8.2 and 21.7% for the severe injury group, respectively, showing that procedure A provides more distinct classification between fatal and nonfatal brain injury. It was also found that representation of ischemia in procedure A provides results sensitive to injury severity and impact conditions, requiring further validation of the initial estimate for the relationship between brain compression and ischemic cell death. Conclusions: Prediction of the probability of fatality by means of a combination of simulations of the primary brain deformation and subsequent ICP increase was found to be more distinct compared to the prediction of primary injury alone combined with the injury probability function from a past study in the select 12 head impact cases. ARTICLE HISTORY

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Section: Discussionmentioning

confidence: 96%

Section: Prediction Of Fatality Ratementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of probability of fatality due to brain injury in traffic accidents

Takahashi

Yanaoka

Sugaya

et al. 2019

Traffic Injury Prevention

Self Cite

View full text Add to dashboard Cite

show abstract

“…The biomechanical characterization of human brain tissue and the development of appropriate mechanical models is crucial to provide realistic computational predictions. These predictions can assist in understanding the mechanical environment involved in neurodevelopment and neurological disorders [1,2], in simulating traumatic brain injury, to investigate the mechanical pathogenesis of head trauma [3] and in studying head injuries and developing protection systems [4]. Mathematical modeling is also the key to devising brain surgery simulation for training, assistance and guidance [5,6].…”

Section: Introductionmentioning

confidence: 99%

Cortex tissue relaxation and slow to medium load rates dependency can be captured by a two-phase flow poroelastic model

Urcun

Rohan

Sciumè

et al. 2022

Journal of the Mechanical Behavior of Biomedical Materials

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Fracture Resistance Biomechanisms of Walnut Shell with High‐Strength and Toughening

Wang

Yin

et al. 2023

Advanced Science

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Walnut shell is lightweight material with high‐strength and toughening characteristics, but it is different from other nut shells’ microstructure with two or three short sclerotic cell layers and long bundle fibers. It is essential to explore the fracture resistance biomechanism of lightweight walnut shell and how to prevent damage of bionic structure. In this study, it is found that the asymmetric mass center and geometric center dissipated impact energy to the whole shell without loading concentration in the loading area. Diaphragma juglandis is a special structure improved walnut shell's toughening. The S‐shape gradient porosity/elastic modulus distribution combined with pits on single auxetic sclerotic cells requires higher energy to crack expansion, then decreases its fracture behavior. These fantastic findings inspire to design fracture resistance devices including helmets, armor, automobile anti‐collision beams, and re‐entry capsule in spacecraft.

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Simulating cerebral edema and delayed fatality after traumatic brain injury using triphasic swelling biomechanics

Cited by 12 publications

References 15 publications

Prediction of probability of fatality due to brain injury in traffic accidents

Prediction of probability of fatality due to brain injury in traffic accidents

Cortex tissue relaxation and slow to medium load rates dependency can be captured by a two-phase flow poroelastic model

Fracture Resistance Biomechanisms of Walnut Shell with High‐Strength and Toughening

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