A quantitative relationship between rotational head kinematics and brain tissue strain from a 2-D parametric finite element analysis

Carlsen, Rika Wright; Fawzi, Alice Lux; Wan, Y.; Kesari, Haneesh; Franck, Christian

doi:10.1016/j.brain.2021.100024

Cited by 37 publications

(35 citation statements)

References 62 publications

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“…This scheme was similarly adopted to derive the principal and/or tract-oriented strain rates from FE simulations of human brains [27, 35, 38] and piglet brains [29, 32, 36]. In contrast, Carlsen, et al [26] conducted a parametric study to evaluate the relationship between rotational head kinematics and brain tissue responses, in which the principal and tract-oriented strain rates were respectively derived as the first principal and tract-aligned components of the strain-rate tensor (i.e., scheme 2). Similarly, Patton, et al [44] simulated 40 unhelmeted head impacts with known injury outcomes to evaluate the injury predictability of various metrics, of which the principal strain rate was computed as the maximum eigenvalue of strain-rate tensor (i.e., scheme 2).…”

Section: Discussionmentioning

confidence: 99%

“…The time-accumulated peaks of and were determined and labelled as and , respectively. Scheme 2 has been previously used to extract the principal strain rate and/or the tract-oriented strain rates in the brain [23, 25, 26, 41-44] and other biological tissues (e.g., leg muscles [45-48], tongue [49, 50], myocardium [51-53]).…”

Section: Methodsmentioning

confidence: 99%

“…In the computational works by Zhou, et al [25] and Carlsen, et al [26], the strain rate was derived from the strain-rate tensor, while King, et al [27] instead calculated the strain rate by differentiating the FEderived maximum principal strain vs. time curves. Concerningly, little or limited knowledge exists on how this disparity in computational schemes affects the resultant strain rate values.…”

Section: Graphic Abstract 1 Introductionmentioning

confidence: 99%

“…In two experimental paradigms, Rashid, et al [23] determined the strain rate from the symmetric part of the velocity gradient in the simple shear experiments of brain tissue, while LaPlaca and Thibault [24] quantified strain rate as the time derivative of strain in an in vitro TBI system. In the computational works by Zhou, et al [25] and Carlsen, et al [26], the strain rate was derived from the strain-rate tensor, while King, et al [27] instead calculated the strain rate by differentiating the FE-derived maximum principal strain vs. time curves. Concerningly, little or limited knowledge exists on how this disparity in computational schemes affects the resultant strain rate values.…”

Section: Introductionmentioning

confidence: 99%

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Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Zhou

Liu

et al. 2022

Preprint

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Traumatic brain injury (TBI) is an alarming global public health issue with high morbidity and mortality rates. Although the causal link between external insults and consequent brain injury remains largely elusive, both strain and strain rate are generally recognized as crucial factors for brain injury development. With respect to the flourishment of strain-based exploration, concerning ambiguity and inconsistency are noted in the scheme for strain rate calculation within the TBI research community. Furthermore, there is no experimental data that can be used to validate the strain rate responses of finite element (FE) models of the human brain. Thus, the current work presented a theoretical clarification of two commonly used strain rate computational schemes: the strain rate was either calculated as the time derivative of strain or derived from the strain-rate tensor. To further substantiate this theoretical disparity, these two schemes were respectively implemented to estimate the strain rate responses from a previous-published cadaveric experiment and an FE brain model secondary to a concussive impact. The results clearly showed scheme-dependent responses, both in the experimentally determined principal strain rate and FE-derived principal and tract-oriented strain rates. The results suggest that cross-scheme comparison of strain rate responses is inappropriate, and the utilized strain rate computational scheme needs to be reported in future studies. The newly calculated experimental strain rate curves can be used for strain rate validation of FE head models.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Graphic Abstract 1 Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Zhou

Liu

et al. 2022

Preprint

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“…Numerous studies have been performed to address this injury mechanism and consequences from different perspectives, such as post-traumatic stress disorder, aggregation of neurological disorders, damage threshold of cytoskeletal components, etc. When the head is impacted by blast-like mechanical force, the resulting pressure wave transmits to the interior of the brain and causes macroscale, tissue-level, and cellular level damage [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. A major part of the brain’s interior is built on over 100 billion neuron cells and its surrounding extra-cellular matrices.…”

Section: Introductionmentioning

confidence: 99%

Effect of Strain Rate on Single Tau, Dimerized Tau and Tau-Microtubule Interface: A Molecular Dynamics Simulation Study

et al. 2021

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Microtubule-associated protein (MAP) tau is a cross-linking molecule that provides structural stability to axonal microtubules (MT). It is considered a potential biomarker for Alzheimer’s disease (AD), dementia, and other neurological disorders. It is also a signature protein for Traumatic Brain Injury (TBI) assessment. In the case of TBI, extreme dynamic mechanical energies can be felt by the axonal cytoskeletal members. As such, fundamental understandings of the responses of single tau protein, polymerized tau protein, and tau-microtubule interfaces under high-rate mechanical forces are important. This study attempts to determine the high-strain rate mechanical behavior of single tau, dimerized tau, and tau-MT interface using molecular dynamics (MD) simulation. The results show that a single tau protein is a highly stretchable soft polymer. During deformation, first, it significantly unfolds against van der Waals and electrostatic bonds. Then it stretches against strong covalent bonds. We found that tau acts as a viscoelastic material, and its stiffness increases with the strain rate. The unfolding stiffness can be ~50–500 MPa, while pure stretching stiffness can be >2 GPa. The dimerized tau model exhibits similar behavior under similar strain rates, and tau sliding from another tau is not observed until it is stretched to >7 times of original length, depending on the strain rate. The tau-MT interface simulations show that very high strain and strain rates are required to separate tau from MT suggesting Tau-MT bonding is stronger than MT subunit bonding between themselves. The dimerized tau-MT interface simulations suggest that tau-tau bonding is stronger than tau-MT bonding. In summary, this study focuses on the structural response of individual cytoskeletal components, namely microtubule (MT) and tau protein. Furthermore, we consider not only the individual response of a component, but also their interaction with each other (such as tau with tau or tau with MT). This study will eventually pave the way to build a bottom-up multiscale brain model and analyze TBI more comprehensively.

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A mechanics theory for the exploration of a high-throughput, sterile 3D in vitro traumatic brain injury model

Wan,

González-Cruz,

Hoffman-Kim

et al. 2024

Biomech Model Mechanobiol

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A quantitative relationship between rotational head kinematics and brain tissue strain from a 2-D parametric finite element analysis

Cited by 37 publications

References 62 publications

Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Effect of Strain Rate on Single Tau, Dimerized Tau and Tau-Microtubule Interface: A Molecular Dynamics Simulation Study

A mechanics theory for the exploration of a high-throughput, sterile 3D in vitro traumatic brain injury model

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