In vivo estimates of axonal stretch and 3D brain deformation during mild head impact

Knutsen, Andrew K.; Gomez, Arnold D.; Gangolli, Mihika; Wang, Wen‐Tung; Chan, Deva D.; Lu, Yuan-Chiao; Christoforou, Eftychios G.; Prince, Jerry L.; Bayly, Philip V.; Butman, John A.; Pham, Dzung L.

doi:10.1016/j.brain.2020.100015

Cited by 57 publications

(54 citation statements)

References 69 publications

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“…An important limitation was that only three elderly (57-67 years), cadaveric subjects were used in the optimization process due to the availability of experimental brain deformation data. However, the calibrated model demonstrated a biofidelic response when verified using the in vivo tMRI dataset, which included younger, living subjects between 21 and 42 years of age (Knutsen et al, 2020). Nonetheless, the calibrated material parameters may not be representative of the general population and this calibration should be repeated once brain deformation data for more specimens is available.…”

Section: Discussionmentioning

confidence: 99%

“…The biofidelity of the calibrated CAB-20MSym template model was assessed using brain deformation data from the experiments conducted by Alshareef et al (2018Alshareef et al ( , 2020a and Knutsen et al (2020). Collectively, these datasets encapsulated various magnitudes (2.5-40 rad/s), durations (30-60 ms), and directions of rotational loading (coronal, sagittal, axial).…”

Section: Discussionmentioning

confidence: 99%

“…This coronal rotation case was selected as preliminary simulations indicated that the deformations predicted in this case were sensitive to the material non-linearity coefficient and avoided calibrating the material parameters under a single loading direction. Finally, the calibrated heterogeneous material parameters were verified using the remaining cases in the in situ brain deformation database, as well as low severity in vivo brain strain data obtained using the in vivo tMRI database ( Knutsen et al, 2020 ). This final verification included 39 simulations; 11 simulations for each SONO subject-specific model (not including case used for calibration) and 6 simulations for the tMRI cases.…”

Section: Methodsmentioning

confidence: 99%

“…To verify the calibrated median shear stiffness (μ 0, m e d = μ m e d ) the remaining 20 rad/s, 60 ms cases in the coronal (X: 20–60) and sagittal (Y: 20–60) directions were simulated and compared to each specimen’s experimental data using wcCORA. Verification of the strain response was performed by simulating in vivo brain strain experiments ( Knutsen et al, 2020 ). In this dataset, three subjects (tM-3978, tM-4838, and tM-6176) were subjected to sagittal rotations (ω max = 1.4–1.6 rad/s) and three subjects (tM-3978, tM-7126, and tM-9475) were subjected to axial rotations (ω max = 4–5.4 rad/s) of the head.…”

Section: Methodsmentioning

confidence: 99%

“…The goal of this study is to calibrate and verify a heterogenous FE brain model by leveraging experimental datasets reporting (1) MRE-derived material properties ( Hiscox et al, 2020 ), (2) high rate, in situ , brain displacements measured from human cadaveric specimens using sonomicrometry ( Alshareef et al, 2020a ), and (3) low rate, in vivo , brain strain measured from human volunteers using tagged magnetic resonance imaging (tMRI; Knutsen et al, 2020 ). Material parameters for the model were developed in three phases.…”

Section: Introductionmentioning

confidence: 99%

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Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

Giudice

Alshareef

et al. 2021

Front. Bioeng. Biotechnol.

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Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

Giudice

Alshareef

et al. 2021

Front. Bioeng. Biotechnol.

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A Soft‐Fiber Bioelectronic Device with Axon‐Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities

Tang,

Han,

Liu

et al. 2024

Advanced Materials

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Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long‐standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high‐quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium‐sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network‐in‐liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300 kPa), low specific impedance (579 kΩ µm2), and high electrical conductivity (32 700 S m−1) – ≈1–3 times higher than hydrogels. Stable single‐unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

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Toward subject-specific evaluation: methods of evaluating finite element brain models using experimental high-rate rotational brain motion

Alshareef

Giudice

et al. 2021

Biomech Model Mechanobiol

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In vivo estimates of axonal stretch and 3D brain deformation during mild head impact

Cited by 57 publications

References 69 publications

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

A Soft‐Fiber Bioelectronic Device with Axon‐Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities

Toward subject-specific evaluation: methods of evaluating finite element brain models using experimental high-rate rotational brain motion

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