MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury

Bayly, Philip V.; Alshareef, Ahmed; Knutsen, Andrew K.; Upadhyay, Kshitiz; Okamoto, Ruth J.; Carass, Aaron; Butman, John A.; Pham, Dzung L.; Prince, Jerry L.; Ramesh, K.T.; Johnson, Curtis L.

doi:10.1007/s10439-021-02820-0

Cited by 35 publications

(27 citation statements)

References 120 publications

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“…A comprehensive in vivo brain imaging protocol is conducted in this study on three healthy adult male subjects (age: 28, 31 and 46 years old) to obtain inputs for the development of subject-specific computational head models, as illustrated in figure 1. Complete details of the data acquisition, subject recruitment and study approval are provided elsewhere [34,35]. Briefly, MRI anatomical images (including T 1 -weighted, T 2 -weighted and SWI) are acquired to obtain the 3D model geometry (figure 1 a ).…”

Section: Experimental Methodsmentioning

confidence: 99%

Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework

Upadhyay

Alshareef

Knutsen

et al. 2022

J. R. Soc. Interface.

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Computational head models are promising tools for understanding and predicting traumatic brain injuries. Most available head models are developed using inputs (i.e. head geometry, material properties and boundary conditions) from experiments on cadavers or animals and employ hereditary integral-based constitutive models that assume linear viscoelasticity in part of the rate-sensitive material response. This leads to high uncertainty and poor accuracy in capturing the nonlinear brain tissue response. To resolve these issues, a framework for the development of subject-specific three-dimensional head models is proposed, in which all inputs are derived in vivo from the same living human subject: head geometry via magnetic resonance imaging (MRI), brain tissue properties via magnetic resonance elastography (MRE), and full-field strain-response of the brain under rapid head rotation via tagged MRI. A nonlinear, viscous dissipation-based visco-hyperelastic constitutive model is employed to capture brain tissue response. Head models are validated using quantitative metrics that compare spatial strain distribution, temporal strain evolution, and the magnitude of strain maxima, with the corresponding experimental observations from tagged MRI. Results show that our head models accurately capture the strain-response of the brain. Further, employment of the nonlinear visco-hyperelastic constitutive framework provides improvements in the prediction of peak strains and temporal strain evolution over hereditary integral-based models.

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Section: Experimental Methodsmentioning

confidence: 99%

Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework

Upadhyay

Alshareef

Knutsen

et al. 2022

J. R. Soc. Interface.

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“…A comprehensive in-vivo brain imaging protocol is conducted in this study on three healthy adult male subjects (age: 28, 31, and 46 years-old) to obtain inputs for the development of the computational model, as illustrated in Figure 1. Complete dsetails on the data acquisition, subject recruitment, and study approval are provided elsewhere [28,29] . Briefly, volumetric anatomical brain images from T1-and T2-weighted MRI and SWI are acquired to obtain the 3D model geometry (Fig.…”

Section: Experimental Methodsmentioning

confidence: 99%

Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

Upadhyay

Alshareef

Knutsen

et al. 2021

Preprint

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Computational models of the human head are promising tools for the study and prediction of traumatic brain injuries (TBIs). Most available head models are developed using inputs (i.e., head geometry, material properties, and boundary conditions) derived from ex-vivo experiments on cadavers or animals and employ linear viscoelasticity (LVE)-based constitutive models, which leads to high uncertainty and poor accuracy in capturing the nonlinear response of brain tissue under impulsive loading conditions. To resolve these issues, a framework for the development of fully subject-specific 3D human head models is proposed, in which model inputs are derived from the same living human subject using a comprehensive in-vivo brain imaging protocol, and the viscous dissipation-based visco-hyperelastic constitutive modeling framework is employed. Specifically, brain tissue material properties are derived from in-vivo magnetic resonance elastography (MRE), and full-field strain-response of brain under rapid rotational acceleration is obtained from tagged MRI, which is used for model validation. The constitutive model comprises the Ogden hyperelastic strain energy density and the Upadhyay-Subhash-Spearot viscous dissipation potential. The simulated strain-response is compared with experimental data and with predictions from subject-specific models employing two commonly used LVE-based constitutive models, using a rigorous validation procedure that evaluates agreement in spatial strain distribution, temporal strain evolution, and differences in maximum values of peak and average strain. Results show that the head model developed in this work reasonably captures 3D brain dynamics, and when compared to LVE-based models, provides improvements in the prediction of peak strains and temporal strain evolution.

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“… 177 Recent strain measurements from tagged MRI with human volunteers may mitigate some of the limitations, as they provide voxel-wise strains. 11 However, their “effective” spatial resolution is similarly limited by spacing between tag lines and imaging planes. 22 , 101 In addition, they are limited to impact severities far below injury, and extrapolation of data to injurious levels may be flawed given the brain non-linear responses.…”

Section: Model Validationmentioning

confidence: 99%

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Ghajari

Mao

et al. 2022

Ann Biomed Eng

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Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.

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MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury

Cited by 35 publications

References 120 publications

Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework

Development and validation of subject-specific 3D human head models based on a nonlinear visco-hyperelastic constitutive framework

Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

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