Quantifying the Local Mechanical Properties of Cells in a Fibrous Three-Dimensional Microenvironment.

Measurements of the mechanical response of biological cells are critical for understanding injury and disease, for developing diagnostic tools, and for computational models in mechanobiology. Although it is well known that cells are sensitive to the topography of their microenvironment, the current paradigm in mechanical testing of adherent cells is mostly limited to specimens grown on flat two-dimensional substrates. In this study, we introduce a technique in which cellular indentation via optical trapping is performed on cells at a high spatial resolution to obtain their regional mechanical properties while they exist in a more favorable three-dimensional microenvironment. We combine our approach with nonlinear contact mechanics theory to consider the effects of a large deformation. This allows us to probe length scales that are relevant for obtaining overall cell stiffness values. The experimental results herein provide the hyperelastic material properties at both high (∼100 s-1) and low (∼1-10 s-1) strain rates of murine central nervous system glial cells. The limitations due to possible misalignment of the indenter in the three-dimensional space are examined using a computational model.

A Three-Dimensional Computational Human Head Model That Captures Live Human Brain Dynamics.

Diffuse axonal injury (DAI) is a debilitating consequence of traumatic brain injury (TBI) attributed to abnormal stretching of axons caused by blunt head trauma or acceleration of the head. We developed an anatomically accurate, subject-specific, three-dimensional (3D) computational model of the human brain, and used it to study the dynamic deformations in the substructures of the brain when the head is subjected to rotational accelerations. The computational head models use anatomy and morphology of the white matter fibers obtained using MRI. Subject-specific full-field shearing motions in live human brains obtained through a recently developed tagged MRI imaging technique are then used to validate the models by comparing the measured and predicted heterogeneous dynamic mechanical response of the brain. These results are used to elucidate the dynamics of local shearing deformations in the brain substructures caused by rotational acceleration of the head. Our work demonstrates that the rotational dynamics of the brain has a timescale of ∼100 ms as determined by the shearing wave speeds, and thus the injuries associated with rotational accelerations likely occur over these time scales. After subject-specific validation using the live human subject data, a representative subject-specific head model is used to simulate a real life scenario that resulted in a concussive injury. Results suggest that regions of the brain, in the form of a toroid, encompassing the white matter, the cortical gray matter, and outer parts of the limbic system have a higher susceptibility to injury under axial rotations of the head.

A multiscale computational approach to estimating axonal damage under inertial loading of the head.

A computational modeling framework is developed to estimate the location and degree of diffuse axonal injury (DAI) under inertial loading of the head. DAI is one of the most common pathological features of traumatic brain injury and is characterized by damage to the neural axons in the white matter regions of the brain. We incorporate the microstructure of the white matter (i.e., the fiber orientations and fiber dispersion) through the use of diffusion tensor imaging (DTI), and model the white matter with an anisotropic, hyper-viscoelastic constitutive model. The extent of DAI is estimated using an axonal strain injury criterion. A novel injury analysis method is developed to quantify the degree of axonal damage in the fiber tracts of the brain and identify the tracts that are at the greatest risk for functional failure. Our modeling framework is applied to analyze DAI in a real-life ice hockey incident that resulted in concussive injury. To simulate the impact, two-dimensional finite element (FE) models of the head were constructed from detailed MRI and DTI data and validated using available human head experimental data. Acceleration loading curves from accident reconstruction data were then applied to the FE models. The rotational (rather than translational) accelerations were shown to dominate the injury response, which is consistent with previous studies. Through this accident reconstruction, we demonstrate a conceptual framework to estimate the degree of axonal injury in the fiber tracts of the human brain, enabling the future development of relationships between computational simulation and neurocognitive impairment.