New brain modeling aims to better understand the mechanics of traumatic brain injury

MechSE Assistant Professor Callan Luetkemeyer was recently awarded a three-year Early Career Program grant from the Army Research Office (ARO) to develop material models of the human brain. Her study, “Dynamic, full-field constitutive modeling of the in vivo brain,” will be done in collaboration with researchers from the Biomedical Imaging Center (BIC) at the Beckman Institute.

“Fundamentally, I’m a mechanician, but I tend to gravitate toward the problems that really impact quality of life,” Luetkemeyer said of her interest in the work. “[Brain health] has such a critical impact, and the brain itself is a good fit for my modeling work in elastography.”

In terms of material behavior, a healthy human brain roughly resembles Jell-O—it maintains a semisolid structure but is extremely sensitive to vibration or other impact. Brain matter contains numerous neural pathways that are constructed from nerve cells coated in a myelin sheath and resemble fibers mechanically. Furthermore, the brain contains regions of grey matter and white matter, each of which have their own densities and stiffnesses. Thus, modeling the brain as a complete system is nebulous and complex.

However, accurately modeling the brain’s material behavior is crucial for understanding the impact of traumatic brain injuries (TBI), particularly those that occur repeatedly over time, resulting in chronic traumatic encephalopathy. These models are currently developed using data from magnetic resonance (MR) elastography, a type of MR imaging that measures mechanical deformation resulting from external vibration. Modeling is currently performed using expensive computational tools such as finite element analysis (FEA)—for which one overly-simplified model of the brain may take a high-performance computing cluster more than 24 hours to produce. By leveraging her expertise in image-based, inversive mechanical modeling, Luetkemeyer notes that the same model can be produced with a laptop in a matter of minutes. This advance makes the development of more sophisticated, realistic models computationally tractable.

“We use specialized MRI pulse sequences to measure how the brain deforms in response to the shear waves propagating through it,” she said.

The ARO is particularly interested in developing more complex brain deformation models to understand the long-term effects of TBI, particularly for warfighters (i.e., soldiers). Soldiers who are repeatedly exposed to blasts from artillery guns or explosive devices are prone to experiencing TBI. The ARO hopes to develop more sophisticated protective equipment that can help minimize the mechanical stretching and compressing that happens in the brain as a result of this exposure.

“Modeling the brain as linear and isotropic—effectively, like a metal—isn’t very predictive,” Luetkemeyer explained. “Over the next three years, we’re focused on developing better models that treat the brain as having nonlinear and anisotropic properties.”

To develop these models, the research team will perform experiments to capture the brain’s deformation in vivo. Bioengineering professor and BIC technical director Brad Sutton and BIC assistant director Aaron Anderson will run the experiments on participating males of service age recruited by Luetkemeyer. Participants place their head on a pneumatically operated pillow within an MRI machine. The machine then captures displacement fields via pulse sequences while the pillow vibrates at roughly 50 hertz. Prior to experiencing the vibration, standard anatomical and diffusion tensor imaging are performed to identify locations of grey and white matter and visualize directions of neural pathways, respectively.

“Ultimately, we need to know how the brain’s material properties change at higher speeds [of vibration], but that’s not something we can do with live participants,” Luetkemeyer explained. “However, we can vary speed within a much smaller range to understand how the properties change in that range, and extrapolate [the findings] to what we might expect at a fast speed.”

This work lays the foundation for important future studies, such as the development of microstructure-based biomarkers that could be identified through these models—essentially, using the brain’s mechanical properties as a measure of its overall health and function.

“A lot of my previous work has shown that if we use more sophisticated models that are based on microstructure, we can be sensitive to microstructure in a way that is potentially diagnostic,” Luetkemeyer said.

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Callan Luetkemeyer is an assistant professor of mechanical engineering and a faculty affiliate for the Carl R. Woese Institute for Genomic Biology, the Department of Bioengineering, the Beckman Institute, and the Materials Research Laboratory.