The primary objective of this research is to develop a mutli-scale modeling approach based on representative volume elements to enable the accurate depiction and finite element analysis of central nervous system (CNS) white matter, in particular of brain and spinal cord trauma. The vehicle to do this is an integrated multi-disciplinary analytical, computational and experimental methodology consisting of several equally important steps. The underlying hypothesis for the project is that axon fibers are neither firmly tethered nor completely uncoupled to the glial matrix during spinal cord trauma; in fact, they become more tethered with increasing stretch. To this end, microstructural kinematics, omitted by current studies, need to be incorporated to accurately represent and model the white matter of the brain and spinal cord. During the course of this project, we will develop a novel material model for CNS white matter that will capture the micro-scale behavior of axons in a macro-scale continuum analysis. The development of this model will be guided and tested by novel in situ experiments. The major intellectual merit of the proposed work lies upon the computational incorporation of the microstructural axon and glial features and properties into the global (macro) response of the CNS white mater, and the in situ experimental correlation and validation of the simulation data for a variety of loading scenarios. Results from this research will spearhead the development of axon damage tolerance criteria, which is of paramount importance since injury to axons is the proximal cause for loss of function following TBI and SCI. It will also assist in designing new in vivo and in vitro models with the goal of inducing injury in specific patterns and locations based on in silico predictions.
The societal impact lies in that, upon completion, the CNS white mater model will be able to be integrated into analyses of SCI and TBI with more complex loading conditions to predict injury at the single axon level. This is a breakthrough in the CNS biomechanical modeling, which can greatly facilitate diagnostics that can ultimately lead to improved means and measures of injury first response and treatment. The impact of this project in terms of basic research and the spread of knowledge is evident since this multidisciplinary program brings in tasks from materials science, bioengineering, controls, and hi-tech computational techniques, to develop a state of the art tissue diagnostic model, with unique quantitative measuring capabilities and that is described mathematically to its entirety. The educational impact will be significant for our graduate students not only in scientific and engineering fields, but also in mentoring and outreach since they are an integral part of our community efforts through the Rutgers Future Scholars program. Graduate students and undergraduates from minority and under represent groups will be actively recruited. These initiatives provide unique opportunities to these students that will excite them about education and training in engineering and help shape future leaders of our scientific and engineering communities. Finally, in support of results dissemination and outreach, the PI has secured funding to attend the CMMI bi-annual grantees' meeting.
