Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Acute spinal cord injury (SCI) begins with a mechanical insult, termed primary injury, followed by an extended biological response, called secondary injury. Research advances over the past decade show, in animal models, that features of the primary injury (e.g. loading rate, direction) have profound influences on the pattern and severity of SCI. Computer simulations of these injuries emphasized the importance of these mechanical effects on tissue damage. These simulations have great potential as design tools for devices and environments for injury prevention (e.g. helmets and automobile interiors). Unfortunately, there exist limitations with these computer models as predictive tools. The main areas for improvement include spinal cord tissue modelling (e.g. grey vs. white matter, anisotropy) and relating the mechanical response to tissue damage (i.e. identifying an appropriate tolerance criterion).

The overall goal of this Discovery Grant program is to determine better tolerance criteria for spinal cord tissue. The specific objectives are to determine the: 1) quasi-static material properties of spinal cord grey and white matter; 2) relative anisotropy of spinal cord grey and white matter; and 3) mechanical criteria (e.g. max. principal strain) that best correlate with spinal cord tissue damage. The proposed research is a natural progression of my current NSERC Discovery Grant.

To address these specific objectives, computational modelling, in vivo experiments, and magnetic resonance (MR) imaging will be conducted. For Obj. 1 and 2, relevant SCIs will be produced in vivo in rats using a custom intra-MR SCI device and MR images obtained of the deformed spinal cords. Image analysis will enable strain pattern estimation in the cord. Inverse finite element (FE) approaches will be used to determine the relative material properties of the grey and white matter. For Obj 3, three types of SCIs will be produced and the FE model used to predict damage patterns with several possible tolerance criteria.

This research program is highly novel by international standards. We are leaders in addressing the biomechanical variables using an in vivo model, and the only group able to produce SCIs inside the bore of an MR scanner. Our ability to computationally model these injuries is well developed and an important component of this proposed research. This research will advance our understanding of the material properties of spinal cord tissue and thus will enhance the quality of our computational models in predicting tissue damage. As the spinal cord is a good model system for injury to central nervous system tissue, these results are likely translatable to brain injury. This will aid the design of environments (e.g. inside of a car) for the prevention of spine and spinal cord injuries. We have a rich, interdisciplinary training environment for HQP and we expect to train two MASc and two PhD students in this timeframe.