Toward Patient Specific Technologies for Injury Prevention: Mapping The Effects of Pre-existing Conditions on Neurospine Injury Risk

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Patient specific technologies have the potential to revolutionize both injury prevention and medical treatment but are limited by our current inability to quantify individual tissue characteristics as well as a lack of information regarding the cumulative effects of aging, gender, body morphology (such as body mass index) and pre-existing conditions (such as osteoporosis or spinal stenosis) on spinal injury risk. The long term objective of the proposed research program is to leverage advances in technology and recent findings on spinal cord damage thresholds to develop the technologies necessary for implementing patient specific approaches into the prevention, diagnosis and treatment of spine and spinal cord injuries. However, before we can implement patient specific approaches in the clinic, there are a number of technical issues that need to be resolved. There are three objectives for this proposal that address some of these technical issues. First, we will define mathematical expressions for the material response of neurological tissues to loading as these expressions affect the accuracy of our patient specific models. Second, we will determine the sensitivity of these models to variations in spinal cord and column size and shape (which change with aging and diseases such as degenerative disc disease). And finally, for this approach to be clinically feasible, we will develop methods for the model construction, execution and analysis to be done automatically and within a short period of time. This work is novel in its application of patient-specific approaches for understanding spine and spinal cord loading resulting from an external impact. The benefit of patient-specific technologies is that they use existing diagnostic tools and procedures more effectively, with limited additional costs. It is expected that these technologies will reduce health care costs by limiting treatment complications and improve patient outcomes by better tailoring treatments and prevention strategies to individuals.