Vascular modelling in non-traumatic spinal cord injury

Non-traumatic spinal cord injuries (NT-SCI) represent a number of pathologies which vary in progression and symptom presentation. Chronic mechanical compression is known to alter cord biomechanics and disrupt cord blood supply. Understanding of the mechanics that trigger ischemia and therefore the cascade of hypoxia and neurological dysfunction remains unknown. This thesis investigates the changes in blood and oxygen supply to the thoracic spinal cord under mild non-traumatic compression. The effects of injury severity, location and profile on the white and grey matter and its vasculature are explored. A fluid-structure interaction model is developed to represent the effect of compression on spinal tissue and its arteries. In order to model microvascular flow, a porous-continuum model is coupled to the arteries to distribute blood though the tissue. Oxygen transport and its consumption was coupled to the blood flow models. Compressions are considered at increasing intervals of 2.5% strain up to 10% strain, with all deformations repeated at anterior, posterior and anteroposterior locations with focal and diffused injury profiles. Results show that focal injuries do not elicit significant changes to vascular response under mild injury. However, larger diffused injuries are effectual. Anterior injury is shown to cause a decrease in blood flow from 2.5% strain and decrease in oxygen consumption at strains of 7.5%, across both matter types. Anteroposterior injury is found to produce a compensatory response in white matter with adverse effect in grey matter seen at 10% strain. Posterior injury had detrimental effect on white matter, followed by grey matter response at 7.5% strain. The work indicates that disruption of the vascular network in NT-SCI takes place at strains well below reported symptomatic thresholds. Patients presenting with diffused anterior injuries are at the highest risk. Further elaboration of vascular response in sub-clinical strains could bring greater understanding to clinical intervention thresholds.