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.