Development of Methods to Assess Intracranial Vessel Stiffness as a Measure of Vascular Disease

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Vascular disease is a major cause of mortality and morbidity, leading to pathologies across many organ systems. In the brain it can lead to transient ischaemic attack, stroke, and vascular dementia. A pre-cursor to overt pathology is a gradual stiffening of blood vessels, which itself can lead to diffuse pathological tissue damage due to damaging pulsatile pressure waves reaching further into the tissue bed. Non-invasive assessment of vascular stiffness has been possible through measurement of the pulse wave velocity (PWV) of the cardiac pressure wave as it passes through the vascular tree, although most measures to date are systemic in nature.This project seeks to develop non-invasive MRI methodologies that target the intracranial vasculature specifically, by measuring PWV within the brain's major arteries. This more specific measure of vessel stiffness should correlate much better with other neurovascular and diffuse brain tissue diseases than conventional measures that only provide a whole-body average.The successful student would have a background in physics, engineering, computer science or a related field, and would have an interest in applying their training to a medical application.High spatial and temporal resolution phase-contrast MRI angiography sequences that incorporate simultaneous multi-slice acquisition will be developed and optimized to sample the cardiac waveform at multiple vessel locations throughout the brain. Analysis approaches will be investigated and optimized to measure the subtle time shifts present between the PWV waveforms collected at different points in the intracranial vascular tree, including the investigation of combined spatio-temporal image reconstruction algorithms that use prior information from the simultaneous nature of the underlying acquisition. Additional analysis methods will be developed to model from angiographic data the vascular pathlengths between key nodes in the vascular tree. Finally, the methods will be deployed for validation in patients with evidence of existing small vessel disease versus healthy subjects.