Development of a novel ECG-based metric and device for monitoring changes in cerebral blood flow in stroke and other neurological disorders

Abstract

Stroke is the second leading cause of death and the third leading cause of disability globally. The most common type of stroke, ischaemic stroke, is caused by a sudden restriction in cerebral blood flow (CBF). Computed tomography (CT) perfusion imaging is the most common method to diagnose stroke. However, to limit radiation exposure, typically only a single CT scan is performed at presentation, with the possibility of one or two follow-up scans over the next 72 hours. Therefore, although useful for the initial assessment and treatment decision making, these scans provide only sparse snapshots of CBF in the brain. Following diagnosis and treatment, patients are at risk of early neurological deterioration (END). Notably, there is currently no continuous monitoring of stroke in-between CT scans, and no technologies have been clinically validated to provide such monitoring. This thesis introduces a novel device and electrocardiography (ECG)-based metric, termed the Electrocardiography Brain Perfusion index (EBPi), which may serve as a proxy for changes in CBF. Apparent changes in CBF were monitored in healthy volunteers using a custom-built head-worn device to wirelessly capture the signals required for EBPi computation. A next-generation device was shown to be safe and well tolerated by ischaemic stroke patients in an acute care environment providing a preliminary assessment of the clinical utility of EBPi. Finally, the feasibility of repurposing existing multi-electrode electroencephalography (EEG)/ECG protocols used in seizure monitoring of epilepsy patients to compute EBPi retrospectively (or simultaneously) was demonstrated and suggests that EBPi could augment current monitoring techniques in that context. Future work should aim to explore the clinical utility of EBPi (in isolation and in combination with quantitative EEG measures) for the continuous monitoring of stroke patients between CT scans to monitor disease progression, treatment outcome and detect END.