A multiscale model of cerebral autoregulation in health and disease

Thesis

With an increasingly elderly population worldwide, many serious cerebrovascular diseases will overtake cardiac disease to be the greatest clinical challenge for many countries. Since impaired cerebral autoregulation is implicated in a range of brain diseases, the mechanism known as cerebral autoregulation that ensures a continuous and sufficient blood supply to the brain in the presence of changes in blood pressure is critical in preventing or delaying those cerebral diseases. A haemodynamic model of cerebral autoregulation that can comprehensively explain the root causes of cerebral diseases is urgently needed. However, the current models of cerebral autoregulation tend to be either high-level compartmental or data-driven models. Thus, a multiscale model of cerebral autoregulation is presented here to provide a better understanding of the mechanisms behind impaired autoregulation, considering factors such as Nitric Oxide (NO), stenosis, and ageing.

A model of a single arteriole is built to predict both the steady-state and dynamic responses of the vessel radius to the blood pressure changes. In particular, the NO component of the model is added here to understand the interaction between NO, the recognized effective vasodilator, and the myogenic response better. This vessel model is then integrated into a full-brain scale and is validated using a range of experimental data from the literature, both steady-state and dynamic. The integrated model can thus predict the response of the arteriole to changes in both driving and baseline pressure, and it captures well the balance between the myogenic and metabolic mechanisms.

Then, the computational model is adapted to apply to examine the spatial impact of stenosis on dynamic cerebral autoregulation (dCA) impairment and cerebral blood flow (CBF) patterns. It is not yet well understood whether impairment in dCA in one brain region is independent or not on dCA impairment in other brain regions. In our model, the stenosis on various large arterials in the Circle of Willis (CoW) is considered, and an analogue circuit diagram is used to quantify the dCA impairment. Our model suggests that stenosis only has a local impact on dCA, which provides the potential to apply this model in cerebrovascular disease treatment.

Finally, the factor of ageing is introduced to the model. Although static cerebral autoregulation (sCA) is known to be impacted while dCA is unaffected by ageing, the mechanism is poorly understood. Hence, the ageing-related parameters including the CBF volume, rate of recovery (RoR), and various time constants are considered. Our model successfully indicated the changing patterns of sCA and dCA in different age groups, and this is validated by the existing literature.

Authors: Tong, Z

• DOI: 10.5287/ora-zooq6a9mr
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: cerebral autoregulation; computational modelling