Physiologically based modelling of cerebral autoregulation

Thesis

The human brain requires sufficient and continuous blood supply to maintain healthy function. Cerebral autoregulation (CA), a highly complex mechanism, plays a crucial role in achieving this function. Increasing evidence confirms the close association between cerebral haemodynamic abnormalities and the occurrence of cerebrovascular diseases, brain dysfunction, and cognitive impairment. To complement clinical trials and improve clinical outcomes, researchers use mathematical models to understand disease progression and test the feasibility of new therapies. However, existing cerebral autoregulation models are predominantly purely mathematical, making it challenging to relate simulation results to clinically measured parameters. Therefore, there is a need to develop CA models based on physiological mechanisms to enhance our understanding of brain physiology and diseases, and to facilitate the clinical translation of cerebral autoregulation.

In this study, we first conducted a data-driven analysis of arterial blood pressure (ABP) and cerebral blood flow (CBF) under different physiological and pathological conditions, providing the latest insights into the human cerebral pressure-flow relationship and serving as a reference for developing new mathematical models. Subsequently, we proposed the first physiologically-based mathematical model capable of simulating both activation and autoregulatory responses. To ensure a solid physio- logical foundation, a single vessel model was first constructed, which was then scaled up to a whole-brain vasculature model using the analogy between cerebral vasculature and electrical circuits. This model not only replicated typical autoregulation curves but also the BOLD response. This CA model was subsequently coupled with a multi- compartment porous Finite Element model, successfully incorporates autoregulation mechanisms into the computational modelling of brain oedema and osmotherapy. The improved model demonstrated closer alignment with clinical data, particularly enhancing consistency in managing intracranial pressure during the rebound phase following osmotherapy. Overall, the combined approach adopted in this study offers crucial insights into the physiological pathways of cerebral autoregulation.

Authors: Wang, Y

• DOI: 10.5287/ora-eoojo0zm8
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: cerebral autoregulation; cerebral blood flow