Cerebral Blood Flow Modeling with Discrete Red Blood Cell Tracking: Analyzing Microvascular Networks and their Perfusion

The brain is vital for every human being and consequently its functioning is a highly relevant research topic. Furthermore, it is one of the organs with the highest energy demand in the human body. To be more precise 25% of the body’s energy is consumed in the brain. This is a remarkable amount, if we keep in mind that the brain makes up for only 2% of the whole body weight. For the brain’s functioning a sustained supply of nutrients is essential. Nonetheless, the brain’s energy storage capabilities are limited and to deliver sufficient nutrients a robust perfusion with blood is crucial. Additionally, the energy demand of different brain areas is fluctuating in response to higher neuronal activity. It is well-established that the cortical vasculature is able to adapt to those changes and to locally up-regulate blood flow. However, the precise regulation mechanisms are not yet fully understood. The aim of this thesis is to improve our understanding of cerebral blood flow, its regulation as well as the underlying cortical vasculature. For this purpose a numerical framework has been developed, which simulates blood flow in realistic microvascular networks. Our approach has the specific feature that it tracks individual red blood cells and thus is a close representation of blood flow in vivo. We demonstrate that this aspect is crucial, because the red blood cell distribution strongly influences the flow field and vice versa. Our investigations are performed in realistic microvascular networks from the mouse parietal cortex. In order to improve our understanding of the flow and pressure field various network and flow characteristics are computed. Our analysis focuses on layer-specific characteristics and differences between vessel types. Moreover, the impact of vasodilations on the flow field are studied. In summary, we demonstrate how our numerical framework can be applied to perform representative simulations in realistic microvascular networks. We reveal important features of the flow in the microvasculature and point towards relevant topics for future research.