CAREER: Multiscale modeling of perivascular flow in the brain

University Of Rochester, Rochester NY

Investigators

Abstract

Cognitive diseases such as Alzheimer's are linked to the buildup of metabolic waste in the brain. In healthy brains, cerebrospinal fluid transports the waste through perivascular spaces that surround the arteries. Perivascular flow is affected by changes in arterial properties and blood flow distribution in the brain, which may explain the correlation between vascular decline and cognitive degeneration. This project is focused on modeling the fluid networks of blood and cerebrospinal fluid throughout the brain to provide insight into the relationship between arterial and perivascular activity. Understanding the mechanics of fluid flow in the brain will advance capabilities to correlate age-related ailments with neurodegeneration, predict patient outcomes, and drive treatment and prevention strategies. Pharmaceutical, surgical, or lifestyle interventions may alter the mechanical properties of vessels and brain tissue to promote waste clearance. The project will contribute to science education by including high school students from the Rochester City School District in undergraduate-level research coursework emphasizing hands-on lab experience, in collaboration with the University of Rochester David T. Kearns Center. Experiments strongly correlate blood and perivascular flows, but a causal mechanism has not yet been established in either experiment or simulation. This project will develop a multiscale model that explicitly relates arterial function to perivascular flow throughout the brain with wave propagation models coupling the arterial and perivascular networks to obtain a system-wide understanding of pressure and flow in the brain’s perivascular spaces. This model will be able to calculate flow distributions anywhere in the brain, beyond regions that are experimentally accessible, and at a broader scale than previous computational studies. Mechanical parameters in the model such as stiffness or diameter will be manipulated to mimic vascular conditions that result from chronic hypertension (high blood pressure), or transient spikes in neural activity (increased blood flow) that occur over short and long time scales. Both conditions will be validated with experimental data generated by collaborators at the University of Rochester Medical Center. The propagation of these effects will give insight into the relative impacts of vascular effects on perivascular flow, and the modeling framework can be expanded to study a range of vascular conditions beyond those in this project. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.