AI Unlocks Mysteries of Brain Fluid Flow: A Leap Forward in Alzheimer’s Research

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Researchers harnessed the power of artificial intelligence (AI) to measure the fluid flow around the brain’s blood vessels, a major breakthrough with far-reaching implications for treating diseases like Alzheimer’s. The team developed innovative AI velocimetry measurements to calculate this fluid flow accurately.

Measuring fluid flow around the brain’s blood vessels using artificial intelligence (AI) could revolutionize the development of treatments for diseases like Alzheimer’s. The intricate perivascular spaces surrounding cerebral blood vessels play a crucial role in transporting fluid and eliminating waste from the brain. However, accurately measuring changes in fluid flow is challenging.

A team of mechanical engineers, neuroscientists, and computer scientists led by University of Rochester’s Associate Professor Douglas Kelley has developed a groundbreaking AI-based technique called AI velocimetry to precisely calculate brain fluid flow. Published in the Proceedings of the National Academy of Sciences, their study combines novel AI methods with measurements obtained from animal models.

To visualize fluid flow, the researchers injected tiny particles into the perivascular spaces and tracked their movement using a 2D video. Byintegrating this data with physics-informed neural networks, they achieved an unparalleled high-resolution 3D understanding of the brain’s fluid flow system.

This research builds upon previous two-dimensional studies conducted by Maiken Nedergaard, coauthor of the study and codirector of Rochester’s Center for Translational Neuromedicine. However, the integration of AI allowed for more complex measurements and a deeper comprehension of the system’s intricacies.

The collaboration with George Karniadakis from Brown University was instrumental in leveraging AI and generating accurate three-dimensional representations of pressures, forces, and flow rates within the brain. This innovative approach provides valuable insights into the pumping mechanisms behind these flows.

The team received support from various sources, including the Collaborative Research in Computational Neuroscience program, the National Institutes of Health Brain Initiative, and the Army Research Office’s Multidisciplinary University Research Initiatives program. This research marks a significant step forward in understanding and potentially treating neurological conditions associated with fluid flow abnormalities in the brain.

Neurologica
Author: Neurologica

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