{"id":699862,"date":"2026-05-27T15:30:13","date_gmt":"2026-05-27T19:30:13","guid":{"rendered":"https:\/\/www.rochester.edu\/newscenter\/?p=699862"},"modified":"2026-05-27T16:48:07","modified_gmt":"2026-05-27T20:48:07","slug":"physics-informed-ai-mri-glymphatic-fluid-flow-velocity-699862","status":"publish","type":"post","link":"https:\/\/www.rochester.edu\/newscenter\/physics-informed-ai-mri-glymphatic-fluid-flow-velocity-699862\/","title":{"rendered":"AI reveals how the brain clears harmful waste"},"content":{"rendered":"

The new approach combines MRI scans and AI tools to measure fluid flow linked to diseases such as Alzheimer\u2019s.<\/strong><\/h2>\n

When a person goes into deep sleep, water-like fluid circulates around the brain, washing away metabolic waste linked to diseases such as Alzheimer\u2019s. This process, known as the glymphatic system, was first described in 2012 by Maiken Nedergaard<\/a>\u2014a pioneering neuroscientist and codirector of the Ä¢¹½´«Ã½<\/a>\u2019s Center for Translational Neuromedicine<\/a>.<\/p>\n

But questions remain about the system\u2019s mechanics\u2014notably, how quickly the fluid circulates. Studying the circulation within a living brain is difficult without causing irreparable harm to a subject.<\/p>\n

\"GIF
3D visualization showing the flow speed across the brain. (Courtesy of Doug Kelley)<\/figcaption><\/figure>\n

\u201cYou can put a microscope on a small patch of the brain and watch what\u2019s happening there with a lot of detail, and we\u2019ve worked with that type of data in the past, but it\u2019s only a tiny view of the overall process,\u201d says Professor Douglas Kelley<\/a> from Ä¢¹½´«Ã½\u2019s Department of Mechanical Engineering<\/a>. \u201cIf you want to image whole brains, an MRI is a great approach because it gives you a three-dimensional view. But an MRI has serious limitations, too, the biggest of which is that it does not capture the fluid flow velocity, at least not for flows this slow.\u201d<\/p>\n

Kelley and his colleagues from URochester, Brown University, and the University of Copenhagen turned to artificial intelligence for help. In a new study<\/a> published in Science Advances<\/em>, they outline how they used physics-informed AI to determine fluid flow velocities from magnetic resonance imaging (MRI) data. Using videos of dye spreading across brain tissue over time, the neural networks the researchers built were able to deduce how fast the fluid flows and how permeable the brain tissue is.<\/p>\n

The results showed that there are two main ways that the glymphatic system washes away particles in the brain such as the amyloid beta proteins linked to Alzheimer\u2019s disease\u2014and one of these ways is much faster than the other. The fast flow of the glymphatic system\u2019s waterlike fluid moves at a few microns per second around the brain\u2019s open regions such as the surface between the skull and the brain, while the slower flow of the waterlike fluid trickles through the brain\u2019s deep tissue at a rate about 50 times slower.<\/p>\n

So far, the researchers have been working to get baseline measurements of fluid flow in the brains of animals such as mice to inform the AI tools. In the future, they hope to be able to compare the fluid flow in healthy and sick brains as well as young and old brains, with aspirations to eventually study circulation in humans.<\/p>\n

\u201cWe\u2019re working hard toward being able to measure the flow of waterlike fluids in and around human brains because then the clinical applications get a lot more important and exciting,\u201d says Kelley. \u201cWe hope to someday be able to see whether an Alzheimer\u2019s patient has poor circulation in their brain or even screen for poor circulation earlier in life to try to stave off Alzheimer\u2019s. Or we could check when somebody has been concussed to see whether the fluid circulation in their brain is disrupted. This study gets us a step closer.\u201d<\/p>\n

Kelley\u2019s collaborators on the study include Brown University PhD student Juan Diego Toscano, Ä¢¹½´«Ã½ computational scientist Yisen Guo, Brown University PhD student Zhibo Wang, Ä¢¹½´«Ã½ PhD student Mohammad Vaezi, University of Copenhagen Associate Professor Yuki Mori, Brown University Professor George Karniadakis, and Ä¢¹½´«Ã½ Assistant Professor Kimberly Boster.<\/p>\n

The NIH National Center for Complementary and Integrative Health and the NIH BRAIN Initiative supported this research.<\/p>\n","protected":false},"excerpt":{"rendered":"

The new approach combines MRI scans and AI tools to measure fluid flow linked to diseases such as Alzheimer\u2019s.<\/p>\n","protected":false},"author":1242,"featured_media":700002,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[24292,19162,23312,29752,18632,18572],"class_list":["post-699862","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sci-tech","tag-artificial-intelligence","tag-center-for-translational-neuromedicine","tag-department-of-mechanical-engineering","tag-douglas-kelley","tag-hajim-school-of-engineering-and-applied-sciences","tag-research-finding"],"acf":[],"yoast_head":"\nAI reveals how the brain clears harmful waste<\/title>\n<meta name=\"description\" content=\"The new approach combines MRI scans and AI tools to measure fluid flow linked to diseases such as Alzheimer\u2019s.\" \/>\n<meta name=\"robots\" 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