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AI helps show how the brain's fluids flow

New research targets diseases including Alzheimer's

Date:
June 14, 2023
Source:
University of Rochester
Summary:
A new, AI-based technique for measuring fluid flow in the brain could lead to treatments for diseases such as Alzheimer's.
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A new artificial intelligence-based technique for measuring fluid flow around the brain's blood vessels could have big implications for developing treatments for diseases such as Alzheimer's.

The perivascular spaces that surround cerebral blood vessels transport water-like fluids around the brain and help sweep away waste. Alterations in the fluid flow are linked to neurological conditions, including Alzheimer's, small vessel disease, strokes, and traumatic brain injuries but are difficult to measure in vivo.

A multidisciplinary team of mechanical engineers, neuroscientists, and computer scientists led by University of Rochester Associate Professor Douglas Kelley developed novel AI velocimetry measurements to accurately calculate brain fluid flow. The results are outlined in a study published by Proceedings of the National Academy of Sciences.

"In this study, we combined some measurements from inside the animal models with a novel AI technique that allowed us to effectively measure things that nobody's ever been able to measure before," says Kelley, a faculty member in Rochester's Department of Mechanical Engineering.

The work builds upon years of experiments led by study coauthor Maiken Nedergaard, the codirector of Rochester's Center for Translational Neuromedicine. The group has previously been able to conduct two-dimensional studies on the fluid flow in perivascular spaces by injecting tiny particles into the fluid and measuring their position and velocity over time. But scientists needed more complex measurements to understand the full intricacy of the system -- and exploring such a vital, fluid system is a challenge.

To address that challenge, the team collaborated with George Karniadakis from Brown University to leverage artificial intelligence. They integrated the existing 2D data with physics-informed neural networks to create unprecedented high-resolution looks at the system.

"This is a way to reveal pressures, forces, and the three-dimensional flow rate with much more accuracy than we can otherwise do," says Kelley. "The pressure is important because nobody knows for sure quite what pumping mechanism drives all these flows around the brain yet. This is a new field."

The scientists conducted the research with support from 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.


Story Source:

Materials provided by University of Rochester. Original written by Luke Auburn. Note: Content may be edited for style and length.


Journal Reference:

  1. Kimberly A. S. Boster, Shengze Cai, Antonio Ladrón-de-Guevara, Jiatong Sun, Xiaoning Zheng, Ting Du, John H. Thomas, Maiken Nedergaard, George Em Karniadakis, Douglas H. Kelley. Artificial intelligence velocimetry reveals in vivo flow rates, pressure gradients, and shear stresses in murine perivascular flows. Proceedings of the National Academy of Sciences, 2023; 120 (14) DOI: 10.1073/pnas.2217744120

Cite This Page:

University of Rochester. "AI helps show how the brain's fluids flow." ScienceDaily. ScienceDaily, 14 June 2023. <www.sciencedaily.com/releases/2023/06/230614220636.htm>.
University of Rochester. (2023, June 14). AI helps show how the brain's fluids flow. ScienceDaily. Retrieved October 31, 2024 from www.sciencedaily.com/releases/2023/06/230614220636.htm
University of Rochester. "AI helps show how the brain's fluids flow." ScienceDaily. www.sciencedaily.com/releases/2023/06/230614220636.htm (accessed October 31, 2024).

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