Cerebral blood vessels are surrounded by perivascular spaces which serve as transport channels for water-like fluids that navigate around the brain, playing a crucial role in the removal of waste. Any anomalies in this fluid movement are associated with various neurological conditions, such as Alzheimer’s, small vessel disease, strokes, and traumatic brain injuries. However, measuring these fluid dynamics in vivo poses a significant challenge. Now, a new technique based on artificial intelligence (AI) offers an innovative way to measure fluid circulation around the brain's blood vessels, potentially paving the way for breakthrough treatments for conditions like Alzheimer’s.

A diverse team comprised of mechanical engineers, neuroscientists, and computer scientists led by University of Rochester (Rochester, NY, USA) has developed novel AI-based velocimetry measurements to accurately measure the flow of brain fluid. Previously, the team had managed to carry out two-dimensional studies on fluid movement in perivascular spaces by injecting tiny particles into the fluid, tracking their position and speed over a period. However, to gain a deeper understanding of this complex system, more complex measurements were necessary. Examining such a vital, fluid system in itself presented a challenge that the team addressed by adopting AI to enhance the existing 2D data with physics-informed neural networks, resulting in a first-of-its-kind high-resolution view of 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,” said University of Rochester Associate Professor Douglas Kelley who led the team. “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.” 

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