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Novel Method Uses Interstitial Fluid Flow to Predict Where Brain Tumor Can Grow Next

By MedImaging International staff writers
Posted on 16 Sep 2025
Image: The novel approach combining MRI, fluid dynamics, and custom algorithms predicts brain cancer recurrence sites (photo courtesy of AdobeStock)
Image: The novel approach combining MRI, fluid dynamics, and custom algorithms predicts brain cancer recurrence sites (photo courtesy of AdobeStock)

Glioblastoma is one of the most aggressive brain cancers, with patients surviving on average only 15 months after diagnosis. Surgery and radiation can temporarily control the tumor, but the disease almost always returns because hidden cancer cells remain in surrounding tissues. Current imaging and dye-based methods fail to detect cells that have migrated beyond the visible tumor margin. Now, a new method based on fluid moving through and near the tumor can better identify where these invasive cells are likely to reappear.

This novel approach, created by researchers at the Fralin Biomedical Research Institute at VTC, combines magnetic resonance imaging (MRI), fluid dynamics knowledge, and a custom algorithm. The method builds on the study of interstitial fluid flow, which describes how fluid moves between cells in tissues. By modeling these flows, the algorithm predicts pathways that tumor cells use to migrate, identifying high-risk areas for recurrence beyond what standard scans reveal.

According to the researchers, faster interstitial flows around a tumor correlated with higher rates of invasion, while more random fluid diffusion corresponded to less spread. The most powerful predictor was a new metric showing how flows converge into pathlines, like streams merging into rivers, which cancer cells follow. These insights, published in npj Biomedical Innovations, demonstrate that fluid flow patterns can highlight hotspots of hidden tumor cells that standard imaging cannot detect.

This predictive model could provide surgeons and oncologists with probability maps to guide more precise and aggressive interventions where tumor cells are most likely to be. It could also spare healthy brain regions from unnecessary treatment by identifying areas with lower invasion risk. These findings are being translated into clinical tools that support personalized surgical and radiation strategies for glioblastoma patients.

“If you can't find the tumor cells, you can't kill the tumor cells, whether that's by cutting them out, hitting them with radiation therapy, or getting drugs to them. This is a method that we now believe can allow us to find those tumor cells,” said Jennifer Munson, PhD, Professor and Director of the Cancer Research Center — Roanoke at the Fralin Biomedical Research Institute at VTC. “This could tell a surgeon where there's going to be a higher chance of there being more tumor cells, so they might be a little more aggressive, if it's safe to the patient to go after a more invasive region.”

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