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Predicting Glioblastoma Recurrence with Fluid Dynamics
What is Glioblastoma and Why is it So Tough too Treat?
Glioblastoma is a devastatingly effective brain cancer. Doctors can cut it out or blast it with radiation, but that only buys time. The cancer has an insidious ability to hide enough tumor cells in tissue around the tumor to allow it to return as deadly as ever.
Patients diagnosed with glioblastoma survive for an average of 15 months.
The challenge lies in the cancer’s ability to spread microscopically, making complete eradication extremely difficult. Even after aggressive treatment, residual cancer cells often remain, leading to unavoidable recurrence.
New Method for Identifying Recurrence Risk
What’s needed is a better way of identifying those hidden cancer cells and predicting where the tumor might grow next. Jennifer Munson believes she and her research team at the Fralin Biomedical Research Institute at VTC have developed a tool to do just that.
Thier method, described in npj Biomedical Innovations, combines magnetic resonance imaging (MRI), Munson’s in-depth knowledge of how fluid moves through human tissues, and an algorithm Munson’s team developed to identify and predict where the cancer might reappear.
“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,” says Munson, professor and director of the FBRI Cancer Research Center-Roanoke. “This is a method that now we believe can allow us to find those tumor cells.”
How Does the Method Work?
The research leverages the understanding that glioblastoma cells often reside along pathways of fluid flow within the brain. These pathways, including interstitial fluid and cerebrospinal fluid, can act as conduits for cancer cell dissemination.
Here’s a breakdown of the process:
- MRI Scanning: High-resolution MRI scans are used to visualize the tumor and surrounding brain tissue.
- Fluid Flow analysis: Munson’s expertise in fluid dynamics is applied to analyze how fluid moves through the brain, identifying potential pathways for cancer cell spread.
- Algorithm Application: The team’s developed algorithm analyzes the MRI data and fluid flow patterns to predict areas of high recurrence risk.
By pinpointing these areas, clinicians can potentially target treatment more effectively, improving patient outcomes.
Implications and Future Directions
This new method represents a significant step forward in glioblastoma treatment. By predicting recurrence patterns, doctors may be able to
