ROANOKE – Glioblastoma, an aggressive form of brain cancer, poses a significant challenge to medical professionals. Current treatments,including surgery and radiation,often provide only temporary relief as the cancer has a tendency to reappear.

The average survival time for patients with glioblastoma is approximately 15 months. A team at the Fralin Biomedical Research Institute at VTC, led by Jennifer Munson, believes they have created a new method to identify hidden cancer cells and forecast future tumor growth.

The team’s approach, detailed in npj Biomedical Innovations, uses magnetic resonance imaging (MRI), fluid dynamics, and a unique algorithm to predict cancer recurrence. This method aims to improve the precision of cancer treatment by identifying areas at high risk of tumor invasion.

“If you can’t find the tumor cells, you can’t kill the tumor cells, weather that’s by cutting them out, hitting them with radiation therapy, or getting drugs to them,” said 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.”

Conventional methods for planning glioblastoma surgeries rely on radiological scans, which offer a limited view beyond the tumor’s immediate edge. While fluorescent dyes can highlight cancer cells during surgery, they lack the ability to penetrate deeply into tissues, leaving potentially dangerous cells undetected.

“Those methods are not going to see a cell that has migrated or invaded further into the tissue, which is something that we think we can do with this method,” said Munson, who also holds an appointment in Virginia Tech’s Department of Biomedical engineering and Mechanics.

Interstitial Fluid Flow and Cancer Prediction

“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,”

Munson’s research centers on interstitial fluid flow, which is the movement of fluid between cells in tissues. The behavior of this flow varies across different diseases. In glioblastoma, faster fluid flows indicate areas where tumor cells are actively invading. Conversely, random fluid motion, or diffusion, is associated with less cancer cell invasion.

The team discovered that the fluid flow around the tumor creates pathways that cancer cells use to spread into surrounding tissue. This new metric is the most accurate predictor of tumor spread.

“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,” Munson said.

Cairina: A Spinoff Company for Personalized Cancer Treatment

Munson’s research has led to the creation of a new company, Cairina, focused on enhancing cancer treatment through personalized approaches to surgery and therapies.

“Cairina is trying to take this to the next level,” Munson said. “Our goal is to supply surgeons and radiation oncologists with probability maps or hotspot maps, where we would predict more cancer cell invasion to support more aggressive therapeutic submission, and also to identify where there may be less invasion, to help spare tissue from unnecessary treatment.”

The research was supported by grants from the National Cancer Institute, the Red Gates Foundation, the American Cancer Society, and the National Institute of Neurological Disorders and Stroke.