Go with the flow: fluid dynamics predict glioblastoma progression

Original story from Virginia Tech (VA, USA).

Researchers combine fluid dynamics and MRI to map hidden glioblastoma cells.

Glioblastoma is an aggressive 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. Patients diagnosed with glioblastoma survive for an average of 15 months.

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 Virginia Tech (VA, USA) have developed a tool to do just that.

Their method combines magnetic resonance imaging, 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,” commented Munson. “This is a method that now we believe can allow us to find those tumor cells.”

Currently, doctors plan surgeries to remove glioblastoma tumors based on radiological scans, but that only provides a view of the area just outside the cancer’s edge. During surgery, fluorescent dyes highlight cancer cells, but the dyes don’t penetrate deeply and the cells must be visible for this method to be effective.

“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,” explained Munson.

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Munson’s research focuses primarily on interstitial fluid flow – the movement of fluid through the spaces between cells in tissues. The flow behaves differently in different diseases. In studying glioblastoma, Munson’s lab found that faster flows predict where tumor cells are invading, while more random fluid motion, or diffusion, correlates with less invasion by the cancer cells.

However, a new metric developed by Munson’s team proved to be the best predictor. The fluid flow around the tumor established pathways, like streams merging into rivers, which the cancer cells follow to migrate into the surrounding tissue.

“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 shared.

Munson’s findings underpin the work of a new spinoff company, Cairina (VA, USA), which aims to improve cancer treatment through a more personalized approach to surgery and cancer therapies.

“Cairina is trying to take this to the next level,” Munson concluded. “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 application, and also to identify where there may be less invasion, to help spare tissue from unnecessary treatment.”

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