A new AI-based model can predict where the most common malignant brain cancer is most likely to return after initial surgery, potentially giving doctors a chance to treat it before it becomes visible on MRI.
Glioblastoma is the most lethal brain tumor in adults, with a median survival of about 17 months after diagnosis. Even after surgeons remove all visible tumor and patients receive follow-up treatment, the cancer almost always returns.
Now, researchers led by UC San Francisco and University of Michigan have developed an AI approach that can predict, with a high degree of accuracy, where first recurrence is likely to appear. In glioblastoma, most patients experience recurrence at or close to the tumor cavity.
The findings, published Sept. 25 in Science Advances and supported by the National Institutes of Health (NIH), could eventually enable doctors to use targeted treatments in these areas before a new tumor becomes visible on MRI.
“The system has incredible potential to provide neurosurgeons with valuable real-time guidance during tumor removal,” said first author Sanjeev Herr, MD, a postdoctoral research fellow at UCSF. “It can also generate insights that guide subsequent treatment decisions.”
These treatments might include removing additional tissue during the initial surgery when it is safe to do so, said senior author Shawn Hervey-Jumper, MD, a neurosurgeon at UCSF Health, and Mitchel S. Berger, MD, endowed professor at the Weill Institute for Neurosciences.
“Patients with disease in parts of the brain that cannot be removed may undergo other treatments targeted at the predicted sites of progression, like higher-dose focal radiation or drugs infused directly into the tumor, via a catheter placed through the skull,” Hervey-Jumper said.