AI model identifies overlooked brain tumors in just 10 seconds
In another triumph for AI in healthcare, researchers have developed a model that can spot bits of brain tumors that surgeons may miss while removing them from patients. It can detect these remaining tissues in as little as 10 seconds, and help prevent a host of long- and short-term post-procedure complications.
Developed by University of Michigan and University of California San Francisco researchers, the technology is called FastGlioma – incorporating the term 'glioma' that refers to a brain or spinal cord tumor.
"The technology works faster and more accurately than current standard of care methods for tumor detection and could be generalized to other pediatric and adult brain tumor diagnoses," said neurosurgeon Todd Hollon, a senior author of the paper detailing FastGlioma's effectiveness that appeared in Nature. "It could serve as a foundational model for guiding brain tumor surgery.”
With most tumor removal surgeries, it's difficult to tell healthy brain tissue and tumorous tissue apart – and as a result, a bit of residual tumor could remain in the cavity from where the mass was removed.
