Artificial intelligence predicts genetics of cancerous brain tumors in under 90 seconds

Using artificial intelligence, researchers have discovered how to screen for genetic mutations in cancerous brain tumors in under 90 seconds - and possibly streamline the diagnosis and treatment of gliomas, a study suggests.

Molecular classification is increasingly central to the diagnosis and treatment of gliomas, as the benefits and risks of surgery vary among brain tumor patients depending on their genetic makeup. In fact, patients with a specific type of diffuse glioma called astrocytomas can gain an average of five years with complete tumor removal compared to other diffuse glioma subtypes.

A team of neurosurgeons and engineers at Michigan Medicine, in collaboration with investigators from New York University, University of California, San Francisco and others, developed an AI-based diagnostic screening system called DeepGlioma that uses rapid imaging to analyze tumor specimens taken during an operation and detect genetic mutations more rapidly.

In a study of more than 150 patients with diffuse glioma, the most common and deadly primary brain tumor, the newly developed system identified mutations used by the World Health Organization to define molecular subgroups of the condition with an average accuracy over 90%. The results are published in Nature Medicine.

However, access to molecular testing for diffuse glioma is limited and not uniformly available at centers that treat patients with brain tumors. When it is available, said researchers, the turn around time for results can take days, even weeks.

“Barriers to molecular diagnosis can result in suboptimal care for patients with brain tumors, complicating surgical decision-making and selection of chemoradiation regimens,” ended researchers.

Reference:

Artificial intelligence predicts genetics of cancerous brain tumors in under 90 seconds; Nature Medicine, DOI:10.1038/s41591-023-02252-4