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

AI & Digital Health Innovation member Todd Hollon, MD along with a team of neurosurgeons and engineers at Michigan Medicine, in collaboration with investigators from New York University, University of California, San Francisco and others, have 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. DeepGlioma can screen for genetic mutations in cancerous brain tumors in under 90 seconds — and possibly streamline the diagnosis and treatment of gliomas.

“This AI-based tool has the potential to improve the access and speed of diagnosis and care of patients with deadly brain tumors,” said creator of DeepGlioma Todd Hollon, MD,  neurosurgeon at University of Michigan Health and assistant professor of neurosurgery at U-M Medical School.

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. DeepGlioma creates an avenue for accurate and more timely identification that would give providers a better chance to define treatments and predict patient prognosis. Prior to DeepGlioma, surgeons did not have a method to differentiate diffuse gliomas during surgery. An idea that started in 2019, the system combines deep neural networks with an optical imaging method known as stimulated Raman histology, also developed at U-M, to image brain tumor tissue in real time. DHI data and resources were used to support this research, including Imaging Data and Armis2 GPUs.

“DeepGlioma creates an avenue for accurate and more timely identification that would give providers a better chance to define treatments and predict patient prognosis,” Hollon said. Even with optimal standard-of-care treatment, patients with diffuse glioma face limited treatment options. The median survival time for patients with malignant diffuse gliomas is only 18 months, Fewer than 10% of patients with glioma are enrolled in clinical trials, which often limit participation by molecular subgroups. Researchers hope that DeepGlioma can be a catalyst for early trial enrollment. 

Collaborators include Sandra Camelo-Piragua, also a Precision Health member. This work was supported by the National Institutes of Health, Cook Family Brain Tumor Research Fund, the Mark Trauner Brain Research Fund, the Zenkel Family Foundation, Ian’s Friends Foundation and the UM Precision Health Investigators Awards grant program. More recently this work has received supported by the Chan Zuckerberg Initiative.

You can read more here: “Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging,” Nature Medicine.DOI: 10.1038/s41591-023-02252-4