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Artificial intelligence helps early detection of brain tumors

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Important progress in the diagnosis and treatment of brain cancer, thanks to artificial intelligence. Researchers at Macquarie University in Sydney, led by the Italian neurosurgeon Antonio Di Ieva, have used it by combining it with a magnetic resonance technique called 2HG Magnetic Resonance Spectroscopy, to obtain extremely detailed images of the brain, with the aim of accelerating diagnosis and eliminate unnecessary surgery.

The combined technologies – reports the scholar on the university website – analyze surgical samples and identify a genetic mutation that allows doctors to accurately confirm the diagnosis of the type of glioma – the most common primary brain tumor. The existence of the mutation, which can usually only be identified with a brain tumor biopsy, allows doctors to determine whether a patient has “long or short” survival prospects.

Professor Di Ieva used deep learning to analyze glioblastoma surgical samples and then identify before surgery if the genetic mutation is present, without having to resort to pathological analyzes. “Instead of the two weeks it takes a pathologist to detect the existence of the mutation, we simply record an image of the sample and analyze the model with a deep learning technique to see if the mutation is present,” he writes. Trials are now underway around the world to use the mutation, called the IDH gene, as a target for specific vaccines, thus opening new possibilities in the treatment of brain cancer.

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