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Artificial intelligence can help to improve prognosis and treatment for glioblastoma

Press releases may be edited for formatting or style | October 29, 2020 Artificial Intelligence MRI

Dr Mi and her colleagues are now validating their results in another, different set of patients, as well as carrying out further studies to characterise changes in the temporalis muscle during follow-up of glioblastoma patients after diagnosis and treatment. They hope to collaborate with other academic centres that have their own repositories of glioblastoma brain MRI scans in order to set up a multi-centre study.

Professor David Harrison, who is Professor of Pathology at the University of St Andrews and chair of the NCRI Cellular Molecular Pathology Initiative, was not involved with the research. He commented: "Doctors who treat cancer patients know that a person's physical condition and frailty is linked to their ability to tolerate treatment. It also affects how they respond and their long-term survival. However, it has been very difficult to develop objective measurements of patients' performance status. This is where AI can help. The research by Ella Mi and her colleagues applies AI in a cancer which is particularly aggressive and difficult to treat successfully in order to select the best treatment approach.

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"At this stage their findings show that there is an association between the temporalis muscle size and a patient's frailty and how their disease progresses. The results do not show that the muscle area actually causes the change in patients' outcomes. The findings deserve study in a larger group of patients to take account of factors such as changes to the muscle caused by other factors, including surgery or radiotherapy."

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