Scientists at the University of Virginia School of Medicine are leveraging artificial intelligence to improve the speed and accuracy of glioblastoma treatment. Glioblastoma, a highly aggressive brain cancer, requires swift action to extend survival and improve patient quality of life. Currently, doctors must wait months after treatment to assess tumour progression using MRI or brain surgery.
The AI imaging approach aims to differentiate between tumour progression and brain changes resulting from treatment. This distinction currently takes months, delaying critical care decisions. Initial testing shows the AI already outperforming standard clinical methods, achieving 74% accuracy in distinguishing between the two in 26 post-treatment glioblastoma patients. The project aims to exceed 80% accuracy with additional patient data for clinical use. This advancement could enable earlier treatment adjustments for brain cancer patients experiencing tumour recurrence.
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