AI tool revolutionized brain tumor treatment by guiding surgeons: Study

An artificial intelligence (AI) tool has emerged to aid doctors in dealing with aggressive brain tumours. This helps identify important features that provide guidance during surgery.

The Cryosection Histopathology Assessment and Review Machine (CHARM) is an advanced tool that efficiently analyzes images to identify the genetic profile of gliomas, a type of aggressive brain tumor. Currently, this process takes several days or weeks. Kun-hsing Yu, Senior Writer July 7 reports In Med, explained that surgeons rely on detailed diagnosis to guide their operations.

Although the accuracy of the tool cannot match that of current genetic tests, it has the potential to rapidly estimate the profile of tumors. This quick analysis enables doctors to proceed with appropriate treatment without the need for rescheduling and additional surgery, thereby saving valuable time, as explained by Yu.

In addition, CHARM can differentiate between malignant and benign tumor cells and determine the grade of a tumor, which reflects its level of aggressiveness. These are assessments that human pathologists typically make during surgery. However, according to Yu, CHARM can eliminate the need for 10 to 15 minutes of waiting or the presence of a pathologist on standby during an operation.

Glioma, a particularly aggressive subtype known as glioblastoma, poses a significant risk, leading to death in less than six months if left untreated. Sadly, only 17% of people with glioblastoma survive past the second year informed of by the American Association of Neurological Surgeons.

Yu and his team trained a machine-learning algorithm using images of brain surgery samples and validated its accuracy against patient diagnoses. Compared to other AI systems, CHARM showed superior performance in identifying tumor genetic profiles.

When making critical decisions about the extent of tissue removal and the potential use of drug-coated wafers in treating glioma tumors, surgeons rely heavily on the tumor’s genetic profile. Unfortunately, obtaining this information is currently a time consuming process.

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The research by Yu and his team is contributing to a wider range of initiatives that use AI to enhance cancer diagnosis and treatment. in a remarkable editorial published In the June edition of Lancet Oncology, the capabilities of certain systems were outlined for the accurate identification of individuals at high risk of pancreatic, lung and breast cancer.

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