A artificial intelligence (AI) has emerged to help clinicians combat aggressive brain tumors. Helps identify crucial features that provide guidance during surgery.
The Cryosection Histopathology Review and Evaluation 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 days or weeks. Kun-Hsing Yu, lead author of a July 7 article report at Med, explained that surgeons rely on detailed diagnoses to guide their operations.
Although the tool's accuracy may not match current genetic testing, it has the ability to rapidly predict a tumor's profile. This rapid analysis allows doctors to proceed with the appropriate treatment without the need to schedule and perform additional surgeries, saving valuable time, Yu explains.
In addition, CHARM can distinguish between malignant and benign tumor cells and determine the grade of the tumor, indicating its level of aggressiveness. These are evaluations that human pathologists typically make during surgery. However, according to Yu, CHARM could eliminate the need for a 10- to 15-minute wait or the presence of a pathologist on standby during the operation.
Glioma, particularly the aggressive subtype known as glioblastoma, poses a significant threat, with untreated cases leading to death in less than six months. Tragically, only 17% of people diagnosed with glioblastoma survive beyond the second year, as reported by the American Association of Neurological Surgeons.
Yu and his team trained a machine learning algorithm using images of brain surgery samples and validating its accuracy against patient diagnoses. CHARM showed superior performance in identifying tumor genetic profiles compared to other AI systems.
When making critical decisions about the extent of tissue removal and the potential use of drug-coated wafers in the treatment of glioma tumors, surgeons rely heavily on the genetic profile of the tumor. Unfortunately, obtaining this information is a very time consuming process these days.
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Research by Yu and his team is contributing to a wide range of initiatives using AI to improve diagnosis and cancer treatment. In a notable editorial published In the June issue of Lancet Oncology, the capabilities of certain systems were highlighted for their accurate identification of people at elevated risk of pancreatic, lung, and breast cancer.
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