Key Features of the AI Tool:

• The tool analyzes shapes and patterns of cells from medical lab slides, which are already used for cancer diagnosis.
• It helps determine the effectiveness of specific chemotherapy treatments for individual patients.
• Importantly, it does not require additional procedures or costs.

Potential Benefits:

• Identifies patients likely to respond positively to specific chemotherapy early in the treatment process.
• Maximizes therapeutic benefits while minimizing unnecessary side effects.
• Facilitates quicker access to clinical trials for eligible patients.

Expert Insights:

Dr. Martina Bazzaro, an associate professor at the University of Minnesota Medical School, stated, “From the time of diagnosis, this AI tool can help identify which treatments are most likely to benefit ovarian cancer patients. It can reduce uncertainty early in the treatment planning process, avoid therapies that are unlikely to help, and lessen both the emotional and financial burden on patients and the healthcare system.”

Dr. Emil Lou, a professor at the University of Minnesota Medical School, added, “We created an AI tool that measures how much of a tumor is made of cancer cells versus surrounding tissue. This measurement is very helpful when someone is first diagnosed, and our AI was just as accurate as expert doctors.”

Next Steps:

The research team plans to initiate clinical trials within the next six months to further evaluate the tool’s real-world impact and integrate it into healthcare systems for automatic delivery of results to care teams.

This research was supported by the Minnesota Ovarian Cancer Alliance, the Randy Shaver Community Fund, and the American Cancer Society.