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E-Newsletter • October 2025 |
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Nationwide Research Investigates Use of AI on Mammograms
October is Breast Cancer Awareness Month. Women over 40 are encouraged to get annual mammograms because early detection is key to beating breast cancer. AI is used in many health settings to help determine the results of breast cancer screenings, but is it effective? The University of California, Davis (UC Davis) Health is coleading a newly funded national clinical trial to evaluate whether AI can help radiologists interpret screening mammograms more accurately. The goal is to improve breast cancer detection and reduce unnecessary callbacks and anxiety for patients.
The study, known as the Pragmatic Randomized Trial of Artificial Intelligence for Screening Mammography (PRISM) trial, is supported by a $16 million award from the Patient-Centered Outcomes Research Institute. The study will involve hundreds of thousands of mammograms interpreted at academic medical centers and breast imaging facilities in California, Florida, Massachusetts, Washington, and Wisconsin.
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“PRISM is the first large-scale randomized trial in the US to evaluate the effectiveness of AI in breast cancer screening interpretation,” says Diana Miglioretti, dual principal investigator and lead of the study’s data coordinating center, which will be based at UC Davis Health. Miglioretti is a professor and division chief of biostatistics at the UC Davis Department of Public Health Sciences and coleads the Population Sciences and Cancer Control program at UC Davis Comprehensive Cancer Center.
“We’re rigorously evaluating whether AI-assisted interpretation improves screening outcomes,” she says. “The goal is not to replace radiologists with AI but to see how effective AI could be as a copilot in reading mammography.”
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Some Breast Tumors Use Fat for Fuel
Scientists at the University of California, San Francisco, observed triple-negative breast tumors building tunnels into fat cells to fuel their growth. In the lab, they were able to halt tumor growth by disrupting this interchange. The discovery points to the possibility that drugs may be used to prevent tumor cells from accessing fat.
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MBI May Benefit Women With Dense Breasts
A multicenter, prospective evaluation of molecular breast imaging (MBI) as an adjunct to digital breast tomosynthesis (DBT) in women with dense breasts increased overall invasive cancer detection. The trial enrolled women from five sites between 2017 and 2022. Each patient received two annual screening rounds of DBT and MBI.
Pain-Free Breast Imaging System Shows Promise
An experimental system that combines photoacoustic and ultrasound imaging offers a potential pain-free breast screening exam that can be done in less than a minute. |
"Although the overall performance of state-of-the-art AI models is very high, AI sometimes makes mistakes. Identifying exams in which AI interpretation is unreliable is crucial to allow for and optimize use of AI models in breast cancer screening programs."
— Sarah D. Verboom, MSc, a doctoral candidate in the department of medical imaging at Radboud University Medical Center in the Netherlands, on the potential of a hybrid mammography reading strategy that incorporates AI with human readers to reduce radiologists’ workload without changing recall or cancer detection rates |
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