$16M study tests if AI helps radiologists detect breast cancer

Seven major medical centers have launched a $16 million study to determine whether AI actually helps or hinders radiologists in detecting breast cancer on mammograms. The PRISM Trial will randomly assign hundreds of thousands of mammogram images for interpretation by either radiologists alone or radiologists assisted by FDA-approved AI, with results potentially reshaping clinical practice, insurance coverage, and patient care standards.

What you should know: This represents the first major rigorous trial to evaluate AI’s real-world effects on breast cancer screening rather than relying on theoretical promises.

• UCLA and UC Davis are co-leading the effort alongside Boston Medical Center, UC San Diego Health, University of Miami, University of Washington – Fred Hutchinson Cancer Center, and the University of Wisconsin–Madison.
• The study will use Transpara, an FDA-approved AI support tool from ScreenPoint Medical, though human radiologists will make all final decisions on patient care.
• Researchers will also conduct focus groups and surveys to assess how patients and radiologists perceive and trust AI-assisted care.

Why this matters: Breast cancer ranks among the leading causes of cancer death for women in the US, making accurate early detection critical for patient outcomes.

• Previous research has shown mixed results, with a 2024 Harvard study finding that AI can actually make it more difficult for some technicians to accurately read medical images like X-rays and CT scans.
• False positives can lead to unnecessary testing, anxiety, and costs, while missed cancers can prove fatal when early detection opportunities are lost.

The challenge: Radiologists sometimes struggle to identify cancer signs in dense breast tissue or when evidence is too small to detect visually.

• “Sometimes radiologists struggle to spot signs of cancer in dense breast tissue, or if the evidence is too small to see,” explains Dr. Christoph Lee, co-principal investigator and professor at the University of Wisconsin-Madison’s School of Medicine and Public Health.

What they’re saying: Researchers emphasize the need for evidence-based evaluation of AI tools rather than assumptions about their benefits.

• “There is a lot of hope that AI will make care better, but very few rigorous trials have actually evaluated its real-world effects,” says Dr. Joann G. Elmore, professor of medicine at UCLA’s David Geffen School of Medicine.
• “This is our opportunity to generate trustworthy evidence, with the patient perspective front and center.”
• “The results will help inform not just clinical practice, but also insurance coverage, technology adoption, and patient communication,” adds Dr. Hannah Milch, co-principal investigator at UCLA.