The University of California, Los Angeles (UCLA) and UC Davis will co-lead a newly funded, multi-institutional clinical trial to evaluate whether artificial intelligence (AI) can help support radiologists in interpreting mammograms more accurately, with the goal of improving breast cancer screening and reducing unnecessary callbacks and anxiety for patients.
The study, known as the PRISM Trial (Pragmatic Randomized Trial of Artificial Intelligence for Screening Mammography), is supported by a $16 million award from the Patient-Centered Outcomes Research Institute (PCORI). 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. The AI support tool studied will be Transpara by ScreenPoint Medical, with clinical workflow integration provided by the Aidoc aiOS platform.
“This is the first large-scale randomized trial of AI in breast cancer screening in the United States,” said Joann G. Elmore, MD, MPH, Dual Principal Investigator and lead of the Administrative Coordinating Site, and Professor of Medicine at the David Geffen School of Medicine at UCLA and of Health Policy and Management at the UCLA Fielding School of Public Health. “We’re looking carefully and objectively at whether AI helps or hinders—and for whom. Expert radiologists remain in the driver’s seat for all interpretations.”
A Pressing Question in Breast Cancer Care
Breast cancer remains one of the leading causes of cancer death among women in the United States. While routine mammography screening reduces mortality through early detection, it also has drawbacks—including false positives that can lead to unnecessary testing, anxiety and costs, and missed cancers.
“AI has great promise, but it also raises real questions,” said Dr. Elmore, who is also an investigator at the UCLA Health Jonsson Comprehensive Cancer Center and serves as Director of the UCLA National Clinician Scholars Program. “We want to know whether AI helps radiologists find more cancers or just flags more exams that ultimately turn out to be normal.”
Patient-Centered—by Design
What makes PRISM different is its emphasis on patient-centered research. The trial was developed in close partnership with patient advocates, clinicians, health system leaders, and policymakers.
Each participating facility will continue routine screening as usual, with no changes to the patient experience. Mammograms will be randomly assigned to be interpreted either by a radiologist on their own or with assistance from a U.S. Food and Drug Administration–cleared AI support tool. In all cases, a radiologist reads the exam and makes the final decision.
“There’s never been a trial of this scope looking at AI in breast cancer screening in the U.S.,” said Hannah S. Milch, MD, Co-Principal Investigator and UCLA Site Principal Investigator and Assistant Professor of Radiology at UCLA. “The results will help inform not just clinical practice, but also insurance coverage, technology adoption, and patient communication.”
“There is a lot of hope that AI will make care better, but very few rigorous trials have actually evaluated its real-world effects,” added Dr. Elmore, who is the Rosalinde and Arthur Gilbert Foundation Endowed Chair in Health Care Delivery. “This is our opportunity to generate trustworthy evidence, with the patient perspective front and center.”
In addition to analyzing cancer detection and recall rates, the study will include focus groups and surveys to capture how patients and radiologists perceive and trust AI-assisted care.
Collaborative Effort Across Six States
The PRISM trial brings together seven leading academic medical centers:
- UCLA (Administrative Coordinating Site led by Dual-Principal Investigator, Dr. Joann Elmore, and Co-Principal Investigator and Site Principal Investigator, Dr. Hannah Milch)
- UC Davis (Data Coordinating Center led by Dual-Principal Investigator, Diana Miglioretti, PhD)
- Boston Medical Center (Site Principal Investigator, Clare B. Poynton, MD, PhD)
- UC San Diego Health (Site Principal Investigator, Haydee Ojeda-Fournier, MD)
- University of Miami (Site Principal Investigator, Jose M. Net, MD)
- University of Washington–Fred Hutchinson Cancer Center (Site Principal Investigator, Janie M. Lee, MD)
- University of Wisconsin–Madison (Co-Principal Investigator, Christoph I. Lee, MD, and Site Principal Investigators, Mai Elezaby, MD, and Ryan Woods, MD).
Dr. Elmore emphasized that the goal is not to replace human expertise but to understand how AI might complement it. “Our expert radiologists will continue to make the final call. AI may be a useful co-pilot—but it’s the radiologist who holds the wheel.”
The trial is expected to inform future policy decisions, best practices in screening, and how to most effectively integrate emerging technologies into patient care.
