Major National Study Launched to Evaluate AI in Breast Cancer Screening

Sylvester part of major national study on AI use in breast cancer screening

University of Miami Miller School of MedicineSep 23 2025 Sylvester Comprehensive Cancer Center, part of University of Miami Miller School of Medicine, 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. As the first major randomized trial of AI in breast cancer screening in the U.S., this study represents a pivotal step. Our goal is to rigorously and objectively assess AI's impact - identifying who benefits and who may not. Radiologists remain firmly in control of all diagnostic decisions." Jose Net, M.D., director of breast imaging services at Sylvester, associate professor of clinical radiology at the Miller School and co-principal investigator of the study A pressing question in breast cancer care Breast cancer remains one of the leading causes of cancer death among women in the U.S. 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. "While AI offers substantial promise, it also prompts critical questions," said Net. "Our focus is on understanding whether AI genuinely enhances cancer detection by radiologists or simply leads to more false alarms." 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 an FDA-cleared AI support tool. In all cases, a radiologist reads the exam and makes the final decision. "A trial of this magnitude focusing on AI in breast cancer screening has never been conducted in the U.S.," stated Net. "The findings will influence not only clinical practices but also insurance policies, technology integration, and patient interactions. According to Net, while there is significant optimism that AI will enhance health care, few rigorous studies have assessed its actual impact in real-world settings. "This trial presents an opportunity to produce reliable evidence with a strong emphasis on the patient's perspective," he stated. 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; Co-Principal Investigator and Site PI, Dr. Hannah Milch) UC Davis (Data Coordinating Center led by Dual-Principal Investigator, Dr. Diana Miglioretti) Boston Medical Center (Site Principal Investigator, Dr. Clare B. Poynton) UC San Diego (Site Principal Investigator, Dr. Haydee Ojeda-Fournier) Sylvester Comprehensive Cancer Center, part of the University of Miami (Site Principal Investigator, Dr. Jose M. Net) University of Washington - Fred Hutchinson Cancer Center (Site Principal Investigator, Dr. Janie M. Lee) University of Wisconsin, Madison (Co-Principal Investigator, Dr. Christoph I. Lee; Site Principal Investigators, Dr. Mai Elezaby and Dr. Ryan Woods) Striking the right balance Net emphasized that the goal is not to replace human expertise but to understand how AI might complement it. "Our skilled radiologists will always have the final say. While AI can serve as a helpful assistant, it is ultimately the radiologist who is in control." The trial is expected to inform future policy decisions, best practices in screening, and how to most effectively integrate emerging technologies into patient care. University of Miami Miller School of Medicine

UCLA to co-lead a large-scale randomized trial of AI in breast cancer screening

University of California - Los Angeles Health SciencesSep 23 2025 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 Dr. Joann G. Elmore, 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 U.S. 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 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 an FDA-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. The results will help inform not just clinical practice, but also insurance coverage, technology adoption, and patient communication." Dr. Hannah Milch, Co-Principal Investigator and UCLA Site PI and assistant professor of radiology at UCLA "There is a lot of hope that AI will make care better, but very few rigorous trials have actually evaluated its real-world effects," said Elmore. "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; Co-Principal Investigator and Site PI, Dr. Hannah Milch) UC Davis (Data Coordinating Center led by Dual-Principal Investigator, Dr. Diana Miglioretti) Boston Medical Center (Site Principal Investigator, Dr. Clare B. Poynton) UC San Diego Health (Site Principal Investigator, Dr. Haydee Ojeda-Fournier) University of Miami (Site Principal Investigator, Dr. Jose M. Net) University of Washington - Fred Hutchinson Cancer Center (Site Principal Investigator, Dr. Janie M. Lee) University of Wisconsin-Madison (Co-Principal Investigator, Dr. Christoph I. Lee; Site Principal Investigators, Dr. Mai Elezaby and Dr. Ryan Woods) Striking the right balance 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. University of California - Los Angeles Health Sciences

Sylvester to Participate in $16M National Study on Artificial Intelligence in Breast Cancer Screening | Newswise

Newswise -- MIAMI, FLORIDA (Sept. 23, 2025) - Sylvester Comprehensive Cancer Center, part of University of Miami Miller School of Medicine, 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. "As the first major randomized trial of AI in breast cancer screening in the U.S., this study represents a pivotal step," said Jose Net, M.D., director of breast imaging services at Sylvester, associate professor of clinical radiology at the Miller School and co-principal investigator of the study. "Our goal is to rigorously and objectively assess AI's impact -- identifying who benefits and who may not. Radiologists remain firmly in control of all diagnostic decisions." A Pressing Question in Breast Cancer Care Breast cancer remains one of the leading causes of cancer death among women in the U.S. 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. "While AI offers substantial promise, it also prompts critical questions," said Net. "Our focus is on understanding whether AI genuinely enhances cancer detection by radiologists or simply leads to more false alarms." 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 an FDA-cleared AI support tool. In all cases, a radiologist reads the exam and makes the final decision. "A trial of this magnitude focusing on AI in breast cancer screening has never been conducted in the U.S.," stated Net. "The findings will influence not only clinical practices but also insurance policies, technology integration, and patient interactions. According to Net, while there is significant optimism that AI will enhance health care, few rigorous studies have assessed its actual impact in real-world settings. "This trial presents an opportunity to produce reliable evidence with a strong emphasis on the patient's perspective," he stated. 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: Striking the Right Balance Net emphasized that the goal is not to replace human expertise but to understand how AI might complement it. "Our skilled radiologists will always have the final say. While AI can serve as a helpful assistant, it is ultimately the radiologist who is in control." The trial is expected to inform future policy decisions, best practices in screening, and how to most effectively integrate emerging technologies into patient care.

UCLA to Lead $16 Million National Study on Artificial Intelligence in Breast Cancer Screening | Newswise

Dr. Hannah Milch, Co-Principal Investigator and Site PI, and Assistant Professor of Radiology at UCLA, reviews a mammogram for signs of breast cancer. Newswise -- 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 Dr. Joann G. Elmore, 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 U.S. 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 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 an FDA-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 Dr. Hannah Milch, Co-Principal Investigator and UCLA Site PI 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," said Elmore. "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; Co-Principal Investigator and Site PI, Dr. Hannah Milch) * UC Davis (Data Coordinating Center led by Dual-Principal Investigator, Dr. Diana Miglioretti) * Boston Medical Center (Site Principal Investigator, Dr. Clare B. Poynton) * UC San Diego Health (Site Principal Investigator, Dr. Haydee Ojeda-Fournier) * University of Miami (Site Principal Investigator, Dr. Jose M. Net) * University of Washington - Fred Hutchinson Cancer Center (Site Principal Investigator, Dr. Janie M. Lee) * University of Wisconsin-Madison (Co-Principal Investigator, Dr. Christoph I. Lee; Site Principal Investigators, Dr. Mai Elezaby and Dr. Ryan Woods) Striking the right balance 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.