CLINICAL AI

ScreenPoint Medical has achieved a significant milestone in medical AI validation with the selection of its Transpara breast imaging artificial intelligence solution for the PRISM Trial, a landmark $16 million randomized controlled study funded by the Patient-Centered Outcomes Research Institute (PCORI). This represents the first large-scale evaluation of AI-assisted mammography interpretation in the United States, positioning Transpara at the forefront of clinical evidence generation for breast cancer screening technologies.
The PRISM Trial (Pragmatic Randomized Trial of Artificial Intelligence for Screening Mammography) will be co-led by UCLA and UC Davis, encompassing hundreds of thousands of mammograms across leading academic medical centers in California, Florida, Massachusetts, Washington, and Wisconsin. The study's primary objectives focus on determining whether AI support can enhance radiologists' diagnostic accuracy, improve early cancer detection rates, and reduce unnecessary patient callbacks that contribute to healthcare anxiety and system inefficiencies.
Transpara's selection for this pivotal study builds upon an extensive foundation of clinical validation spanning over 35 peer-reviewed publications and real-world deployment across more than 30 countries. The AI system has processed over 10 million mammograms and demonstrated remarkable performance metrics in the Swedish MASAI trial, where Transpara-assisted workflows increased cancer detection by 29% while reducing radiologist workload by 44% without compromising specificity. These results represent some of the most compelling evidence for AI efficacy in breast imaging to date.
The clinical workflow integration will be facilitated through Aidoc's aiOS platform, ensuring seamless incorporation into existing radiology practices without disrupting established interpretation protocols. Transpara's FDA-cleared technology supports both 2D mammography and digital breast tomosynthesis, providing comprehensive risk assessment through sophisticated machine learning algorithms that identify soft-tissue lesions and calcifications while generating exam-level risk scores. This dual capability addresses the full spectrum of current mammographic screening modalities.
Beyond immediate diagnostic support, recent research published in PMC demonstrates Transpara's potential for long-term risk stratification, with AI scores on mammograms obtained 2-5.5 years before cancer diagnosis showing significant associations with future malignancy development. This temporal predictive capability suggests applications extending beyond immediate screening into personalized risk assessment and surveillance optimization.
The PRISM Trial's patient-centered design, developed in collaboration with patient advocates, clinicians, and healthcare policymakers, ensures that outcomes will reflect real-world clinical needs and patient experiences. As radiologist shortages continue to challenge healthcare systems globally, AI-assisted interpretation represents a promising solution for maintaining high-quality breast cancer screening while optimizing resource utilization. The trial's results will provide crucial evidence for regulatory bodies, healthcare administrators, and clinical practitioners evaluating AI integration strategies in mammography programs.