.jpg?width=2000&height=511&name=LDB_587_Prognosia%20hero%20image_220x563px_Final%20(2).jpg "LDB_587_Prognosia hero image_220x563px_Final (2)")
The Future of Breast Cancer Screening: Image-Based
Risk Has Arrived
We’re expanding our breast cancer ecosystem to include groundbreaking image-based risk assessment. This AI-powered innovation estimates a woman’s risk of developing breast cancer within the next five years, using only a screening mammogram — no extra tests, no added effort.
Lunit has acquired the image-based breast cancer risk prediction model developed by Graham A. Colditz, MD, DrPH, and Shu (Joy) Jiang, PhD, of Washington University School of Medicine in St. Louis. The tool has been granted FDA Breakthrough Device Designation — strengthening our leadership in AI-powered breast imaging.
This breakthrough solution leverages either digital mammography or synthetic DBT images calibrated to SEER data and validated in diverse populations, enabling more accurate, personalized and efficient risk assessment.
L-R: Melissa Hill, PhD, Senior Imaging Scientist & Global Research Lead, Volpara; Kihwan Kim, MD, Group Head, Cancer Screening Group, Lunit; Dr. Christopher Austin, Global Medical Director, Cancer Screening Group, Lunit; Graham Colditz, MD, DrPH, President and Founder, Prognosia; Shu (Joy) Jiang, PhD, Co-founder, Prognosia; Minji Song, MD, Medical Director, Team Leader, Cancer Screening Group, Lunit; Thijs Kooi, PhD, Dept. Head of AI Research, Cancer Screening Group, Lunit.
Discover What’s Next in Breast Cancer Risk Prediction
Read the latest articles, studies, and news on this breakthrough image-based risk model — and
sign up to stay in the loop as Lunit brings a new era to life.
News Articles
- Lunit Acquires Prognosia Breast Cancer Risk AI - The Imaging Wire
- AI breast cancer risk technology earns FDA Breakthrough status – WashU Medicine
Research Papers
- Development and Validation of Dynamic 5-Year Breast Cancer Risk Model Using Repeated Mammograms - published in JCO Clinical Cancer Informatics
- Deriving a Mammogram-Based Risk Score from Screening Digital Breast Tomosynthesis for 5-Year Breast Cancer Risk Prediction - published in AACR Journals
- Validation of a Dynamic Risk Prediction Model Incorporating Prior Mammograms in a Diverse Population - published in JAMA Network Open
Build Your AI Breast Cancer Ecosystem Today
From immediate cancer detection to lifetime risk, the addition of image-based risk to our breast cancer ecosystem will deliver a complete picture of breast health. Our solutions work together to show what’s happening now, forecasting near-term risk, and mapping long-term risk factors — while keeping providers and patients engaged and informed every step of the way.
We provide full support during implementation, including training and adoption, and continue to work with you long after deployment to help you adapt, scale, and succeed.
Lunit INSIGHT MMG and INSIGHT DBT
Strengthen your foundation for early cancer detection.
See what’s happening right now. Lunit INSIGHT MMG/DBT improves accuracy and efficiency in 2D/3D mammography reading — detecting cancers earlier, reducing interval cancers and recalls, and boosting radiologist confidence without disrupting workflows.
Volpara Risk Pathways
Build the infrastructure for personalized screening.
Plan across a lifetime. Risk Pathways combines genetics, family history, and breast density into a single profile — aligning with respected models like Tyrer-Cuzick (TC8) and supporting guidelines such as NCCN. This foundation enables long-term, personalized screening strategies and lays the groundwork for precision care.
Explore Risk Pathways →
Volpara Patient Hub
Extend connections beyond the clinic.
Keep patients engaged and close the loop on risk. Patient Hub integrates risk information into the patient record, mammography workflow, and correspondence with both patients and referring physicians. Personalized reminders, educational resources, and streamlined communications build trust, drive compliance, and support more accessible care.
Explore Patient Hub →
Volpara Scorecard
Raise the standard of breast imaging quality.
Achieve consistent breast density assessment across radiologists. Scorecard provides automated, objective breast density measurement and is validated for use with the Tyrer-Cuzick 8 risk model. By reducing variability and improving diagnostic accuracy, it strengthens confidence in every exam and helps identify women who may benefit from adjunctive imaging.
Explore Scorecard →
Redefining Breast Cancer Screening with AI
By combining detection, density, lifetime risk, and short-term image-based risk, Lunit is building the most comprehensive ecosystem in breast imaging. Together, we’re making screening more accurate, proactive, and efficient for women everywhere.
