Can DeepHealth AI Suite Transform Breast Cancer Screening?
DeepHealth, a RadNet company, has launched the DeepHealth Breast Suite - a modular AI platform built to improve detection, risk assessment and day-to-day workflow in breast imaging. The company says the suite now supports more than 10 million mammograms each year, bringing detection and risk intelligence into one environment.
Kees Wesdorp, President and CEO of DeepHealth, frames it simply: bring stronger detection and risk signals into the same workflow radiologists use, and you create earlier findings, tighter consistency and more confident decisions.
What's inside the Breast Suite
- AI detection with prior comparison: The ProFound Pro engine uses prior exams, automatically localizes suspicious regions and assigns a degree-of-suspicion score to help focus reads.
- Automated density assessment: Consistent density scoring for both 2D and 3D mammography to support reporting and follow-up decisions.
- Near-term risk modeling: An AI-driven model estimating a patient's 1-2 year breast cancer risk. DeepHealth reports accuracy roughly twice that of traditional questionnaire-based tools.
- In development - breast arterial calcification (BAC): A tool to flag BAC on routine mammograms to inform cardiovascular risk discussions without extra imaging.
Evidence from large-scale studies
A study published in the Nature portfolio analyzed more than 579,000 mammograms across 100+ community imaging sites and reported a 21% increase in breast cancer detection rate using DeepHealth technology. Gains were higher in dense-breast and diverse patient groups, and generalist radiologists approached the performance of more specialized readers.
In Science Translational Medicine, a separate evaluation of DeepHealth's risk model in 154,000 women in Europe found that offering additional screening only to the highest-risk 10% could have detected 44% of cancers earlier. Using the Tyrer-Cuzick model, the figure was 20%.
Built for modern imaging teams
The Breast Suite includes a cloud-first viewer that supports mammography, MRI and ultrasound, with secure remote access. A prioritized worklist and rapid alerts help surface high-suspicion cases fast, while Safeguard Review adds a second-look workflow to reduce false negatives.
Intelligent reporting supports guideline-based templates and automatically populates density findings for consistency. The suite runs on DeepHealth's operating system, integrates with customer environments and is updated over time based on clinical feedback.
Why this matters for risk-stratified screening
Imaging volumes keep rising, and health systems are exploring more personalized, risk-based approaches to screening. By unifying detection, density and near-term risk in one platform, Breast Suite helps teams focus attention where it's most needed and manage throughput without losing quality.
The modular setup offers flexibility: adopt a single capability or deploy the full stack. That gives large networks and smaller centers a practical path to AI-enabled screening.
Practical considerations for adoption
- Systems integration: Confirm smooth connectivity with PACS/RIS, single sign-on and cloud security requirements.
- Local validation: Test performance against your population (including dense-breast cohorts) before wide rollout.
- Workflow design: Define when to use near-term risk and how to route high-suspicion alerts and second reviews.
- Training and QA: Provide reader training, track key metrics (recall rate, PPV, false negatives) and tune thresholds over time.
- Policy and communication: Align on risk-informed follow-up protocols and patient communication, especially when incorporating BAC findings.
The takeaway
DeepHealth's Breast Suite brings detection, density and near-term risk into one workflow and backs it with large, real-world studies. For teams moving toward risk-stratified screening, it offers a clear, scalable route to earlier detection and more consistent reads - without adding friction for clinicians.
If your organization is building AI skills across clinical and technical teams, you can explore practical training options by role at Complete AI Training.
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