by
Gus Iversen, Editor in Chief | December 02, 2025
RadNet and DeepHealth at RSNA 2025
DeepHealth, a subsidiary of RadNet, has introduced a new AI-based software platform aimed at improving breast cancer screening, diagnosis, and workflow.
The platform, called Breast Suite, integrates multiple AI applications designed to aid radiologists in clinical decision-making and streamline reporting across breast imaging.
The system supports more than 10 million mammograms annually and incorporates tools for cancer detection, density classification, risk stratification, and in development, breast arterial calcification analysis. In addition to its diagnostic capabilities, Breast Suite includes workflow tools such as cloud-based image viewing, customizable reporting, and a prioritization system for high-risk cases.
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“The launch of Breast Suite marks a pivotal step toward a new, AI-powered standard of care in breast cancer screening and diagnostic pathways,” said Kees Wesdorp, president and CEO of RadNet’s digital health division, DeepHealth. “By embedding detection and risk intelligence with workflow tools, we give radiologists more capabilities to detect cancers earlier, with more confidence and to elevate patient care.”
ProFound Pro, one of the applications within the suite, uses prior imaging data to localize suspicious regions and assess malignancy likelihood. Other features include automated breast density scoring and an AI-driven model that estimates short-term cancer risk with higher reported accuracy than traditional questionnaire-based tools.
According to a recent study published in Nature Health, DeepHealth’s software contributed to a 21% increase in cancer detection among over 579,000 women screened at more than 100 sites across the U.S. Improvements were also reported in historically underserved populations, with 23% more cancers detected in women with dense breast tissue and 20% more in Black, non-Hispanic women.
The suite’s risk model was further validated in a separate European study involving 154,000 women, which found that AI-based risk estimates could significantly improve early detection compared to conventional models.
Breast Suite is built on DeepHealth OS, the company’s cloud-native operating system, and is designed to integrate with existing imaging infrastructure.
