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What You Should Know: 

– DeepHealth, a subsidiary of RadNet, Inc., has launched the DeepHealth Breast Suite, a modular, end-to-end AI platform that unifies cancer detection, breast density, and risk assessment with cloud-first workflow tools. 

– The suite is designed to elevate the standard of care by accelerating interpretation and driving earlier disease detection (“stage shifting”). Clinical data from over 579,000 mammograms shows that the suite’s applications enabled a 21% increase in the breast cancer detection rate.

DeepHealth’s New Suite Unifies Breast Cancer Detection and Workflow at Scale

The pathway from routine breast cancer screening to diagnosis is often complex, fragmented, and prone to variability. DeepHealth, the AI-powered health informatics leader and wholly owned subsidiary of RadNet, Inc., is aiming to transform this entire continuum with the launch of the DeepHealth Breast Suite.

Announced today, the Breast Suite is a first-of-its-kind end-to-end platform that integrates modular, interoperable AI applications with cloud-first viewing and reporting tools. This centralized approach addresses real-world clinical challenges across the entire screening and detection pathway, building upon technologies and innovations integrated from iCAD.

“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.

Stage Shift Disease: Elevating Detection Accuracy and Equity

The core mission of the Breast Suite is to stage shift disease—meaning, detecting cancer earlier when treatment is most effective. The suite integrates a broad array of validated clinical AI capabilities:

• AI-Powered Cancer Detection (ProFound Pro): Enables more accurate diagnosis with automatic localization of regions of interest and assessment of suspicion. Components of the suite enhance diagnostic accuracy and standardization of care across more than 10 million mammograms annually.
• Automated Density Assessment: Provides consistent, objective density classification for 2D or 3D mammograms.
• AI-Powered Risk Assessment: Identifies the short-term risk of developing breast cancer (in 1-2 years) with 2x greater accuracy than traditional questionnaire-based risk models, based solely on a mammogram.
• Breast Arterial Calcification (BAC) Assessment: (Currently in development) Intended to automatically flag breast arterial calcifications on screening mammograms, revealing a potential cardiovascular disease risk.

Validation and Equity

These capabilities are supported by major, large-scale clinical studies. Recently published research in Nature Health, the largest real-world analysis of AI-powered breast cancer screening in the U.S., demonstrated that DeepHealth Breast Suite applications enabled a 21% increase in the breast cancer detection rate across diverse patient populations.

Specifically, the study showed:

• 23% more cancers detected in women with dense breasts.
• 20% more cancers detected in Black, non-Hispanic women.

Furthermore, the technology has been proven to raise the performance of generalist radiologists to the level of specialists, expanding access to high-quality breast care in areas with limited experienced readers. This underscores the suite’s potential to drive more equitable and effective breast cancer care.

Workflow Optimization: From Priority Lists to Seamless Reporting

Beyond clinical detection, the Breast Suite incorporates intelligent workflow tools built on the DeepHealth OS that boost operational efficiency and radiologist performance.

• Prioritized Worklist: Creates efficient workflows by prioritizing cases based on suspicion level.
• Cloud-first Multi-modality Viewer: Enables comprehensive image viewing—including MRI and ultrasound alongside mammograms—accessible from anywhere.
• AI-powered Safeguard Review: Improves cancer detection rate with a second reviewer workflow, decreasing false negatives and flagging likely missed cancers.
• Intelligent Reporting: Improves clinical consistency through customizable reporting, guideline standardization, and automatic pre-population of breast density findings.

By embedding detection and risk intelligence directly within these workflow tools, DeepHealth provides radiologists with enhanced capabilities to detect cancers earlier and with more confidence. The applications integrate seamlessly with existing customer technology, offering secure, fast remote access and ensuring a standardized clinical experience.