
AI use in breast radiology increased cancer detection without higher recall rates, according to a 100,000+ case multicenter study.
Key Details
- 1Study conducted across four sites and included nine experienced breast radiologists.
- 2Over 100,000 digital breast tomosynthesis (DBT) exams analyzed.
- 3Results compared pre- and post-AI implementation: 54,000 exams before AI (339 true positives) vs. nearly 49,000 with AI (369 true positives).
- 4AI improved invasive and dense breast cancer detection and lowered average diagnosis stage.
- 5No increase in recall rates was observed with AI usage.
- 6The AI tool was provided by iCAD and the DBT system by GE HealthCare.
Why It Matters

Source
Radiology Business
Related News

AI Advances in Breast Cancer Risk, CEUS Training Updates, and Imaging AI Variability
This week's top radiology news reviews AI advances in breast and lung cancer risk prediction, new CEUS training standards, and prostate screening updates with imaging modalities.

DeepHealth's Prostate AI Gains FDA Clearance for MRI Workflows
DeepHealth, a RadNet subsidiary, received FDA clearance for its AI solution to assist prostate cancer detection and MRI workflow.

Mammography AI Model Outperforms Rivals for 10-Year Breast Cancer Risk
A new mammography-based AI model predicts 10-year breast cancer risk more accurately than established clinical and AI models.