iCAD has received clearance from the U.S. Food and Drug Administration (FDA) for the latest version of its ProFound Detection software for digital breast tomosynthesis.
ProFound Detection 4.0 was trained using advanced deep-learning convolutional neural networks and achieved a 22% overall improvement over the prior version in detecting some of the most challenging and aggressive cancer subtypes, iCAD said. The new version also delivers more precise lesion marking, with an 18% improvement in cases with no marks, which reduces potential false positives, according to the vendor.
Significantly, ProFound Detection Version 4.0 now enables clinicians to incorporate a prior exam into its AI analysis and case-score/lesion assessment on the current case, which emulates the approach radiologists take when interpreting current screening exams with historical context, iCAD said.











![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)






