SonoSim has launched an Introduction to Breast Ultrasound Clinical Training module, the first in a planned three-part series designed to train healthcare learners in breast ultrasound image acquisition, interpretation, and clinical decision-making.
The module includes six simulation cases drawn from real patient cases covering a range of breast anatomy, including dense fibrous tissue, axillary lymph nodes, cysts, fluid-filled lactiferous ducts, and post-menopausal breast anatomy.
The module is aligned with the 2025 update of the American College of Radiology (ACR) BI-RADS Atlas.
This module also introduces new scanning guides featuring animated instructional videos demonstrating probe positioning and scanning techniques on a virtual patient, the firm said. It is available now to existing SonoSim customers.
![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&dpr=2&fit=crop&h=167&q=70&w=250)
