Monday, November 30 | 10:40 a.m.-10:50 a.m. | SSC06-02 | Room S402AB
A newly developed computer-aided detection (CAD) scheme can find cases of craniosynostosis -- the premature fusion of skull bones -- that normal prenatal ultrasound can miss, researchers from Brown University report."While many birth defects are diagnosed in utero by ultrasound, many are missed," wrote lead author Dr. Helena Taylor, PhD. "Although craniosynostosis is one of the most common congenital anomalies, head shape is not routinely analyzed. Here we perform rigorous head shape analysis on prenatal ultrasounds, demonstrating that craniosynostosis can be reliably diagnosed prenatally."
The investigators collected ultrasound images from 22 children who had CT-confirmed postnatal diagnosis, along with 22 controls. They trained two machine-learning algorithms with six measurements, revealing accuracy of about 89% and specificity of about 95%.
The CAD technique is a reliable tool for quantitatively assessing prenatal ultrasound images for craniosynostosis, with accuracies far exceeding surgeons' assessments, the group wrote.












![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)






