The American College of Radiology (ACR) Data Science Institute (DSI) has released six new artificial intelligence (AI) use cases detailing how the technology can be used in a variety of disease detection and lesion quantification scenarios in neuroradiology.
The new AI use cases include the following:
- Hemorrhagic brain contusion
- Detection of communicating hydrocephalus
- Cerebrospinal fluid flow quantification
- White-matter lesion tracking in multiple sclerosis
- Quantifying carotid stenosis on CT angiography
- Identifying non-enhancing infiltrative tumor in high-grade glioma
With the new releases, the ACR DSI has now published 21 use cases for neuroradiology AI, according to the organization. All AI use cases are available for free on the ACR DSI's website.
![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)
