Dear Women's Imaging Insider,
The debate over breast cancer screening -- when women should start, how often they should be screened, and which modality is best -- shows no signs of waning. What's needed to resolve the discussion is up-to-date information, according to researchers in California.
Dr. Laura Esserman, director of the Carol Franc Buck Breast Care Center at the University of California, San Francisco, is leading a team that plans to launch a five-year study this spring to explore how screening protocols can be tailored to women depending on their risk level. They hope the data will shed light on the screening debate; learn more about their plans in our Insider Exclusive.
When you've finished, check out what else is going on in the Women's Imaging Community:
- Discover why more women are publishing radiology research -- and why there should be even more effort to boost their numbers.
- Find out why Georgetown University researchers believe that politics are clouding mammography guidelines.
- Read why discrepancies in how breast density is measured could spell trouble for patients.
- Find out why using 3-tesla MRI for examining fetal abnormalities is a safe bet.
- Finally, get the scoop on the U.S. Preventive Services Task Force's final recommendations for breast cancer screening.
As always, if you have a comment, report, or article idea to share about any aspect of women's imaging, please contact me.



















![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)
