Dear Women's Imaging Insider,
Interval breast cancers can be a big problem, both for clinicians and for women -- especially since they often present in more aggressive and deadly forms than screen-detected disease. In this edition of our Women's Imaging Insider, we're highlighting research presented at the recent virtual ECR 2020 that tackles the question of how the rate of interval cancer can be reduced. Take a look at our coverage, posted today.
In other women's imaging news, a group of Danish investigators say that cardiac CT used to evaluate women's heart health could have a bonus benefit: opportunistic screening for osteoporosis. And in a study published in the European Journal of Radiology, a team from Massachusetts General Hospital in Boston found that preoperative breast MRI finds 11% more cancer in women with ductal carcinoma in situ -- which could improve surgical planning and outcomes.
Take a look at our article on how a new ultrasound transducer design could improve elastography outcomes, as well as our report on how women's reluctance to comply with breast cancer screening affects programs in Germany and Sweden.
Finally, don't miss an interview with Dr. László Tabár as he reflects on his 50 years of work to improve mammography screening.
These reports make up only part of our Women's Imaging Community coverage. Check out the rest by scrolling through our full list of articles below.
![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.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![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.auntminnieeurope.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)
