Dear AuntMinnie Member,
Is the debate that's been raging over the effectiveness of breast screening largely contrived? That's the intriguing question posed by a new study in our Women's Imaging Digital Community this week.
A group of researchers that included Robert A. Smith, PhD, of the American Cancer Society, Dr. Stephen Duffy of Queen Mary University of London, and Dr. László Tabár of Falun Central Hospital wanted to see why there was so much variance in the findings of different population-based screening trials -- variance that has been fueling debate over the effectiveness of breast screening.
In results presented this week at the San Antonio Breast Cancer Symposium (SABCS), the researchers talked about their work in standardizing a number of variables between four major breast screening studies. Once that was done, they found that the variance in the number of women needed to screen to produce a mortality benefit wasn't that different after all.
Read more about the study by clicking here, or visit the community at women.auntminnie.com.
Imaging ED services go unpaid
If you had to guess, what percentage of imaging services that radiology provides to emergency departments (ED) goes unpaid?
A research team led by Dr. Richard Duszak Jr. from the American College of Radiology's Harvey L. Neiman Health Policy Institute analyzed that question in a study that was presented at last week's RSNA meeting in Chicago.
The answer? Fully one-third of services are uncompensated, amounting to $2,483 per month of lost income per radiologist. Read more about the study and its implications for radiology by clicking here, or visit our RADCast @ RSNA section at rsna.auntminnie.com.















![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)


