Dear Women’s Imaging Insider,
As Californians head to the polls tomorrow to wade through the gubernatorial recall quagmire, they’ll be asked to consider other issues as well. Proposition 54, for example, seeks to ban the collection of race-related data in public records.
Opponents of Prop. 54 claim it would prohibit the medical community from collecting race-related data, thus preventing efforts to identify and study disease patterns in ethnic communities. Proponents of the ballot initiative say that’s hogwash: healthcare organizations are exempt under Prop. 54. Medical folks fire back that the exemption is pointless -- many population-based healthcare studies collect their initial information from public records.
The debate shows how prickly the topic of racial disparity can be. When it comes to healthcare, however, racial profiling can be a lifesaver. Breast cancer is a prime example of the value of race-based research.
The latest U.S. figures show that Caucasian women have a higher incidence of breast cancer than other racial or ethnic groups. Yet the latter groups must contend with higher death rates from breast carcinoma. The reasons for the discrepancy are manifold and complex, according to our Insider Exclusive article on racial disparity in breast cancer screening and outcomes.
Access, cultural norms, and physical differences are just some of the theories that researchers put forth to explain differences among the groups -- theories that wouldn’t exist if it weren’t for specific data on ethnicity. You'll find more about it here.
Also, be sure to check in with the Women’s Imaging Digital Community over the course of Breast Cancer Awareness month. We’ll be featuring reports from international radiologists on breast cancer screening in their countries. We’ll also have an interview with the executive director of the Academy of Molecular Imaging on the role of that modality in breast cancer research.
We’ll also be featuring a resident’s perspective on how to beckon new radiologists to breast imaging. And if you haven’t already done so, also check out our Breast Cancer Awareness Month kick-off article on breast ultrasound.











![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)






