Anyone, from students to residents to experienced radiologists, can become advocates for medical imaging. Just ask Amy Patel, MD, who for over a decade now has balanced her work in "radvocacy" with her day-to-day clinical breast imaging work.
Patel is the medical director of the Breast Care Center at Liberty Hospital in Missouri and is a clinical associate professor of radiology at the University of Kansas School of Medicine. She also chairs the American College of Radiology (ACR) Radiology Advocacy Network (RAN) and RADPAC.
In the inaugural episode of AuntMinnie's new biweekly Women's Imaging MinnieCast podcast series, Patel shares her journey in breast imaging and advocacy, detailing her experiences from residency to leadership roles in organizations like RAN and RADPAC. She discusses the importance of patient education, the differences in advocacy at local and federal levels, and the collaborative efforts needed to address healthcare challenges.
Patel also emphasizes the need for continuous advocacy work, especially in light of current healthcare issues, and encourages involvement from all levels of the medical community.











![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)




