Catch up on the top radiology content of the past week.
Commentary|Videos|June 9, 2026
From Hesitation to Integration: Evidence-Based Adoption of Breast Imaging AI
Fact checked by: Austin Littrell
David Gruen, MD, MBA, FACR, of Advanced Radiology Consultants, shares how leading programs turned clinical evidence into operational reality.
Advertisement
Advertisement
Breast imaging artificial intelligence (AI) has moved beyond “Does it work?” to “Can we implement it — reliably, repeatably, and at scale?”
Related to this article
Catch up on the top radiology content of the past week.
This summer's breast imaging research spanned digital breast tomosynthesis (DBT) efficiency gains, AI models that flag cancer risk years before diagnosis, a cautionary study on automation bias, and advances in ultrasound, MRI, and contrast-enhanced mammography (CEM). Here is a look back at the most well-viewed breast imaging content of the summer.
In the second of a two-part podcast episode, Lauren Nicola, MD, Christoph Wald, MD, PhD, MBA, and Peter Shen discuss challenges with evaluating value and ROI for AI software, the physician time required to do so, and possible solutions to facilitate improved clarity and consistency with AI reimbursement.
While AI tools abound in radiology, how many AI-enabled software products have incorporated insights from clinical radiologists?
In the first of a two-part podcast episode, Lauren Nicola, MD, Christoph Wald, MD, PhD, MBA, and Peter Shen discuss current challenges with reimbursement for AI in radiology.
Catch up on the top radiology content of the past week.
Catch up on the most-well viewed radiology content in August 2026.
Advertisement
Advertisement