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Generative AI Risks, Regulations, and Reality

Radiology Podcast | RSNA

Release Date: 12/02/2025

Photon Counting CT Changes Thoracic Imaging show art Photon Counting CT Changes Thoracic Imaging

Radiology Podcast | RSNA

In this episode, Dr. Linda Chu reviews new Radiology studies exploring how photon counting CT is transforming thoracic imaging with ultra‑high resolution and dramatically lower radiation and contrast doses. She examines whether these visually striking images translate into better diagnostic confidence and meaningful improvements in patient care for emphysema and lung cancer imaging.        

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Body Fat Distribution at MRI show art Body Fat Distribution at MRI

Radiology Podcast | RSNA

Hosted by Dr. Sid Dogra, this episode of the Radiology Podcast explores new research showing that where fat is distributed in the body—particularly visceral and organ-specific fat—may matter more for brain health than overall BMI. Drawing on a large UK Biobank MRI study, Dr. Dogra discusses how specific fat distribution patterns, including pancreatic-predominant and “skinny fat” phenotypes, are associated with accelerated brain aging, cognitive decline, and increased neurologic disease risk.  

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The Rise of Deepfake Medical Imaging show art The Rise of Deepfake Medical Imaging

Radiology Podcast | RSNA

Hosted by Dr. Ashwin Singh Parihar, this episode features Dr. Mickael Tordjman and Dr. Bachir Taouli discussing their landmark Radiology study on AI‑generated deepfake medical images that are realistic enough to fool trained radiologists. Together, they examine what this new level of image realism means for diagnostic accuracy, clinical trust, and the future of safeguards in medical imaging.    

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New Look at Cervical Spine Evaluation show art New Look at Cervical Spine Evaluation

Radiology Podcast | RSNA

Dr. Celina Nahyun Jo talks with Dr. Mahla Radmard about how NEXUS and the Canadian C‑Spine Rule shape cervical spine imaging decisions in trauma patients. Together they explore new research that questions long‑standing imaging practices and highlights opportunities to improve value safety and accuracy in patient care.

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Incidental Adnexal Lesions show art Incidental Adnexal Lesions

Radiology Podcast | RSNA

Dr. Refky Nicola speaks with Dr. Atul Shinagare about his team’s research showing that incidental adnexal lesions on single‑phase CT are often difficult for radiologists to classify consistently, with only certain classic lesions yielding strong agreement. Their conversation underscores the limitations of CT compared with ultrasound or MRI and reinforces that most incidental adnexal findings are benign, though many still require additional imaging for clarification.  

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Inside PSMA PET Frameworks show art Inside PSMA PET Frameworks

Radiology Podcast | RSNA

Dr. Ashwin Parihar speaking with Drs. Sungmin Woo and Alberto Vargas about why standardized PSMA PET scoring systems—such as PSMA‑RADS and PROMISE—are becoming essential for consistent interpretation, communication, and treatment planning in prostate cancer. They explore the evidence behind these frameworks, current barriers to adoption, and how future harmonization efforts like the SPARC Initiative may shape the evolution of PSMA PET reporting.  

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Reassessing NSF Risk with Modern Contrast show art Reassessing NSF Risk with Modern Contrast

Radiology Podcast | RSNA

Dr. Lauren Kim speaks with Adarsh Mallepally and Dr. Cory Trankle about their large-scale retrospective study of nearly 4 million patients examining the risk of nephrogenic systemic fibrosis after gadolinium-based contrast administration in those with advanced renal dysfunction. They discuss how modern group 2 and macrocyclic agents were associated with an exceedingly low incidence of NSF, offering important reassurance for evidence-based contrast use and evolving clinical practice.  

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The New Era of Coronary CT show art The New Era of Coronary CT

Radiology Podcast | RSNA

Dr. Linda Chu speaks with Dr. Kavitha Chinnaiyan and Dr. Jonathon Leipsic about why 2026 marks an inflection point for coronary CT, from AI-enabled plaque quantification to FFR-CT and evolving guideline support for CT-first evaluation of suspected coronary artery disease. They explore how advanced imaging tools are reshaping risk assessment, personalizing prevention and revascularization decisions, and strengthening collaboration between radiology and cardiology while highlighting the need for validation, standardization, and equitable access.

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Black-White Racial Differences in BPE at Breast MRI show art Black-White Racial Differences in BPE at Breast MRI

Radiology Podcast | RSNA

Dr. Reni Butler speaks with Dr. Anne Marie McCarthy and Dr. Christine Edmonds about their study examining Black–White racial differences in background parenchymal enhancement (BPE) on contrast-enhanced breast MRI. They discuss the finding that black women had higher odds of high BPE independent of breast density, explore potential biologic and environmental drivers, and consider how quantitative BPE assessment could improve breast cancer risk stratification and screening equity.

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New Guidance on Iodinated Contrast Reactions show art New Guidance on Iodinated Contrast Reactions

Radiology Podcast | RSNA

Hosted by Dr. Lauren Kim, this episode explores the most downloaded Radiology article of 2025 with guests Dr. Carolyn Wang, Dr. Allison Ramsey, and Dr. David Lang, focusing on updated consensus guidance for managing hypersensitivity reactions to iodinated contrast media. The discussion highlights major changes in clinical practice, including more selective use of corticosteroid premedication and switching contrast agents when feasible to reduce the risk of recurrent reactions and standardize patient care.

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More Episodes

Dr. Sid Dogra talks with Dr. Paul Yi about the safe use of large language models and other generative AI tools in radiology, including evolving regulations, data privacy concerns, and bias. They also discuss practical steps departments can take to evaluate vendors, protect patient information, and build a long term culture of responsible AI use.

Best Practices for the Safe Use of Large Language Models and Other Generative AI in Radiology. Yi et al. Radiology 2025; 316(3):e241516.