Screening Mammography with AI Support

Dr. Linda Chu speaks with Dr. Andrew Trout, Professor of Radiology and Director of Clinical Research at Cincinnati Children’s, and Dr. Erin Angel, Vice President of Research and Scientific Affairs at GE HealthCare. They discuss the unique challenges of pediatric imaging and how collaboration and technology are advancing care for young patients while improving imaging for all. Sponsored by GE HealthCare.

Dr. Linda Chu and Dr. Sid Dogra speak with Jessie Gommers and Dr. Ioannis Sechopoulos about their study on how AI decision support influences radiologist performance and visual search in screening mammography. They explore key findings on sensitivity, specificity, reading time, and the future role of visual tracking in optimizing human–AI collaboration. Influence of AI Decision Support on Radiologists’ Performance and Visual Search in Screening Mammography. Gommers and Verboom et al. Radiology 2025; 316(1):e243688.  

Dr. Refky Nicola speaks with Dr. Perry Pickhardt about his study comparing CT colonography and multi-targeted stool DNA testing for colorectal cancer screening. They explore differences in sensitivity, specificity, cost-effectiveness, and strategies to optimize detection while minimizing invasiveness. CT Colonography versus Multitarget Stool DNA Test forColorectal Cancer Screening: A Cost-Effectiveness Analysis. Pickhardt et al. Radiology 2025; 315(3):e243775.

In this episode, we explore how nonprofit organizations like LBDA are working alongside industry partners to shape the evolving landscape of dementia biomarkers—bridging scientific innovation with real-world care. Featuring an engaging conversation with Dr. Sudhir Sivakumaran, Dr. Kathleen Poston, and Dr. Dustin Dunham on clinical utility, patient-centered research, and the road to broader adoption of biomarkers in Lewy body dementia, Alzheimer’s disease and related disorders. This episode is sponsored by GE HealthCare

In this episode, Dr. Linda Chu explores a major Radiology consensus statement on optimizing CT angiography for suspected pulmonary embolism. The discussion covers advanced imaging techniques, key considerations for special populations, and standardized reporting practices to improve diagnostic clarity and patient outcomes. Optimal Approach to Performing and Reporting ComputedTomography Angiography for Suspected Acute PulmonaryEmbolism: A Clinical Consensus Statement of the ESC Working Groupon Pulmonary Circulation & Right Ventricular Function, the FleischnerSociety, the Association for Acute Cardiovascular Care (ACVC) andthe European Association of Cardiovascular Imaging (EACVI) of theESC, Endorsed by European Respiratory Society (ERS), Asian Societyof Thoracic Radiology (ASTR), European Society of Thoracic Imaging(ESTI), and Society of Thoracic Radiology (STR). Radiology 2025; 315(3):e243833.

Dr. Linda Chu speaks with Dr. Ramin Khorasani about targeted interventions that reduced ambiguous radiologist recommendations for additional imaging while dramatically improving the clarity and follow-through of actionable recommendations. They explore how a structured system of care, closed-loop communication, and leadership engagement can advance high-value, patient-centered care in radiology. This episode is sponsored by Mayo Clinic.  Cumulative Effect of Targeted Interventions on Radiologist Recommendations for Additional Imaging. Abbasi et al. Radiology 2025; 315(3):e243750.

Host Dr. Reni Butler is joined by Dr. Sarah Eskreis-Winkler and Dr. Katja Pinker to discuss their recent work on adaptive breast MRI scanning using AI to improve breast cancer diagnosis and management. They explore how advanced MRI techniques and artificial intelligence can enhance imaging precision, leading to better patient care in breast imaging. Adaptive Breast MRI Scanning Using AI. Eskreis-Winkler et al. Radiology 2025; 315(3):e242924

Dr. Linda Chu reviews recent articles in the Generative AI Collection, covering clinical history extraction, case interpretation with vision language models, and report proofreading.   The articles covered in the podcast are: Leveraging Large Language Models to Generate Clinical Histories for Oncologic Imaging Requisitions | Radiology   Assessing Completeness of Clinical Histories Accompanying Imaging Orders Using Adapted Open-Source and Closed-Source Large Language Models | Radiology   Impact of Multimodal Prompt Elements on Diagnostic Performance of GPT-4V in Challenging Brain MRI Cases | Radiology   Generative Large Language Models Trained for Detecting Errors in Radiology Reports | Radiology   Large-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports | Radiology

Dr. Lauren Kim is joined by Parminder Bhatia, Chief AI Officer, and Roland Rott, President and CEO of GE HealthCare Imaging, to explore how artificial intelligence is reshaping medical imaging. They discuss the potential of AI to improve efficiency, enhance diagnostic accuracy, and address key challenges like workforce shortages and rising demand for care.  This episode is sponsored by GE HealthCare. 

In this episode, host Dr. Refky Nicola speaks with Dr. Bettina Siewert about her compelling article on moral distress, moral injury, and burnout in radiology. Together, they explore the systemic challenges radiologists face today and practical strategies for fostering a healthier work environment. Moral Distress, Moral Injury, and Burnout in Radiology Practice. Siewert and Ayyala. Radiology 2025; 315(2):e241174. Tackling Moral Distress in Radiology: Root Causes andSystemic Solutions. Hanneman and Makary. Radiology 2025; 315(2):e250273.