Claim OwnershipRadiology Podcast | RSNA
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Radiology Podcast Editor Linda Chu, MD and guests discuss recently published research in the January 2021 Issue of Radiology. Subscribe today on Apple Podcasts, Google Play, Spotify, or ask Alexa to "play Radiology podcasts on TuneIn".
267 Episodes
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Dr. Linda Chiu unpacks how natural language processing and large language models are transforming radiology, with insights from a review by Dr. Felipe Kitamura and colleagues. From tokenization to transformers, she explores both the promise and challenges of applying these powerful AI tools to clinical practice. Texts Are More than Notes, They Are Data: A Glimpse intoHow Machines Understand Text. Kitamura et al. Radiology 2025; 316(2):e243217.
Dr. Refky Nicola speaks with Dr. Bari Dane, Associate Professor of Radiology at NYU, about the new SAR consensus recommendations for defining small bowel Crohn’s disease strictures on CT and MR enterography. They explore updated imaging criteria, the challenges of distinguishing inflammation from fibrosis, and emerging roles for ultrasound and AI in diagnosis and treatment response. SAR Consensus Recommendations for Defining Small BowelCrohn Disease Strictures at CT and MR Enterography. Dane et al. Radiology 2025; 316(1):e243123.
Dr. Lauren Kim speaks with Dr. Anna Rita Larici about the international consensus guidelines for imaging and managing post-COVID-19 residual lung abnormalities. They discuss the importance of standardized definitions, CT imaging protocols, and unified terminology to guide diagnosis and follow-up care for patients with long COVID. Best Practice: International Multisociety Consensus Statement forPost–COVID-19 Residual Abnormalities on Chest CT Scans. Yoon et al. Radiology 2025; 316(1):e243374.
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.
Dr. Linda Chu speaks with Dr. Rajiv Gupta and Dr. Andrea Diociasi about new findings linking repetitive blast exposure in Special Operations Forces (SOF) members to distinct changes in brain connectivity and cortical volume. They discuss how advanced MRI techniques and predictive models are uncovering correlations between neuroimaging markers and long-term neurobehavioral symptoms. Distinct Functional MRI Connectivity Patterns and CorticalVolume Variations Associated with Repetitive BlastExposure in Special Operations Forces Members. Diociasi et al. Radiology 2025; 315(1):e233264.
In this episode, Dr. Ashwin Parihar speaks with Dr. Petrice Cogswell about the radiologist’s critical role in diagnosing Alzheimer’s disease and how imaging advances are reshaping early detection. They also explore how innovation at scale, platform thinking, and operational alignment drive progress across complex healthcare systems. This episode is sponsored by Eli Lilly and Company.
In this episode, host Dr. Reni Butler speaks with Dr. Kalina Slavkova, Dr. Ruya Kang, Dr. Despina Kontos, and Dr. Habib Rahbar about their groundbreaking research using MRI-based radiomic features to improve risk stratification in ductal carcinoma in situ (DCIS). The discussion explores how combining clinical data, imaging, and AI-driven analysis could help personalize treatment and reduce overtreatment in breast cancer care. MRI-based Radiomic Features for Risk Stratification of Ductal Carcinoma in Situ in a Multicenter Setting (ECOG-ACRIN E4112 Trial). Slavkova and Kang et al. Radiology 2025; 315(1):e241628.
Dr. Lauren Kim is joined by Dr. Ivan Pedrosa and Dr. Robert Watson to discuss the newly updated ACR MRI Safety Manual. They explore key changes, the rationale behind new guidelines, and the implications for both clinical practice and research. American College of Radiology Manual on MR Safety:2024 Update and Revisions. Pedrosa et al. Radiology 2025; 315(1):e241405. The Updated ACR Manual on MR Safety and How It WillAffect Your Practice. Kanal. Radiology 2025; 315(1):e242954. ACR Manual on MR Safety 2024
In this episode, Dr. Ashwin Singh Parihar is joined by Dr. Jelijn Knip and Dr. Willemien Menke to discuss their study comparing FDG PET and FES PET for staging grade 1 or 2 ER-positive breast cancer, highlighting how FES PET may offer more accurate results for certain tumors. Tune in to learn how these imaging techniques can impact treatment decisions. The Diagnostic Accuracy of 18F-FDG PET and 18F-FES PET for Staging Grade 1–2 Estrogen Receptor–Positive Breast Cancer. Knip and Iqbal et al. Radiology 2025; 314(3):e241850.
In this episode, Dr. Linda Chu speaks with Sarah Atzen, Lead Scientific Editor for Radiology, about best practices for writing AI research papers. They explore key tips from the recent article “Top 10 Tips for Writing about AI in Radiology” to help authors improve clarity, accuracy, and impact. Top 10 Tips for Writing about AI in Radiology: A Brief Guide for Authors. Atzen. Radiology 2025; 314(2):e243347.
1Dr. Lauren Kim speaks with Dr. Andrea Rockall, Clinical Chair of Radiology at Imperial College London, about the growing movement toward sustainable practices in radiology. They explore global collaboration, innovative technologies, and the power of data in reducing the environmental impact of medical imaging. Sustainability in Radiology: Position Paper and Call to Actionfrom ACR, AOSR, ASR, CAR, CIR, ESR, ESRNM, ISR, IS3R,RANZCR, and RSNA. Rockall et al. Radiology 2025; 314(3):e250325. RSNA’s online resources for environmental sustainability in imaging
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it's so good to upgrade our knowledge, thank's Dr. Blumke