Radiology Podcast | RSNA

Host Dr. Celina Nahyun Jo sits down with Dr. Perry Pickhardt to explore how opportunistic CT screening is transforming routine imaging into a powerful tool for cardiometabolic risk assessment, bone health evaluation, liver disease detection, and body composition analysis. Together, they discuss the role of explainable AI, the future of CT-based biologic age, and why value-added imaging has the potential to reshape preventive care.
 
CT-based Opportunistic Screening for Adding Clinical Value:How I Do It. Pickhardt et al. Radiology 2026; 319(1):e252106.

Dr. Linda Chu speaks with Dr. Eddy Zandee and Dr. Kirk Davis about multidisciplinary expert consensus recommendations aimed at reducing the use of low yield radiographs and improving imaging appropriateness across healthcare settings. They explore which common radiographic exams may offer limited clinical value, when CT or MRI may be more appropriate, and how education and workflow changes can help optimize imaging utilization.
Optimizing Radiography Utilization: Multidisciplinary Expert Consensus Recommendations Endorsed by the Society of Academic Bone Radiologists, Society of Skeletal Radiology, American Societyof Emergency Radiology, Orthopaedic Trauma Association, American Academy of Emergency Medicine, and American Rhinologic Society. Zandee van Rilland et al. Radiology 2026; 319(2):e252309.

Dr. Ashwin Singh Parihar sits down with Dr. Louise Emmett to discuss how post-therapy Lutetium-177 PSMA SPECT/CT may help predict overall survival in patients with metastatic castration resistant prostate cancer and shape future treatment decisions. Drawing from the ENZA-p trial run by ANZUP cancer trials group, they explore quantitative imaging, treatment response assessment, adaptive dosing strategies, and the growing role of theranostics in precision oncology.
 
177Lu-PSMA-617 SPECT/CT for Early Prediction of Overall Survival in Participants with Metastatic Castration-Resistant Prostate Cancer. Ayati et al. Radiology 2026; 319(1):e252672.

Dr. Siddhant Dogra sits down with Dr. Su Hwan Kim to discuss how reader experience influences the performance and real world utility of large language models for brain MRI differential diagnosis. Together they explore AI assisted decision making, automation bias, radiology training, and why strong AI performance does not always translate into meaningful clinical benefit.
Performing Best When Needed Least: Reader Experience ShapesAccuracy Gains in Large Language Model–assisted Brain MRIDifferential Diagnosis. Schramm et al. Radiology 2026; 319(2):e253477.

Dr. Reni Butler discusses career advice for early, mid, and late career radiologists, mentorship, and work life integration with Dr. Stamatia Destounis and Dr. Mark Mullins.
This episode was first published Oct 10, 2023