Hosted by The Radiological Society of North America · 🇺🇸 US · EN · 23 episodes
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A podcast showcasing articles from the Radiology Advances journal.Podcast TeamLead Podcast Editor- Diego Lopez-Gonzalez, MD, MPH,Trainee Editors- Nelson Gil, MD, PhD and Luca Salhöfer, MD
The Radiological Society of North America hosts Radiology Advances Podcast | RSNA, a science show with 23 episodes published.
This episode covers a study from the Mallinckrodt Institute of Radiology at Washington University in St. Louis evaluating whether patient-specific lung shunt fraction measurement is necessary for every yttrium-90 selecti
This episode discusses a study from New York University evaluating whether deep learning can predict acute pancreatitis severity from contrast-enhanced CT acquired within 24 hours of admission. Using self-supervised pret
This episode discusses a study from the University of California, San Francisco in the United States that tested whether GPT-4o-generated patient-friendly summaries improve comprehension of lung cancer screening CT repor
This episode explores a study from the University of Texas Southwestern Medical Center and MD Anderson Cancer Center in the United States that clinically validates an FDA-cleared AI tool for measuring total cardiac volum
This episode explores a study from the Emory Sports Performance and Research Center and the University of Lausanne that determined how few annotated MRI exams are needed to train a reliable deep learning model for thigh
This episode discusses a study from UCLA in the United States that used federated learning to train a deep learning model for automatic segmentation and quantification of visceral and subcutaneous abdominal fat in childr
This episode reviews a proof-of-concept study from Mayo Clinic Minnesota on the use of ferumoxytol-enhanced MRI for detecting gastrointestinal bleeding after a comprehensive conventional workup has been negative. We exam
This episode reviews a study from the ROADMAP Group evaluating deep reinforcement learning for automatic aortic landmark localization in Stanford Type B aortic dissection — examining whether AI can match expert human per
This episode explores a technological advance from Johns Hopkins in the United States that improves diagnostic ultrasound for breast masses. By combining short-lag spatial coherence imaging with an objective metric calle
This episode highlights a study from Korea using deep learning to generate synthetic contrast-enhanced brain MRI images—without injecting contrast agents. The model accurately segmented the choroid plexus and matched rea
This episode explores a study from Radiology Advances tackling one of AI's toughest challenges in medical imaging: consistent pancreas segmentation across CT scans. The authors benchmarked multiple models against multi-r
This episode explores a study from Radiology Advances challenging FDA's acoustic output limits for liver ultrasound elastography for obese patients. The authors tested the exam at a mechanical index of 2.5, well above th
This episode features a cutting-edge study from Radiology Advances exploring Deep Silicon Photon-Counting CT (DS-IPCCT) for liver fat quantification. Using in silico models, the investigational system demonstrated high s
This episode explores Radiology Advances research on RadGPT—a hybrid AI system combining image analysis with a language model to interpret knee radiographs. Built on 77,000 images, the system incorporates mandatory human
This episode covers a study from Radiology Advances evaluating deep learning–accelerated MRI across routine neuroradiology exams. Using Siemens' Deep Resolve, scan times were cut by over 50% without sacrificing diagnosti
This episode discusses a study from Radiology Advances evaluating contrast-enhanced CT as a non-invasive alternative for lung shunt fraction (LSF) estimation in hepatic radioembolization to the current standard, 99mTc-MA
This episode covers a study in Radiology Advances evaluating deep learning–accelerated T1 MPRAGE MRI in patients with memory loss. The approach cut scan time by more than half while preserving image quality and measureme
This episode spotlights a study from Radiology Advances introducing a fully automated deep learning pipeline for myocardial infarct segmentation on late gadolinium enhancement cardiac MRI. Developed at the Medical Univer
A prospective study evaluates ultrasound-derived fat fraction (UDFF) as a tool to monitor hepatic steatosis after bariatric surgery. Host commentary unpacks how UDFF may offer a non-invasive, accessible, and quantitative
A multi-center study evaluating an AI model for automated CT segmentation of intracerebral hemorrhage, intraventricular hemorrhage, and perihematomal edema. Host commentary highlights how the deep learning tool delivers
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Radiology Advances Podcast | RSNA is hosted by The Radiological Society of North America. The show is categorised under science (health) and has published 23 episodes.
Radiology Advances Podcast | RSNA has published 23 episodes.
Radiology Advances Podcast | RSNA regularly covers science, health, fitness. It sits in the science category, with a health focus.
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Episodes of Radiology Advances Podcast | RSNA average 11 minutes. a focused format where a clear narrative arc and tight preparation matter most.
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