Demystifying AI in Clinical Practice

Quantitative Imaging Redefines Value in Neuroradiology

21 min · 5. mar. 2026
episode Quantitative Imaging Redefines Value in Neuroradiology cover

Description

From the Applied Radiology booth at RSNA, one of the most technically rich—and clinically consequential—conversations focused on the evolving role of quantitative imaging in neuroradiology. In a live discussion, Lawrence Tanenbaum, MD sat down with Suzie Bash, MD to examine how volumetric and quantitative tools are reshaping diagnosis, longitudinal surveillance, and treatment decision-making.

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episode AI in Radiology: Isolated Algorithms to Scalable Clinical Impact artwork

AI in Radiology: Isolated Algorithms to Scalable Clinical Impact

Artificial intelligence in radiology is often discussed in broad, aspirational terms, but far less attention is paid to what happens after algorithms are cleared, purchased, and deployed. In a recent discussion hosted by Applied Radiology, experts examined how AI is being implemented at scale and what it takes to translate technical capability into meaningful clinical impact. During the conversation, Avi Sharma, MD, host of Applied Radiology’s AI Podcast was joined by co-host Lawrence Tanenbaum, MD, and Greg Sorenson, MD, Chief Science Officer at RadNet, and, to explore how AI moves from isolated tools to enterprise-level infrastructure. The discussion focused less on individual algorithms and more on workflow, adoption, and sustainability in real-world imaging environments

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