Radiology conference highlights imaging progress

To maximize availability and accessibility, the cloud is increasingly a major means for the deployment of AI applications. 
Jeff Rowe

If you were to sum up this year’s 104th annual meeting of the Radiological Society of North America (RSNA – www.RSNA.org), “AI everywhere” might be the best way to describe it.

That’s according to a recent review of the meeting by health IT consultant Joe Marion, who notes that while, in previous years, there was a lot of talk about how AI was going to “revolutionize” radiology, “this year, the emphasis seemed to really shift from the “pie-in-the-sky” discussion to real-world, commercially available solutions.”

As Marion explains, commercializing AI has been somewhat of “a key development conundrum.”  While academic centers have been actively researching AI applications, so-called “boutique” companies have struggled with how to get developments to market.  “Large imaging informatics companies have likewise wrestled with how to approach bringing AI applications to market.  The solution prevalent this year seems to be for both large and small companies to offer a “platform” for the implementation of AI.”

In offering software development toolkits (SDK’s), Marion says, “vendors are providing a means for commercialization of academic and third-party applications without themselves reinventing the wheel.”

In essence, he says, AI vendors are imitating “the way smart-phone applications have evolved by providing the infrastructure for the validation and distribution of AI applications.  What is not yet clear is the liability of providing access to other entity’s applications.  Is the Store vendor responsible for the application, or the developer?  Who files for and secures FDA approval?”

As for uses of AI in radiology, Marion notes, AI is widely considered a suite of “clinical tools to improve the radiologist’s interpretation efficiency, not as a replacement to the radiologist from a clinical perspective.”  

At the same time, at RSNA “there were a number of applications that make use of AI technology to enhance the way information is handled and presented, and the way it impacts the decision process.  Much of this revolves around the way information is collected and made available to the clinician, such as retrieving relevant lab and other study information.”