Nicholas Hamm

It should come as no surprise that AI was featured heavily in this year’s 

Radiological Society of North America convention

. From booths to sessions to one-on-one conversations around the hall, it seemed like almost everyone had something to say about AI.

Nearly every major company on the show floor was excited to talk about their advancements in the field, showcasing in real time just how well their programs could help radiologists and patients alike. While many technologies were still in the development or approval-gathering stages, many offered real glimpses at the tools radiologists have available right now.

But even with those available and soon-to-available tools, questions still swarmed the show about AI: How do current AI products fit into practices right now? What will happen in the next 5, 10, 15 years? What is the main goal of AI? Will there be any patient impact? Will AI replace the radiologist?

The questions and answers about AI seemed to all come in three categories: The relationship between AI and the radiologist, the workflow, and improvements to patient care.

Seemingly the biggest question-and greatest fear-was a simple one: will radiologists be around in 15 years, or will machines be doing everything?

On the show floor, exhibitors were quick to point out that any currently-available AI technologies, and any near-future ones, aren’t meant to replace the radiologist but to enhance the radiologist’s abilities. So far, nothing can bypass the radiologist’s expert eyes. Instead, most of the products featured at the show-from GE’s Edison to Samsung’s AI to ScreenPoint to Fujifilm’s REiLI-offered deep learning to help triage cases.

With these programs, the computer can detect any abnormalities and bring them to the radiologist first. Several exhibitors described this as a way to give radiologists the most difficult cases first, so as to avoid getting them toward the end of the workload while working with tired eyes.

Even if programs could develop to the point where the computer could bypass a set of human eyes completely, experts say it still probably wouldn’t affect the field.

In a roundtable discussion session titled “Artificial Intelligence: Impact and Implications to Radiology,” one of the presenters, Lawrence Tanenbaum, MD, stressed that regulatory and risk-mitigation will continue to play a role in AI’s future. He pointed to cardiology as an example, where EKG’s can be read by a computer, but liability issues have led to cardiologists still having a significant role in reading and interpreting them.

Other experts echoed those same concerns, asking, “What company is going to be the first one to take the risk of not having a radiologist in the room?”

Another roundtable discussion of AI, “AI After Dark” brought together dozens of AI experts and questioning radiologists. One of the major discussions of the event revolved around who would be the “referee” for AI, if it were to ever approach replacing a human. Who decides when the technology is good enough? How are potential problems going to be addressed?

These questions don’t have an answer yet, but nearly every expert agreed that radiologists would need to play at least some part in designing and confirming any AI.

So, while AI isn’t going to replace radiologists any time soon, some radiologists are excited about the work that can be replaced in their day to day.

According to some reports, radiologists are dealing with 7% more work per patient year over year-not to mention the increasing patient load itself. As a result, many radiologists in forums across RSNA expressed interests in offloading simple cases in favor of being able to spend more time with complicated cases.

If AI was the overarching theme of the RSNA trade floor, workflow improvement seemed to be the main goal. While there was talk of more refined images and new screening methods, most of the innovations on the floor related to a more streamlined workflow. Major innovations seemed to all take the form of increasing automation of simple tasks for faster processing, promising greater speed.

Exhibitors were also concerned with creating products that radiologists might actually use. A piece of software that doesn’t get used-or worse, actually requires more steps to do the same amount of work-doesn’t end up helping anyone, so exhibitors were quick to point out how seamlessly their new software or hardware could integrate into a practice.  

Artificial intelligence in radiology: Friend or foe?

The next logical question, then, is if AI tools are going to make radiologists faster and more efficient in their day to day jobs, what are radiologists going to do with all of that extra time and brain power that they no longer have to waste on triaging cases or handling mundane tasks?

In the “Artificial Intelligence: Impact and Implications to Radiology,” session, presenter Michael Recht, MD stressed that AI shouldn’t just be about helping out radiologists manage caseloads or make faster diagnoses-AI should be used to make radiologists better.

“Better” can mean many different things-better at diagnosing quickly, better at diagnosing difficult cases-but as Julius Chapiro, MD, said in that same session, AI should ultimately be about improving patient care.

During the “AI After Dark” session, perhaps the biggest positive reaction was to the statement “Let radiologists be physicians again.” Across this session and others, radiologists seemed unified in the hope that if AI does live up to the hype it will allow them more contact time patients-or at the very least more time with difficult cases and better patient outcomes.

While experts were wary to say that the future of AI will allow radiologists to interact with patients in the same way as if they were primary physicians, there is the possibility to at least give radiologists more time than before. One interesting patient-focused application Recht theorized was voice-to-text software that could automatically translate complex medical terms into a readable report for patients. While other experts said this type of technology would be extremely difficult-if not impossible-to develop, it demonstrates that radiologists and vendors alike are interested in the patient question.

Other experts in rural areas and from developing countries were especially interested in the prospect of AI’s impact on healthcare. The consensus seemed to be that equipment, especially lower-priced systems, is being diffused more quickly than qualified personnel-giving AI a chance directly impact patient care where only limited care was previously available.

The overarching question of RSNA 2018, after all of the discussions about the current state and future of AI, was “Is AI worth the hype?”

While it’s unquestionably true that AI is-and will be-doing incredible things to help both doctors and patients alike, many questioned if it will be truly as much of a paradigm shift as pundits claim it will be.

When asked the question, Chapiro said that especially after speaking with others that AI is overhyped, but that it is ultimately a tool that will make radiologists better. He added that AI will have a unifying effect, providing better solutions and ultimately energizing the field of radiology.

Artificial Intelligence Makes Gains in Radiology

Tanenbaum said that he sees AI making radiologists more valuable, because they can be moved on to more valuable tasks. He concluded that “I see a rosy future for us and for our field.” Rechet agreed, concluding that while there is a significant amount of hype, AI “is going to rapidly change our field for the better.”

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