As one year ends and a new year begins, it is a good time for introspection and considered contemplation of what lies ahead. Just such an exemplary exercise on the past and future of the medical specialty of radiology has just been published in journal Radiology, authored by James Brink, M.D., radiologist-in-chief at Massachusetts General Hospital and Hedvig Hricak, M.D. She is chairman of the Department of Radiology at Memorial Sloan-Kettering Cancer Center as well as Professor of Radiology at the Weill Medical College of Cornell University. Their essay is entitled "Radiology 2040." 

Innovation and disruptive change has long been the hallmark of radiology.  It has been 40 years since I joined the staff of the American College of Radiology as a young lawyer. As an observer of technological innovation in radiology, I saw my clients embrace the imaging modalities of CT and MRI in the 1980s, which - as Drs. Brink and Hricak observe - required radiologists to master considerably greater levels of data as they interpreted these then-new cross-sectional imaging modalities. Over these decades, functional and molecular imaging were developed, and there has been tremendous growth in applications of interventional radiology.

The authors note, correctly I believe, that radiologists are in some ways the victims of their own success, as the demand for imaging increases exponentially. Radiologists have had to cope with increasingly large volumes of radiology studies that require their radiological interpretations.  That challenge is compounded by the large increases in the number of images generated by each examination, and the demand for 24/7 coverage and prompt final interpretations in hospital settings, leading to widespread burnout by an increasing number of radiologists.

So what will radiology look like in 2040? One thing is clear. Artificial intelligence (AI) will be a powerful force in radiology. Drs. Brink and Hricak believe that AI could help streamline and reduce radiologists' workload, but embracing all of AI's tools also poses challenges to the specialty's relevance. The authors believe that AI will affect all aspects of radiology practice: from examination triage and planning to lesion detection, characterization, and measurement. AI, they say, will also enable greater assessment of disease likelihood and potential treatment outcomes by seamless integration of imaging findings with other clinical indicators. Because radiologists’ role in this continuum is not assured, they must work to add value at every step. The authors observe that while it is tempting to imagine a scenario where AI-powered radiologist generalists deliver the value typically seen with subspecialists, they counter that subspecialized training will remain critically important, as "radiologists’ clinical relevance can only be assured by radiologists being as knowledgeable as our subspecialized referring physicians."

Technological change, of course, is constantly accelerating. As that change emerges, they urge radiologists to be focused on ways in which they can add value to the healthcare continuum. They offer a list of 14 items that will measure in 2040 whether radiology is still thriving, such as: radiologists must be the keepers of AI algorithms and oversee their use unequivocally.  And radiology must remain subspecialized. 

This is an essay of significance. The editors of Radiology recognized the importance of this commentary, and they have published it without a paywall. I commend it to your attention.