Those that have been inside a casino should be aware of the concept of table stakes. There is a certain amount that is needed to be wagered to play any particular game. This amount is considered a “minimum bet” or “table stakes”, and is required to participate in the game. A similar concept of minimum criteria needed to be eligible to be interviewed by a radiology residency program, such as minimum board scores or involvement in research. In continuum, a particular level of medical knowledge and problem solving ability are required as table stakes for our radiology trainees, as embodied by the pass-fail American Board of Radiology (ABR) core and certifying exams. However, should we balance the basic knowledge expectations, or table stakes, with preparing our trainees for the potentially paradigm shifting disruptive integration of artificial intelligence (AI)?

Radiology residency program directors ensure that the didactic curriculum and rotational experiences help our trainees achieve the basic skills necessary to graduate and be competent radiologists. The ABR has also developed core competencies around noninterpretive skills that are integrated into the clinical knowledge and problem solving curriculum, that we as a profession have established as table stakes. I advocate that educators in radiology embrace the impending impact that artificial intelligence is going to have on diagnostic imaging. So, how

do we prepare our trainees for such change? What should the balance of time and faculty educational effort be attributed to basic diagnostic and interventional skills, compared to AI integration?

I propose a dedicated ABR endorsed and tested AI curriculum for radiology residency programs that mimics and augments the organ based curricula currently in place. The AI curriculum will cover the basics of what AI is, and the different types of AI, as well as pragmatic how to workflow topics (similar to current clinical based step wise questions about image guided procedures or imaging technology). This new curriculum will be part of ABR core competency and certifying exam problem sets.


Author: Timothy Kasprzak

Status: Project Concept