Artificial Intelligence in Radiology: A Leadership Survey.

Abstract

Purpose: Surveys to assess views about artificial intelligence (AI) of various diagnostic radiology constituencies have revealed interesting combinations of enthusiasm, caution, and implementation priorities. We surveyed academic radiology leaders about their views on AI and how they intend to approach AI implementation in their departments.

Materials and methods: We conducted a web survey of Society of Chairs of Academic Radiology Departments (SCARD) members between October 5 and October 31, 2023 to solicit optimism or pessimism about AI, target use cases, planned implementation, and perceptions of their workforce. P-values are provided only for descriptive purposes and have not been adjusted for multiple testing in this exploratory research.

Results: The survey was sent to the 112 SCARD members and 43 responded (38%). Chairs were optimistic, with no statistical difference between views of AI in general versus generative AI. Chairs plan to implement AI to improve quality and efficiency (43/43, 100%), burnout (41/43, 95%), healthcare costs (22/43, 51%), and equity (27/43, 63%) and most likely will target the post-processing (26/43, 60%), interpretation workflow (26/43, 60%), and image acquisition (18/43, 42%) steps in the imaging value chain. Chairs perceived that radiologists (36/43, 84%) and technologists (38/43, 88%) were not particularly worried about being displaced but saw trainees as slightly less confident (31/43, 72%). Free text responses revealed concerns about the cost of AI and emphasized trade-offs that needed to be balanced.

Conclusion: Radiology Chairs are optimistic about AI and poised to tackle departmental challenges. Concerns about generative AI and workforce replacement are minimal.