Radiology AI may improve workflows and patient care, but the technology also brings challenges for radiology departments, research suggests.
A focus issue from the Journal of the American College of Radiology brings together invited research and reviews exploring how AI is being used across different practice types.
Barriers include insufficient infrastructure, strict institutional regulations and a lack of insurance reimbursement, all of which can hamper the integration of AI into routine clinical workflows.
Radiology, the branch of medicine that uses imaging such as X-rays and scans to diagnose and treat disease, is widely seen as one of the fields most likely to be reshaped by AI.
The research includes contributions arguing that workflow improvement is not simply a secondary benefit of AI, but a main determinant of whether a tool succeeds.
Gelareh Sadigh, associate editor for health services research at the Journal of the American College of Radiology, said: “When thoughtfully implemented, AI can complement human expertise and improve efficiency and patient care.
“Successful workflow optimisation requires the integration of AI technology into routine workflows.
“This can be hampered by insufficient infrastructure, strict institutional regulations, and lack of insurance reimbursement.
“Poor integration of AI may degrade workflows, satisfaction, and safety and perpetuate bias in healthcare.”
According to Dr Sadigh, the articles in the focus issue reflect a broader shift in radiology: workflow is not a secondary benefit of AI, but a key factor in whether a tool is successful.
If AI is going to meaningfully help radiology, it must make care delivery better and not more complicated.
Ruth C. Carlos, editor-in-chief of the Journal of the American College of Radiology, said: “This focus issue provides meaningful signposts for AI effectiveness as we navigate a rapidly shifting landscape.”