ACR and SIIM Pair AI Practice Guidance With a Registry Designed for Real-World Monitoring
The ACR and SIIM have approved an AI practice parameter and introduced the Assess-AI registry to track real-world use of imaging algorithms. The move underscores how rapidly radiology is building infrastructure for oversight, not just adoption.
The joint ACR-SIIM announcement is a strong indicator that radiology is trying to get ahead of the AI rollout curve. Rather than waiting for problems to emerge after deployment, the field is designing a mechanism to document how algorithms behave in actual clinical operations.
That approach is important because imaging AI often performs best in the narrow conditions of a validation study and less predictably when exposed to the messiness of routine care. Differences in patient mix, imaging protocols, and local workflow can all affect whether the promised gains show up in practice.
The Assess-AI registry could become especially useful if it captures more than accuracy metrics. Information about workflow impact, false positives, reader behavior, and site-to-site variation will likely matter as much as model performance in deciding which tools are sustainable.
This is a subtle but meaningful shift in the AI market. Vendors have spent years emphasizing clinical potential; professional societies are now asking for evidence of operational durability. That shift will likely reward companies that can prove consistency over time, not just impressive launch-day results.