The American College of Radiology (ACR), Radiological Society of North America (RSNA) and Society for Imaging Informatics in Medicine (SIIM) urged U.S. Department of Health and Human Services (HHS) officials to reject a proposal by the immediate-past HHS Secretary Alex Azar to permanently exempt certain medical devices from the Food and Drug Administration’s (FDA) 510(k) premarket notification requirements.
The proposal would include several types of devices used by radiologists in patient care, including artificial intelligence/machine learning (AI/ML)-enabled software for computer-assisted/aided triage, detection or diagnosis. The associations say the proposal was noteworthy for the lack of FDA involvement and for contradicting the agency’s stated plans for enhancing oversight of AI/ML-enabled software.
“The proposal is extraordinarily concerning from a patient safety perspective. Although we do not anticipate implementation by the current administration, informatics experts must inform regulators of the potentially harmful impacts resulting from this idea in case the proposal resurfaces,” said Howard B. Fleishon, M.D., chair of the ACR board of chancellors, in a statement.
While the FDA has cleared or authorized many AI/ML-enabled devices for the radiology market, the agency continues to face oversight challenges due to the impact on algorithm performance of changing practice environments, diverse patient populations and input devices. The ACR said it would continue to work with the FDA on these issues.
“Rather than exempting these devices from 510(k) premarket notification requirements and deferring many safety and effectiveness questions about individual products to concerned consumers, FDA should explore ways to enhance its current approaches to overseeing AI/ML-enabled imaging software,” the organizations’ letter to HHS said. “This could include ideas such as requiring multisite validation to ensure AI is generalizable across practices and patient populations, requiring longitudinal performance monitoring to assess real-world algorithm performance, requiring publication of the structured use case used to develop the model, and other approaches that balance safety and effectiveness considerations with ensuring access to promising innovations.”
“We encourage the FDA to bolster their capabilities to ensure algorithms perform as intended in the real world and over time,” said Christoph Wald, M.D., Ph.D., M.B.A., chair of the ACR Commission on Informatics, in a statement. “This should include multisite validation, post-market monitoring of longitudinal performance and other measures.”
