Washington, D.C – The Medical Imaging & Technology Alliance (MITA) this week submitted comments on a Food and Drug Administration (FDA) Public Workshop, “The Evolving Role of Artificial Intelligence in Radiological Imaging.” The letter indicates that artificial intelligence (AI) continues to have a growing impact on medical imaging modalities across the United States and beyond.
“MITA applauds the FDA for its collaborative and deliberate approach towards AI-based healthcare solutions,” said Patrick Hope, Executive Director of MITA. “We look forward to further work with the FDA and other agencies to ensure a smooth delivery of innovative AI treatments from the lab to the patient bedside.”
The latest MITA comment letter expands upon previous comments submitted by the organization in March of this year. That letter outlined the benefits of international consensus Standards, the utility of existing regulatory mechanisms, and the importance and applicability of AI in the advancement of Quadruple Aim goals, among other areas.
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The June 2020 letter, which was sent to the U.S. FDA Center for Devices and Radiological Health, provided further detail about a series of pressing areas, including improved risk analysis, international consensus Standards for data quality, and post-market data collection:
Risk Analysis and Artificial Intelligence
Following the initial FDA AI workshop in February, MITA has worked to address the most challenging issues around ensuring the safety and efficacy of future AI imaging technologies. As a result of these efforts, the letter outlined a series of preliminary questions for the agency to consider when evaluating the risks associated with AI-based healthcare solutions. These questions range from broader points, like the purpose and format of the output, to more granular points, like the process for updating an algorithm.
After outlining a broad spectrum of risks associated with AI solutions, MITA urged the agency to adopt a risk analysis framework, which, when paired with a review of current regulatory structures and processes, would help clarify expectations and hasten the introduction of efficacious AI products that improve patient care outcomes.
International Consensus Standards
Noting the importance of clear and consistent Standards in driving algorithm development, the letter underscored the need for the establishment of International Consensus Standards and Frameworks to encourage stable and consistent expectations for AI Imaging applications. The development of an internationally agreed-upon Consensus Standard would also reduce the burden on industry while simultaneously raising the bar for quality.
The letter concluded by reiterating the need for flexible data collection mechanisms for the purpose of past-market analytics. Effective and trustworthy collection methods depend on the device generating the data, the integrity of the data pipeline, and the data type generated. This broad range of considerations suggests that flexibility will be critical in determining the best collection method for AI-based products or services.