USA – FDA takes a step forward for machine learning with quantitative imaging guidance

The US Food and Drug Administration finalized guidance on what to consider when using quantitative imaging algorithms in radiological device submissions. While most imaging diagnostics rely on qualitative readings by trained physicians, imaging devices increasingly rely on quantitative imaging results using machine learning.

On 15 June, FDA finalized its Technical Performance Assessment of Quantitative Imaging in Radiological Device Premarket Submissions guidance, which was first proposed in 2019. The document outlines the agency’s thinking on what manufacturers need to consider in their algorithms when relying on quantitative analysis to output results. (RELATED: CDRH drafts guidance on quantitative imagingRegulatory Focus 18 April 2019)

In the guidance, FDA said that a sponsor’s premarket submission should include a technical description of the device’s quantitative imaging functions with enough detail for regulators to understand how it functions.

“In some instances, a more general description of the measurement process may be sufficient; however, you should provide a more detailed description of the processes for more complex quantitative imaging functions, to ensure FDA’s understanding of your device,” the agency said…