Data Transparency Gaps in FDA-Cleared Alzheimer’s Imaging AI Devices Highlighted

Research finds insufficient data transparency for FDA-cleared AI devices in Alzheimer’s imaging, raising bias and generalizability concerns.

Key Details

• 24 AI/ML-based devices for Alzheimer's disease and related dementias (ADRD) were FDA-authorized between January 2015 and December 2024.
• 91.7% (22/24) were cleared via the 510(k) pathway; 8.3% (2/24) through de novo classification.
• For 12 devices, there was no info on training or validation data in FDA summaries or peer-reviewed articles.
• Only 2 FDA summaries (8.3%) included external validation data; 10 peer-reviewed articles (41.7%) provided such data.
• Reporting of disease status, age, sex, race, and ethnicity was rare across most devices; demographic transparency was lacking.
• Most devices (21) were reviewed by radiology panels and primarily involved MRI and PET imaging.

Why It Matters

Transparent disclosure of training and validation data, especially demographic details, is vital for assessing bias and clinical accuracy in AI-based imaging devices. Without sufficient data transparency, there is uncertainty about the generalizability and safety of these AI tools in real-world, diverse patient populations.

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