Growth and Structure of the FDA-Authorized Radiology AI Landscape, 1998-2025.

Rationale

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Objectives

There are over one thousand FDA-authorized radiology artificial intelligence (AI) devices, but prior analyses have addressed single device subtypes or single regulatory dimensions rather than the entire cohort. We characterized these devices by function, clinical application, manufacturer segment, and regulatory features.

Methods

We included 1094 radiology AI devices from the FDA AI-Enabled Medical Devices list authorized through December 2025, classified by functional category, computer-aided detection subtype when applicable, clinical use case, and manufacturer segment (original equipment manufacturer [OEM] versus non-OEM). Regulatory features included FDA review time, predetermined change control plan (PCCP) authorization, and AI predicate citation. Comparisons used chi-square, Wilcoxon rank-sum, and Kruskal-Wallis tests.

Results

Despite a 42% rise in annual authorizations from 2023 to 2025, functional composition remained stable: medical image management/processing systems (38.2%) and imaging systems (33.4%) predominated, and interpretive tools accounted for 21.5%. Among non-dental interpretive devices, cardiothoracic imaging and neuroradiology rose from 42% of authorizations before 2020 to 70% during 2023-2025; multi-finding devices rose from 3.8% to 18.3% (P=.03). OEM versus non-OEM devices differed in functional composition, median review time (118 vs 138 days; P<.001), PCCP authorization (1.5% vs 4.2%; P=.02), and primary AI predicate citation (44.8% vs 74.1%; P<.001), with a larger OEM predicate gap (32.9% vs 10.6%; P<.001). PCCP authorization rose from 0.8% (2020-2023) to 8.7% (2025).

Conclusion

FDA-authorized radiology AI has grown rapidly while maintaining stable functional composition, with interpretive devices concentrated in cardiothoracic imaging and neuroradiology, distinct regulatory profiles between OEM and non-OEM manufacturers, and increasing PCCP authorization.