The absence of full lifecycle risk management for AI-based medical devices in radiology.
Authors
Affiliations (4)
Affiliations (4)
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.
- Henan Key Laboratory of Nanomedicine for Targeting Diagnosis and Treatment, Zhengzhou, China.
- School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China. [email protected].
- Henan Key Laboratory of Nanomedicine for Targeting Diagnosis and Treatment, Zhengzhou, China. [email protected].
Abstract
This study represents the systematic examination of full lifecycle management for radiology artificial intelligence medical (AI) devices approved by the US Food and Drug Administration (FDA), with an in-depth analysis of post-market adverse events, recalls, and software update patterns. An analysis of 956 radiology AI medical devices approved by the FDA between September 1995 and September 2025 revealed that 429 (44.87%) of these devices had undergone software version updates. Adverse events related to software defects involved 15 products (34.88%); among these, 4 products (26.67%) underwent version updates, and for 3 products (20%), the companies initiated recalls following the occurrence of adverse events. There were a total of 124 reports (68.13%) of product recalls caused by software defects; for 38 of these reports (30.65%), corresponding to 8 products, the manufacturers corrected the defects by updating the software after implementing the recall. We make three contributions: (1) identifying that the vast majority of companies lack a closed-loop risk management system encompassing adverse events, recalls, and software updates, (2) analysing the frequency and characteristics of software updates for radiology equipment, and (3) exploring the critical role of full lifecycle management in the regulation of AI-based medical devices.