Copyright: ©Author(s) 2026.
World J Gastrointest Endosc. Apr 16, 2026; 18(4): 117976
Published online Apr 16, 2026. doi: 10.4253/wjge.v18.i4.117976
Published online Apr 16, 2026. doi: 10.4253/wjge.v18.i4.117976
Table 2 Comparison of regulatory approaches to artificial intelligence-assisted endoscopic ultrasound in foreign countries
| Feature | United States (FDA) | European Union (MDR/IVDR + AI Act) |
| Regulatory core | Function-based (what the software does) tiered regulation | Device risk + AI system risk dual matrix regulation. |
| Classification logic | CADt → CADe → CADx → CADa, with increasing risk | Class I, IIa, IIb, III (device risk), plus the AI Act’s “high-risk” category for most medical AI |
| Primary pathways | 510(k) (substantial equivalence), De Novo (novel low-moderate risk), PMA (high risk) | Self-certification (class I low risk), notified body conformity assessment (class IIa and above) |
| Adaptability | Predetermined change control plans allow for iterative updates to cleared algorithms within defined bounds without new submission | Update processes under regulations are stricter; significant software changes typically require re-assessment/notification to the notified body |
| Clinical evidence | Emphasizes prospective, multi-center clinical trials to demonstrate safety and effectiveness | Emphasizes clinical evaluation with comprehensive technical documentation and performance validation, aligned with GDPR |
| Transparency | Requires disclosure of algorithm performance | The AI act emphasizes transparency, requiring high-risk AI systems to provide clear usage information and ensure outputs are interpretable and overseen by humans |
| Process flowcharts | AI medical device concept → determine intended use and function: CADt, CADe, CADx, or CADa → assign FDA risk class → generate clinical and technical evidence → submit to FDA for review → FDA approval clearance → post-market surveillance | Medical AI product → determine device risk class per MDR/IVDR → determine AI system risk level per AI act (typically “high-risk”) → comply with both sets of requirements → undergo conformity Assessment by a notified body (for class IIa and above) → obtain CE marking |
- Citation: Chen ZY, Wang YQ, Tan XZ, Liu P, Peng Y. Artificial intelligence in endoscopic ultrasound: Clinical translation of a prediction, navigation, and diagnosis framework. World J Gastrointest Endosc 2026; 18(4): 117976
- URL: https://www.wjgnet.com/1948-5190/full/v18/i4/117976.htm
- DOI: https://dx.doi.org/10.4253/wjge.v18.i4.117976