AI medical device post-market surveillance regulations: consensus recommendations by the European Society of Radiology

The increasing integration of artificial intelligence as medical devices (AIaMDs) within diagnostic imaging necessitates a robust understanding of associated regulatory frameworks among clinical practitioners. Despite the growing commercial availability and adoption of AIaMD, a significant awareness gap persists among radiologists regarding pertinent European Union regulations, including the Medical Device Regulation (MDR) and the novel EU AI Act, both of which lack explicit provisions tailored to AI components. This regulatory ambiguity underscores a critical need for clarified guidelines concerning "high-risk" AI classification and best practices for safe deployment within the radiological workflow. Legal responsibility for AIaMD Post-Market Surveillance (PMS) primarily rests with software providers, yet radiologists are expected to contribute to the ongoing monitoring of safety and performance. Recognizing the need to raise awareness and provide practical guidance, the European Society of Radiology (ESR) eHealth and Informatics Subcommittee, supported by the ESR AI Working Group, conducted a modified Delphi procedure involving 16 domain experts (of which 14 acted as panelists) to establish a set of shared recommendations. These aim to establish essential practices for AIaMD PMS and post-market clinical feedback (PMCF), as stipulated by the MDR and partially updated by the AI Act. This paper also provides an overview of relevant regulations to enhance awareness among all stakeholders, particularly deployers (e.g., radiologists) and providers (e.g., vendors). These recommendations represent a foundational step towards improving consistency in AIaMD deployment, providing a critical reference standard for physicians navigating the unique challenges posed by these novel technologies. CRITICAL RELEVANCE STATEMENT: Radiologists need to familiarize themselves with AIaMD EU regulations due to shared PMS responsibilities and current ambiguities. ESR recommendations aim to bridge this awareness gap, standardizing safe AI deployment and enhancing clinical feedback within medical imaging. KEY POINTS: Radiologists need a clear understanding of EU regulations for AIaMDs, as current laws lack imaging-specific guidance. There is a shared responsibility for AIaMD safety, with radiologists contributing to PMS and clinical feedback systems. The ESR provides crucial recommendations to standardize AI deployment and improve clinical feedback in imaging.

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Publication Details

Journal
Insights into Imaging
Published
2025-12-12
DOI
https://doi.org/10.1186/s13244-025-02146-8
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31

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article

AI medical device post-market surveillance regulations: consensus recommendations by the European Society of Radiology

Costin Minoiu, Merel Huisman, Robin Decoster, Maija Radziņa et al.
2 citations
Insights into Imaging
Artificial Intelligence in Healthcare and Education
1.31
article

AI medical device post-market surveillance regulations: consensus recommendations by the European Society of Radiology

Costin Minoiu, Merel Huisman, Robin Decoster, Maija Radziņa, Konstantin Nikolaou, Daniel Pinto dos Santos, Susan Cheng Shelmerdine, Luís Curvo‐Semedo, Evis Sala, Tugba Akinci D’Antonoli, Michelle C. Williams, Laurens Topff, Renato Cuocolo, David Bernardini, Luis Martí‐Bonmatí, Michail E. Klontzas, Elmar Kotter, Emanuele Neri
article en
2 citations

Abstract

The increasing integration of artificial intelligence as medical devices (AIaMDs) within diagnostic imaging necessitates a robust understanding of associated regulatory frameworks among clinical practitioners. Despite the growing commercial availability and adoption of AIaMD, a significant awareness gap persists among radiologists regarding pertinent European Union regulations, including the Medical Device Regulation (MDR) and the novel EU AI Act, both of which lack explicit provisions tailored to AI components. This regulatory ambiguity underscores a critical need for clarified guidelines concerning "high-risk" AI classification and best practices for safe deployment within the radiological workflow. Legal responsibility for AIaMD Post-Market Surveillance (PMS) primarily rests with software providers, yet radiologists are expected to contribute to the ongoing monitoring of safety and performance. Recognizing the need to raise awareness and provide practical guidance, the European Society of Radiology (ESR) eHealth and Informatics Subcommittee, supported by the ESR AI Working Group, conducted a modified Delphi procedure involving 16 domain experts (of which 14 acted as panelists) to establish a set of shared recommendations. These aim to establish essential practices for AIaMD PMS and post-market clinical feedback (PMCF), as stipulated by the MDR and partially updated by the AI Act. This paper also provides an overview of relevant regulations to enhance awareness among all stakeholders, particularly deployers (e.g., radiologists) and providers (e.g., vendors). These recommendations represent a foundational step towards improving consistency in AIaMD deployment, providing a critical reference standard for physicians navigating the unique challenges posed by these novel technologies. CRITICAL RELEVANCE STATEMENT: Radiologists need to familiarize themselves with AIaMD EU regulations due to shared PMS responsibilities and current ambiguities. ESR recommendations aim to bridge this awareness gap, standardizing safe AI deployment and enhancing clinical feedback within medical imaging. KEY POINTS: Radiologists need a clear understanding of EU regulations for AIaMDs, as current laws lack imaging-specific guidance. There is a shared responsibility for AIaMD safety, with radiologists contributing to PMS and clinical feedback systems. The ESR provides crucial recommendations to standardize AI deployment and improve clinical feedback in imaging.

Insights into ImagingVol. 16(1)
Università Cattolica del Sacro Cuore (IT), University of Pisa (IT), University of Salerno (IT), University of Crete (GR), Radboud University Nijmegen (NL), University of Freiburg (DE), Carol Davila University of Medicine and Pharmacy (RO), Johannes Gutenberg University Mainz (DE), Great Ormond Street Hospital (GB), University Medical Center Freiburg (DE), European Society of Radiology (AT), University Hospital of Basel (CH), Radboud University Medical Center (NL), The Netherlands Cancer Institute (NL), Hospital Universitari i Politècnic La Fe (ES), British Heart Foundation (GB), University Medical Center of the Johannes Gutenberg University Mainz (DE), Oncode Institute (NL), Odisee, University of Applied Sciences (BE), University Children’s Hospital Basel (CH), Riga Stradiņš University (LV), Sydney Local Health District (AU), University College London (GB), University of Coimbra (PT), University of Tübingen (DE)
British Heart Foundation, University College London, Università di Pisa
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
1.31
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