Evidence map›Paper›PMID 41714355›Full record

ArticleAbdominal radiology (New York)2026

The AI Act and the MDR post-market requirements for semiautonomous AI SaMD: a radiology case study in prostate cancer.

Shakila Shojaei, Derya Yakar, Nynke Vellinga, Vilma Bozgo, Thomas Kwee, Henkjan Huisman, Jeanne Pia Mifsud Bonnici

Abstract read
In one paragraph

Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shakila ShojaeiDepartment of Radiology, University Medical Center Groningen, Groningen, Netherlands. s.shojaei@umcg.nl.
Derya YakarDepartment of Radiology, University Medical Center Groningen, Groningen, Netherlands.
Nynke VellingaSecurity, Technology and e-Privacy Research Group (STeP), University of Groningen, Groningen, Netherlands.
Vilma BozgoDiagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, Netherlands.
Thomas KweeDepartment of Radiology, University Medical Center Groningen, Groningen, Netherlands.
Henkjan HuismanDiagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, Netherlands.
Jeanne Pia Mifsud BonniciSecurity, Technology and e-Privacy Research Group (STeP), University of Groningen, Groningen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo clarify overlapping post-market obligations under the EU Artificial Intelligence Act (AIA) and EU Medical Device Regulation (MDR) for high-risk artificial intelligence (AI) Software as a Medical Device (SaMD), and to map the regulatory landscape for manufacturers, healthcare providers, AI providers, and AI deployers.

methodsWe conducted a qualitative doctrinal legal analysis of post-market provisions in the AIA and MDR, using a case study of a high-risk Class III AI SaMD for prostate cancer radiology. No empirical clinical or performance data were collected. The analysis focused on key stakeholders, including device manufacturers and deployers (e.g., healthcare providers). We sought to identify (1) convergence, where both regulations impose overlapping or complementary requirements, and (2) divergence, where obligations are addressed by only one regulation, revealing potential regulatory gaps.

resultsWe organized the extracted post-market obligations into ten categories. Overall, both regulations place increasing emphasis on lifecycle traceability and continuous monitoring. We identified convergence in areas such as documentation and performance monitoring, while divergences emerged in domains like human oversight (in the AIA) and reporting non-serious patterns (in the MDR). We also identified gaps in regulatory guidance, particularly regarding system updates, human oversight, and the evolving responsibilities of healthcare providers.

conclusionThe AIA and MDR share common ground in some post-market areas but also diverge in key responsibilities. To ensure safe and effective use of high-risk AI in healthcare, clearer coordination between the two frameworks is needed, especially in areas such as human oversight and system modification, where current guidance remains limited.

Indexed as

Artificial IntelligenceProstatic NeoplasmsEuropeHumansMaleArtificial intelligenceMagnetic resonance imagingMedical Device RegulationPostmarketingProstatic neoplasms

Identifiers

PMID41714355
PMCPMC13476294

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.