Evidence map›Paper›PMID 41060417›Full record

ReviewEuropean radiology2026

Safe for kids? AI medical devices in radiology overlook paediatric suitability.

Brendan S Kelly, Jennifer Lee, Edward Antram, Owen Arthurs, Susan C Shelmerdine

Abstract readReview
PubMed Publisher
In one paragraph

Review in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Reply to Srikanth M.Pediatric radiology · 2026
    Article
  7. Article
  8. Article
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

5 authors.

Brendan S KellyDepartment of Clinical Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK. brendan.kelly@gosh.nhs.uk.ORCID http://orcid.org/0000-0002-3449-8017
Jennifer LeeDepartment of Clinical Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Edward AntramDepartment of Radiology, St Georges Hospital NHS Foundation Trust, London, UK.
Owen ArthursDepartment of Clinical Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Susan C ShelmerdineDepartment of Clinical Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.

Funding

National Institute for Health and Care Research NIHR-301322National Institute for Health and Care Research NIHR-CDF-2017-10-037
6 · The paper itself

Abstract

objectivesPrior publications have highlighted inconsistent labelling of intended use cases and target population for U.S. Food and Drug Administration-approved AI medical devices, especially for children. The extent to which this issue applies to devices within Europe remains unaddressed. MATERIALS AND

methodsA comprehensive review was conducted of all regulatory-approved AI medical devices for use in radiology from a non-profit, publicly available database. Two independent reviewers assessed information about all the devices regarding use case, modality and intended population. A third reviewer resolved any discrepancies. Where the intended population was unclear, a standardised review of the available evidence and marketing materials for the AI device was conducted.

resultsOnly four (4/213, 2%) AI medical devices were clearly labelled for paediatric use. A further 11% were intended for all ages, including children. The majority (88/213; 41%) of all AI medical devices did not clearly demonstrate their intended population on the database. Further examination of the scientific literature and marketing of these "unclear" devices showed that 6 (6/88, 7%) of these included patients under 18 in their intended target population, but 47% (41/88) still remained unclear after further review.

conclusionMost regulated radiology AI medical devices have missing or unclear information regarding the appropriate use in children. This poses significant potential risk, including inadvertent off-label use, which could compromise patient safety. The EU AI Act emphasises the need for transparency and accountability in AI device deployment, and we therefore advocate for a standardised paediatric safety indicator to clearly communicate suitability. KEY POINTS: Question To what extent do European-approved radiology AI devices provide clear labelling of intended use and suitability for paediatric populations? Findings Many radiology AI medical devices in Europe lack explicit paediatric use information, raising concerns about unintended off-label use. Clinical relevance Clear labelling of AI device suitability for children is essential to ensure safe use. A standardised safety indicator could aid clinicians in appropriate device selection.

Indexed as

Artificial IntelligenceEquipment and SuppliesEquipment SafetyPediatricsRadiologyChildDevice ApprovalEuropeHumansPatient SafetyProduct LabelingUnited StatesUnited States Food and Drug AdministrationArtificial intelligenceIndications for useMedical devicesPaediatric radiology

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.