Evidence map›Paper›PMID 42701682›Full record

ArticlePEC innovation2026

Stakeholders' perspectives on an autonomous brain MRI: An interview study.

Christien N Mensinga, Leonie N C Visser, Jonathan Ebbers, Sjenny A C M Winters, Dennis W J Klomp, Marielle H Emmelot-Vonk, Huiberdina L Koek

Abstract read
In one paragraph

Article in PEC innovation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Christien N MensingaDepartment of Geriatrics, University Medical Center Utrecht, Utrecht University, the Netherlands.
Leonie N C VisserMedical Psychology, Amsterdam UMC location AMC, University of Amsterdam, the Netherlands.
Jonathan EbbersDepartment of Geriatrics, University Medical Center Utrecht, Utrecht University, the Netherlands.
Sjenny A C M WintersQuaRijn, Health Care Organization for the Elderly, the Netherlands.
Dennis W J KlompCenter for Image Sciences, University Medical Center Utrecht, Utrecht University, the Netherlands.
Marielle H Emmelot-VonkDepartment of Geriatrics, University Medical Center Utrecht, Utrecht University, the Netherlands.
Huiberdina L KoekDepartment of Geriatrics, University Medical Center Utrecht, Utrecht University, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study explored how patients, care partners, and healthcare professionals perceive an autonomous Magnetic Resonance Imaging (MRI) scanning system in which individuals perform their own brain scans and images are interpreted using Artificial Intelligence (AI) for early detection and monitoring of brain-related conditions. Methods: Semi-structured interviews were conducted with patients ( Results: Twelve of fourteen TDF domains were found relevant. Knowledge and communication were key facilitators for confidence and trust. Participants emphasised the need for clear, step-by-step information before and during the scan. Concerns focused on patients' ability to manage scanning independently, the absence of on-site staff in emergencies, and the transparency and accountability of AI. Patients valued convenience, while professionals highlighted early detection and efficiency as primary benefits. Conclusion: Trust in autonomous MRI depends on clear communication and education, and clarity about human oversight and responsibility. Innovation: Our findings show the relevance of combining technological innovation with human-centred communication. Integrating effective communication strategies and educational materials, such as visual and interactive instructions, can empower patients and professionals and support the adoption of autonomous MRI in healthcare practice, making neuroimaging more accessible while maintaining safety and quality.

Indexed as

Artificial intelligenceAutonomous MRICommunicationHealthcare innovationImplementationPatient educationTrust

Identifiers

PMID42701682
PMCPMC13545706

What Socratic 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 Socratic graph.