ArticleEuropean journal of radiology open2025
Exploring scenarios for implementing fast quantitative MRI.
Article in European journal of radiology open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
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Who cites it
4 citing papers in PubMed.
- Feasibility of angiographic imaging using fast 3D Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT).Magma (New York, N.Y.) · 2026Article
- Advanced magnetic resonance imaging techniques for structural and functional assessment of salivary glands.Radiology and oncology · 2026Review
- Anticipating Moral and Economic Considerations, Opportunities, and Potential Frictions for AI in Medical Imaging: Multistakeholder Cocreation Study.Journal of medical Internet research · 2026Article
- Synergistic terahertz platforms for precision oncology.Theranostics · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: MRI waitlists and discomfort from long scanning sessions are significant problems in clinical radiology. Novel multiparametric quantitative MRI techniques (qMRI) for radiological imaging enable acquisition of full-brain data within minutes to address these problems. While technical and clinical work is advancing, there has been limited research on implementing fast qMRI. This paper aims to identify implementation factors and scenarios within a healthcare setting facing rising demand, staff shortages, and limited capacity of MRI systems. Methods: The paper reports on data collected using qualitative methods: 1) Interviews and guided discussions, 2) co-creation workshop. Both steps involved key representatives with various backgrounds and expertise, such as radiologists, lab technicians, insurers, and patients. Results: Workshop participants visualised current and future workflows, which helped articulate implementation factors for qMRI. Supply and demand in MRI will change with increased accessibility and shortened timeslots. Three implementation scenarios came forward: 1) stable deployment, 2) extension to conducting more complex diagnostic exams, and 3) (more) preventive screening. Discussion and conclusions: This paper demonstrates challenges, solutions, and opportunities for successfully implementing fast qMRI in the clinic, and five lessons for adoption in the clinic: 1) importance of balancing perfectionism with confidence when it comes to clinicians' expectations, 2) good use of Artificial Intelligence, 3) considering a learning curve associated with implementation, 4) regarding competing technologies, and 5) including patients' experiences. Future research should investigate salient issues regarding future of AI in radiology and for moving imaging practices out of the clinic.
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Registered trials
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.