Evidence map›Paper›PMID 42432872›Full record

ArticleMagnetic resonance in medicine2026

Real-Time Targeted Slice Reacquisition for Motion-Corrupted Fetal Diffusion MRI.

Jordina Aviles Verdera, Sara Neves Silva, Susanne Schulz-Heise, Sarah McElroy, Mary Rutherford, Joseph V Hajnal, Raphael Tomi-Tricot, Jana Hutter

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Article in Magnetic resonance in medicine, 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
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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

8 authors.

Jordina Aviles VerderaImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0009-0007-7575-4244
Sara Neves SilvaImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0009-0009-7520-081X
Susanne Schulz-HeiseRadiology Institute, Uniklinikum Erlangen, Erlangen, Germany.
Sarah McElroyImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Mary RutherfordImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0000-0003-3361-1337
Joseph V HajnalImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0000-0002-2690-5495
Raphael Tomi-TricotMR Research Collaborations, Siemens Healthcare Limited, Camberley, UK.
Jana HutterImaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID https://orcid.org/0000-0003-3476-3500

Funding

Deutsche Forschungsgemeinschaft 502024488European Research Council 101165242Lower Saxony Ministry of Science and Culture ZN4257Medical Research Council MR/X010007/1
6 · The paper itself

Abstract

purposeTo develop and evaluate a real-time framework for targeted slice-level reacquisition in fetal diffusion MRI.

methodsA DW-SE-EPI sequence was modified to support independent diffusion preparation per slice. A pathology-robust nnU-Net segmentation network, updated from a previously published baseline (V1) using pathological fetal cases and physics-inspired augmentation (V2), and intensity-based artifact detection drive automated reacquisition prioritization. Retrospective validation was performed on 60 cases across three cohorts at two field strengths and prospective deployment in 14 cases at two clinical sites.

resultsSegmentation V2 significantly outperformed V1 across all cohorts (

conclusionReal-time slice-level fetal diffusion reacquisition is demonstrated for the first time, opening a pathway toward routine quantitative fetal diffusion MRI in research and clinical settings.

Indexed as

Diffusion Magnetic Resonance ImagingFetusImage Processing, Computer-AssistedPrenatal DiagnosisAlgorithmsArtifactsBrainFemaleHumansMotionPregnancyReproducibility of ResultsRetrospective Studiesartifact detectionbrain segmentationfetal diffusion MRIreal‐time reacquisition

Identifiers

PMID42432872
PMCPMC13527251

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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.