Evidence map›Paper›PMID 41189047›Full record

ArticleMagnetic resonance in medicine2026

Automatic Respiratory and Bulk Patient Motion Corrected 3D Fetal MRI.

Robin Ferincz, Leonor Alamo, Aurelio Secinaro, Estelle Tenisch, Aurélien Bustin, Davide Piccini, Milan Prša, Jérôme Yerly, Christopher W Roy

Abstract read
In one paragraph

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Robin FerinczDepartment of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0009-0001-9296-8582
Leonor AlamoDepartment of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Aurelio SecinaroAdvanced Cardiothoracic Imaging Unit, Department of Imaging, Bambino Gesù Children's Hospital IRCCS, Rome, Italy.
Estelle TenischDepartment of Radiology and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Aurélien BustinDepartment of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-2845-8617
Davide PicciniScientific Collaborations and Strategic Partnerships, Siemens Healthcare Srl, Milano, Italy.ORCID https://orcid.org/0000-0003-4663-3244
Milan PršaWoman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-9483-7957
Jérôme YerlyDepartment of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Christopher W RoyDepartment of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 202140
6 · The paper itself

Abstract

purposeTo develop a framework (ACROBATIC) for correcting motion in 3D radial fetal MRI.

methodsData were simulated (N = 200) and acquired in utero (N = 11, gestational age: 32 ± 2 weeks). Motion due to maternal respiration was estimated by extracting a self-gating signal and applying focused navigation. Bulk motion was estimated by splitting the acquisition into sequential bins, reconstructing 3D volumes and applying rigid image registration. These combined motion estimates were used to correct k-space. Self-gating signals were compared to ground truth in simulations and an external sensor in utero. The cumulative position error (CPE) measured the accuracy of motion estimations relative to ground truth in simulations and relative sharpness measured the corresponding impact on image quality for both simulations and in utero data. An expert reviewer performed a blinded ranking of in utero images including uncorrected and corrected data.

resultsSelf-gating signals correlated strongly with ground truth for simulations (R = 0.97 ± 0.01) and a external sensor for in utero data (R = 0.75 ± 0.23). CPE decreased significantly using ACROBATIC (uncorrected: 13.33[12.73-14.05], corrected: 2.20[1.80-2.61]). Relative image sharpness increased with ACROBATIC for both simulated (4.51[2.89-5.79]) and in utero data (1.12[0.77-1.44]) consistent with expert ranking where ACROBATIC images were given the best rank in the majority of cases.

conclusionACROBATIC enables motion correction in 3D radial fetal MRI. Correction of displacement due to maternal respiration and bulk motion results in improved image quality in simulations and in utero. Comparison to 2D frameworks are now warranted to establish the added diagnostic value of this approach.

Indexed as

ArtifactsImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPrenatal DiagnosisRespiratory-Gated Imaging TechniquesAlgorithmsFemaleFetusHumansImage EnhancementMotionPregnancyReproducibility of ResultsRespirationSensitivity and Specificity3Dfetalfree‐runningmotion correctionradialsimulation

Identifiers

PMID41189047
PMCPMC12850569

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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.