Evidence map›Paper›PMID 41456340›Full record

ReviewJournal of magnetic resonance imaging : JMRI2026

Motion Mitigation Techniques for Abdominal and Cardiac MR Imaging.

Eric M Schrauben, Gastao Lima da Cruz, Christopher W Roy, Thomas Küstner

Abstract readReview
In one paragraph

Review in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Differential Diagnosis Using MRI of Canine Intestinal Neoplasms, Including Lymphoma, Adenocarcinoma, and Inflammatory Polyp: Case Series.Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association · 2026
    Article
  5. 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

4 authors.

Eric M SchraubenRadiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, the Netherlands.ORCID https://orcid.org/0000-0002-7922-3615
Gastao Lima da CruzRadiology, University of Michigan, Ann Arbor, Michigan, USA.
Christopher W RoyLausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Vaud, Switzerland.ORCID https://orcid.org/0000-0002-3111-8840
Thomas KüstnerMedical Image and Data Analysis (MIDAS.Lab), Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tuebingen, Germany.

Funding

Deutsche Forschungsgemeinschaft 390727645NIH HHS NIH R01 HL153034Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung PZ00P3_202140
6 · The paper itself

Abstract

MRI of the heart and abdominal organs provides unparalleled soft tissue contrast and quantitative biomarkers, yet remains highly susceptible to physiological motion. Contractions of the myocardium, respiratory excursions, peristalsis, vascular pulsatility, and unpredictable bulk patient movement generate artifacts that impair image quality, limit reproducibility, and may necessitate repeat scans. This review summarizes motion correction strategies in cardiac and abdominal MRI, emphasizing both clinical applications and methodological principles. Techniques to address motion can be broadly categorized into prospective and retrospective approaches. Prospective methods adjust acquisition in real time, for example through respiratory or cardiac gating, navigator echoes, or external sensors, while retrospective strategies apply corrections during or after reconstruction, using k-space binning, image registration, or model-based reconstructions. Rigid motion, such as translations or rotations of organs, can often be corrected efficiently, whereas non-rigid motion including myocardial contraction or peristalsis requires more sophisticated elastic registration or motion-compensated reconstruction. Application-specific challenges and solutions are highlighted across cardiac cine imaging, flow quantification, tagging, and quantitative mapping, as well as abdominal imaging of the liver, kidneys, and gastrointestinal tract. In each domain, examples are provided of how motion impacts diagnostic performance and how motion correction strategies can mitigate these effects. Strengths and limitations of current approaches are reviewed, from conventional breath-holding to advanced free-breathing motion-resolved imaging. Emerging trends include integration of artificial intelligence with motion-compensated reconstruction, advanced sensor technologies for real-time tracking, and hybrid approaches combining multiple strategies. While many methods remain research-focused, vendor-embedded solutions and open-source tools are increasingly available, narrowing the gap between technical advances and routine practice. Motion correction is poised to become a core feature of clinical MRI, enabling faster, more robust, and patient-friendly examinations that reduce repeat rates, improve diagnostic confidence, and expand access to high-quality imaging in challenging patient populations. EVIDENCE LEVEL: N/A. TECHNICAL EFFICACY: Stage 5.

Indexed as

AbdomenHeartImage Processing, Computer-AssistedMagnetic Resonance ImagingArtifactsHumansMotionMovementReproducibility of Resultsabdominalcardiacmotionmotion mitigation

Identifiers

PMID41456340
PMCPMC12963815

What OpenQuestion holds

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LicenceCC BY
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.