Evidence map›Paper›PMID 35997609›Full record

ReviewRadiology2023

Respiratory Motion Management in Abdominal MRI:

Pankaj Nepal, Barun Bagga, Li Feng, Hersh Chandarana

Abstract readCase ReportsReview
In one paragraph

Review in Radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  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
  6. Review
  7. Simple Frame-based Approach for MR Imaging-guided Abdominal Biopsy: Preliminary Evaluation in a Phantom Model.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Advanced Abdominal MRI Techniques and Problem-Solving Strategies.Journal of the Korean Society of Radiology · 2024
    Review
  13. Deep Learning-accelerated MRI in Body and Chest.Journal of computer assisted tomography
    Review
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.

Pankaj NepalFrom the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (P.N.); Department of Radiology, New York University School of Medicine, New York, NY (B.B., H.C.); and Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (L.F.).ORCID 0000-0001-6400-8915
Barun BaggaFrom the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (P.N.); Department of Radiology, New York University School of Medicine, New York, NY (B.B., H.C.); and Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (L.F.).ORCID 0000-0002-0647-5766
Li FengFrom the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (P.N.); Department of Radiology, New York University School of Medicine, New York, NY (B.B., H.C.); and Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (L.F.).
Hersh ChandaranaFrom the Department of Radiology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114 (P.N.); Department of Radiology, New York University School of Medicine, New York, NY (B.B., H.C.); and Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (L.F.).

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion QuantificationR01EB030549 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FENG, LI · 2021 to 2024
$1.7M
Rapid Structure-Function MRI of the Lung for Post-COVID-19 ManagementR01EB031083 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FENG, LI · 2021 to 2021
$1.5M
3D Free-Breathing Fat and Iron Corrected T1 MappingR21EB032917 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FENG, LI · 2022 to 2023
$465k
NIBIB NIH HHS P41 EB017183NIBIB NIH HHS R01 EB030549NIBIB NIH HHS R01 EB031083NIBIB NIH HHS R21 EB032917
6 · The paper itself

Abstract

A 96-year-old woman had a suboptimal evaluation of liver observations at abdominal MRI due to significant respiratory motion. State-of-the-art strategies to minimize respiratory motion during clinical abdominal MRI are discussed.

Indexed as

AbdomenRadiologyAged, 80 and overFemaleHumansMagnetic Resonance ImagingMotionRadiographyRespiration

Identifiers

PMID35997609
PMCPMC9792710

What OpenQuestion 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 OpenQuestion graph.