Evidence map›Paper›PMID 26220204›Full record

ArticleMagnetic resonance in medicine2016

Robust self-navigated body MRI using dense coil arrays.

Tao Zhang, Joseph Y Cheng, Yuxin Chen, Dwight G Nishimura, John M Pauly, Shreyas S Vasanawala

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
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  8. Free-breathing MRI techniques for fat and RMagma (New York, N.Y.) · 2024
    Review
  9. Article
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  16. Free-breathing fat and RMagnetic resonance in medicine · 2020
    Article
  17. Article
  18. Article
  19. Multipoint 5D flow cardiovascular magnetic resonance - accelerated cardiac- and respiratory-motion resolved mapping of mean and turbulent velocities.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2019
    Article
  20. 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

6 authors.

Tao ZhangDepartment of Radiology, Stanford University, Stanford, California, USA.
Joseph Y ChengDepartment of Radiology, Stanford University, Stanford, California, USA.
Yuxin ChenDepartment of Statistics, Stanford University, Stanford, California, USA.
Dwight G NishimuraDepartment of Electrical Engineering, Stanford University, Stanford, California, USA.
John M PaulyDepartment of Electrical Engineering, Stanford University, Stanford, California, USA.
Shreyas S VasanawalaDepartment of Radiology, Stanford University, Stanford, California, USA.

Funding

Training and DisseminationP41EB015891 · NIBIB · STANFORD UNIVERSITY · PI GLOVER, GARY H · 2012 to 2019
$10.7M
Rapid Robust Pediatric MRIR01EB009690 · NIBIB · STANFORD UNIVERSITY · PI LUSTIG, MICHAEL, VASANAWALA, SHREYAS S · 2010 to 2021
$5.6M
Development and Translation of High Performance Receive Arrays for Pediatric MRIR01EB019241 · NIBIB · STANFORD UNIVERSITY · PI PAULY, JOHN M., VASANAWALA, SHREYAS S · 2014 to 2018
$5.6M
NIBIB NIH HHS P41 EB015891NIBIB NIH HHS R01 EB009690NIBIB NIH HHS R01 EB019241
6 · The paper itself

Abstract

purposeTo develop a robust motion estimation method for free-breathing body MRI using dense coil arrays.

methodsSelf-navigating pulse sequences can measure subject motion without using external motion monitoring devices. With dense coil arrays, individual coil elements can provide localized motion estimates. An averaged motion estimate over all coils is often used for motion compensation. However, this motion estimate may not accurately represent the dominant motion within the imaging volume. In this work, a coil clustering method is proposed to automatically determine the dominant motion for dense coil arrays. The feasibility of the proposed method is investigated in free-breathing abdominal MRI and cardiac MRI, and compared with manual motion estimate selection for respiratory motion estimation and electrocardiography for cardiac motion estimation.

resultsAutomated motion estimation achieved similar respiratory motion estimation compared to manual selection (averaged correlation coefficient 0.989 and 0.988 for abdominal MRI and cardiac MRI, respectively), and accurate cardiac triggering compared to electrocardiography (averaged temporal variability 17.5 ms).

conclusionThe proposed method can provide accurate automated motion estimation for body MRI using dense coil arrays. It can enable self-navigated free-breathing abdominal and cardiac MRI without the need for external motion monitoring devices. Magn Reson Med 76:197-205, 2016. © 2015 Wiley Periodicals, Inc.

Indexed as

ArtifactsCardiac-Gated Imaging TechniquesEquipment DesignHumansImage EnhancementMagnetic Resonance ImagingMagneticsMotionMovementPhantoms, ImagingReproducibility of ResultsRespiratory-Gated Imaging TechniquesSensitivity and Specificityabdominal MRIcardiac MRIcoil arraysmotion correctionparallel imagingself-navigated MRI

Identifiers

PMID26220204
PMCPMC4732937

What OpenQuestion holds

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LicenceTDM
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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.