Evidence map›Paper›PMID 32243665›Full record

ArticleMagnetic resonance in medicine2020

Motion-robust, high-SNR liver fat quantification using a 2D sequential acquisition with a variable flip angle approach.

Ruiyang Zhao, Yuxin Zhang, Xiaoke Wang, Timothy J Colgan, Jennifer L Rehm, Scott B Reeder, Kevin M Johnson, Diego Hernando

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Optimized motion-insensitive PDFF mapping of the liver.Magnetic resonance in medicine · 2026
    Article
  5. Observational
  6. Free-breathing MRI techniques for fat and RMagma (New York, N.Y.) · 2024
    Review
  7. Article
  8. Article
  9. 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

8 authors.

Ruiyang ZhaoDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-2386-9767
Yuxin ZhangDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0001-9852-7959
Xiaoke WangDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-0892-2339
Timothy J ColganDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-4400-7525
Jennifer L RehmDepartment of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0003-2736-7753
Scott B ReederDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0003-4728-8171
Kevin M JohnsonDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-8660-0853
Diego HernandoDepartment of Radiology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0002-0016-0317

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
Technical Validation of MRI Biomarkers of Liver FatR01DK088925 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B., SIRLIN, CLAUDE B · 2010 to 2021
$7.1M
Confounder-Corrected Quantitative MRI Biomarkers of HepaticR01DK100651 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B. · 2014 to 2017
$2.7M
MRI-based Quantitative Susceptibility Mapping of Hepatic Iron OverloadR01DK117354 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI HERNANDO, DIEGO · 2018 to 2021
$2.3M
Technical Development of Quantitative Biomarkers of Fatty Liver Disease with MRIR01DK083380 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B. · 2010 to 2013
$1.2M
Evolution of Quantitative MRI Biomarkers of Metabolic Syndrome During PubertyK24DK102595 · NIDDK · UNIVERSITY OF WISCONSIN-MADISON · PI REEDER, SCOTT B. · 2014 to 2018
$927k
Quantitative Magnetic Resonance Imaging PhantomsR41EB025729 · NIBIB · CALIMETRIX, LLC · PI HERNANDO, DIEGO · 2018 to 2018
$239k
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NIBIB NIH HHS R41 EB025729NIDDK NIH HHS K24 DK102595NIDDK NIH HHS R01 DK083380NIDDK NIH HHS R01 DK088925NIDDK NIH HHS R01 DK100651NIDDK NIH HHS R01 DK117354
6 · The paper itself

Abstract

purposeChemical shift encoded (CSE)-MRI enables quantification of proton-density fat fraction (PDFF) as a biomarker of liver fat content. However, conventional 3D Cartesian CSE-MRI methods require breath-holding. A motion-robust 2D Cartesian sequential method addresses this limitation but suffers from low SNR. In this work, a novel free breathing 2D Cartesian sequential CSE-MRI method using a variable flip angle approach with centric phase encoding (VFA-centric) is developed to achieve fat quantification with low

methodsNumerical simulation was performed for variable flip angle schedule design and preliminary evaluation of VFA-centric method, along with several alternative flip angle designs. Phantom, adults (n = 8), and children (n = 27) were imaged at 3T. Multi-echo images were acquired and PDFF maps were estimated. PDFF standard deviation was used as a surrogate for SNR.

resultsIn both simulation and phantom experiments, the VFA-centric method enabled higher SNR imaging with minimal

conclusionsThe proposed free breathing 2D Cartesian sequential CSE-MRI method with variable flip angle approach and centric-ordered phase encoding achieved motion robustness, low

Indexed as

LiverMagnetic Resonance ImagingAdultArtifactsChildHumansMotionReproducibility of Results2D Cartesianfree breathinghigh SNRliver fatlowlow blurring artifactvariable flip angle

Identifiers

PMID32243665
PMCPMC7366366

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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.