Evidence map›Paper›PMID 33783066›Full record

ArticleJournal of magnetic resonance imaging : JMRI2021

Limits of Fat Quantification in the Presence of Iron Overload.

Timothy J Colgan, Ruiyang Zhao, Nathan T Roberts, Diego Hernando, Scott B Reeder

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Impact of particle size onMagnetic resonance in medicine · 2025
    Article
  9. Review
  10. Review
  11. Review
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Timothy J ColganDepartment of Radiology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0002-4400-7525
Ruiyang ZhaoDepartment of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
Nathan T RobertsDepartment of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
Diego HernandoDepartment of Radiology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0002-0016-0317
Scott B ReederDepartment of Radiology, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0003-4728-8171
University of Wisconsin–Madison · US

Funding

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
Quantitative Magnetic Resonance Imaging PhantomsR44EB025729 · NIBIB · CALIMETRIX, LLC · PI BRITTAIN, JEAN H., HERNANDO, DIEGO · 2019 to 2020
$1.5M
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
NIBIB NIH HHS R41 EB025729NIBIB NIH HHS R44 EB025729NIDDK NIH HHS K24 DK102595NIDDK NIH HHS R01 DK088925NIDDK NIH HHS R01 DK100651NIDDK NIH HHS R01 DK117354
6 · The paper itself

Abstract

backgroundChemical shift encoded magnetic resonance imaging (CSE-MRI)-based tissue fat quantification is confounded by increased R2* signal decay rate caused by the presence of excess iron deposition. PURPOSE: To determine the upper limit of R2* above which it is no longer feasible to quantify proton density fat fraction (PDFF) reliably, using CSE-MRI. STUDY TYPE: Prospective. POPULATION: Cramér-Rao lower bound (CRLB) calculations, Monte Carlo simulations, phantom experiments, and a prospective study in 26 patients with known or suspected liver iron overload. FIELD STRENGTH/SEQUENCE: Multiecho gradient echo at 1.5 T and 3.0 T. ASSESSMENT: CRLB calculations were used to develop an empirical relationship between the maximum R2* value above which PDFF estimation will achieve a desired number of effective signal averages. A single voxel multi-TR, multi-TE stimulated echo acquisition mode magnetic resonance spectroscopy acquisition was used as a reference standard to estimate PDFF. Reconstructed PDFF and R2* maps were analyzed by one analyst using multiple regions of interest drawn in all nine Couinaud segments. STATISTICAL TESTS: None.

resultsSimulations, phantom experiments, and in vivo measurements demonstrated unreliable PDFF estimates with increased R2*, with PDFF errors as large as 20% at an R2* of 1000 s DATA

conclusionWe successfully developed a theoretically-based empirical formula that may provide an easily calculable guideline to identify R2* values above which PDFF is not reliable in research and clinical applications using CSE-MRI to quantify PDFF in the presence of iron overload. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

Indexed as

Iron OverloadHumansLiverMagnetic Resonance ImagingPhantoms, ImagingProspective StudiesReproducibility of ResultsfatironliverPDFFproton density fat fractionR2* chemical shift encoded magnetic resonance imaging

Identifiers

PMID33783066
PMCPMC8440489
OpenAlexW3147441881

What OpenQuestion holds

Textmetadata
LicenceTDM
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.