Evidence map›Paper›PMID 26114603›Full record

ArticleJournal of magnetic resonance imaging : JMRI2015

In vivo breath-hold (1) H MRS simultaneous estimation of liver proton density fat fraction, and T1 and T2 of water and fat, with a multi-TR, multi-TE sequence.

Gavin Hamilton, Michael S Middleton, Jonathan C Hooker, William M Haufe, Nketi I Forbang, Matthew A Allison, Rohit Loomba, Claude B Sirlin

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Confounder-corrected TMagnetic resonance in medicine · 2023
    Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Limits of Fat Quantification in the Presence of Iron Overload.Journal of magnetic resonance imaging : JMRI · 2021
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Characterizing a short TMagnetic resonance in medicine · 2019
    Article
  17. Article
  18. Article
  19. Mapping tissue water TNMR in biomedicine · 2019
    Article
  20. Stimulated echo based mapping (STEM) of TMagnetic resonance in medicine · 2019
    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

8 authors.

Gavin HamiltonLiver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA.
Michael S MiddletonLiver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA.
Jonathan C HookerLiver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA.
William M HaufeLiver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA.
Nketi I ForbangDepartment of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
Matthew A AllisonDepartment of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
Rohit LoombaDepartment of Family Medicine and Public Health, University of California, San Diego, San Diego, California, USA.
Claude B SirlinLiver Imaging Group, Department of Radiology, University of California, San Diego, San Diego, California, USA.

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
MR Imaging of Non-Alcoholic Fatty Liver DiseaseR01DK075128 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SIRLIN, CLAUDE B · 2006 to 2010
$2.4M
GENETIC EPIDEMIOLOGY OF NONALCOHOLIC FATTY LIVER DISEASEK23DK090303 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LOOMBA, ROHIT · 2011 to 2014
$721k
NIDDK NIH HHS 5R01 DK075128-04NIDDK NIH HHS K23 DK090303NIDDK NIH HHS K23-DK090303NIDDK NIH HHS R01 DK075128NIDDK NIH HHS R01 DK088925NIDDK NIH HHS R01 DK088925 -05
6 · The paper itself

Abstract

purposeTo examine the intra-examination repeatability of proton density fat fraction (PDFF) and T1 and T2 of liver water and fat as estimated by a novel multi-repetition time (TR)-echo time (TE) (1) H magnetic resonance spectroscopy (MRS)-stimulated echo acquisition mode (STEAM) sequence that acquires 32 spectra for a range of TRs and TEs in single breath-hold. MATERIALS AND

methodsSixty-seven subjects undergoing liver MRI examinations at 3T had three multi-TR-TE sequences acquired consecutively in a single session. This sequence was designed to allow accurate estimation of T1 and T2 of both water and fat, as well as PDFF, in a single breath-hold. A standard long-TR, multi-TE sequence was also acquired to allow comparison of estimated PDFF. Regression and interclass correlation (ICC) analyses were performed.

resultsThere was strong agreement between PDFF estimated by the multi-TR-TE and long-TR, multi-TE sequences (slope 0.997; intercept -0.03; R = 0.997). The multi-TR-TE sequence had high repeatability for estimating PDFF (ICC = 0.999), water T2 (ICC = 0.920), water T1 (ICC = 0.845), and fat T2 (ICC = 0.760), and moderate repeatability for estimating fat T1 (ICC = 0.556).

conclusionA novel multi-TR-TE sequence can estimate PDFF and water and fat T1 and T2 in a single breath-hold. Refinement may be needed to improve repeatability for fat T1 estimation.

Indexed as

AdiposityAdipose TissueAlgorithmsBody WaterBreath HoldingFemaleHumansLiverMaleMiddle AgedNon-alcoholic Fatty Liver DiseaseProton Magnetic Resonance SpectroscopyReproducibility of ResultsSensitivity and Specificitymagnetic resonance spectroscopyNAFLDNASHrelaxation

Identifiers

PMID26114603
PMCPMC4691228

What OpenQuestion holds

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Registered trials

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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.