Evidence map›Paper›PMID 32103549›Full record

ArticleMagnetic resonance in medicine2020

Fat-water separation by fast metabolite cycling magnetic resonance spectroscopic imaging at 3 T: A method to generate separate quantitative distribution maps of musculoskeletal lipid components.

Ahmad A Alhulail, Debra A Patterson, Pingyu Xia, Xiaopeng Zhou, Chen Lin, M Albert Thomas, Ulrike Dydak, Uzay E Emir

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Journal of orthopaedic translation · 2023
    Review
  3. Article
  4. Article
  5. 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.

Ahmad A AlhulailSchool of Health Sciences, Purdue University, West Lafayette, Indiana.ORCID 0000-0002-6393-5415
Debra A PattersonSchool of Health Sciences, Purdue University, West Lafayette, Indiana.
Pingyu XiaSchool of Health Sciences, Purdue University, West Lafayette, Indiana.
Xiaopeng ZhouSchool of Health Sciences, Purdue University, West Lafayette, Indiana.
Chen LinDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.
M Albert ThomasDepartment of Radiology, University of California Los Angeles, Los Angeles, California.
Ulrike DydakSchool of Health Sciences, Purdue University, West Lafayette, Indiana.ORCID 0000-0003-1852-7110
Uzay E EmirSchool of Health Sciences, Purdue University, West Lafayette, Indiana.ORCID 0000-0001-5376-0431

Funding

Indiana Clinical and Translational Sciences InstituteUL1TR001108 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$23.3M
3T MRI Scanner dedicated to Life Sciences ResearchS10OD012336 · OD · PURDUE UNIVERSITY · PI DYDAK, ULRIKE · 2015 to 2015
$2.0M
NCATS NIH HHS UL1 TR001108NIH HHS S10 OD012336
6 · The paper itself

Abstract

purposeTo provide a rapid, noninvasive fat-water separation technique that allows producing quantitative maps of particular lipid components.

methodsThe calf muscles in 5 healthy adolescents (age 12-16 years; body mass index = 20 ± 3 kg/m

resultsThe proposed MRSI technique provided individual fat fraction maps for eight musculoskeletal lipid components identified by LCModel analysis (IMC/L [CH

conclusionThis MRSI technique can be a useful tool when individual lipid fat fraction maps are desired within a clinically acceptable time and with a nominal spatial resolution of 0.25 mL.

Indexed as

Magnetic Resonance ImagingWaterLegLipidsMagnetic Resonance SpectroscopyLipidsWaterfast MRSIfat fractionIMCLlipidmusculoskeletalquantification

Identifiers

PMID32103549
PMCPMC7583348

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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.