Evidence map›Paper›PMID 29427349›Full record

ArticleMagnetic resonance in medicine2018

Quantifying precision in cardiac diffusion tensor imaging with second-order motion-compensated convex optimized diffusion encoding.

Eric Aliotta, Kévin Moulin, Patrick Magrath, Daniel B Ennis

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Robust cardiacMagnetic resonance in medicine · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Myofiber strain in healthy humans using DENSE and cDTI.Magnetic resonance in medicine · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Diffusion tensor magnetic resonance imaging of the heart: Now feasible on your neighborhood scanner.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    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

4 authors.

Eric AliottaDepartment of Radiological Sciences, University of California, Los Angeles, California.
Kévin MoulinDepartment of Radiological Sciences, University of California, Los Angeles, California.
Patrick MagrathDepartment of Bioengineering, University of California, Los Angeles, California.
Daniel B EnnisDepartment of Radiological Sciences, University of California, Los Angeles, California.

Funding

UCLA Muscular Dystrophy Core CenterP30AR057230 · NIAMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SPENCER, MELISSA JAN · 2009 to 2018
$6.2M
Validating Cardiac MRI Biomarkers and Genotype-Phenotype Correlations for DMDR01HL131975 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ENNIS, DANIEL B · 2016 to 2019
$2.5M
A New Framework for Understanding the Mechanisms of Diastolic DysfunctionR01HL131823 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ENNIS, DANIEL B · 2017 to 2020
$2.3M
NHLBI NIH HHS R01 HL131823NHLBI NIH HHS R01 HL131975NIAMS NIH HHS P30 AR057230
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Diffusion Tensor ImagingRespirationAlgorithmsAnisotropyArtifactsDiastoleDiffusion Magnetic Resonance ImagingHeartHumansImage Processing, Computer-AssistedLikelihood FunctionsPhantoms, ImagingReproducibility of ResultsSignal-To-Noise Ratiocardiac diffusioncardiac MRIdiffusion tensor imaging

Identifiers

PMID29427349
PMCPMC5980763

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.