Evidence map›Paper›PMID 26530323›Full record

ArticleMagma (New York, N.Y.)2016

Contrast-optimized composite image derived from multigradient echo cardiac magnetic resonance imaging improves reproducibility of myocardial contours and T2* measurement.

Pandji Triadyaksa, Astri Handayani, Hildebrand Dijkstra, Kadek Y E Aryanto, Gert Jan Pelgrim, Xueqian Xie, Tineke P Willems, Niek H J Prakken, Matthijs Oudkerk, Paul E Sijens

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In one paragraph

Article in Magma (New York, N.Y.), 2016. 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. Cardiac MR Fingerprinting: Overview, Technical Developments, and Applications.Journal of magnetic resonance imaging : JMRI · 2024
    Review
  2. Article
  3. Cardiac TJournal of magnetic resonance imaging : JMRI · 2020
    Review
  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

10 authors.

Pandji TriadyaksaCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands. p.triadyaksa@umcg.nl.
Astri HandayaniCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Hildebrand DijkstraCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Kadek Y E AryantoCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Gert Jan PelgrimCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Xueqian XieCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Tineke P WillemsDepartment of Radiology, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Niek H J PrakkenCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Matthijs OudkerkCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
Paul E SijensCenter for Medical Imaging-North East Netherlands, EB45, University of Groningen, University Medical Center Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesReproducibility of myocardial contour determination in cardiac magnetic resonance imaging is important, especially when determining T2* values per myocardial segment as a prognostic factor of heart failure or thalassemia. A method creating a composite image with contrasts optimized for drawing myocardial contours is introduced and compared with the standard method on a single image. MATERIALS AND

methodsA total of 36 short-axis slices from bright-blood multigradient echo (MGE) T2* scans of 21 patients were acquired at eight echo times. Four observers drew free-hand myocardial contours on one manually selected T2* image (method 1) and on one image composed by blending three images acquired at TEs providing optimum contrast-to-noise ratio between the myocardium and its surrounding regions (method 2).

resultsMyocardial contouring by method 2 met higher interobserver reproducibility than method 1 (P < 0.001) with smaller Coefficient of variance (CoV) of T2* values in the presence of myocardial iron accumulation (9.79 vs. 15.91%) and in both global myocardial and mid-ventricular septum regions (12.29 vs. 16.88 and 5.76 vs. 8.16%, respectively).

conclusionThe use of contrast-optimized composite images in MGE data analysis improves reproducibility of myocardial contour determination, leading to increased consistency in the calculated T2* values enhancing the diagnostic impact of this measure of iron overload.

Indexed as

AdolescentAdultAlgorithmsContrast MediaFemaleHeartHumansImage Processing, Computer-AssistedIronIron OverloadMagnetic Resonance ImagingMaleMiddle AgedMyocardiumObserver VariationReproducibility of ResultsContrast MediaIronContrast-optimized composite imageIron overloadMagnetic resonance imagingMyocardiumT2* quantification

Identifiers

PMID26530323
PMCPMC4751173

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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.