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A novel multiparametric imaging approach to acute myocarditis using T2-mapping and CMR feature tracking

Overview of attention for article published in Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd), September 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)

Mentioned by

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27 tweeters
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Citations

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20 Dimensions

Readers on

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58 Mendeley
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Title
A novel multiparametric imaging approach to acute myocarditis using T2-mapping and CMR feature tracking
Published in
Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd), September 2017
DOI 10.1186/s12968-017-0387-x
Pubmed ID
Authors

Bettina Baeßler, Melanie Treutlein, Frank Schaarschmidt, Christian Stehning, Bernhard Schnackenburg, Guido Michels, David Maintz, Alexander C. Bunck

Abstract

The aim of this study was to evaluate the diagnostic potential of a novel cardiovascular magnetic resonance (CMR) based multiparametric imaging approach in suspected myocarditis and to compare it to traditional Lake Louise criteria (LLC). CMR data from 67 patients with suspected acute myocarditis were retrospectively analyzed. Seventeen age- and gender-matched healthy subjects served as control. T2-mapping data were acquired using a Gradient-Spin-Echo T2-mapping sequence in short-axis orientation. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values and pixel-standard deviation (SD) were recorded. Afterwards, the parameters maxT2 (the highest segmental T2 value) and madSD (the mean absolute deviation (MAD) of the pixel-SDs) were calculated for each subject. Cine sequences in three long axes and a stack of short-axis views covering the left and right ventricle were analyzed using a dedicated feature tracking algorithm. A multiparametric imaging model containing madSD and LV global circumferential strain (GCSLV) resulted in the highest diagnostic performance in receiver operating curve analyses (area under the curve [AUC] 0.84) when compared to any model containing a single imaging parameter or to LLC (AUC 0.79). Adding late gadolinium enhancement (LGE) to the model resulted in a further increased diagnostic performance (AUC 0.93) and yielded the highest diagnostic sensitivity of 97% and specificity of 77%. A multiparametric CMR imaging model including the novel T2-mapping derived parameter madSD, the feature tracking derived strain parameter GCSLV and LGE yields superior diagnostic sensitivity in suspected acute myocarditis when compared to any imaging parameter alone and to LLC.

Twitter Demographics

The data shown below were collected from the profiles of 27 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 21%
Other 7 12%
Student > Postgraduate 6 10%
Student > Master 5 9%
Student > Ph. D. Student 5 9%
Other 13 22%
Unknown 10 17%
Readers by discipline Count As %
Medicine and Dentistry 42 72%
Nursing and Health Professions 2 3%
Computer Science 1 2%
Energy 1 2%
Physics and Astronomy 1 2%
Other 0 0%
Unknown 11 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2018.
All research outputs
#1,516,288
of 17,826,855 outputs
Outputs from Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd)
#75
of 1,101 outputs
Outputs of similar age
#36,248
of 284,815 outputs
Outputs of similar age from Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd)
#1
of 1 outputs
Altmetric has tracked 17,826,855 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,101 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 284,815 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them