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Mapping tissue inhomogeneity in acute myocarditis: a novel analytical approach to quantitative myocardial edema imaging by T2-mapping

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, December 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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11 X users
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2 patents
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1 Facebook page

Citations

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53 Dimensions

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79 Mendeley
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Title
Mapping tissue inhomogeneity in acute myocarditis: a novel analytical approach to quantitative myocardial edema imaging by T2-mapping
Published in
Critical Reviews in Diagnostic Imaging, December 2015
DOI 10.1186/s12968-015-0217-y
Pubmed ID
Authors

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

Abstract

The purpose of the present study was to investigate the diagnostic value of T2-mapping in acute myocarditis (ACM) and to define cut-off values for edema detection. Cardiovascular magnetic resonance (CMR) data of 31 patients with ACM were retrospectively analyzed. 30 healthy volunteers (HV) served as a control. Additionally to the routine CMR protocol, T2-mapping data were acquired at 1.5 T using a breathhold Gradient-Spin-Echo T2-mapping sequence in six short axis slices. T2-maps were segmented according to the 16-segments AHA-model and segmental T2 values as well as the segmental pixel-standard deviation (SD) were analyzed. Mean differences of global myocardial T2 or pixel-SD between HV and ACM patients were only small, lying in the normal range of HV. In contrast, variation of segmental T2 values and pixel-SD was much larger in ACM patients compared to HV. In random forests and multiple logistic regression analyses, the combination of the highest segmental T2 value within each patient (maxT2) and the mean absolute deviation (MAD) of log-transformed pixel-SD (madSD) over all 16 segments within each patient proved to be the best discriminators between HV and ACM patients with an AUC of 0.85 in ROC-analysis. In classification trees, a combined cut-off of 0.22 for madSD and of 68 ms for maxT2 resulted in 83 % specificity and 81 % sensitivity for detection of ACM. The proposed cut-off values for maxT2 and madSD in the setting of ACM allow edema detection with high sensitivity and specificity and therefore have the potential to overcome the hurdles of T2-mapping for its integration into clinical routine.

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X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
United States 1 1%
Unknown 76 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 23%
Student > Doctoral Student 12 15%
Student > Ph. D. Student 9 11%
Student > Master 8 10%
Other 7 9%
Other 14 18%
Unknown 11 14%
Readers by discipline Count As %
Medicine and Dentistry 45 57%
Engineering 8 10%
Nursing and Health Professions 3 4%
Computer Science 2 3%
Mathematics 2 3%
Other 6 8%
Unknown 13 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 16 November 2021.
All research outputs
#2,976,870
of 25,522,520 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#150
of 1,379 outputs
Outputs of similar age
#47,235
of 397,355 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#6
of 54 outputs
Altmetric has tracked 25,522,520 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,379 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done well, scoring higher than 89% 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 397,355 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 88% of its contemporaries.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.