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Contrast-free detection of myocardial fibrosis in hypertrophic cardiomyopathy patients with diffusion-weighted cardiovascular magnetic resonance

Overview of attention for article published in Critical Reviews in Diagnostic Imaging, December 2015
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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 (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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13 X users
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1 Facebook page

Citations

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50 Dimensions

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85 Mendeley
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1 CiteULike
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Title
Contrast-free detection of myocardial fibrosis in hypertrophic cardiomyopathy patients with diffusion-weighted cardiovascular magnetic resonance
Published in
Critical Reviews in Diagnostic Imaging, December 2015
DOI 10.1186/s12968-015-0214-1
Pubmed ID
Authors

Christopher Nguyen, Minjie Lu, Zhaoyang Fan, Xiaoming Bi, Peter Kellman, Shihua Zhao, Debiao Li

Abstract

Previous studies have shown that diffusion-weighted cardiovascular magnetic resonance (DW-CMR) is highly sensitive to replacement fibrosis of chronic myocardial infarction. Despite this sensitivity to myocardial infarction, DW-CMR has not been established as a method to detect diffuse myocardial fibrosis. We propose the application of a recently developed DW-CMR technique to detect diffuse myocardial fibrosis in hypertrophic cardiomyopathy (HCM) patients and compare its performance with established CMR techniques. HCM patients (N = 23) were recruited and scanned with the following protocol: standard morphological localizers, DW-CMR, extracellular volume (ECV) CMR, and late gadolinium enhanced (LGE) imaging for reference. Apparent diffusion coefficient (ADC) and ECV maps were segmented into 6 American Heart Association (AHA) segments. Positive regions for myocardial fibrosis were defined as: ADC > 2.0 μm(2)/ms and ECV > 30 %. Fibrotic and non-fibrotic mean ADC and ECV values were compared as well as ADC-derived and ECV-derived fibrosis burden. In addition, fibrosis regional detection was compared between ADC and ECV calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) using ECV as the gold-standard reference. ADC (2.4 ± 0.2 μm(2)/ms) of fibrotic regions (ADC > 2.0 μm(2)/ms) was significantly (p < 0.01) higher than ADC (1.5 ± 0.2 μm(2)/ms) of non-fibrotic regions. Similarly, ECV (35 ± 4 %) of fibrotic regions (ECV > 30 %) was significantly (p < 0.01) higher than ECV (26 ± 2 %) of non-fibrotic regions. In fibrotic regions defined by ECV, ADC (2.2 ± 0.3 μm(2)/ms) was again significantly (p < 0.05) higher than ADC (1.6 ± 0.3 μm(2)/ms) of non-fibrotic regions. In fibrotic regions defined by ADC criterion, ECV (34 ± 5 %) was significantly (p < 0.01) higher than ECV (28 ± 3 %) in non-fibrotic regions. ADC-derived and ECV-derived fibrosis burdens were in substantial agreement (intra-class correlation = 0.83). Regional detection between ADC and ECV of diffuse fibrosis yielded substantial agreement (κ = 0.66) with high sensitivity, specificity, PPV, NPV, and accuracy (0.80, 0.85, 0.81, 0.85, and 0.83, respectively). DW-CMR is sensitive to diffuse myocardial fibrosis and is capable of characterizing the extent of fibrosis in HCM patients.

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X Demographics

The data shown below were collected from the profiles of 13 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Brazil 1 1%
Unknown 83 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Researcher 13 15%
Other 9 11%
Student > Master 9 11%
Student > Postgraduate 8 9%
Other 12 14%
Unknown 14 16%
Readers by discipline Count As %
Medicine and Dentistry 33 39%
Engineering 17 20%
Physics and Astronomy 6 7%
Computer Science 2 2%
Unspecified 2 2%
Other 5 6%
Unknown 20 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 11 March 2016.
All research outputs
#5,162,878
of 25,522,520 outputs
Outputs from Critical Reviews in Diagnostic Imaging
#324
of 1,379 outputs
Outputs of similar age
#78,655
of 396,159 outputs
Outputs of similar age from Critical Reviews in Diagnostic Imaging
#9
of 32 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 79th 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 76% 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 396,159 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 80% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.