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Improved workflow for quantification of left ventricular volumes and mass using free-breathing motion corrected cine imaging

Overview of attention for article published in Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd), February 2016
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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 (83rd percentile)

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15 tweeters
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2 Facebook pages

Citations

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20 Dimensions

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37 Mendeley
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Title
Improved workflow for quantification of left ventricular volumes and mass using free-breathing motion corrected cine imaging
Published in
Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd), February 2016
DOI 10.1186/s12968-016-0231-8
Pubmed ID
Authors

Russell Cross, Laura Olivieri, Kendall O’Brien, Peter Kellman, Hui Xue, Michael Hansen

Abstract

Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function. Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test. Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37 % reduction in acquisition and reconstruction time. The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Germany 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 27%
Other 5 14%
Student > Postgraduate 4 11%
Student > Ph. D. Student 4 11%
Professor > Associate Professor 2 5%
Other 5 14%
Unknown 7 19%
Readers by discipline Count As %
Medicine and Dentistry 12 32%
Engineering 6 16%
Computer Science 3 8%
Nursing and Health Professions 2 5%
Mathematics 1 3%
Other 3 8%
Unknown 10 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 March 2016.
All research outputs
#2,222,130
of 17,026,329 outputs
Outputs from Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd)
#138
of 1,042 outputs
Outputs of similar age
#44,346
of 270,024 outputs
Outputs of similar age from Journal of Cardiovascular Magnetic Resonance (Taylor & Francis Ltd)
#1
of 1 outputs
Altmetric has tracked 17,026,329 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,042 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 86% 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 270,024 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 83% 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