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Left ventricular ejection fraction estimation using mutual information on technetium-99m multiple-gated SPECT scans

Overview of attention for article published in BioMedical Engineering OnLine, January 2015
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Title
Left ventricular ejection fraction estimation using mutual information on technetium-99m multiple-gated SPECT scans
Published in
BioMedical Engineering OnLine, January 2015
DOI 10.1186/s12938-015-0117-2
Pubmed ID
Authors

Shih-Neng Yang, Shung-Shung Sun, Geoffrey Zhang, Kuei-Ting Chou, Shih-Wen Lo, Yu-Rou Chiou, Fang-Jing Li, Tzung-Chi Huang

Abstract

A new non-linear approach was applied to calculate the left ventricular ejection fraction (LVEF) using multigated acquisition (MUGA) images. In this study, 50 patients originally for the estimation of the percentage of LVEF to monitor the effects of various cardiotoxic drugs in chemotherapy were retrospectively selected. All patients had both MUGA and echocardiography examinations (ECHO LVEF) at the same time. Mutual information (MI) theory was utilized to calculate the LVEF using MUGA imaging (MUGA MI). MUGA MI estimation was significantly different from MUGA LVEF and ECHO LVEF, respectively (p < 0.005). The higher repeatability for MUGA MI can be observed in the figure by the higher correlation coefficient for MUGA MI (r = 0.95) compared with that of MUGA LVEF (r = 0.80). Again, the reproducibility was better for MUGA MI (r = 0.90, 0.92) than MUGA LVEF (r = 0.77, 0.83). The higher correlation coefficients were obtained between proposed MUGA MI and ECHO LVEF compared to that between the conventional MUGA LVEF and ECHO LVEF. MUGA image with the aid of MI is promising to be more interchangeable LVEF to ECHO LVEF measurement as compared with the conventional approach on MUGA image.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 27%
Student > Master 5 19%
Researcher 3 12%
Other 2 8%
Librarian 2 8%
Other 5 19%
Unknown 2 8%
Readers by discipline Count As %
Medicine and Dentistry 19 73%
Nursing and Health Professions 3 12%
Immunology and Microbiology 1 4%
Unknown 3 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 December 2015.
All research outputs
#3,307,878
of 6,818,838 outputs
Outputs from BioMedical Engineering OnLine
#144
of 387 outputs
Outputs of similar age
#150,623
of 295,530 outputs
Outputs of similar age from BioMedical Engineering OnLine
#7
of 19 outputs
Altmetric has tracked 6,818,838 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 387 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 295,530 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.