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Diagnostic accuracy of semi-automatic quantitative metrics as an alternative to expert reading of CT myocardial perfusion in the CORE320 study

Overview of attention for article published in Journal of Cardiovascular Computed Tomography, April 2018
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
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Title
Diagnostic accuracy of semi-automatic quantitative metrics as an alternative to expert reading of CT myocardial perfusion in the CORE320 study
Published in
Journal of Cardiovascular Computed Tomography, April 2018
DOI 10.1016/j.jcct.2018.03.010
Pubmed ID
Authors

Mohammad R Ostovaneh, Andrea L Vavere, Vishal C Mehra, Klaus F Kofoed, Matthew B Matheson, Armin Arbab-Zadeh, Yasuko Fujisawa, Joanne D Schuijf, Carlos E Rochitte, Arthur J Scholte, Kakuya Kitagawa, Marc Dewey, Christopher Cox, Marcelo F DiCarli, Richard T George, Joao A C Lima

Abstract

To determine the diagnostic accuracy of semi-automatic quantitative metrics compared to expert reading for interpretation of computed tomography perfusion (CTP) imaging. The CORE320 multicenter diagnostic accuracy clinical study enrolled patients between 45 and 85 years of age who were clinically referred for invasive coronary angiography (ICA). Computed tomography angiography (CTA), CTP, single photon emission computed tomography (SPECT), and ICA images were interpreted manually in blinded core laboratories by two experienced readers. Additionally, eight quantitative CTP metrics as continuous values were computed semi-automatically from myocardial and blood attenuation and were combined using logistic regression to derive a final quantitative CTP metric score. For the reference standard, hemodynamically significant coronary artery disease (CAD) was defined as a quantitative ICA stenosis of 50% or greater and a corresponding perfusion defect by SPECT. Diagnostic accuracy was determined by area under the receiver operating characteristic curve (AUC). Of the total 377 included patients, 66% were male, median age was 62 (IQR: 56, 68) years, and 27% had prior myocardial infarction. In patient based analysis, the AUC (95% CI) for combined CTA-CTP expert reading and combined CTA-CTP semi-automatic quantitative metrics was 0.87(0.84-0.91) and 0.86 (0.83-0.9), respectively. In vessel based analyses the AUC's were 0.85 (0.82-0.88) and 0.84 (0.81-0.87), respectively. No significant difference in AUC was found between combined CTA-CTP expert reading and CTA-CTP semi-automatic quantitative metrics in patient based or vessel based analyses(p > 0.05 for all). Combined CTA-CTP semi-automatic quantitative metrics is as accurate as CTA-CTP expert reading to detect hemodynamically significant CAD.

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The data shown below were collected from the profiles of 8 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 21%
Researcher 2 11%
Student > Doctoral Student 2 11%
Unspecified 1 5%
Lecturer 1 5%
Other 2 11%
Unknown 7 37%
Readers by discipline Count As %
Medicine and Dentistry 10 53%
Materials Science 1 5%
Unspecified 1 5%
Unknown 7 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 22 June 2018.
All research outputs
#7,310,010
of 25,394,764 outputs
Outputs from Journal of Cardiovascular Computed Tomography
#422
of 917 outputs
Outputs of similar age
#120,041
of 343,144 outputs
Outputs of similar age from Journal of Cardiovascular Computed Tomography
#19
of 30 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 917 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has gotten more attention than average, scoring higher than 52% 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 343,144 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.