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Korean J Radiol. 2013 Jan-Feb;14(1):21-9. doi: 10.3348/kjr.2013.14.1.21. Epub 2012 Dec 28.

Time efficiency and diagnostic accuracy of new automated myocardial perfusion analysis software in 320-row CT cardiac imaging.

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  • 1Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin 10117, Germany.



We aimed to evaluate the time efficiency and diagnostic accuracy of automated myocardial computed tomography perfusion (CTP) image analysis software.


320-row CTP was performed in 30 patients, and analyses were conducted independently by three different blinded readers by the use of two recent software releases (version 4.6 and novel version 4.71GR001, Toshiba, Tokyo, Japan). Analysis times were compared, and automated epi- and endocardial contour detection was subjectively rated in five categories (excellent, good, fair, poor and very poor). As semi-quantitative perfusion parameters, myocardial attenuation and transmural perfusion ratio (TPR) were calculated for each myocardial segment and agreement was tested by using the intraclass correlation coefficient (ICC). Conventional coronary angiography served as reference standard.


The analysis time was significantly reduced with the novel automated software version as compared with the former release (Reader 1: 43:08 ± 11:39 min vs. 09:47 ± 04:51 min, Reader 2: 42:07 ± 06:44 min vs. 09:42 ± 02:50 min and Reader 3: 21:38 ± 3:44 min vs. 07:34 ± 02:12 min; p < 0.001 for all). Epi- and endocardial contour detection for the novel software was rated to be significantly better (p < 0.001) than with the former software. ICCs demonstrated strong agreement (≥ 0.75) for myocardial attenuation in 93% and for TPR in 82%. Diagnostic accuracy for the two software versions was not significantly different (p = 0.169) as compared with conventional coronary angiography.


The novel automated CTP analysis software offers enhanced time efficiency with an improvement by a factor of about four, while maintaining diagnostic accuracy.


Automated analysis; Computed tomography; Coronary disease; Myocardial perfusion imaging; Software

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