Authors: M Fawad Khan Stefan Wesarg Jessen Gurung Selami Dogan Adel Maataoui Boris Brehmer Christopher Herzog Hanns Ackermann Birgit Aßmus Thomas J Vogl
Publish Date: 2006/03/10
Volume: 16, Issue: 8, Pages: 1789-1795
Abstract
The purpose of this study was to investigate a 3D coronary artery segmentation algorithm using 16row MDCT data sets Fifty patients underwent cardiac CT Sensation 16 Siemens and coronary angiography Automatic and manual detection of coronary artery stenosis was performed A 3D coronary artery segmentation algorithm Fraunhofer Institute for Computer Graphics Darmstadt was used for automatic evaluation All significant stenoses 50 in vessels 15 mm in diameter were protocoled Each detection tool was used by one reader who was blinded to the results of the other detection method and the results of coronary angiography Sensitivity and specificity were determined for automatic and manual detection as well as was the time for both CTbased evaluation methods The overall sensitivity and specificity of the automatic and manual approach were 931 vs 9583 and 861 vs 819 The time required for automatic evaluation was significantly shorter than with the manual approach ie 24604±4317 s for the automatic approach and 52688±4571 s for the manual approach P00001 In 94 of the coronary artery branches automatic detection required less time than the manual approach Automatic coronary vessel evaluation is feasible It reduces the time required for cardiac CT evaluation with similar sensitivity and specificity as well as facilitates the evaluation of MDCT coronary angiography in a standardized fashion
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