title: Facilitating coronary artery evaluation in MDCT using a 3D automatic vessel segmentation tool.
abstract: The purpose of this study was to investigate a 3D coronary artery segmentation algorithm using 16-row 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 >1.5 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 CT-based evaluation methods. The overall sensitivity and specificity of the automatic and manual approach were 93.1 vs. 95.83% and 86.1 vs. 81.9%. The time required for automatic evaluation was significantly shorter than with the manual approach, i.e., 246.04+/-43.17 s for the automatic approach and 526.88+/-45.71 s for the manual approach (P<0.0001). 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.
authors.affiliation: Institute for Diagnostic and Interventional Radiology, Johann Wolfgang Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany. fawad@gmx.de
authors.forename: M Fawad
authors.initials: MF
authors.lastname: Khan
authors.forename: Stefan
authors.initials: S
authors.lastname: Wesarg
authors.forename: Jessen
authors.initials: J
authors.lastname: Gurung
authors.forename: Selami
authors.initials: S
authors.lastname: Dogan
authors.forename: Adel
authors.initials: A
authors.lastname: Maataoui
authors.forename: Boris
authors.initials: B
authors.lastname: Brehmer
authors.forename: Christopher
authors.initials: C
authors.lastname: Herzog
authors.forename: Hanns
authors.initials: H
authors.lastname: Ackermann
authors.forename: Birgit
authors.initials: B
authors.lastname: Assmus
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Vogl
mesh_terms: D000368:Aged; D000465:Algorithms; D017023:Coronary Angiography; D003327:Coronary Disease / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*