Visual and automatic grading of coronary artery stenoses with 64-slice CT angiography in reference to invasive angiography.
The aim of this study was to assess the performance of a software tool for quantitative coronary artery analysis of computed tomography coronary angiography (CT-QCA) in comparison with invasive coronary angiography with quantitative analysis (CAG-QCA) as standard of reference. Two radiologists reviewed the CT angiography data sets (Siemens Sensation 64) of 25 patients, grading coronary artery stenoses visually and with a software tool (Circulation, Siemens). Twenty-three data sets with sufficient image quality were included in the final analysis. CAG revealed a total of 30 wall irregularities and 28 stenoses, of which 17 were graded as moderate and nine as hemodynamically significant. CT-QCA showed a better agreement to CAG-QCA, with a systematic overestimation of the degree of stenosis of 6.1% and limits of agreement of +36.1% and -23.9; the correlation coefficient was 0.82 (p < 0.0001). Using CT-QCA, sensitivity, specificity, and positive and negative predictive value were 89%, 100%, 89%, and 100%, respectively, for significant area stenoses greater than 75%. The positive predictive value for the visual assessment amounted to 53%. Interobserver variability between CT-QCA and visual assessment showed a kappa value of 0.72. In conclusion, software-supported CT-QCA makes it possible to quantify significant coronary artery stenoses automatically, with good agreement to CAG-QCA.
Busch
Stephanie
S
Department of Clinical Radiology, University of Munich, Marchioninistr. 15, 81377 Munich, Germany. Stephanie.Busch@med.uni-muenchen.de
Johnson
Thorsten R C
TR
Nikolaou
Konstantin
K
von Ziegler
Franz
F
Knez
Andreas
A
Reiser
Maximilian F
MF
Becker
Christoph R
CR
D003287:Contrast Media; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D007472:Iohexol / Q000031:analogs & derivatives; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*
D003287:Contrast Media; D007472:Iohexol; C038192:iopromide