Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound.
OBJECTIVE
We evaluated the accuracy of a new 64-slice computed tomography (CT) scanner, compared with intravascular ultrasound, to visualize atherosclerosis in the proximal coronary system.


BACKGROUND
Noninvasive determination of plaque composition and plaque burden may be important to improve risk stratification.


METHODS
In 20 patients, a 64-slice CT scan (Sensation 64, Siemens Medical Solutions, Forchheim, Germany) and an intravascular ultrasound investigation of vessels without stenosis >50% was performed. Diagnostic image quality with 64-slice CT was obtained in 36 vessels in 19 patients.


RESULTS
In these vessels, which were divided in 3-mm sections, 64-slice CT enabled a correct detection of plaque in 54 of 65 (83%) sections containing noncalcified plaques, 50 of 53 (94%) sections containing mixed plaques, and 41 of 43 (95%) sections containing calcified plaques. In 192 of 204 (94%) sections, atherosclerotic lesions were excluded correctly. In addition, 64-slice CT enabled the visualization of 7 of 10 (70%) sections revealing a lipid pool and could identify a spotty calcification pattern in 27 of 30 (90%) sections. The correlation coefficient to determine plaque volumes per vessel was r2 = 0.69 (p < 0.001) with an underestimation of mixed and noncalcified plaque volumes (p < 0.03) and a trend to overestimate calcified plaque volumes by 64-slice CT. The interobserver variability to determine plaque volumes was 37%. Interobserver agreement to identify atherosclerotic sections was good (Cohen's kappa coefficient = 0.75).


CONCLUSIONS
We conclude that 64-slice CT reveals encouraging results to noninvasively detect different types of coronary plaques located in the proximal coronary system. The ability to determine plaque burden currently is hampered by mainly an insufficient reproducibility.
Leber
Alexander W
AW
Department of Cardiology, Klinikum Grosshadern, University of Munich, Munich, Germany. aleber@med.uni-muenchen.de
Becker
Alexander
A
Knez
Andreas
A
von Ziegler
Franz
F
Sirol
Marc
M
Nikolaou
Konstantin
K
Ohnesorge
Bernd
B
Fayad
Zahi A
ZA
Becker
Christoph R
CR
Reiser
Maximilian
M
Steinbeck
Gerhard
G
Boekstegers
Peter
P
D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D019160:Endosonography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed