Validation of an automated system for luminal and medial-adventitial border detection in three-dimensional intravascular ultrasound.
The precise tomographic assessment of coronary artery disease by intravascular ultrasound (IVUS) is useful in quantitative studies. Such studies require identification of luminal and medial-adventitial (MA) borders in a sequence of IVUS images. We have developed a three-dimensional (3D) active-surface system for border detection that facilitates the analysis of many images with minimal user interaction. To assess the validity of the technique, luminal and MA borders in 529 end-diastolic images from nine coronary arterial segments (58.8 +/- 14.2 images per patient) were traced manually by four experienced observers. The computer-detected borders were compared with borders determined by the four observers using a modified Williams' index (WI), the ratio of inter-observer variability to computer-observer variability. While manual tracing required 49.2 +/- 12.1 min for analysis, the analysis system identified luminal (R2 = 0.92) and MA borders (R2 = 0.97) in 13.8 +/- 4.0 min, a decrease of 35.4 min (p < 0.000001). The computer minus observer differences in lumen area and MA area were -0.88 +/- 0.90 and -0.07 +/- 0.63 mm2. Therefore, the computer system underestimated both lumen and MA area, but this effect was very small in MA area. The WI values and 95% confidence intervals were 0.98 (0.89,1.06) for luminal border detection and 0.99 (0.95,1.04) for MA border detection. Plaque volume measurements, a common endpoint of clinical trials, also verified the accuracy of the technique (R2 = 0.98). The proposed 3D active-surface border detection system provides a faster and less-tedious alternative to manual tracing for assessment of coronary artery anatomy in vivo.
Department of Biomedical Engineering, Lerner Research Institute, The Cleveland Clinic Foundation, Cleveland, OH 44195, USA.
Jon D
JD
Klingensmith
E Murat
EM
Tuzcu
Steven E
SE
Nissen
D Geoffrey
DG
Vince
D000328:Adult; D000368:Aged; D000465:Algorithms; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008875:Middle Aged; D015588:Observer Variation; D013997:Time Factors; D018084:Ultrasonography, Interventional / Q000379:methods*