A deterministic approach to automated stenosis quantification.
We developed a new approach to quantitative coronary angiography (QCA), which overcomes several limitations of available programs, such as dependence on operator input; limited tracking ability; fixed correction of the point spread function (PSF); and different calibration on empty vs. contrast-filled catheters. The program (Intelligent Images QCA, version 1.4) provides absolute reproducibility by deterministic, operator-independent identification of the skeleton and the edges of the coronary tree. The algorithm works as follows: application of a matched filter to emphasize selectively the coronary arteries; adaptive threshold binarization; binary thinning and skeletonization; perpendicular resampling with sub-pixel interpolation; derivative filtering; minimal cost edge detection; and automatic identification and quantification of the stenosis. Operator's interaction is restricted to definition of a region of interest; editing of either skeleton or edges is not allowed. PSF correction is fine-tuned to the actual frequency response of the imaging chain by calibration on a contrast-filled conical lucite phantom. Catheter calibration is carried out by a second derivative-based edge detection much less sensitive to the presence of contrast. In vitro phantom analysis (0. 5 to 5.0 mm) showed accuracy of 0.028-0.031 mm and precision of 0. 054-0.062 mm on nonmagnified images from the angio TV chain and the cine projector, respectively. In vivo evaluation on a series of consecutive diagnostic angiograms yielded correct contour detection of 70/73 stenoses (96%); interobserver intraframe MLD variability 0. 00 mm; correct tracking of catheter edges 100%; interobserver variation coefficient of catheter calibration 3.3%; and mean difference of calibration factor on contrast-filled vs. empty catheters 2.7%. This new approach significantly improves reproducibility with respect to conventional QCA, maintaining high accuracy, precision, and applicability. Cathet. Cardiovasc. Intervent. 48:435-445, 1999.
Tommasini
G
G
Divisione di Cardiologia, E.O. Ospedali Galliera, Genova, Italy. giortomm@iol.it
Rubartelli
P
P
Piaggio
M
M
D000465:Algorithms; D002138:Calibration; D017023:Coronary Angiography / Q000379:methods*; D003327:Coronary Disease / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015203:Reproducibility of Results; D012984:Software