L. Klein et al., PERFORMANCE STANDARDS AND EDGE-DETECTION WITH COMPUTERIZED QUANTITATIVE CORONARY ARTERIOGRAPHY, The American journal of cardiology, 77(10), 1996, pp. 815-822
Quantitative coronary angiography (QCA) has become an important tool f
or evaluating coronary angiograms. Many methodologic factors, such as
the choice of frame to analyze, the selection of the ''normal,'' segme
nt and the method of edge detection used may affect the results of QCA
. The sequential steps in performing QCA, including a comparison of vi
sual and automated edge-detection methodologies, were evaluated using
12 precision-drilled phantoms and 20 patient films. Normal diameter, m
inimal lumen diameter, and diameter stenosis were measured. In the pha
ntom studies, the measurements from both visual and automated systems
correlated well with the true measurements of the phantoms and between
systems (all r values >0.92). To study the difference between methodo
logies on QCA results as influenced by the choice of frame and normal
segment analyzed, the patient films were analyzed independently in 3 s
eparate rounds of interpretation. In round 1, each system's operator i
ndividually chose frames and normal segments for analysis. In round 2,
both systems analyzed the same preselected frames, but independently
chose normal segments. In round 3, both systems analyzed the same pres
elected normal segments and frames. The intersystem correlations betwe
en visual and automatic systems for rounds 1, 2, and 3 were: normal di
ameter, r = 0.25, r = 0.37, and r = 0.75, respectively; minimal lumen
diameter, r = 0.79, r = 0.86, and r = 0.85, respectively; and diameter
stenosis, r = 0.65, r = 0.73, and r = 0.87, respectively. The manual
edge-detection and automated edge-detection systems used in this study
are reasonably accurate and consistent on phantom studies. In patient
studies, the nonautomated processes (choice of frame and normal segme
nt for analysis) produced significant differences in the QCA results,
thus illustrating that operator-dependent factors other than edge dete
ction are very important in QCA.