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BACKGROUND AND PURPOSE: Some recent studies of noninvasive carotid imaging have identified high rates of inappropriate decision-making about endarterectomy compared with conventional arterial angiography (CAA), but there is substantial inconsistency across the published literature. CAA is usually regarded as the gold standard for carotid imaging, partly because the degree of angiographic stenosis is a powerful predictor of ischemic stroke and hence of benefit from endarterectomy. However, there are very few published data on the extent to which predictive power varies with type of CAA or the number and quality of views of the stenosis obtained. METHODS: We analyzed measurements of stenosis made by 2 independent observers on 967 consecutive patients randomized to medial treatment alone in the European Carotid Surgery Trial (ECST). We determined prediction of 3-year risk of ipsilateral ischemic stroke (as a hazard ratio from a Cox model and as the area under a receiver operating characteristic curve [AUC]) in relation to the technique of angiography, the number and quality of views of the stenosis, and the use of 2 independent measurements. RESULTS: Using 2 independent measurements of stenosis increased predictive power slightly, but the effect was much smaller than that attributable to the type of CAA and the number of views of the stenosis. Prognostic value was greater in patients who had selective carotid injection CAA and at least biplane views (AUC, 0.75; 0.68 to 0.82) than in patients with only a single view or aortic arch injection CAA (AUC, 0.65; 0.56 to 0.73; P=0.03). CONCLUSIONS: The dependence of the prognostic value of CAA on the type of angiography and the number of views of the stenosis obtained has implications for the future development and validation of noninvasive methods of carotid imaging.

Original publication




Journal article



Publication Date





1785 - 1791


Aged, Area Under Curve, Brain Ischemia, Carotid Stenosis, Cerebral Angiography, Endarterectomy, Carotid, Female, Follow-Up Studies, Humans, Male, Middle Aged, Observer Variation, Predictive Value of Tests, Prognosis, Proportional Hazards Models, ROC Curve, Randomized Controlled Trials as Topic, Risk Factors, Single-Blind Method