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AJNR - American Journal of Neuroradiology

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American Journal of Neuroradiology 24:1747-1756, October 2003
© 2003 American Society of Neuroradiology

HEAD AND NECK

Accuracy of Contrast-Enhanced MR Angiography in Predicting Angiographic Stenosis of the Internal Carotid Artery: Linear Regression Analysis

Gasser M Hathout^a,b, Michael J. Duh^b and Suzie M. El-Saden^a,b

^a Departments of Radiology, West Los Angeles Veterans Administration Hospital, Los Angeles, CA
^b University of California, Los Angeles Medical Center, Los Angeles, CA

Address reprint requests to G.M. Hathout, MD, Associate Professor, University of California, Los Angeles, Staff Neuroradiologist, Department of Radiology, West Los Angeles Veterans Administration Hospital, 11301 Wilshire Boulevard, Los Angeles, CA 90073

BACKGROUND AND PURPOSE: We sought to assess whether contrast-enhanced MR angiography is able to predict the degree of angiographic stenosis of the internal carotid artery within a clinically acceptable margin of error, thereby decreasing the need for angiography. In addition, we sought to assess whether adding ultrasound peak systolic velocity (PSV) as an additional regressor improves the accuracy of prediction.

METHODS: A retrospective review of our institution’s records for a 4-year period was conducted to identify all patients who had undergone evaluation of their carotid arteries using digital subtraction angiography, contrast-enhanced MR angiography, and ultrasonography. All internal carotid artery stenoses ranging from 10% to 90% at carotid angiography were selected (n = 22). Measurements were then obtained based on the North American Symptomatic Carotid Endarterectomy Trial style by using the digital subtraction angiograms and contrast-enhanced MR angiograms in a blinded fashion. The correlation between digital subtraction angiography data and contrast-enhanced MR angiography data was assessed by conducting linear regression analysis. Multiple regression analysis was then conducted to determine whether the inclusion of ultrasound PSV as an additional regressor increased the accuracy of prediction.

RESULTS: The correlation between the degree of stenosis measured by digital subtraction angiography and that measured by contrast-enhanced MR angiography was r = 0.967. The 95% confidence interval for the line of means showed low errors bounds, ranging as low as ±2.8%. The 95% confidence interval for individual prediction of angiographic stenosis based on a given contrast-enhanced MR angiographic measurement, however, was significantly larger, being no less than ±13.6%. With the inclusion of PSV, the adjusted correlation was r = 0.965.

CONCLUSION: A clear linear relationship exists between digital subtraction angiographic and contrast-enhanced MR angiographic measurements of carotid stenosis. Increasing severity of stenosis as measured by contrast-enhanced MR angiography corresponds to increasing severity at angiography. Although the predictive value of contrast-enhanced MR angiography is excellent in the mean, it is less reliable for predicting the degree of angiographic stenosis in the individual patient, showing rather wide confidence intervals. Furthermore, the inclusion of PSV as an additional regressor does not improve the predictive accuracy beyond that of contrast-enhanced MR angiography alone.

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