BACKGROUND AND PURPOSE: Various Doppler criteria have been used to predict hemodynamically significant carotid stenosis. This study was performed to elucidate whether hemodynamically significant stenosis can be predicted indirectly by the blood flow velocity in the common carotid artery (CCA) measured with duplex ultrasonography in patients with unilateral stenosis of internal carotid artery (ICA). METHODS: Eighty-five patients who were scheduled to undergo carotid endarterectomy for unilateral stenosis of ICA origin were analyzed. The flow velocities and their side-to-side ratios in the CCA were calculated. The flow velocities in the CCA were measured with conventional ultrasonography and poststenotic blood flow with transoral carotid ultrasonography. Cerebral angiography was performed to evaluate the intracranial collateral flow. RESULTS: Among the absolute values and side-to-side ratios of Doppler flow velocities in the CCA, the end diastolic flow velocity (EDV) ratio in the CCA best correlated with the residual lumen area (r = 0.35; P = .0009), stenosis of diameter (r = 0.48; P < .0001), and poststenotic flow (r = 0.60; P < .0001). EDV ratios in the CCA were significantly lower in patients with collateral pathways (anterior communicating artery, P = .0005; posterior communicating artery, P = .004; ophthalmic artery, P < .0001; leptomeningeal collateral, P = .004). The optimal threshold value of the EDV ratio in the CCA for the presence of intracranial collateral flow and stenosis of diameter ≥70% was 1.2. Those for tight stenosis in a cross-sectional area >95%, the reduction of poststenotic flow, and poststenotic narrowing were 1.4, 1.5, and 1.6, respectively. CONCLUSION: The EDV ratio in the CCA appears to be an additional parameter for predicting hemodynamically significant stenosis in patients with unilateral ICA stenosis.
|Number of pages||6|
|Journal||American Journal of Neuroradiology|
|Publication status||Published - 2005|
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
- Clinical Neurology