Sonographic NASCET index: a new doppler parameter for assessment of internal carotid artery stenosis.
OBJECTIVE
Established Doppler parameters for carotid stenosis assessment do not reflect North American Symptomatic Carotid Endarterectomy Trial (NASCET)-style methodology. We derived a Doppler parameter, termed sonographic NASCET index (SNI), and hypothesized that the SNI would provide greater angiographic correlation and better accuracy in predicting stenosis of 70% or greater than that of currently used peak systolic velocity (PSV) measurements.


METHODS
Inclusion criteria of angiographically proved carotid stenoses of 40-95% and measured proximal and distal internal carotid artery Doppler PSV values were established. Occlusions and near occlusions were specifically excluded. Doppler and angiographic data meeting the inclusion criteria from 32 carotid bifurcations were identified; actual angiographic stenoses ranged 40-89%. SNI values were calculated for each vessel. PSV and SNI were correlated with angiography by using linear regression analysis. Accuracies of SNI and PSV in predicting stenosis of 70% or greater were compared at two thresholds.


RESULTS
Correlation between SNI and angiography was superior to that between PSV and angiography (r2=0.64 vs 0.38). PSV and SNI values that corresponded to 70% angiographic stenosis were 345 cm/s and 45.5, respectively. Accuracy of PSV of 345 cm/s or greater in predicting stenosis of 70% or greater was 78%, compared with 88% for SNI of 45.5 or greater. The SNI value that corresponded to a PSV threshold of 250 cm/s was 33. Accuracy of PSV of 250 cm/s or greater in predicting stenosis of 70% or greater was 81%, compared with 88% for SNI of 33 or greater.


CONCLUSIONS
Correlation between SNI and angiography was greater than that between PSV and angiography. Accuracy of SNI in predicting stenosis of 70% or greater was also superior to that of PSV at two thresholds. These results suggest that SNI may be a better predictor of high-grade carotid stenosis than is PSV.
Hathout
Gasser M
GM
Department of Radiology, University of California at Los Angeles 90073, USA.
Fink
James R
JR
El-Saden
Suzie M
SM
Grant
Edward G
EG
D015901:Angiography, Digital Subtraction; D001783:Blood Flow Velocity / Q000502:physiology; D002343:Carotid Artery, Internal / Q000000981:diagnostic imaging* / Q000601:surgery; D016893:Carotid Stenosis / Q000000981:diagnostic imaging* / Q000601:surgery; D002533:Cerebral Angiography; D004691:Endarterectomy; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012044:Regression Analysis; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D018615:Ultrasonography, Doppler, Color / Q000379:methods*; D017585:Ultrasonography, Doppler, Transcranial / Q000379:methods*