Classification of carotid stenosis by millimeter CT angiography measures: effects of prevalence and gender.
OBJECTIVE
Previous studies quantifying moderate and severe carotid stenosis by direct millimeter measures on CT angiography (CTA) did not consider how prevalence and gender may influence classification cutoff values.


METHODS
Three hundred nineteen carotid arteries were evaluated in consecutive patients with known or suspected carotid artery disease. Millimeter measures were obtained of the stenotic carotid bulb lumen and distal internal carotid artery (ICA). Interclass correlation coefficients (ICC) defined interobserver and intraobserver agreement. North American Symptomatic Carotid Endarterectomy Trial (NASCET)-style percent stenosis ratios were calculated per carotid artery and used in linear regression and receiver operating characteristic (ROC) curve analysis to define equivalent millimeter quantification and classification values. Likelihood ratios and prevalence-specific positive/negative predictive values (PPV/NPV) were calculated to determine the most appropriate millimeter cutoff values to classify stenosis.


RESULTS
Interobserver agreement was excellent for stenosis measures (0.90) and good for distal ICA measures (0.79). Gender-specific regression curves and ROC curves indicated that millimeter stenosis is an excellent tool to quantify and classify carotid stenosis. Assuming a 10% prevalence of severe stenosis, we found that the cutoff value maximizing NPV and PPV was 1.1 mm for both genders (female: PPV = 86.2, NPV = 97.7; male: PPV = 83.2, NPV = 95.9). Assuming a 40% prevalence of moderate stenosis, we found that the cutoff values differed between genders: female = 2.0 mm (PPV = 91.3, NPV = 91.5), male = 2.1 mm (PPV = 91.6, NPV = 92.4). Specific millimeter cutoffs will vary depending upon the clinical scenario, prevalence, and gender.


CONCLUSIONS
Direct millimeter stenosis measures are an excellent tool to classify moderate and severe carotid artery stenosis. Millimeter classification cutoff values that best approximate NASCET classifications vary depending on prevalence and gender.
Bartlett
E S
ES
University of Toronto, Princess Margaret Hospital, Toronto, Ontario, Canada. eric.bartlett@uhn.on.ca
Walters
T D
TD
Symons
S P
SP
Aviv
R I
RI
Fox
A J
AJ
D000792:Angiography / Q000379:methods*; D002343:Carotid Artery, Internal / Q000000981:diagnostic imaging; D016893:Carotid Stenosis / Q000145:classification* / Q000000981:diagnostic imaging* / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D015588:Observer Variation; D012372:ROC Curve; D012044:Regression Analysis; D015203:Reproducibility of Results; D012737:Sex Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*