Author:
White Jeremy H.,Bartlett Eric S.,Bharatha Aditya,Aviv Richard I.,Fox Allan J.,Thompson Andrew L.,Bitar Richard,Symons Sean P.
Abstract
Purpose:To compare the reproducibility of semi-automated vessel analysis software to manual measurement of carotid artery stenosis on computed tomography angiography (CTA).Methods:Two observers separately analyzed 81 carotid artery CTAs using semi-automated vessel analysis software according to a blinded protocol. The software measured the narrowest stenosis in millimeters (mm), distal internal carotid artery (ICA) in mm, and calculated percent stenosis based on NASCET criteria. One observer performed this task twice on each carotid, the second analysis delayed two months in order to mitigate recall bias. Two other observers manually measured the narrowest stenosis in mm, distal ICA in mm, and calculated NASCET percent stenosis in a blinded fashion. Correlation coefficients were calculated for each group comparing the narrowest stenosis in mm, distal ICA in mm, and NASCET percent stenosis.Results:The semi-automated vessel analysis software provided excellent intraobserver correlation for narrowest stenosis in mm, distal ICA in mm, and NACSET percent stenosis (Pearson correlation coefficients of 0.985, 0.954, and 0.977 respectively). The semi-automated vessel analysis software provided excellent interobserver correlation (0.925, 0.881, and 0.892 respectively). The interobserver correlation for manual measurement was good (0.595, 0.625, and 0.555 respectively). There was a statistically significant difference in the interobserver correlation between the semi-automated vessel analysis software observers and the manual measurement observers (P < 0.001).Conclusion:Semi-automated vessel analysis software is a highly reproducible method of quantifying carotid artery stenosis on CTA. In this study, semi-automated vessel analysis software determination of carotid stenosis was shown to be more reproducible than manual measurement.
Publisher
Cambridge University Press (CUP)
Subject
Clinical Neurology,Neurology,General Medicine
Cited by
14 articles.
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