Detection of Carotid Artery Stenosis Based on Video Motion Analysis for Fast Screening

Abstract

Background Carotid artery stenosis (CAS) is a common cause of ischemic stroke, and the early detection of CAS may improve patient outcomes. Carotid Doppler ultrasound is commonly used to diagnose CAS. However, it is costly and may not be practical for regular screening practice. This article presents a novel noninvasive and noncontact detection technique using video‐based motion analysis (VMA) to extract useful information from subtle pulses on the skin surface to screen for CAS. Methods and Results We prospectively enrolled 202 patients with prior carotid Doppler ultrasound data. A short 30‐second video clip of the neck was taken using a commercial mobile device and analyzed by VMA with mathematical quantification of the amplitude of skin motion changes in a blinded manner. The first 40 subjects were used to set up the VMA protocol and define cutoff values, and the following 162 subjects were used for validation. Overall, 54% of the 202 subjects had ultrasound‐confirmed CAS. Using receiver operating characteristic curve analysis, the area under the curve of VMA‐derived discrepancy values to differentiate patients with and without CAS was excellent (area under the curve, 0.914 [95% CI, 0.874–0.954]; P <0.01). The best cutoff value of VMA‐derived discrepancy values to screen for CAS was 5.1, with a sensitivity of 87% and a specificity of 87%. The diagnostic accuracy was consistently high in different subject subgroups. Conclusions A simple and accurate screening technique to quickly screen for CAS using a VMA system is feasible, with acceptable sensitivity and specificity.