The proposed adaptive kernel size selection method improves the accuracy of wall shear stress estimation in the common carotid artery using ultrasound blood flow imaging.
Adaptive kernel sizing may lower bias in simulated WSS estimates; leaves open in vivo validation before clinical use.
In this paper, we propose a method for adaptive selection of the kernel size used in estimation of the wall shear stress (WSS) based on flow velocity profiles obtained by the blood flow imaging method based on enhancement of RF echo signals from blood cells using a singular value decomposition based clutter filter. Two simulation phantom experiments with the Field II program were performed to validate the proposed method. In the simulation experiments, the average bias error (BE) between the WSSs estimated by the conventional method and theoretical one was 16.5%. The proposed method could reduce the average BE to 12.3%. Also, the proposed method was applied to RF echo signals from a common carotid artery (CCA) of a healthy male subject. The WSSs in the CCA were estimated during one cardiac cycle and in a range similar to that in previous reports.
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Nagaoka et al. (2020) studied this question.
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