Robust Estimation of Carotid Artery Wall Motion Using the Elasticity-based State-space Approach

Publication date: Available online 10 January 2017
Source:Medical Image Analysis
Author(s): Zhifan Gao, Huahua Xiong, Xin Liu, Heye Zhang, Dhanjoo Ghista, Wanqing Wu, Shuo Li
The dynamics of the carotid artery wall has been recognized as a valuable indicator to evaluate the status of atherosclerotic disease in the preclinical stage. However, it is still a challenge to accurately measure this dynamics from ultrasound images. This paper aims at developing an elasticity-based state-space approach for accurately measuring the two-dimensional motion of the carotid artery wall from the ultrasound imaging sequences. In our approach, we have employed a linear elasticity model of the carotid artery wall, and converted it into the state space equation. Then, the two-dimensional motion of carotid artery wall is computed by solving this state-space approach using the H∞ filter and the block matching method. In addition, a parameter training strategy is proposed in this study for dealing with the parameter initialization problem. In our experiment, we have also developed an evaluation function to measure the tracking accuracy of the motion of the carotid artery wall by considering the influence of the sizes of the two blocks (acquired by our approach and the manual tracing) containing the same carotid wall tissue and their overlapping degree. Then, we have compared the performance of our approach with the manual traced results drawn by three medical physicians on 37 healthy subjects and 103 unhealthy subjects. The results have showed that our approach was highly correlated (Pearson's correlation coefficient equals 0.9897 for the radial motion and 0.9536 for the longitudinal motion), and agreed well (width the 95% confidence interval is 89.62 μm for the radial motion and 387.26 μm for the longitudinal motion) with the manual tracing method. We also compared our approach to the three kinds of previous methods, including conventional block matching methods, Kalman-based block matching methods and the optical flow. Altogether, we have been able to successfully demonstrate the efficacy of our elasticity-model based state-space approach (EBS) for more accurate tracking of the 2-dimensional motion of the carotid artery wall, towards more effective assessment of the status of atherosclerotic disease in the preclinical stage.

Graphical abstract

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