Fast Von Mises strain imaging on ultrasound carotid vessel wall by flow driven diffusion method.

Abstract

The elasticity of the vessel wall is important for the clinical identification of rupture-risks. The Von Mises strain can be a potential index for the indication of carotid vessel pathologies. In this paper, a fast clinically applicable real-time algorithm from time-sequence of B-mode carotid images is developed. Due to the compression induced by the normal cardiac pulsation, tissue motion occurs radially and non-rigidly. To obtain an accurate motion field, we developed a variational functional integrating the optical flow equation and an anisotropic regularizer, and designed a diffusion tensor to encourage coherence diffusion. The motion field is smoothed along the desired motion flow orientation. A fast, additive operator splitting scheme, which is ten times faster than the conventional discrete method, is used for the numerical implementation. To demonstrate the efficiency of the proposed approach, finite element models are set up for normal and pathological carotid vessel walls. The results indicate that the proposed diffusion approach obtains an accurate smooth and continuous motion field and greatly improves the follow up strain estimation using a fast differential strain filter. Furthermore, our approach using the Von Mises strain imaging on clinical ultrasound images of the carotid artery is validated. Participants above 65-years in age suffering from different stages of atherosclerosis in their carotid artery are selected. The results are evaluated by an experienced physician. The evaluation results demonstrate that the Von Mises strain has a good correspondence to the presence of certain suspicious areas in the B-mode images. The proposed method is therefore clinically applicable for the real-time Von Mises strain imaging of carotid vessel walls, and can be of great value as a complementary method to B-mode image for the clinical identification of the risk of plaque vulnerability.