Dynamic Block Matching to assess the longitudinal component of the dense motion field of the carotid artery wall in B-mode ultrasound sequences -- Association with coronary artery disease

TL;DR

This paper introduces a novel dense motion tracking method for carotid artery walls in ultrasound sequences, capturing comprehensive longitudinal motion data and revealing its association with coronary artery disease.

Contribution

The study presents the first method specifically designed to assess the dense motion field of the carotid artery wall in ultrasound images.

Findings

Dense displacement field accurately estimated with ~150 μm error.

Significant correlation between wall motion inhomogeneity and coronary artery disease.

Method demonstrates potential for improved arterial motion analysis.

Abstract

Purpose: The motion of the common carotid artery tissue layers along the vessel axis during the cardiac cycle, observed in ultrasound imaging, is associated with the presence of established cardiovascular risk factors. However, the vast majority of the methods are based on the tracking of a single point, thus failing to capture the overall motion of the entire arterial wall. The aim of this work is to introduce a motion tracking framework able to simultaneously extract the trajectory of a large collection of points spanning the entire exploitable width of the image. Method: The longitudinal motion, which is the main focus of the present work, is determined in two steps. First, a series of independent block matching operations are carried out for all the tracked points. Then, an original dynamic-programming approach is exploited to regularize the collection of similarity maps and estimate the globally optimal motion over the entire vessel wall. Sixty-two atherosclerotic participants at high cardiovascular risk were involved in this study. Results: A dense displacement field, describing the longitudinal motion of the carotid far wall over time, was extracted. For each cine-loop, the method was evaluated against manual reference tracings performed on three local points, with an average absolute error of 150+/-163 um. A strong correlation was found between motion inhomogeneity and the presence of coronary artery disease (beta-coefficient=0.586, p=0.003). Conclusions: To the best of our knowledge, this is the first time that a method is specifically proposed to assess the dense motion field of the carotid far wall. This approach has potential to evaluate the (in)homogeneity of the wall dynamics. The proposed method has promising performances to improve the analysis of arterial longitudinal motion and the understanding of the underlying patho-physiological parameters.