M-mode state based identification in ultrasound videos of the atherosclerotic carotid plaque

Abstract

Monitoring the wall and plaque changes in the carotid artery (CA) can provide useful information for the assessment of the atherosclerotic disease. Using a motion mode (M-mode) image, detailed information may be obtained about wall and lumen dimensions, systolic and diastolic artery diameter and distension, wall and plaque motion and thickness, and also their corresponding states (timings). The wall thickness and the diameter of the CA change during the cardiac cycle are an indicator of regional contraction and therefore an indication of a disease. The objective of this work was to investigate how M-mode state based modeling of the CA can be derived from a B-mode ultrasound video. Briefly, 10 longitudinal CA ultrasound videos acquired from symptomatic subjects at risk of atherosclerosis were broken into frames and their M-mode images were generated. These were then despeckled and the atherosclerotic carotid plaque was segmented from each video, in order to extract the states of the video. By identifying the states of the CA, we can distinguish between normal and abnormal plaque motion. It was shown in this work, that M-mode state based modeling derived from B-mode videos can be used successfully to derive the carotid states and assess the corresponding wall changes. However, further work in a larger number of videos is needed for validating the proposed method and to differentiate between normal and abnormal state based plaque motion analysis.