An end-to-end framework for intima media measurement and atherosclerotic plaque detection in the carotid artery.

Background And Objectives: The detection and delineation of atherosclerotic plaque are usually manually performed by medical experts on the carotid artery. Evidence suggests that this manual process is subject to errors and has a large variability between experts, equipment, and datasets. This paper proposes a robust end-to-end framework for automatic atherosclerotic plaque detection.

Polyvascular Subclinical Atherosclerosis: Correlation Between Ankle Brachial Index and Carotid Atherosclerosis in a Population-Based Sample.

We assessed the correlation between the biomarkers of lower limb atherosclerosis (eg, ankle-brachial index [ABI]) and of carotid atherosclerosis (eg, common carotid intima-media thickness (IMT) and presence of atherosclerotic plaque) in a population-based cohort from Girona (Northwest Spain) recruited in 2010. Ankle-brachial index and carotid ultrasound were performed in all participants. Generalized additive multivariable models were used to adjust a regression model of common carotid IMT on ABI.

Do individuals with autoimmune disease have increased risk of subclinical carotid atherosclerosis and stiffness?

To explore the role of chronic inflammation inherent to autoimmune diseases in the development of subclinical atherosclerosis and arterial stiffness, this study recruited two population-based samples of individuals with and without autoimmune disease (ratio 1:5) matched by age, sex, and education level and with a longstanding (≥6 years) diagnosis of autoimmune disease. Common carotid intima-media thickness (IMT) and arterial distensibility and compliance were assessed with carotid ultrasound. Multivariable linear and logistic regression models were adjusted for 10-year cardiovascular risk.

Semantic segmentation with DenseNets for carotid artery ultrasound plaque segmentation and CIMT estimation.

Background And Objective: The measurement of carotid intima media thickness (CIMT) in ultrasound images can be used to detect the presence of atherosclerotic plaques. Usually, the CIMT estimation strategy is semi-automatic, since it requires: (1) a manual examination of the ultrasound image for the localization of a region of interest (ROI), a fast and useful operation when only a small number of images need to be measured; and (2) an automatic delineation of the CIM region within the ROI. The existing efforts for automating the process have replicated the same two-step structure, resulting in two consecutive independent approaches.

A Convolutional Neural Network for Automatic Characterization of Plaque Composition in Carotid Ultrasound.

Characterization of carotid plaque composition, more specifically the amount of lipid core, fibrous tissue, and calcified tissue, is an important task for the identification of plaques that are prone to rupture, and thus for early risk estimation of cardiovascular and cerebrovascular events. Due to its low costs and wide availability, carotid ultrasound has the potential to become the modality of choice for plaque characterization in clinical practice. However, its significant image noise, coupled with the small size of the plaques and their complex appearance, makes it difficult for automated techniques to discriminate between the different plaque constituents.