Ultrasound-Based Image Analysis for Predicting Carotid Artery Stenosis Risk - A Comprehensive Review of the Problem, Techniques, Datasets, and Future Directions

Aug 2, 2026

The carotid artery is a major blood vessel supplying the brain, and plaque buildup can drive severe cardiovascular outcomes including atherosclerosis and stroke. Ultrasound imaging serves as a primary non-invasive diagnostic route, enabling computer-assisted interpretation. This review synthesizes existing ultrasound image analysis methods for plaque detection and characterization in the carotid artery, focusing on dataset analyses, segmentation of plaque area, lumen area, and intima–media thickness (IMT), and plaque measurement, characterization, classification, and stenosis grading using deep learning and machine learning. It also summarizes performance, key challenges, and future research directions.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages33

Reading Time1 h 23 min

AccessFree to download

Introduction

Cardiovascular disease burden and need for early detection

Carotid artery stenosis: clinical significance and imaging modalities

Ultrasound imaging as a diagnostic foundation

diagnostics Review Ultrasound-Based Image Analysis for Predicting Carotid Artery Stenosis Risk: A Comprehensive Review of the Problem, Techniques, Datasets, and Future Directions Najmath Ottakath 1, *, Somaya Al-Maadeed 1, Susu M. Zughaier 2, Omar Elharrouss 1, Hanadi Hassen Mohammed 1, Muhammad E. H. Chowdhury 3 and Ahmed Bouridane 4 Citation: Ottakath, N.; Al-Maadeed, S.; Zughaier, S.M.; Elharrouss, O.; Mohammed, H.H.; Chowdhury, M.E.H.; Bouridane, A. UltrasoundBased Image Analysis for Predicting Carotid Artery Stenosis Risk: A Comprehensive Review of the Problem, Techniques, Datasets, and Future Directions. Diagnostics 2023, 13, 2614. [https://doi.org/](https://doi.org/)[ ](https://doi.org/)[10.3390/diagnostics13152614](10.3390/diagnostics13152614) Academic Editors: Jaafar M. Alghazo and Ghazanfar Latif Received: 15 June 2023 Revised: 25 July 2023 Accepted: 25 July 2023 Published: 7 August 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . 1 Department of Computer Science and Engineering, Qatar University, Doha 2713, Qatar; [s_alali@qu.edu.qa](s_alali@qu.edu.qa) (S.A.-M.); [elharrouss.omar@gmail.com](elharrouss.omar@gmail.com) (O.E.); [hm1409611@qu.edu.qa](hm1409611@qu.edu.qa) (H.H.M.) 2 College of Medicine, Qatar University, Doha 2713, Qatar; [szughaier@qu.edu.qa](szughaier@qu.edu.qa) 3 Department of Electrical and Electronics Engineering, Qatar University, Doha 2713, Qatar; [mchowdhury@qu.edu.qa](mchowdhury@qu.edu.qa) 4 Centre for Data Analytics and Cybersecurity, University of Sharjah, Sharjah 27272, United Arab Emirates; [abouridane@sharjah.ac.ae](abouridane@sharjah.ac.ae) * [Correspondence: no1912348@qu.edu.qa](Correspondence: no1912348@qu.edu.qa) Abstract: The carotid artery is a major blood vessel that supplies blood to the brain. Plaque buildup in the arteries can lead to cardiovascular diseases such as atherosclerosis, stroke, ruptured arteries, and even death. Both invasive and non-invasive methods are used to detect plaque buildup in the arteries, with ultrasound imaging being the ﬁrst line of diagnosis. This paper presents a comprehensive review of the existing literature on ultrasound image analysis methods for detecting and characterizing plaque buildup in the carotid artery. The review includes an in-depth analysis of datasets; image segmentation techniques for the carotid artery plaque area, lumen area, and intima–media thickness (IMT); and plaque measurement, characterization, classiﬁcation, and stenosis grading using deep learning and machine learning. Additionally, the paper provides an overview of the performance of these methods, including challenges in analysis, and future directions for research. Keywords: carotid artery stenosis risk; US; computer vision; deep learning; machine learning; segmentation; classiﬁcation; plaque characterization 1. Introduction The cardiovascular system is the major life-supporting system in the human body. Diseases of the cardiovascular system have emerged among the leading causes of death worldwide. According to WHO (World Health Organization) ([https://www.who.int/news-room/fact](https://www.who.int/news-room/fact)sheets/detail/cardiovascular-disease (accessed on 2 January 2022)) 2000–2019 statistics, an estimate of 17.9 million people died from cardiovascular diseases (CVDs), of which 38% were due to heart attack and stroke. The cause of this mostly lies in risky behaviors, such as alcohol and tobacco intake, poor diet, and physical inactivity. Early detection and management of the diseases can increase the life span and reduce the mortality rate due to CVDs. The vast cardiovascular system consists of blood vessels transp

FAQs

Why is ultrasound imaging important for carotid artery stenosis risk assessment?

Ultrasound imaging is presented as the first-line non-invasive diagnostic approach. It enables analysis of carotid plaque patterns that relate to stenosis risk.

Which ultrasound image analysis tasks are covered in the review?

The review covers dataset analysis, segmentation of plaque area, lumen area, and IMT, and plaque measurement, characterization, classification, and stenosis grading.

How do deep learning and machine learning contribute to stenosis grading?

The paper summarizes methods that use deep learning and machine learning to perform plaque characterization and classification, culminating in stenosis grading and related performance evaluation.

Aug 2, 2026

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