A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine
Aditya M Sharma1, Ajay Gupta, P Krishna Kumar
1Division of Cardiovascular Medicine, Department of Medicine, University of Virginia, Charlottesville, VA, USA.
Insights
This review explores ultrasonic tissue characterization for analyzing carotid plaque, aiding stroke risk stratification. Advanced methods and multimodality imaging are crucial for improving cardiovascular disease risk assessment.
Area of Science:
- Vascular Ultrasound
- Medical Imaging
- Cardiovascular Disease Research
Background:
- Cardiovascular diseases, including stroke and heart attack, are leading global causes of death.
- Understanding arterial plaque buildup, fibrous cap rupture, and vasa vasorum abnormalities is limited.
- Ultrasonic characterization of carotid plaque shows clinical utility in stroke risk classification.
Purpose of the Study:
- To provide a comprehensive review of ultrasonic vascular morphology tissue characterization for plaque analysis.
- To present fundamental and advanced ultrasonic tissue characterization and feature extraction methods.
- To demonstrate risk stratification using machine learning paradigms for cardiovascular diseases.
Main Methods:
- Review of state-of-the-art ultrasonic tissue characterization techniques.
- Analysis of plaque morphology and echogenicity using ultrasound.
- Application of machine learning for risk stratification based on ultrasonic features.
Main Results:
- Ultrasonic echogenicity and morphological characterization of carotid plaque can classify stroke risks.
- Characterization supports decisions for intensive medical therapy and procedures like endarterectomy and stenting.
- Machine learning paradigms are utilized for risk stratification using plaque analysis.
Conclusions:
- Ultrasonic vascular morphology tissue characterization is a valuable tool for analyzing carotid plaque.
- Further development of advanced segmentation methods and multimodality imaging is needed for improved stroke and cardiovascular risk stratification.
Abstract:
Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in today's world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and stenting. This is the first state-of-the-art review to provide a comprehensive understanding of the field of ultrasonic vascular morphology tissue characterization. This paper presents fundamental and advanced ultrasonic tissue characterization and feature extraction methods for analyzing plaque. Additionally, the paper shows how the risk stratification is achieved using machine learning paradigms. More advanced methods need to be developed which can segment the carotid artery walls into multiple regions such as the bulb region and areas both proximal and distal to the bulb. Furthermore, multimodality imaging is needed for validation of such advanced methods for stroke and cardiovascular risk stratification.
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