A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework

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.

COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification: A review

“…A disadvantage, however, is their inability to provide a “risk assessment.” The application of artificial intelligence (AI) can enhance the information provided by these imaging modalities, resulting in a more accurate characterization of the tissue and the disease process [ [45] , [46] , [47] , [48] , [49] , [50] , [51] ]. The combination of AI and medical imaging has been shown to improve diagnosis and risk stratification, speed up patient evaluation, enhance disease monitoring, and accelerate early intervention [ 40 , 48 , [52] , [53] , [54] , [55] , [56] , [57] ]. Thus, this review will focus on the use of AI-based tissue characterization of images of comorbid patients affected by COVID-19.…”

Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: A web-based point-of-care tool for multicenter clinical trial

“…Current systems are not fully automated 30 and lack advanced image-based features for risk assessment. 31,32 Often, these systems lack reliability, accuracy, reproducibility, and provide no comparative reference marker needed for monitoring. Furthermore, there is no standardization towards clinical trials.…”

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“…Recently, ultrasonic tissue characterization of carotid plaque has been also used in improving the prediction of coronary artery disease (CAD) events [28]. Furthermore several studies have shown that the presence of carotid plaque is better than that of carotid IMT for predicting future cardiovascular events [20,29,30].…”