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Shear Stress

Abstract

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Low shear stress induces vascular eNOS uncoupling via autophagy-mediated eNOS phosphorylation Role of local coronary blood flow patterns and shear stress on the development of microvascular and epicardial endothelial dysfunction and coronary plaque Comparison Of High Shear Stress-Induced Thrombotic And Thrombolytic Effect Between Aspirin, Clopidogrel And Very Low Dose Rivaroxaban And Aspirin, Ticagrelor Treatments In Patients With Acute Coronary Syndrome Evolving insights into the role of local shear stress in late stent failure from neoatherosclerosis formation and plaque destabilization Low shear stress induces endothelial reactive oxygen species via the AT1R/eNOS/NO pathway Role of Low Endothelial Shear Stress and Plaque Characteristics in the Prediction of Nonculprit Major Adverse Cardiac Events: The PROSPECT Study Transcatheter Aortic Valve Implantation Represents an Anti-Inflammatory Therapy Via Reduction of Shear Stress-Induced, Piezo-1-Mediated Monocyte Activation Implications of the local hemodynamic forces on the formation and destabilization of neoatherosclerotic lesions
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Review Article2018 May 21;20(7):33.

JOURNAL：Curr Atheroscler Rep. Article Link

A Survey on Coronary Atherosclerotic Plaque Tissue Characterization in Intravascular Optical Coherence Tomography

Boi A, Jamthikar AD, Suri JS et al. Keywords: Atherosclerosis; Cardiovascular disease; Coronary; Machine learning and deep learning; Optical coherence tomography; Plaque characterization; Risk stratification

ABSTRACT

PURPOSE OF REVIEW - Atherosclerotic plaque deposition within the coronary vessel wall leads to arterial stenosis and severe catastrophic events over time. Identification of these atherosclerotic plaque components is essential to pre-estimate the risk of cardiovascular disease (CVD) and stratify them as a high or low risk. The characterization and quantification of coronary plaque components are not only vital but also a challenging task which can be possible using high-resolution imaging techniques.


RECENT FINDING - Atherosclerotic plaque components such as thin cap fibroatheroma (TCFA), fibrous cap, macrophage infiltration, large necrotic core, and thrombus are the microstructural plaque components that can be detected with only high-resolution imaging modalities such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Light-based OCT provides better visualization of plaque tissue layers of coronary vessel walls as compared to IVUS. Three dominant paradigms have been identified to characterize atherosclerotic plaque components based on optical attenuation coefficients, machine learning algorithms, and deep learning techniques. This review (condensation of 126 papers after downloading 150 articles) presents a detailed comparison among various methodologies utilized for plaque tissue characterization, classification, and arterial measurements in OCT. Furthermore, this review presents the different ways to predict and stratify the risk associated with the CVD based on plaque characterization and measurements in OCT. Moreover, this review discovers three different paradigms for plaque characterization and their pros and cons. Among all of the techniques, a combination of machine learning and deep learning techniques is a best possible solution that provides improved OCT-based risk stratification.
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