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  • Open Access


    An In Vitro Study of Correlation Between the Compositions, Structure and Mechanical Properties of the Arterial Plaque

    Mohamed Abdulsalam1, Jiling Feng1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09884

    Abstract Atherosclerosis developed in the arterial wall is the major cause of cardiovascular events such as stroke and heart failure. Atherosclerosis, also referred to as arterial plaque can be classified as stable, unstable, and vulnerable plaque. In terms of the features of compositions and structures, atherosclerosis also can be classified as calcified plaque, the plaque with a lipid core, and plaque with a thin fibrous cap. It is expected that the compositions, structures, and mechanical properties of the plaques interrelate with each other. The correlations between the compositions, structure, and mechanical properties are expected to characterize the nature of the rupture… More >

  • Open Access


    Computer Aided Coronary Atherosclerosis Plaque Detection and Classification

    S. Deivanayagi1,*, P. S. Periasamy2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 639-653, 2022, DOI:10.32604/iasc.2022.025632

    Abstract Coronary artery disease (CAD) remains a major reason for increased mortality over the globe, comprising myocardial infarction and ischemic cardiomyopathy. The CAD is highly linked to coronary stenosis owing to the encumbrance of atherosclerotic plaques. Particularly, diversified atherosclerotic plaques are highly responsible for major cardiac adverse events over the calcified and non-calcified plaques. There, the recognition and classification of atherosclerotic plaques play a vital role to prevent and intervene in CAD. The process of detecting various class labels of the atherosclerotic plaques is significant to identify the disease at the earlier stages. Since several automated coronary plaque recognition models are… More >

  • Open Access


    Machine Learning Model Comparison for Automatic Segmentation of Intracoronary Optical Coherence Tomography and Plaque Cap Thickness Quantification

    Caining Zhang1, Xiaopeng Guo2, Xiaoya Guo3, David Molony4, Huaguang Li2, Habib Samady4, Don P. Giddens4,5, Lambros Athanasiou6, Dalin Tang1*,7, Rencan Nie2,*, Jinde Cao8

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 631-646, 2020, DOI:10.32604/cmes.2020.09718

    Abstract Optical coherence tomography (OCT) is a new intravascular imaging technique with high resolution and could provide accurate morphological infor￾mation for plaques in coronary arteries. However, its segmentation is still com￾monly performed manually by experts which is time-consuming. The aim of this study was to develop automatic techniques to characterize plaque components and quantify plaque cap thickness using 3 machine learning methods including convolutional neural network (CNN) with U-Net architecture, CNN with Fully convolutional DenseNet (FC-DenseNet) architecture and support vector machine (SVM). In vivo OCT and intravascular ultrasound (IVUS) images were acquired from two patients at Emory University with informed consent… More >

  • Open Access


    Associations between Carotid Bifurcation Geometry and Atherosclerotic Plaque Vulnerability: A Chinese Atherosclerosis Risk Evaluation II Study

    Peirong Jiang1, Zhensen Chen2, Daniel S. Hippe2, Hiroko Watase3, Bin Sun1, Ruolan Lin1, Zheting Yang1, Yunjing Xue1,*, Xihai Zhao4,*, Chun Yuan2,4

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 34-35, 2019, DOI:10.32604/mcb.2019.07394

    Abstract This article has no abstract. More >

  • Open Access


    Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

    Caining Zhang1, Huaguang Li2, Xiaoya Guo3, David Molony4, Xiaopeng Guo2, Habib Samady4, Don P. Giddens4,5, Lambros Athanasiou6, Rencan Nie2,*, Jinde Cao3,*, Dalin Tang1,*,7

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 31-31, 2019, DOI:10.32604/mcb.2019.06983

    Abstract Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT coronary plaque data from 5… More >

  • Open Access


    Image-Based Modeling for Atherosclerotic Coronary Plaque Progression and Vulnerability Research

    Rui Lv1, Liang Wang1, Dalin Tang1,*,2

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 27-28, 2019, DOI:10.32604/mcb.2019.06829

    Abstract Medical imaging and image-based computational modeling have been used by many researchers in recent years to quantify atherosclerotic plaque morphological and biomechanical characteristics and predict the coronary plaque growth and rupture processes. However, it has been hard to validate model predictions due to imaging resolution limitation, lack of clinical events and plaque rupture data. This article reviews recent advances in coronary plaque research over the past decade, including medical imaging techniques represented by intravascular ultrasound (IVUS) and optical coherence tomography (OCT), computational modeling and their applications in plaque progression and vulnerability analyses and predictions. The clinical application and future development… More >

  • Open Access


    Impact of Plaque Erosion on Stress/Strain and Flow Shear Stress Calculation: An OCT-Based FSI Modeling Study

    Liang Wang1, Haibo Jia2, Luping He2, Rui Lv1, Xiaoya Guo3, Chun Yang4,5, Don P. Giddens6,7, Habib Samady6, Akiko Maehara8, Gary S. Mintz8, Dalin Tang1,*,5

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 23-24, 2019, DOI:10.32604/mcb.2019.07522

    Abstract Plaque erosion, one of the primary causes for coronary thrombosis, is responsible for about one third of the patients with acute coronary syndrome (ACS) [1]. Histological studies characterized the eroded plaque as a plaque with following morphological features: 1) plaque intima having direct contact with intraluminal thrombus due to the absence of endothelium or endothelial injury; 2) without rupture in the fibrous cap; 3) abundance of proteoglycans and smooth muscle cells on the luminal surface under the thrombus [2]. These characteristics has been applied in in vivo diagnosis of plaque erosion using optical coherence tomography (OCT) imaging technology and specific… More >

  • Open Access


    The Influence of Enhanced External Counterpulsation Intervention on the Biomechanical Stress Distribution of Advanced Plaque: A 3D FSI Study Based on in vivo Animal Experiment

    Yahui Zhang1, Hui Wang1,2, Zhouming Mai1,2, Jianhang Du1,2,3,*, Guifu Wu1,2,3

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 85-86, 2019, DOI:10.32604/mcb.2019.05836

    Abstract Enhanced external counter pulsation (EECP) is an effective therapy to provide beneficial assistance for the failing heart by reducing cardiac afterload and increasing blood flow perfusion noninvasively. The technique of EECP involves the use of the EECP device to inflate and deflate a series of compression cuffs wrapped around the patient’s calves, lower thighs, and upper thighs. As the result, the enhanced flow perfusion is derived from the device’s propelling blood from veins of lower body to arteries of upper body and increases the blood supply for the important organs and brain. In the ACCF/AHA Guideline and ESC Guideline on… More >

  • Open Access


    Using 3D Thin-Layer Model with in Vivo Patient-Specific Vessel Material Properties to Assesse Carotid Atherosclerotic Plaque Vulnerability

    Qingyu Wang1, Dalin Tang1,2,*, Gador Canton3, Zheyang Wu2, Thomas S. Hatsukami4, Kristen L Billiar5, Chun Yuan6

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 81-82, 2019, DOI:10.32604/mcb.2019.05748

    Abstract This article has no abstract. More >

  • Open Access


    Automatic Segmentation Methods Based on Machine Learning for Intracoronary Optical Coherence Tomography Image

    Caining Zhang1, Xiaoya Guo2, Dalin Tang1,3,*, David Molony4, Chun Yang3, Habib Samady4, Jie Zheng5, Gary S. Mintz6, Akiko Maehara6, Mitsuaki Matsumura6, Don P. Giddens4,7

    Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 79-80, 2019, DOI:10.32604/mcb.2019.05747

    Abstract Cardiovascular diseases are closely associated with sudden rupture of atherosclerotic plaques. Previous image modalities such as magnetic resonance imaging (MRI) and intravascular ultrasound (IVUS) were unable to identify vulnerable plaques due to their limited resolution. Optical coherence tomography (OCT) is an advanced intravascular imaging technique developed in recent years which has high resolution approximately 10 microns and could provide more accurate morphology of coronary plaque. In particular, it is now possible to identify plaques with fibrous cap thickness <65 μm, an accepted threshold value for vulnerable plaques. However, the current segmentation of OCT images are still performed manually by physicians… More >

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