S. Deivanayagi^1,*, 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 >

Peirong Jiang¹, Zhensen Chen², Daniel S. Hippe², Hiroko Watase³, Bin Sun¹, Ruolan Lin¹, Zheting Yang¹, Yunjing Xue^1,*, Xihai Zhao^4,*, Chun Yuan^2,4

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

Abstract This article has no abstract. More >

Caining Zhang¹, Huaguang Li², Xiaoya Guo³, David Molony⁴, Xiaopeng Guo², Habib Samady⁴, Don P. Giddens^4,5, Lambros Athanasiou⁶, Rencan Nie^2,*, Jinde Cao^3,*, Dalin Tang^1,*,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 >

Qingyu Wang¹, Dalin Tang^1,2,*, 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 >

Caining Zhang¹, Xiaoya Guo², Dalin Tang^1,3,*, David Molony⁴, Chun Yang³, Habib Samady⁴, Jie Zheng⁵, Gary S. Mintz⁶, Akiko Maehara⁶, Mitsuaki Matsumura⁶, Don P. Giddens^4,7

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 >

Yifan Yin¹, Chunliu He¹, Biao Xu², Zhiyong Li^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 57-57, 2019, DOI:10.32604/mcb.2019.05732

Abstract The tissue composition and morphological structure of atherosclerotic plaques determine its stability or vulnerability. Intravascular optical coherence tomography (IVOCT) has rapidly become the method of choice for assessing the pathology of the coronary arterial wall in vivo due to its superior resolution. However, in clinical practice, the analysis of plaque composition of OCT images mainly relies on the interpretation of images by well-trained experts, which is a time-consuming, labor-intensive procedure and it is also subjective. The purpose of this study is to use the Convolutional neural network (CNN) method to automatically extract the best feature information from the OCT images… More >

Muyi Guo¹, Yan Cai¹, Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 49-49, 2019, DOI:10.32604/mcb.2019.05727

Abstract Observational studies have identified angiogenesis from the adventitial vasa vasorum and intraplaque hemorrhage (IPH) as critical factors in atherosclerotic plaque progression and destabilization. Here we propose a mathematical model incorporating intraplaque neovascularization and hemodynamic calculation for the quantitative evaluation of atherosclerotic plaque hemorrhage. An angiogenic microvasculature based on histology of a patient’s carotid plaque is generated by two-dimensional nine-point model of endothelial cell migration. Three key cells (endothelial cells, smooth muscle cells and macrophages) and three key chemicals (vascular endothelial growth factors, extracellular matrix and matrix metalloproteinase) are involved in the intraplaque angiogenesis model, and described by the reaction-diffusion partial… More >

Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 29-30, 2019, DOI:10.32604/mcb.2019.06308

Abstract In this article, we summarize our previous work in imaging-based computational modelling and simulation of the interaction between blood flow and atherosclerotic plaque. We also discussed our recent developments in multiphysical modelling of plaque progression and destabilization. Significance and translation of the modelling study to clinical practice are discussed in order to better assess plaque vulnerability and accurately predict a possible rupture. More >

J. J. Wentzel^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 7-8, 2019, DOI:10.32604/mcb.2019.05696

Abstract The pathophysiology of atherosclerosis is complex and multifactorial, involving systemic risk factors and biomechanical stimuli. Atherosclerotic plaques predominantly form in regions that are exposed to low shear stress of the blood at the vessel wall, whereas regions of moderate and high shear stress are generally protected. For more than 20 years, my research group performs studies to investigate the role of shear stress in atherosclerotic plaque formation and rupture in coronary and carotid arteries of patients and laboratory animals. For that reason, new technology was developed to 3D reconstruct arteries based on fusion of multiple invasive and non-invasive imaging modalities.… More >

Mingchao Cai, Chun Yang, Mehmet H. Kural, Richard Bach, David Muccigrosso, Deshan Yang, Jie Zheng, Kristen L. Billiar, Dalin Tang

The International Conference on Computational & Experimental Engineering and Sciences, Vol.19, No.4, pp. 97-104, 2011, DOI:10.3970/icces.2011.019.097

Abstract Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better risk assessment and rupture predictions. In vivo patient-specific coronary plaque models are lagging due to limitations on non-invasive image resolution, flow data, and vessel material properties. We propose a procedure where intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling are combined together to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. More >