Sevan Goenezen^1,*, Ping Luo¹, Baik Jin Kim¹, Maulik Kotecha¹, Yue Mei^2,3

Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 46-48, 2019, DOI:10.32604/mcb.2019.07348

Abstract It is well known that the mechanical properties of tissues may vary spatially due to changing tissue types or due to inherent tissue disease. For example, the biomechanical properties are known to vary throughout blood vessels [1]. Diseases such as cancers may also lead to locally altered mechanical properties, thus allow a preliminary diagnosis via finger palpation. Quantifying the mechanical property distribution of tissues for a given constitutive equation will allow to characterize the biomechanical response of tissues. This may help to 1) predict disease progression, 2) diagnose diseases that alter the biomechanics of the tissue, e.g., skin cancers, breast… 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 >

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 >

Lijian Xu^1,2, Lekang Yin³, Fuyou Liang^1,2,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 71-72, 2019, DOI:10.32604/mcb.2019.05741

Abstract Recent studies have revealed that aortic valve diseases are associated with the increased incidence of the aortopathy development. However, the influence of aortic valve diseases on aortic hemodynamics remains unclear. The purpose of this study was therefore to investigate the hemodynamic differences in patients with and without aortic valve disease through patient-specific simulations performed on two aorta models (BAV with severe stenosis vs. normal tricuspid aortic valve (TAV)). Realistic geometries and boundary conditions were obtained from computed tomography angiography (CTA) and phase-contrast magnetic resonance imaging (PC-MRI) measurements, respectively. In addition, 4D-MRI were performed to validate the numerical methods used to… More >

Ju Huang¹, Cuiru Sun^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 67-68, 2019, DOI:10.32604/mcb.2019.05738

Abstract Intravascular optical coherence tomography (OCT) has the characteristics of high resolution and fast imaging speed. Continuous images of the same section of the same vessel can reflect the deformation characteristics of the vessel wall under different blood pressure. Digital image processing may be used to segment various structures on the vascular wall and extract the deformation incorporating with biomechanical analysis. Image filtering plays a very important role in image processing. Median filter was used to filter salt and pepper noise in OCT images. Fuzzy function gray processing method was used to suppress irrelevant information and improve image clarity. Dividing point… More >

Junjie Jia¹, Cuiru Sun^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 61-64, 2019, DOI:10.32604/mcb.2019.05736

Abstract Intravascular optical coherence tomography (IVOCT) has been employed to clinical coronary imaging for several years. But the influence of flushing and OCT catheter to the blood vessel biomechanical properties have not been studied. In this paper, IVOCT imaging is integrated with the fluid-structure interaction (FSI) simulation to study the blood flow velocity and the stress distribution of a porcine carotid artery during IVOCT imaging. 3D geometric model is built based on the in vivo OCT images, and a hyperelastic model is employed for the material properties of the vascular wall. The blood flow profile and wall stress distributions under various… More >

Haibo Jia^1,*, Bo Yu¹

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 23-24, 2019, DOI:10.32604/mcb.2019.05708

Abstract Coronary angiography is the traditional standard imaging modality for visual evaluation of coronary anatomy and guidance of percutaneous coronary interventions (PCI). However, the 2-dimensional lumenogram cannot depict the arterial vessel per se and plaque characteristics, or directly assess the stenting result. Intracoronary imaging by means of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) provides valuable incremental information that can be used clinically to optimize stent implantation and thereby minimize stent-related problems. Beyond guidance of stent selection and optimisation, imaging provides critical insights into the pathophysiology of acute coronary syndrome (ACS), greater clarity when confronted with angiographically ambiguous lesions and… More >

Hu Xiaofang, Xu Feng, Wang Ming, Wu Xiaoping

The International Conference on Computational & Experimental Engineering and Sciences, Vol.18, No.4, pp. 119-120, 2011, DOI:10.3970/icces.2011.018.119

Abstract The Synchrotron Radiation X-ray Computed Tomography (SR-CT) technique is a non- destructive detection technology which can give the in-situ observation of microstructure evolution of materials under the external field (e.g., high pressure, high temperature, electromagnetic field, intense radiation, etc.), and it has a significant application in the area of plants and crops, advanced manufacturing, advanced materials, biomedicine, mechanics, archaeology and so on. 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, No.2, pp. 153-161, 2019, DOI:10.32604/mcb.2019.06873

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 >

Yuxiang Huang¹, Chuliu He¹, Jiaqiu Wang², Yuehong Miao¹, Tongjin Zhu¹, Ping Zhou¹, Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.15, No.2, pp. 117-125, 2018, DOI: 10.3970/mcb.2018.02478

Abstract Intravascular optical coherence tomography (IVOCT) is becoming more and more popular in clinical diagnosis of coronary atherosclerotic. However, reading IVOCT images is of large amount of work. This article describes a method based on image feature extraction and support vector machine (SVM) to achieve semi-automatic segmentation of IVOCT images. The image features utilized in this work including light attenuation coefficients and image textures based on gray level co-occurrence matrix. Different sets of hyper-parameters and image features were tested. This method achieved an accuracy of 83% on the test images. Single class accuracy of 89% for fibrous, 79.3% for calcification and… More >