Liu Haofei, Cai Mingchao, Yang Chun, Zheng Jie, Bach Richard, Kural Mehmet H, Billiar Kristen L, Muccigrosso David, Lu Dongsi, Tang Dalin
Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA 01609, USA.
Mol Cell Biomech. 2012 Mar;9(1):77-93.
Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better plaque 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. A framework is proposed to combine intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling with fluid-structure interactions and anisotropic material properties to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. Impact of pre-shrink-stretch process, vessel curvature and high blood pressure on stress, strain, flow velocity and flow maximum principal shear stress was investigated.
基于图像的计算建模已被引入用于易损动脉粥样硬化斑块,以识别可能用于更好的斑块评估和破裂预测的关键力学条件。由于无创图像分辨率、血流数据和血管材料特性的限制,体内患者特异性冠状动脉斑块模型的发展滞后。本文提出了一个框架,将血管内超声(IVUS)成像、双轴力学测试和计算建模与流固相互作用及各向异性材料特性相结合,以获取更好、更完整的斑块数据,并进行更准确的斑块易损性评估和预测。研究了预收缩-拉伸过程、血管曲率和高血压对应力、应变、流速和流动最大主剪应力的影响。