The objective of this project is to combine anisotropic computational modeling with in vivo intravascular ultrasound (IVUS), angiography, ex vivo Magnetic Resonance Imaging (MRI), mechanical testing, and pathohistological analysis to analyze vulnerable atherosclerotic coronary plaques and identify critical blood flow and plaque stress/strain indicators for quantitative coronary plaque vulnerability assessment. The long term goals are: a) develop computational mechanical image analysis tools for more accurate plaque assessment and possible quantitative improvement to the current American Heart Association (AHA) plaque classification scheme;b) identify critical flow and stress/strain plaque vulnerability risk indicators which could be monitored for early prediction, diagnosis, treatment, and prevention of related cardiovascular diseases. The hypotheses are: (1) Critical plaque stress/strain conditions correlate closely with plaque vulnerability and may be used as indicators to further differentiate plaques within AHA advanced plaque classifications (types V- VIII) and provide more quantitative methods to assess plaque rupture risk;(2) Combination of in vivo IVUS imaging, pressure and flow measurements and 3D anisotropic multi-component models with fluid-structure interactions (FSI) and cyclic bending will improve the accuracy of mechanical analysis for coronary plaques and lead to more accurate in vivo plaque vulnerability assessment. This project has four specific aims.
Aim 1 : Develop and integrate in vivo IVUS imaging, flow and pressure measurements techniques, angiography, multi-contrast ex vivo MRI, histological analysis, and biaxial mechanical testing techniques to quantify plaque morphology, tissue components, curvature, intra-coronary flow and pressure conditions at the lesion site, and anisotropic vessel material properties.
Aim 2 : Develop 3D anisotropic multi-component FSI models for 100 human coronary plaques (50 in vivo IVUS, 50 ex vivo MRI) with cyclic bending and intra-coronary flow and pressure conditions (IVUS only) to obtain 3D flow shear stress and plaque stress/strain data;
Aim 3 : perform 3D mechanical image analysis for coronary plaques and identify correlations between critical stress/strain conditions (potential risk indicators) and plaque morphology and composition, vessel mechanical properties and blood flow pressure conditions (patient data). Computational models will be validated by both in vivo IVUS and in vitro experimental data.
Aim 4 : Introduce quantitative in vivo/ex vivo/histological plaque vulnerability assessment schemes and compare with AHA histology-based plaque classifications for possible quantitative improvements on AHA scheme and potential screening practice. Success of this project will lead to more accurate plaque vulnerability assessment and predictions for possible plaque rupture risk so that better decisions for treatment can be made leading to better public health and reduced costs of Medicare. Mechanical image analysis and software additions to enhance MRI/IVUS imaging technology for clinical applications are possible with future large-scale patient study validations.
Many cardiovascular events (such as heart attack and stroke) are caused by atherosclerotic plaque rupture which may happen without any warning signals. Success of this project will lead to more accurate in vivo coronary plaque vulnerability assessment and predictions for possible plaque rupture risk so that better and timely decisions for treatment can be made leading to better public health and reduced costs of Medicare. Commercialization of the research results is possible with the automation of model construction and data analysis procedures.
|Wang, Liang; Wu, Zheyang; Yang, Chun et al. (2015) IVUS-based FSI models for human coronary plaque progression study: components, correlation and predictive analysis. Ann Biomed Eng 43:107-21|
|Fan, Rui; Tang, Dalin; Yang, Chun et al. (2014) Human coronary plaque wall thickness correlated positively with flow shear stress and negatively with plaque wall stress: an IVUS-based fluid-structure interaction multi-patient study. Biomed Eng Online 13:32|
|Huang, Xueying; Yang, Chun; Zheng, Jie et al. (2014) Higher critical plaque wall stress in patients who died of coronary artery disease compared with those who died of other causes: a 3D FSI study based on ex vivo MRI of coronary plaques. J Biomech 47:432-7|
|Tang, Dalin; Kamm, Roger D; Yang, Chun et al. (2014) Image-based modeling for better understanding and assessment of atherosclerotic plaque progression and vulnerability: data, modeling, validation, uncertainty and predictions. J Biomech 47:834-46|
|Tang, Dalin; Yang, Chun; Zheng, Jie et al. (2013) Image-based modeling and precision medicine: patient-specific carotid and coronary plaque assessment and predictions. IEEE Trans Biomed Eng 60:643-51|
|Tang, Dalin; Yang, Chun; Canton, Gador et al. (2013) Correlations between carotid plaque progression and mechanical stresses change sign over time: a patient follow up study using MRI and 3D FSI models. Biomed Eng Online 12:105|
|Liu, Haofei; Canton, Gador; Yuan, Chun et al. (2012) Using in vivo Cine and 3D multi-contrast MRI to determine human atherosclerotic carotid artery material properties and circumferential shrinkage rate and their impact on stress/strain predictions. J Biomech Eng 134:011008|
|Kural, Mehmet H; Cai, Mingchao; Tang, Dalin et al. (2012) Planar biaxial characterization of diseased human coronary and carotid arteries for computational modeling. J Biomech 45:790-8|
|Liu, Haofei; Cai, Mingchao; Yang, Chun et al. (2012) IVUS-based computational modeling and planar biaxial artery material properties for human coronary plaque vulnerability assessment. Mol Cell Biomech 9:77-93|
|Yang, Chun; Tang, Dalin; Atluri, Satya (2011) Patient-Specific Carotid Plaque Progression Simulation Using 3D Meshless Generalized Finite Difference Models with Fluid-Structure Interactions Based on Serial In Vivo MRI Data. Comput Model Eng Sci 72:53-77|
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