Stroke is the third leading cause of death in the United States which is often caused by atherosclerotic carotid plaque rupture. Stroke may lead to various brain damages, brain malfunctions and disability. A large number of victims who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs. The objectives of this project are to integrate computational modeling, Magnetic Resonance Imaging (MRI) technology, ultrasound/Doppler technology (US), mechanical testing, and pathological analysis to perform quantitative mechanical analysis to atherosclerotic carotid plaques, to quantify critical blood flow and plaque stress/strain conditions under which plaque rupture is likely to occur, and to seek the potential that quantitative mechanical analysis can be integrated into state-of-the-art imaging technologies for better screening and diagnostic applications. Those objectives are consistent with the mission of the NIBIB. Forty patients scheduled to undergo carotid endarterectomy will be recruited to participate in this study with proper consent. Fifty additional cadaveric or ex-vivo endarterectomy carotid plaque samples will also be used in the study.
The specific aims are: (1) Develop and integrate 3D MRI, US technologies and computational methods to quantify plaque structure and vessel material properties; (2) Develop 3D multi-component computational models with blood- vessel interactions based on in vitro, ex vivo and in vivo measurements obtained by MRI, US technologies and intra- operative measurements; (3) Perform complete mechanical analysis for atherosclerotic plaques and identify correlations between critical stress/strain conditions and plaque morphology and composition, vessel mechanical properties and blood flow pressure conditions; (4) Quantify and validate correlations between critical stress/strain conditions and plaque vulnerability and identify critical stress/strain indicators which could be used by doctors to make clinical and diagnostic decisions. This will establish the base for future software development and technology integration. With large-scale patient study validations, the long term goal is to establish that integration of computational modeling with MRI and US imaging technologies can lead to better interpretation of the information already contained in MRI and ultrasound images, new development of imaging software for more accurate assessment of plaque vulnerability, and potential early prediction of possible stroke. With improved accuracy of predictions, certain unnecessary operations may be avoided, cost of medical care can be reduced, and some fatal events may be prevented. The integrated computational mechanical image analysis improves current image analysis techniques and can serve as basis for many further research activities involving complex biological structures with multi-component interactions.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB004759-03
Application #
7078500
Study Section
Special Emphasis Panel (ZRG1-BBBP-C (50))
Program Officer
Peng, Grace
Project Start
2004-09-01
Project End
2008-06-30
Budget Start
2006-07-01
Budget End
2007-06-30
Support Year
3
Fiscal Year
2006
Total Cost
$258,276
Indirect Cost
Name
Worcester Polytechnic Institute
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
041508581
City
Worcester
State
MA
Country
United States
Zip Code
01609
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Wang, Liang; Zhu, Jian; Samady, Habib et al. (2017) Effects of Residual Stress, Axial Stretch, and Circumferential Shrinkage on Coronary Plaque Stress and Strain Calculations: A Modeling Study Using IVUS-Based Near-Idealized Geometries. J Biomech Eng 139:
Guo, Xiaoya; Zhu, Jian; Maehara, Akiko et al. (2017) Quantify patient-specific coronary material property and its impact on stress/strain calculations using in vivo IVUS data and 3D FSI models: a pilot study. Biomech Model Mechanobiol 16:333-344
Tang, Dalin; Yang, Chun; Huang, Sarayu et al. (2017) Cap inflammation leads to higher plaque cap strain and lower cap stress: An MRI-PET/CT-based FSI modeling approach. J Biomech 50:121-129
Huang, Xueying; Yang, Chun; Zheng, Jie et al. (2016) 3D MRI-based multicomponent thin layer structure only plaque models for atherosclerotic plaques. J Biomech 49:2726-2733
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
Liu, Biyue; Zheng, Jie; Bach, Richard et al. (2015) Influence of model boundary conditions on blood flow patterns in a patient specific stenotic right coronary artery. Biomed Eng Online 14 Suppl 1:S6
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
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

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