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IVUS-Based FSI Models for Human Coronary Plaque Progression Study: Components, Correlation and Predictive Analysis

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Abstract

Atherosclerotic plaque progression is believed to be associated with mechanical stress conditions. Patient follow-up in vivo intravascular ultrasound coronary plaque data were acquired to construct fluid–structure interaction (FSI) models with cyclic bending to obtain flow wall shear stress (WSS), plaque wall stress (PWS) and strain (PWSn) data and investigate correlations between plaque progression measured by wall thickness increase (WTI), cap thickness increase (CTI), lipid depth increase (LDI) and risk factors including wall thickness (WT), WSS, PWS, and PWSn. Quarter average values (n = 178–1016) of morphological and mechanical factors from all slices were obtained for analysis. A predictive method was introduced to assess prediction accuracy of risk factors and identify the optimal predictor(s) for plaque progression. A combination of WT and PWS was identified as the best predictor for plaque progression measured by WTI. Plaque WT had best overall correlation with WTI (r = −0.7363, p < 1E−10), cap thickness (r = 0.4541, p < 1E−10), CTI (r = −0.4217, p < 1E−8), LD (r = 0.4160, p < 1E−10), and LDI (r = −0.4491, p < 1E−10), followed by PWS (with WTI: (r = −0.3208, p < 1E−10); cap thickness: (r = 0.4541, p < 1E−10); CTI: (r = −0.1719, p = 0.0190); LD: (r = −0.2206, p < 1E−10); LDI: r = 0.1775, p < 0.0001). WSS had mixed correlation results.

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Acknowledgments

This research was supported by US NIH/NIBIB R01 EB004759. Yang’s research was supported in part by National Sciences Foundation of China 11171030.

Conflict of interest

Other than the grants listed in the acknowledgement section, the authors declare that they have no other conflict of interest.

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Authors and Affiliations

  1. Mathematical Sciences Department, Worcester Polytechnic Institute, Worcester, MA, USA

    Liang Wang, Zheyang Wu, Chun Yang & Dalin Tang

  2. Network Technology Research Institute, China United Network Communications Co., Ltd, Beijing, China

    Chun Yang

  3. Mallinckrodt Institute of Radiology, Washington University, Saint Louis, MO, USA

    Jie Zheng & David Muccigrosso

  4. Cardiovascular Division, Washington University School of Medicine, Saint Louis, MO, USA

    Richard Bach

  5. Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, USA

    Kristen Billiar

  6. The Cardiovascular Research Foundation, Columbia University, New York, NY, USA

    Akiko Maehara & Gary S. Mintz

  7. School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China

    Dalin Tang

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  1. Liang Wang
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Associate Editor Diego Gallo oversaw the review of this article.

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Wang, L., Wu, Z., Yang, C. et al. IVUS-Based FSI Models for Human Coronary Plaque Progression Study: Components, Correlation and Predictive Analysis. Ann Biomed Eng 43, 107–121 (2015). https://doi.org/10.1007/s10439-014-1118-1

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