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Available Computational Techniques to Model Atherosclerotic Plaque Progression Implementing a Multi-Level Approach

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Computational Biomechanics for Medicine

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Abstract

The mechanisms of atherosclerosis remain unclear and computational modeling has been used to provide insights for the understanding of the processes which lead to the initiation of plaque and its progress. In this work we review the available methodologies for vascular image processing and cardiovascular mechanics. Moreover, we present a multi-level modeling approach which can be used: (i) for the prediction of regions which are prone to plaque formation, (ii) for the medical decision support providing computational estimation of the fractional flow reserve (FFR), and (iii) for simulating the deformation of stent in coronary arteries. More specifically, in the first level three-dimensional (3D) arterial reconstruction is performed. In the second level, the 3D arteries are used for modeling of blood flow and computation of endothelial shear stress (ESS). In the third level the accumulation of lipoproteins and monocytes into the arterial wall is simulated, while in the fourth level the plaque growth process is modeled considering the lipoprotein oxidation, the macrophages differentiation, and the foam cells formation. Moreover, in the fifth level FFR is calculated implementing a novel methodology, while in the sixth level the stent deformation in stenosed arteries is modeled. Each modeling level has been validated using human data and the results show that computational modeling might assist in understanding the pathophysiology of atherosclerosis.

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Acknowledgements

This work is partially funded by the European Commission (Project SMARTOOL, GA number: 689068, H2020).

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Authors and Affiliations

  1. Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece

    Antonis I. Sakellarios, Georgia Karanasiou, Panagiotis Siogkas, Vasiliki Kigka, Themis Exarchos, George Rigas & Dimitrios I. Fotiadis

  2. Department of Biomedical Research, Institute of Molecular Biology and Biotechnology – FORTH, University Campus of Ioannina, Ioannina, Greece

    Antonis I. Sakellarios, Georgia Karanasiou, Panagiotis Siogkas, Vasiliki Kigka, Themis Exarchos, George Rigas & Dimitrios I. Fotiadis

  3. Department of Cardiology, Medical School, University of Ioannina, Ioannina, Greece

    Lampros K. Michalis

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  1. Antonis I. Sakellarios
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  2. Georgia Karanasiou
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Correspondence to Dimitrios I. Fotiadis .

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Editors and Affiliations

  1. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Adam Wittek

  2. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Grand Joldes

  3. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand

    Poul M.F. Nielsen

  4. School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Barry J. Doyle

  5. Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, West Australia, Australia

    Karol Miller

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Sakellarios, A.I. et al. (2017). Available Computational Techniques to Model Atherosclerotic Plaque Progression Implementing a Multi-Level Approach. In: Wittek, A., Joldes, G., Nielsen, P., Doyle, B., Miller, K. (eds) Computational Biomechanics for Medicine. Springer, Cham. https://doi.org/10.1007/978-3-319-54481-6_4

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