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Proceedings Paper

A FSI-based structural approach for micromechanical characterization of adipose tissue
Author(s): Behzad Seyfi; Masoumeh Sabzalinejad; Seyed M. H. Haddad; Nasser Fatouraee; Abbas Samani
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Paper Abstract

This paper presents a novel computational method for micromechanical modeling of adipose tissue. The model can be regarded as the first step for developing an inversion based framework that uses adipose stiffness data obtained from elastography to determine its microstructural alterations. Such information can be used as biomarkers for diseases associated with adipose tissue microstructure alteration (e.g. adipose tissue fibrosis and inflammation in obesity). In contrast to previous studies, the presented model follows a multiphase structure which accounts for both solid and fluid components as well as their mechanical interaction. In the model, the lipid droplets and extracellular matrix were considered as the fluid and solid phase, respectively. As such, the fluid-structure interaction (FSI) problem was solved using finite element method. In order to gain insight into how microstructural characteristics influence the macro scale mechanical properties of the adipose tissue, a compression mechanical test was simulated using the FSI model and its results were fitted to corresponding experimental data. The simulation procedure was performed for adipocytes in healthy conditions while the stiffness of extracellular matrix in normal adipose tissue was found by varying it systematically within an optimization process until the simulation response agreed with experimental data. Results obtained in this study are encouraging and show the capability of the proposed model to capture adipose tissue macroscale mechanical behavior based on its microstructure under health and different pathological conditions.

Paper Details

Date Published: 13 March 2017
PDF: 7 pages
Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101370G (13 March 2017); doi: 10.1117/12.2254652
Show Author Affiliations
Behzad Seyfi, Amirkabir Univ. of Technology (Iran, Islamic Republic of)
Masoumeh Sabzalinejad, National Institute of Genetic Engineering and Biotechnology (Iran, Islamic Republic of)
Seyed M. H. Haddad, Western Univ. (Canada)
Nasser Fatouraee, Amirkabir Univ. of Technology (Iran, Islamic Republic of)
Abbas Samani, Western Univ. (Canada)
Robarts Research Institute (Canada)


Published in SPIE Proceedings Vol. 10137:
Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor Gimi, Editor(s)

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