13 March 2017 Characterizing the lung tissue mechanical properties using a micromechanical model of alveolar sac
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According to statistics, lung disease is among the leading causes of death worldwide. As such, many research groups are developing powerful tools for understanding, diagnosis and treatment of various lung diseases. Recently, biomechanical modeling has emerged as an effective tool for better understanding of human physiology, disease diagnosis and computer assisted medical intervention. Mechanical properties of lung tissue are important requirements for methods developed for lung disease diagnosis and medical intervention. As such, the main objective of this study is to develop an effective tool for estimating the mechanical properties of normal and pathological lung parenchyma tissue based on its microstructure. For this purpose, a micromechanical model of the lung tissue was developed using finite element (FE) method, and the model was demonstrated to have application in estimating the mechanical properties of lung alveolar wall. The proposed model was developed by assembling truncated octahedron tissue units resembling the alveoli. A compression test was simulated using finite element method on the created geometry and the hyper-elastic parameters of the alveoli wall were calculated using reported alveolar wall stress-strain data and an inverse optimization framework. Preliminary results indicate that the proposed model can be potentially used to reconstruct microstructural images of lung tissue using macro-scale tissue response for normal and different pathological conditions. Such images can be used for effective diagnosis of lung diseases such as Chronic Obstructive Pulmonary Disease (COPD).
Conference Presentation
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Elham Karami, Elham Karami, Behzad Seify, Behzad Seify, Hadi Moghadas, Hadi Moghadas, Masoomeh Sabsalinejad, Masoomeh Sabsalinejad, Ting-Yim Lee, Ting-Yim Lee, Abbas Samani, Abbas Samani, } "Characterizing the lung tissue mechanical properties using a micromechanical model of alveolar sac", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1013709 (13 March 2017); doi: 10.1117/12.2254542; https://doi.org/10.1117/12.2254542

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