Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

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SHR Neuro Krebs Kardio Lipid

Gsell, MAF; Augustin, CM; Prassl, AJ; Karabelas, E; Fernandes, JF; Kelm, M; Goubergrits, L; Kuehne, T; Plank, G.
Assessment of wall stresses and mechanical heart power in the left ventricle: Finite element modeling versus Laplace analysis.
Int J Numer Method Biomed Eng. 2018;
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Autor/innen der Med Uni Graz:
Augustin Christoph
Karabelas Elias
Plank Gernot
Prassl Anton J.

Dimensions Citations:

Plum Analytics:
Stenotic aortic valve disease (AS) causes pressure overload of the left ventricle (LV) that may trigger adverse remodeling and precipitate progression towards heart failure (HF). As myocardial energetics can be impaired during AS, LV wall stresses and biomechanical power provide a complementary view of LV performance that may aide in better assessing the state of disease. Using a high-resolution electro-mechanical (EM) in silico model of the LV as a reference, we evaluated clinically feasible Laplace-based methods for assessing global LV wall stresses and biomechanical power. We used N = 4in silico finite element (FE) EM models of LV and aorta of patients suffering from AS. All models were personalized with clinical data under pre-treatment conditions. LV wall stresses and biomechanical power were computed accurately from FE kinematic data and compared to Laplace-based estimation methods which were applied to the same FE model data. Laplace estimates of LV wall stress are able to provide a rough approximation of global mean stress in the circumferential-longitudinal plane of the LV. However, according to FE results spatial heterogeneity of stresses in the LV wall is significant, leading to major discrepancies between local stresses and global mean stress. Assessment of mechanical power with Laplace methods is feasible, but these are inferior in accuracy compared to FE models. The accurate assessment of stress and power density distribution in the LV wall is only feasible based on patient-specific FE modeling. This article is protected by copyright. All rights reserved.

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