Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

Patient-specific computer simulations can be a powerful tool in clinical applications, helping in diagnostics and the development of new treatments. However, its practical use depends on the reliability of the models. The construction of cardiac simulations involves several steps with inherent uncer...

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Published inPhilosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences Vol. 378; no. 2173; p. 20190381
Main Authors Campos, J. O., Sundnes, J., dos Santos, R. W., Rocha, B. M.
Format Journal Article
LanguageEnglish
Published England The Royal Society Publishing 12.06.2020
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ISSN1364-503X
1471-2962
1471-2962
DOI10.1098/rsta.2019.0381

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Summary:Patient-specific computer simulations can be a powerful tool in clinical applications, helping in diagnostics and the development of new treatments. However, its practical use depends on the reliability of the models. The construction of cardiac simulations involves several steps with inherent uncertainties, including model parameters, the generation of personalized geometry and fibre orientation assignment, which are semi-manual processes subject to errors. Thus, it is important to quantify how these uncertainties impact model predictions. The present work performs uncertainty quantification and sensitivity analyses to assess the variability in important quantities of interest (QoI). Clinical quantities are analysed in terms of overall variability and to identify which parameters are the major contributors. The analyses are performed for simulations of the left ventricle function during the entire cardiac cycle. Uncertainties are incorporated in several model parameters, including regional wall thickness, fibre orientation, passive material parameters, active stress and the circulatory model. The results show that the QoI are very sensitive to active stress, wall thickness and fibre direction, where ejection fraction and ventricular torsion are the most impacted outputs. Thus, to improve the precision of models of cardiac mechanics, new methods should be considered to decrease uncertainties associated with geometrical reconstruction, estimation of active stress and of fibre orientation. This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
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One contribution of 16 to a theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.4955573.
ISSN:1364-503X
1471-2962
1471-2962
DOI:10.1098/rsta.2019.0381