Optimization Framework to Identify Constitutive Law Parameters of the Human Heart
Over the last decades, computational models have been applied in in-silico simulations of the heart biomechanics. These models depend on input parameters. In particular, four parameters are needed for the constitutive law of Guccione et al., a model describing the stress-strain relation of the heart...
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| Auteurs principaux: | , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
De Gruyter
2020
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| Accès en ligne: | https://doaj.org/article/6b3e271ba647496f8bc2cc406d311b86 |
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| Résumé: | Over the last decades, computational models have been applied in in-silico simulations of the heart biomechanics. These models depend on input parameters. In particular, four parameters are needed for the constitutive law of Guccione et al., a model describing the stress-strain relation of the heart tissue. In the literature, we could find a wide range of values for these parameters. In this work, we propose an optimization framework which identifies the parameters of a constitutive law. This framework is based on experimental measurements conducted by Klotz et al.. They provide an end-diastolic pressure-volume relationship. We applied the proposed framework on one heart model and identified the following elastic parameters to optimally match the Klotz curve: C=313 Pa, bf=17.8, bt=7.1and bft=12A. In general, this approach allows to identify optimized parameters for a constitutive law, for a patient-specific heart geometry. The use of optimized parameters will lead to physiological simulation results of the heart biomechanics and is therefore an important step towards applying computational models in clinical practice. |
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