Longitudinal Parameter Estimation in 3D Electromechanical Models: Application to Cardiovascular Changes in Digestion
| Autor: | Manasi Datar, Xavier Pennec, Roch Molléro, Jakob A. Hauser, Nicholas Ayache, Alexander Jones, Tobias Heimann, Hervé Delingette, Maxime Sermesant |
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| Přispěvatelé: | Analysis and Simulation of Biomedical Images (ASCLEPIOS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), University College of London [London] (UCL), Siemens Corporate Technology, Imaging and Computer Vision, Erlangen, Siemens Corporate Technology |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Cardiac output
Computer science Estimation theory 020207 software engineering 02 engineering and technology 01 natural sciences 010101 applied mathematics Design studies Blood pressure Digestion (alchemy) Discriminative model Control theory Heart rate 0202 electrical engineering electronic engineering information engineering [INFO.INFO-IM]Computer Science [cs]/Medical Imaging 0101 mathematics Constant (mathematics) Simulation |
| Zdroj: | FIMH 2017-9th international conference on Functional Imaging and Modeling of the Heart FIMH 2017-9th international conference on Functional Imaging and Modeling of the Heart, Jun 2017, Toronto, Canada. pp.432-440, ⟨10.1007/978-3-319-59448-4_41⟩ Functional Imaging and Modelling of the Heart ISBN: 9783319594477 FIMH |
| DOI: | 10.1007/978-3-319-59448-4_41⟩ |
| Popis: | International audience; Computer models of the heart are of increasing interest for clinical applications due to their discriminative and predictive abilities. However the number of simulation parameters in these models can be high and expert knowledge is required to properly design studies involving these models, and analyse the results. In particular it is important to know how the parameters vary in various clinical or physiological settings. In this paper we build a data-driven model of cardiovascular parameter evolution during digestion, from a clinical study involving more than 80 patients. We first present a method for longitudinal parameter estimation in 3D cardiac models, which we apply to 21 patient-specific hearts geometries at two instants of the study, for 6 parameters (two fixed and four time-varying parameters). From these personalised hearts, we then extract and validate a law which links the changes of cardiac output and heart rate under constant arterial pressure to the evolution of these parameters, thus enabling the fast simulation of hearts during digestion for future patients. |
| Databáze: | OpenAIRE |
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