151. Patient-specific modeling for left ventricular mechanics using data-driven boundary energies
- Author
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Asner, L., Hadjicharalambous, M., Chabiniok, R., Peressutti, D., Sammut, E., Wong, J., Carr-White, G., Razavi, R., King, A.P., Smith, N., Lee, J., Nordsletten, D., Imaging Sciences and Biomedical Engineering Division [London], Guy's and St Thomas' Hospital [London]-King‘s College London, Mathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine (M3DISIM), Laboratoire de mécanique des solides (LMS), Centre National de la Recherche Scientifique (CNRS)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École polytechnique (X)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Paris-Saclay, École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, École polytechnique (X)-MINES ParisTech - École nationale supérieure des mines de Paris, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-MINES ParisTech - École nationale supérieure des mines de Paris
- Subjects
Patient-specific modeling ,Finite element method ,Mechanics of Materials ,Mechanical Engineering ,Patient-specific boundary conditions ,Computational Mechanics ,[SPI.MECA.BIOM]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Biomechanics [physics.med-ph] ,Medical imaging ,Physics and Astronomy(all) ,Cardiac mechanic ,[MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA] ,Computer Science Applications - Abstract
International audience; Supported by the wide range of available medical data available, cardiac biomechanical modeling has exhibited significant potential to improve our understanding of heart function and to assisting in patient diagnosis and treatment. A critical step towards the development of accurate patient-specific models is the deployment of boundary conditions capable of integrating data into the model to enhance model fidelity. This step is often hindered by sparse or noisy data that, if applied directly, can introduce non-physiological forces and artifacts into the model. To address these issues, in this paper we propose novel boundary conditions which aim to balance the accurate use of data with physiological boundary forces and model outcomes through the use of data-derived boundary energies. The introduced techniques employ Lagrange multipliers, penalty methods and moment-based constraints to achieve robustness to data of varying quality and quantity. The proposed methods are compared with commonly used boundary conditions over an idealized left ventricle as well as over in vivo models, exhibiting significant improvement in model accuracy. The boundary conditions are also employed in in vivo full-cycle models of healthy and diseased hearts, demonstrating the ability of the proposed approaches to reproduce data-derived deformation and physiological boundary forces over a varied range of cardiac function.
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