title: Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling.
abstract: Computational models of cardiac electromechanics (EM) are increasingly being applied to clinical problems, with patient-specific models being generated from high fidelity imaging and used to simulate patient physiology, pathophysiology and response to treatment. Current structured meshes are limited in their ability to fully represent the detailed anatomical data available from clinical images and capture complex and varied anatomy with limited geometric accuracy. In this paper, we review the state of the art in image-based personalization of cardiac anatomy for biophysically detailed, strongly coupled EM modeling, and present our own tools for the automatic building of anatomically and structurally accurate patient-specific models. Our method relies on using high resolution unstructured meshes for discretizing both physics, electrophysiology and mechanics, in combination with efficient, strongly scalable solvers necessary to deal with the computational load imposed by the large number of degrees of freedom of these meshes. These tools permit automated anatomical model generation and strongly coupled EM simulations at an unprecedented level of anatomical and biophysical detail.
authors.affiliation: Institute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010, Graz, Austria.
authors.forename: A
authors.initials: A
authors.lastname: Crozier
authors.affiliation: Institute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010, Graz, Austria.
authors.forename: C M
authors.initials: CM
authors.lastname: Augustin
authors.affiliation: Institute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010, Graz, Austria.
authors.forename: A
authors.initials: A
authors.lastname: Neic
authors.affiliation: Institute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010, Graz, Austria.
authors.forename: A J
authors.initials: AJ
authors.lastname: Prassl
authors.affiliation: Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria.
authors.forename: M
authors.initials: M
authors.lastname: Holler
authors.affiliation: Department of Biomedical Engineering, King's College London, London, United Kingdom.
authors.forename: T E
authors.initials: TE
authors.lastname: Fastl
authors.affiliation: Modeling and Simulation Group, Fraunhofer MEVIS, Bremen, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Hennemuth
authors.affiliation: Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria.
authors.forename: K
authors.initials: K
authors.lastname: Bredies
authors.affiliation: Non-Invasive Cardiac Imaging in Congenital Heart Disease Unit, Charité-Universitätsmedizin, Berlin, Germany.|German Heart Institute, Berlin, Germany.
authors.forename: T
authors.initials: T
authors.lastname: Kuehne
authors.affiliation: Department of Biomedical Engineering, King's College London, London, United Kingdom.
authors.forename: M J
authors.initials: MJ
authors.lastname: Bishop
authors.affiliation: Department of Biomedical Engineering, King's College London, London, United Kingdom.
authors.forename: S A
authors.initials: SA
authors.lastname: Niederer
authors.affiliation: Institute of Biophysics, Medical University of Graz, Harrachgasse 21/IV, 8010, Graz, Austria. gernot.plank@medunigraz.at.
authors.forename: G
authors.identifier: http://orcid.org/0000-0002-7380-6908
authors.initials: G
authors.lastname: Plank
mesh_terms: D000818:Animals; D006321:Heart / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008955:Models, Cardiovascular; D057285:Precision Medicine / Q000379:methods*; D011859:Radiography
keywords: Finite element; High performance computing; Mesh; Myocardial fiber architecture; Strong scaling