title: High-resolution data assimilation of cardiac mechanics applied to a dyssynchronous ventricle.
abstract: Computational models of cardiac mechanics, personalized to a patient, offer access to mechanical information above and beyond direct medical imaging. Additionally, such models can be used to optimize and plan therapies in-silico, thereby reducing risks and improving patient outcome. Model personalization has traditionally been achieved by data assimilation, which is the tuning or optimization of model parameters to match patient observations. Current data assimilation procedures for cardiac mechanics are limited in their ability to efficiently handle high-dimensional parameters. This restricts parameter spatial resolution, and thereby the ability of a personalized model to account for heterogeneities that are often present in a diseased or injured heart. In this paper, we address this limitation by proposing an adjoint gradient-based data assimilation method that can efficiently handle high-dimensional parameters. We test this procedure on a synthetic data set and provide a clinical example with a dyssynchronous left ventricle with highly irregular motion. Our results show that the method efficiently handles a high-dimensional optimization parameter and produces an excellent agreement for personalized models to both synthetic and clinical data.
authors.affiliation: Simula Research Laboratory, P.O. Box 134 1325 Lysaker, Norway.|Department of Informatics, University of Oslo, P.O. Box 1080, Blindern 0316 Oslo, Norway.|Center for Cardiological Innovation, Songsvannsveien 9, 0372 Oslo, Norway.
authors.forename: Gabriel
authors.identifier: 0000-0002-6794-9611
authors.initials: G
authors.lastname: Balaban
authors.affiliation: Simula Research Laboratory, P.O. Box 134 1325 Lysaker, Norway.|Department of Informatics, University of Oslo, P.O. Box 1080, Blindern 0316 Oslo, Norway.|Center for Cardiological Innovation, Songsvannsveien 9, 0372 Oslo, Norway.
authors.forename: Henrik
authors.initials: H
authors.lastname: Finsberg
authors.affiliation: Faculty of Medicine, University of Oslo, P.O. Box 1078 Blindern, 0316 Oslo, Norway.|Department of Pediatrics, Oslo University Hospital, PO Nydalen, Oslo, Norway.
authors.forename: Hans Henrik
authors.initials: HH
authors.lastname: Odland
authors.affiliation: Simula Research Laboratory, P.O. Box 134 1325 Lysaker, Norway.|Department of Mathematics, University of Oslo, P.O Box 1053, Blindern 0316 Oslo, Norway.
authors.forename: Marie E
authors.initials: ME
authors.lastname: Rognes
authors.affiliation: Faculty of Medicine, University of Oslo, P.O. Box 1078 Blindern, 0316 Oslo, Norway.|Center for Cardiological Innovation, Songsvannsveien 9, 0372 Oslo, Norway.
authors.forename: Stian
authors.initials: S
authors.lastname: Ross
authors.affiliation: Simula Research Laboratory, P.O. Box 134 1325 Lysaker, Norway.|Department of Informatics, University of Oslo, P.O. Box 1080, Blindern 0316 Oslo, Norway.|Center for Cardiological Innovation, Songsvannsveien 9, 0372 Oslo, Norway.
authors.forename: Joakim
authors.initials: J
authors.lastname: Sundnes
authors.affiliation: Simula Research Laboratory, P.O. Box 134 1325 Lysaker, Norway.|Center for Cardiological Innovation, Songsvannsveien 9, 0372 Oslo, Norway.|Department of Mathematical Science and Technology, Norwegian University of Life Sciences, Universitetstunet 3 1430 Ås, Norway.
authors.forename: Samuel
authors.initials: S
authors.lastname: Wall
mesh_terms: D001696:Biomechanical Phenomena; D006352:Heart Ventricles / Q000033:anatomy & histology / Q000503:physiopathology*; D006801:Humans; D008954:Models, Biological
keywords: adjoint, cardiac mechanics, data assimilation, dyssynchrony, patient specific