1. Estimation of passive and active properties in the human heart using 3D tagged MRI
- Author
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Reza Razavi, Gerald Carr-White, Radomir Chabiniok, Philip Chowienczyk, Devis Peresutti, Eva Sammut, Andrew P. King, David Nordsletten, Myrianthi Hadjicharalambous, Jack Lee, Nicolas P. Smith, Liya Asner, James Wong, 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), École polytechnique (X)-MINES ParisTech - 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 ParisTech - 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, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Department of cardiology [Guy's and St. Thomas ' hospitals] [London], Guy's and St Thomas' Hospital [London]-Guy's Hospital [London], Department of Clinical Pharmacology [London], Faculty of Engineering [Auckland], University of Auckland [Auckland], École polytechnique (X)-Mines Paris - PSL (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 Paris - PSL (École nationale supérieure des mines de Paris)
- Subjects
Computer science ,Systole ,Patient-specific modelling ,[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging ,Pipeline (computing) ,0206 medical engineering ,Image processing ,02 engineering and technology ,Kinematics ,computer.software_genre ,030218 nuclear medicine & medical imaging ,Magnetic Resonance Imaging/methods ,3D tagged MRI ,03 medical and health sciences ,0302 clinical medicine ,Imaging, Three-Dimensional ,Modelling and Simulation ,Medical imaging ,Parameter estimation ,Humans ,[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP] ,Computer Simulation ,Original Paper ,Estimation theory ,Mechanical Engineering ,Model selection ,Systole/physiology ,Heart ,020601 biomedical engineering ,Magnetic Resonance Imaging ,Heart/physiology ,Cardiac mechanics ,Modeling and Simulation ,Identifiability ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,Data mining ,Noise (video) ,computer ,Biotechnology - Abstract
International audience; Advances in medical imaging and image processing are paving the way for personalised cardiac biomechani-cal modelling. Models provide the capacity to relate kinematics to dynamics and—through patient-specific modelling— derived material parameters to underlying cardiac muscle pathologies. However, for clinical utility to be achieved, model-based analyses mandate robust model selection and parameterisation. In this paper, we introduce a patient-specific biomechanical model for the left ventricle aiming to balance model fidelity with parameter identifiability. Using non-invasive data and common clinical surrogates, we illustrate unique identifiability of passive and active parameters over the full cardiac cycle. Identifiability and accuracy of the estimates in the presence of controlled noise are verified with a number of in silico datasets. Unique parametrisation is then obtained for three datasets acquired in vivo. The model predictions show good agreement with the data extracted from the images providing a pipeline for personalised biomechan-ical analysis.
- Published
- 2015
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