@article{1b75e267775f4bc2a340c06050cbf573,
title = "Estimation of passive and active properties in the human heart using 3D tagged MRI",
abstract = "Advances in medical imaging and image processing are paving the way for personalised cardiac biomechanical 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 biomechanical analysis.",
keywords = "3D tagged MRI, Cardiac mechanics, Parameter estimation, Patient-specific modelling",
author = "Liya Asner and Myrianthi Hadjicharalambous and Radomir Chabiniok and Devis Peresutti and Eva Sammut and James Wong and Gerald Carr-White and Philip Chowienczyk and Jack Lee and Andrew King and Nicolas Smith and Reza Razavi and David Nordsletten",
note = "Funding Information: The authors would like to acknowledge funding from the BHF New Horizons Program (NH/11/5/29058) and the Engineering and Physical Sciences Research Council (EP/H046410/1 and EP/K030310/1), and support from the Wellcome Trust EPSRC Centre of Excellence in Medical Engineering (WT 088641/Z/09/Z) and the NIHR Biomedical Research Centre at Guy's and St. Thomas' NHS Foundation Trust and KCL. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the DoH. The Image Registration Toolkit (IRTK) was used under Licence from Ixico Ltd. The authors would like to thank Dr E. Kerfoot for providing medical image and model visualisation software. Work presented is funded by the BHF New Horizons program (NH/11/5/29058). Funding Information: Work presented is funded by the BHF New Horizons program (NH/11/5/29058). Funding Information: The authors would like to acknowledge funding from the BHF New Horizons Program (NH/11/5/29058) and the Engineering and Physical Sciences Research Council (EP/H046410/1 and EP/K030310/1), and support from the Wellcome Trust EPSRC Centre of Excellence in Medical Engineering (WT 088641/Z/09/Z) and the NIHR Biomedical Research Centre at Guy{\textquoteright}s and St. Thomas{\textquoteright} NHS Foundation Trust and KCL. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the DoH. The Image Registration Toolkit (IRTK) was used under Licence from Ixico Ltd. The authors would like to thank Dr E. Kerfoot for providing medical image and model visualisation software. Publisher Copyright: {\textcopyright} 2015, The Author(s).",
year = "2016",
month = oct,
day = "1",
doi = "10.1007/s10237-015-0748-z",
language = "English (US)",
volume = "15",
pages = "1121--1139",
journal = "Biomechanics and Modeling in Mechanobiology",
issn = "1617-7959",
publisher = "Springer Verlag",
number = "5",
}