TY - JOUR
T1 - Investigating the reference domain influence in personalised models of cardiac mechanics
T2 - Effect of unloaded geometry on cardiac biomechanics
AU - Hadjicharalambous, Myrianthi
AU - Stoeck, Christian T.
AU - Weisskopf, Miriam
AU - Cesarovic, Nikola
AU - Ioannou, Eleftherios
AU - Vavourakis, Vasileios
AU - Nordsletten, David A.
N1 - Funding Information:
The authors would like to acknowledge funding from the University of Cyprus; V.V. acknowledges UCY’s StartUp Grant and the PostDoctoral Fellowships scheme. D.N. would like to acknowledge funding from Engineering and Physical Sciences Research Council (EP/N011554/1 and EP/R003866/1). CTS would like to acknowledge funding from Swiss national science foundation (PZ00P2_174144).
Funding Information:
Financial support was received from the University of Cyprus, the Engineering and Physical Sciences Research Council (EP/N011554/1 and EP/R003866/1) and from Swiss national science foundation (PZ00P2_174144).
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/8
Y1 - 2021/8
N2 - A major concern in personalised models of heart mechanics is the unknown zero-pressure domain, a prerequisite for accurately predicting cardiac biomechanics. As the reference configuration cannot be captured by clinical data, studies often employ in-vivo frames which are unlikely to correspond to unloaded geometries. Alternatively, zero-pressure domain is approximated through inverse methodologies, which, however, entail assumptions pertaining to boundary conditions and material parameters. Both approaches are likely to introduce biases in estimated biomechanical properties; nevertheless, quantification of these effects is unattainable without ground-truth data. In this work, we assess the unloaded state influence on model-derived biomechanics, by employing an in-silico modelling framework relying on experimental data on porcine hearts. In-vivo images are used for model personalisation, while in-situ experiments provide a reliable approximation of the reference domain, creating a unique opportunity for a validation study. Personalised whole-cycle cardiac models are developed which employ different reference domains (image-derived, inversely estimated) and are compared against ground-truth model outcomes. Simulations are conducted with varying boundary conditions, to investigate the effect of data-derived constraints on model accuracy. Attention is given to modelling the influence of the ribcage on the epicardium, due to its close proximity to the heart in the porcine anatomy. Our results find merit in both approaches for dealing with the unknown reference domain, but also demonstrate differences in estimated biomechanical quantities such as material parameters, strains and stresses. Notably, they highlight the importance of a boundary condition accounting for the constraining influence of the ribcage, in forward and inverse biomechanical models.
AB - A major concern in personalised models of heart mechanics is the unknown zero-pressure domain, a prerequisite for accurately predicting cardiac biomechanics. As the reference configuration cannot be captured by clinical data, studies often employ in-vivo frames which are unlikely to correspond to unloaded geometries. Alternatively, zero-pressure domain is approximated through inverse methodologies, which, however, entail assumptions pertaining to boundary conditions and material parameters. Both approaches are likely to introduce biases in estimated biomechanical properties; nevertheless, quantification of these effects is unattainable without ground-truth data. In this work, we assess the unloaded state influence on model-derived biomechanics, by employing an in-silico modelling framework relying on experimental data on porcine hearts. In-vivo images are used for model personalisation, while in-situ experiments provide a reliable approximation of the reference domain, creating a unique opportunity for a validation study. Personalised whole-cycle cardiac models are developed which employ different reference domains (image-derived, inversely estimated) and are compared against ground-truth model outcomes. Simulations are conducted with varying boundary conditions, to investigate the effect of data-derived constraints on model accuracy. Attention is given to modelling the influence of the ribcage on the epicardium, due to its close proximity to the heart in the porcine anatomy. Our results find merit in both approaches for dealing with the unknown reference domain, but also demonstrate differences in estimated biomechanical quantities such as material parameters, strains and stresses. Notably, they highlight the importance of a boundary condition accounting for the constraining influence of the ribcage, in forward and inverse biomechanical models.
KW - Finite-element simulations
KW - Inverse methodologies
KW - Patient-specific model
KW - Unloaded geometry
KW - Zero-pressure domain
UR - http://www.scopus.com/inward/record.url?scp=85106680370&partnerID=8YFLogxK
U2 - 10.1007/s10237-021-01464-2
DO - 10.1007/s10237-021-01464-2
M3 - Article
AN - SCOPUS:85106680370
SN - 1617-7959
VL - 20
SP - 1579
EP - 1597
JO - Biomechanics and Modeling in Mechanobiology
JF - Biomechanics and Modeling in Mechanobiology
IS - 4
ER -