In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 19, No. 6 ( 2023-6-26), p. e1011257-
Abstract:
Cardiac pump function arises from a series of highly orchestrated events across multiple scales. Computational electromechanics can encode these events in physics-constrained models. However, the large number of parameters in these models has made the systematic study of the link between cellular, tissue, and organ scale parameters to whole heart physiology challenging. A patient-specific anatomical heart model, or digital twin, was created. Cellular ionic dynamics and contraction were simulated with the Courtemanche-Land and the ToR-ORd-Land models for the atria and the ventricles, respectively. Whole heart contraction was coupled with the circulatory system, simulated with CircAdapt, while accounting for the effect of the pericardium on cardiac motion. The four-chamber electromechanics framework resulted in 117 parameters of interest. The model was broken into five hierarchical sub-models: tissue electrophysiology, ToR-ORd-Land model, Courtemanche-Land model, passive mechanics and CircAdapt. For each sub-model, we trained Gaussian processes emulators (GPEs) that were then used to perform a global sensitivity analysis (GSA) to retain parameters explaining 90% of the total sensitivity for subsequent analysis. We identified 45 out of 117 parameters that were important for whole heart function. We performed a GSA over these 45 parameters and identified the systemic and pulmonary peripheral resistance as being critical parameters for a wide range of volumetric and hemodynamic cardiac indexes across all four chambers. We have shown that GPEs provide a robust method for mapping between cellular properties and clinical measurements. This could be applied to identify parameters that can be calibrated in patient-specific models or digital twins, and to link cellular function to clinical indexes.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1011257
DOI:
10.1371/journal.pcbi.1011257.g001
DOI:
10.1371/journal.pcbi.1011257.g002
DOI:
10.1371/journal.pcbi.1011257.g003
DOI:
10.1371/journal.pcbi.1011257.g004
DOI:
10.1371/journal.pcbi.1011257.g005
DOI:
10.1371/journal.pcbi.1011257.g006
DOI:
10.1371/journal.pcbi.1011257.g007
DOI:
10.1371/journal.pcbi.1011257.g008
DOI:
10.1371/journal.pcbi.1011257.g009
DOI:
10.1371/journal.pcbi.1011257.g010
DOI:
10.1371/journal.pcbi.1011257.t001
DOI:
10.1371/journal.pcbi.1011257.t002
DOI:
10.1371/journal.pcbi.1011257.t003
DOI:
10.1371/journal.pcbi.1011257.t004
DOI:
10.1371/journal.pcbi.1011257.s001
DOI:
10.1371/journal.pcbi.1011257.s002
DOI:
10.1371/journal.pcbi.1011257.s003
DOI:
10.1371/journal.pcbi.1011257.s004
DOI:
10.1371/journal.pcbi.1011257.s005
DOI:
10.1371/journal.pcbi.1011257.s006
DOI:
10.1371/journal.pcbi.1011257.s007
DOI:
10.1371/journal.pcbi.1011257.s008
DOI:
10.1371/journal.pcbi.1011257.s009
DOI:
10.1371/journal.pcbi.1011257.s010
DOI:
10.1371/journal.pcbi.1011257.s011
DOI:
10.1371/journal.pcbi.1011257.s012
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2193340-6
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