152 research outputs found
Code for: Credibility Assessment of Patient-Specific Computational Modeling using Patient-Specific Cardiac Modeling as an Exemplar
No full textCode for used to run the simulation studies in
Credibility Assessment of Patient-Specific Computational Modeling using Patient-Specific Cardiac Modeling as an Exemplar
S. Galappaththige, R. Gray, C. Costa, S. Niederer and P. Pathmanathan
(under submission
A comparison of discrete and continuum models of cardiac electrophysiology
No full textWhen modelling tissue-level cardiac electrophysiology, a continuum approximation to the discrete cell-level equations, known as the bidomain equations, is often used to maintain computational tractability. The bidomain equations are derived from the discrete equations using a mathematical technique known as homogenisation. As part of this derivation conductivity tensors are specified for use in the continuum model. Analysing the derivation of the bidomain equations allows us to investigate how microstructure, in particular gap junctions that electrically connect cells, affect tissue-level conductivity properties and model solutions. We perform two distinct but related strands of investigation in this thesis. In the first, we consider the effect of including gap junctions on the results of both discrete and continuum simulations, and identify when the continuum model fails to be a good approximation to the discrete model. Secondly, we perform a comprehensive study into how cell-level microstructure properties, such as cell shape, impact the homogenised conductivities to be used in a tissue-level continuum model. This will allow us to predict how the onset of a disease or a change in cellular microstructure will affect the propagation of action potentials. To do this, we first derive a modified version of the bidomain equations that explicitly takes gap junctions into account. We then derive analytic solutions for the homogenised conductivity tensors on a simplified two-dimensional geometry and find that diseased gap junctions have a large impact on the results of homogenisation. On this same geometry we compare the results of discrete and continuum simulations and find a significant discrepancy between model conduction velocities when we introduce gap junctions with lower coupling strength, or when we consider elongated cells. From this, we conclude that the bidomain equations are less likely to give an accurate representation of the underlying discrete system when modelling diseased states whose symptoms include reduced gap junction coupling or an increase in myocyte length. We then use a more realistic two-dimensional geometry and numerically approximate the homogenised conductivity tensors on this geometry. We discover that the packing of cells has a substantial effect on conduction, with a brick-wall geometry particularly beneficial for fast propagation, and that gap junctions also have a large effect on conduction. Finally, we consider a three-dimensional cellular geometry and show that the effect of changing gap junction properties is different when compared to two dimensions, and discover that the anisotropy ratios of the tissue are highly sensitive to changes in gap junction parameters. Overall, we conclude that gap junctions and cell structure have a large effect on discrete and continuum model results, and on homogenised conductivity calculations in tissue-level cardiac electrophysiology
Impact of tissue microstructure on a model of cardiac electromechanics based on MRI data
No full textCardiac motion is a vital process as it sustains the pumping of blood in the body. For this reason motion abnormalities are often associated with severe cardiac pathologies. Clinical imaging techniques, such as MRI, are powerful in assessing motion abnormalities but their connection with pathology often remains unknown.

Computational models of cardiac motion, integrating imaging data, would thus be of great help in linking tissue structure (i.e. cells organisation into fibres and sheets) to motion abnormalities and to pathology. Current models, though, are not able yet to correctly predict realistic cardiac motion in the healthy or diseased heart.

Our hypothesis is that a more realistic description of tissue structure within an electromechanical model of the heart, with structural information extracted from data rather than mathematically defined, and a more careful definition of tissue material properties, would better represent the high heterogeneity of cardiac tissue, thus improving the predictive power of the model
Code for: Model evaluation framework for epidemiological models with application to COVID-19 models
No full textPython code used to generate the results of
Model evaluation framework for epidemiological models with application to COVID-19 models
by K. Dautel, E. Agyingi and P. Pathmanatha
Ensuring reliability of safety-critical clinical applications of computational cardiac models
No full textComputational models of cardiac electro-physiology have been used for over half a century to investigate physiological mechanisms and generate hypotheses for experimental testing, and are now starting to play a role in clinical applications. There is currently a great deal of interest in using models as diagnostic or therapeutic aids, for example using patient-specific whole-heart simulations to optimise cardiac resynchronization therapy, ablation therapy, and defibrillation. However, if models are to be used in safety-critical clinical decision making, the reliability of their predictions needs to be thoroughly investigated. In engineering and the physical sciences, the field of 'verification, validation and uncertainty quantification' (VVUQ) (also known as 'verification and validation' (V&V)) has been developed for rigorously evaluating the credibility of computational model predictions. In this article we first discuss why it is vital that cardiac models be developed and evaluated within a VVUQ framework, and then consider cardiac models in the context of each of the stages in VVUQ. We identify some of the major difficulties which may need to be overcome for cardiac models to be used in safely-critical clinical applications
Validation and Trustworthiness of Multiscale Models of Cardiac Electrophysiology
No full textComputational models of cardiac electrophysiology have a long history in basic science applications and device design and evaluation, but have significant potential for clinical applications in all areas of cardiovascular medicine, including functional imaging and mapping, drug safety evaluation, disease diagnosis, patient selection, and therapy optimisation or personalisation. For all stakeholders to be confident in model-based clinical decisions, cardiac electrophysiological (CEP) models must be demonstrated to be trustworthy and reliable. Credibility, that is, the belief in the predictive capability, of a computational model is primarily established by performing validation, in which model predictions are compared to experimental or clinical data. However, there are numerous challenges to performing validation for highly complex multi-scale physiological models such as CEP models. As a result, credibility of CEP model predictions is usually founded upon a wide range of distinct factors, including various types of validation results, underlying theory, evidence supporting model assumptions, evidence from model calibration, all at a variety of scales from ion channel to cell to organ. Consequently, it is often unclear, or a matter for debate, the extent to which a CEP model can be trusted for a given application. The aim of this article is to clarify potential rationale for the trustworthiness of CEP models by reviewing evidence that has been (or could be) presented to support their credibility. We specifically address the complexity and multi-scale nature of CEP models which makes traditional model evaluation difficult. In addition, we make explicit some of the credibility justification that we believe is implicitly embedded in the CEP modeling literature. Overall, we provide a fresh perspective to CEP model credibility, and build a depiction and categorisation of the wide-ranging body of credibility evidence for CEP models. This paper also represents a step toward the extension of model evaluation methodologies that are currently being developed by the medical device community, to physiological models
Patient-Specific Cardiovascular Computational Modeling: Diversity of Personalization and Challenges
No full textEffect of Fibre Orientation Optimisation in an Electromechanical Model of Left Ventricular Contraction in Rat
No full textSubject-specific, or personalised, modelling is one of the main targets in current cardiac modelling research. The aim of this study is to assess the improvement in predictive power gained by introducing subject-specific fibre models within an electromechanical model of left ventricular contraction in rat. A quantitative comparison of a series of global rule-based fibre models with an image-based locally optimised fibre model was performed. Our results show small difference in the predicted values of ejection fraction, wall thickening and base-to-apex shortening between the fibre models considered. In comparison, much larger differences appear between predicted values and those measured in experimental images. Further study of the constitutive behaviour and architecture of cardiac tissue is required before electromechanical models can fully benefit from the introduction of subject-specific fibres. Additionally, our study shows that, in the current model, an orthotropic description of the tissue is preferable to a transversely isotropic one, for the metrics considered. © 2013 Springer-Verlag
A Parsimonious Model of the Rabbit Action Potential Elucidates the Minimal Physiological Requirements for Alternans and Spiral Wave Breakup.
No full textElucidating the underlying mechanisms of fatal cardiac arrhythmias requires a tight integration of electrophysiological experiments, models, and theory. Existing models of transmembrane action potential (AP) are complex (resulting in over parameterization) and varied (leading to dissimilar predictions). Thus, simpler models are needed to elucidate the "minimal physiological requirements" to reproduce significant observable phenomena using as few parameters as possible. Moreover, models have been derived from experimental studies from a variety of species under a range of environmental conditions (for example, all existing rabbit AP models incorporate a formulation of the rapid sodium current, INa, based on 30 year old data from chick embryo cell aggregates). Here we develop a simple "parsimonious" rabbit AP model that is mathematically identifiable (i.e., not over parameterized) by combining a novel Hodgkin-Huxley formulation of INa with a phenomenological model of repolarization similar to the voltage dependent, time-independent rectifying outward potassium current (IK). The model was calibrated using the following experimental data sets measured from the same species (rabbit) under physiological conditions: dynamic current-voltage (I-V) relationships during the AP upstroke; rapid recovery of AP excitability during the relative refractory period; and steady-state INa inactivation via voltage clamp. Simulations reproduced several important "emergent" phenomena including cellular alternans at rates > 250 bpm as observed in rabbit myocytes, reentrant spiral waves as observed on the surface of the rabbit heart, and spiral wave breakup. Model variants were studied which elucidated the minimal requirements for alternans and spiral wave break up, namely the kinetics of INa inactivation and the non-linear rectification of IK.The simplicity of the model, and the fact that its parameters have physiological meaning, make it ideal for engendering generalizable mechanistic insight and should provide a solid "building-block" to generate more detailed ionic models to represent complex rabbit electrophysiology
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