2 research outputs found
Incorporating inter-sample variability into cardiac electrophysiology simulations
Sudden cardiac death kills 5-10 people per 10,000 population in Europe and the US each year. Individual propensity to arrhythmia and sudden cardiac death is typically assessed through clinical biomarkers. Variability in these biomarkers is a major challenge for risk stratification. Variability is observed at a wide range of spatio-temporal scales within the heart, from temporal fluctuations in ion channel behaviour, to inter-cell and inter-regional differences in ion channel expression, to structural differences between hearts. The extent to which variability manifests between spatial and temporal scales remains unclear but has a potentially crucial role in determining susceptibility to arrhythmia. In this dissertation we present a multi-scale study of the causes and consequences of variability in electrophysiology. At a sub-cellular level we demonstrate that, taking into account inter-individual variability in ion channel conductance, mRNA expression levels in failing human hearts predict the electrophysiological remodelling observed experimentally. On a tissue scale, we advocate the use of phenomenological models where information on subcellular processes is unavailable. We introduce a modification to a phenomenological model to capture beat-to-beat variability in action potential repolarisation recorded from four individual guinea pig myocytes. We demonstrate that, whilst temporal variability is dramatically reduced by inter-cell coupling, differences in their mean action potential duration may become apparent at a tissue level. The ventricular myocardium has a heterogeneous structure not captured by the simplified representation of conduction used above. In our final case study, we challenge a model of conduction by directly comparing simulations to optical mapping recordings of ventricular activation from failing and non-failing human hearts. We observe that good fits to experimental data are obtained only when endocardially bound structures are not in view, suggesting a role in conduction for these structures that are often ignored in cardiac simulations. Finally, we present future directions for the work presented. We make the case for reporting of inter-sample variability in experimental results and conclude that whilst variability may not always manifest across scales, its impact should be considered in both theoretical and experimental studies.</p
Incorporating inter-sample variability into cardiac electrophysiology simulations
Sudden cardiac death kills 5-10 people per 10,000 population in Europe and the
US each year. Individual propensity to arrhythmia and sudden cardiac death is
typically assessed through clinical biomarkers. Variability in these biomarkers
is a major challenge for risk stratification. Variability is observed at a wide
range of spatio-temporal scales within the heart, from temporal fluctuations in
ion channel behaviour, to inter-cell and inter-regional differences in ion
channel expression, to structural differences between hearts. The extent to
which variability manifests between spatial and temporal scales remains unclear
but has a potentially crucial role in determining susceptibility to
arrhythmia.
In this dissertation we present a multi-scale study of the causes and
consequences of variability in electrophysiology. At a sub-cellular level we
demonstrate that, taking into account inter-individual variability in ion
channel conductance, mRNA expression levels in failing human hearts predict
the electrophysiological remodelling observed experimentally.
On a tissue scale, we advocate the use of phenomenological models where
information on subcellular processes is unavailable. We introduce a modification
to a phenomenological model to capture beat-to-beat variability in action
potential repolarisation recorded from four individual guinea pig myocytes. We
demonstrate that, whilst temporal variability is dramatically reduced by
inter-cell coupling, differences in their mean action potential duration may
become apparent at a tissue level.
The ventricular myocardium has a heterogeneous structure not captured
by the simplified representation of conduction used above. In our final case
study, we challenge a model of conduction by directly comparing simulations to
optical mapping recordings of ventricular activation from failing and
non-failing human hearts. We observe that good fits to experimental data are
obtained only when endocardially bound structures are not in view, suggesting a
role in conduction for these structures that are often ignored in cardiac
simulations.
Finally, we present future directions for the work presented. We make the case
for reporting of inter-sample variability in experimental results and conclude
that whilst variability may not always manifest across scales, its impact should
be considered in both theoretical and experimental studies.</p