34 research outputs found
Effect of myofibril architecture on the active contraction of dystrophic muscle. A mathematical model
No full textDuchenne muscular dystrophy (DMD) is a muscle degenerative disease caused by a mutation in the dystrophin gene. The lack of dystrophin leads to persistent inflammation, degeneration/regeneration cycles of muscle fibers, Ca2+ dysregulation, incompletely regenerated fibers, necrosis, fibrotic tissue replacement, and alterations in the fiber ultrastructure i.e., myofibril misalignment and branched fibers. This work aims to develop a comprehensive chemo-mechanical model of muscle-skeletal tissue accounting for dispersion in myofibrillar orientations, in addition to the disorders in sarcomere pattern and the fiber branching. The model results confirm a significant correlation between the myofibrillar dispersion and the reduction of isometric force in the dystrophic muscle and indicate that the reduction of contraction velocity in the dystrophic muscle seems to be associated with the local disorders in the sarcomere patterns of the myofibrils. Also, the implemented model can predict the force–velocity response to both concentric and eccentric loading. The resulting model represents an original approach to account for defects in the muscle ultrastructure caused by pathologies as DMD
A mathematical model of healthy and dystrophic skeletal muscle biomechanics
No full textDuchenne Muscular Dystrophy (DMD) is a common X-linked disease, caused by mutations in the gene encoding dystrophin and characterized by widespread muscle damage that invariably leads to paralysis and death. Lack of dystrophin in the muscles of DMD patients determines an increased fragility of muscle fibers, leading to repeated cycles of necrosis and regeneration that result in failed regeneration, increased fibrosis and progressive loss of muscle function. In this work, we propose a three-dimensional chemo-mechanical mathematical model of skeletal muscle in DMD. This model is based on stress-strain mechanical data of the muscle and studies of changes in fiber structure and interaction aiming to shade light into the biophysical mechanisms regulating muscle contraction. The results show that the model is able to reproduce the experimental data of maximum isometric force, maximum contraction velocity and concentric normalized F-V curve for the healthy and dystrophic muscle. Furthermore, the model is capable of predicting the force-velocity response of the muscle to eccentric loading without explicitly imposing its functional form in the formulation, and it is able to reproduce the concentric normalized F-V curve of the healthy fiber, as an additional proof of the predictive capabilities of the model. The resulting model represents a novel approach to study DMD pathogenesis by providing insights into the underlying mechanisms of muscle response to force associated with the impaired muscle functionality. Moreover, it could be an innovative tool for researchers to predict muscle response under conditions that are not possible to explore in the laboratory and an important step towards a new paradigm of in-silico trials that could allow identifying novel therapies bypassing the use of animal models
Repolarization Variability Mechanisms and its Relation with Cardiac Arrhytmogenesis
No full textEnhanced temporal variability of ventricular repolarization has been related to increased ventricular arrhythmic risk. In this study, we investigate the influence of stochastic ion channel gating on the variability of four arrhythmic risk biomarkers: action potential (AP) duration (APD), AP triangulation and systolic and diastolic calcium levels. Different levels of white noise, representing different channel numbers, were introduced by means of a stochastic differential equation for the gating variables of the ten Tusscher-Panfilov human ventricular model (TP06). In single cells the rapid and slow delayed rectifier potassium currents (IKr and IKs) were the main contributors to biomarkers variability, which was shown to be increased at fast pacing frequencies, particularly for APD and diastolic calcium. At tissue level, electrotonic coupling masked the effects of stochastic gating on the variability of all the investigated biomarkers. In particular, a very notable reduction in variability was obtained for 2D and 3D tissue models, with 80% reduction with respect to 1D models, and more than 20 folds with respect to isolated cells under physiological conditions. This indicates that large variations in cellular AP are required in order to reproduce physiological variability levels measured in tissue
Validation of the V-index through Finite Element 2D Simulations.
No full textA physiological spatial heterogeneity of ventricular repolarization (SHVR) is responsible for the T-wave on the ECG. However, an increased SHVR might favor the development of ventricular arrhythmias. The V-index is a metric introduced with the aim of assessing SHVR from ECG.
In this work, the V-index was validated by means of 2D computer simulations, using a modified version of the ten Tusscher-Panfilov (TP06) model that accounts for repolarization variability. Synthetic ECG were simulated at 12 different positions at the external surface with two different strategies. Also, a theoretical extension of the V-index definition was derived, to address situations where fluctuations in repolarization times are correlated across nodes.
At tissue level, theoretical values of V-index were in agreement with SHVR with a constant pacing (maximum error: 3.4 ms). However, with a variable RR, a selection of stationary beats was necessary to overcome the stronger temporal correlation across nodes (maximum error: 3.2 ms). On the other hand, values of V-index numerically estimated from the ECG were always in agreement with their theoretical values (average error in the estimates: 15 perpendicular to 9%). The results confirmed that the V-index indeed provides an approximate and reliable measure of SHVR
Oscillatory regime in excitatory media with global coupling: Application to cardiac dynamics
No full textLimitations in electrophysiological model development and validation caused by differences between simulations and experimental protocols
No full textModels of ion channel dynamics are usually built by fitting isolated cell experimental values of individual parameters while neglecting the interaction between them. Another shortcoming regards the estimation of ionic current conductances, which is often based on quantification of Action Potential (AP)-derived markers. Although this procedure reduces the uncertainty in the calculation of conductances, many studies evaluate electrophysiological AP-derived markers from single cell simulations, whereas experimental measurements are obtained from tissue preparations. In this work, we explore the limitations of these approaches to estimate ion channel dynamics and maximum current conductances and how they could be overcome by using multiscale simulations of experimental protocols. Four human ventricular cell models, namely ten Tusscher and Panfilov (2006), Grandi et al. (2010), O'Hara et al. (2011), and Carro et al. (2011), were used. Two problems involving scales from ion channels to tissue were investigated: 1) characterization of L-type calcium voltage-dependent inactivation ICa,L; 2) identification of major ionic conductance contributors to steady-state AP markers, including APD90, APD75, APD50, APD25, Triangulation and maximal and minimal values of V and dV/dt during the AP (Vmax, Vmin, dV/dtmax, dV/dtmin). Our results show that: 1) ICa,Linactivation characteristics differed significantly when calculated from model equations and from simulations reproducing the experimental protocols. 2) Large differences were found in the ionic currents contributors to APD25, Triangulation, Vmax, dV/dtmaxand dV/dtminbetween single cells and 1D-tissue. When proposing any new model formulation, or evaluating an existing model, consistency between simulated and experimental data should be verified considering all involved effects and scales
Structural damage models for fibrous biological soft tissues
No full textAbstractThis paper presents a comparison between deterministic and stochastically based three-dimensional finite-strain damage models for fibrous biological soft tissues, accounting for separate contributions on damage for the matrix and the fibers. Both models are compared in terms of their numerical performance and qualitative predictions under different loading conditions. Continuum damage mechanics is used to describe the softening behavior of soft tissues under large deformation, making use of the concept of internal variables which provides a very general description of materials involving irreversible effects. In the stochastic model, statistical aspects related to the distribution of fiber length lead to the strain-driven damage model for the fibrous part. Simulations of a uniaxial test, a hollowed plate under biaxial displacement control, and a 3D simulation of a coronary artery undergoing balloon angioplasty are used to compare the performance of both models. Numerical simulations indicate that both models provide similar predictions of damage
A response surface optimization approach to adjust ionic current conductances of cardiac electrophysiological models. Application to the study of potassium level changes.
No full textCardiac electrophysiological computational models are often developed from previously published models. The new models may incorporate additional features to adapt the model to a different species or may upgrade a specific ionic formulation based on newly available experimental data. A relevant challenge in the development of a new model is the estimation of certain ionic current conductances that cannot be reliably identified from experiments. A common strategy to estimate those conductances is by means of constrained non-linear least-squares optimization. In this work, a novel methodology is proposed for estimation of ionic current conductances of cardiac electrophysiological models by using a response surface approximation-based constrained optimization with trust region management. Polynomial response surfaces of a number of electrophysiological markers were built using statistical sampling methods. These markers included action potential duration (APD), triangulation, diastolic and systolic intracellular calcium concentration, and time constants of APD rate adaptation. The proposed methodology was applied to update the Carro et al. human ventricular action potential model after incorporation of intracellular potassium ([K+]i) dynamics. While the Carro et al. model was well suited for investigation of arrhythmogenesis, it did not allow simulation of [K+]i changes. With the methodology proposed in this study, the updated Carro et al. human ventricular model could be used to simulate [K+]i changes in response to varying extracellular potassium ([K+]o) levels. Additionally, it rendered values of evaluated electrophysiological markers within physiologically plausible ranges. The optimal values of ionic current conductances in the updated model were found in a notably shorter time than with previously proposed methodologies. As a conclusion, the response surface optimization-based approach proposed in this study allows estimating ionic current conductances of cardiac electrophysiological computational models while guaranteeing replication of key electrophysiological features and with an important reduction in computational cost with respect to previously published approaches. The updated Carro et al. model developed in this study is thus suitable for the investigation of arrhythmic risk-related conditions, including those involving large changes in potassium concentration
Applicability analysis to evaluate credibility of an <i>in silico</i> thrombectomy procedure
No full textIntra-arterial thrombectomy is a minimally invasive procedure in which an obstructing thrombus (clot) is removed using a minimally-invasive device: a stent-retriever. The stent-retriever is first deployed, and then the thrombus is removed during stent-retriever retraction. This procedure can be simulated using a detailed computational model. However, to be useful for an in silico trial in a clinical setting, model credibility should be demonstrated. The aim of this work is to apply a credibility process for the validation phases to the thrombectomy procedure in order to deem it credible for use in an in silico trial. Validation evidence is proposed for the identified context of use and then used to build credibility to the numerical model. Applicability of the proposed model is justified and assessed using a rigorous step-by-step method based on the ASME V&V40 protocol.</p
mRNA expression levels in failing human hearts predict cellular electrophysiological remodelling: A population−based simulation study
No full textDifferences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I, and changes in CaT biomarkers are driven predominantly by reduction in I and SERCA. In particular, the role of I is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure
