Computational modeling of acute myocardial infarction

Advancement in computational simulation and validation of congenital heart disease: a review

The improvement in congenital heart disease (CHD) treatment and management has increased the life expectancy in infants. However, the long-term efficacy is difficult to assess and thus, computational modelling has been applied for evaluating this. Here, we provide an overview of the applications of computational modelling in CHD based on three categories; CHD involving large blood vessels only, heart chambers only, and CHD that occurs at multiple heart structures. We highlight the advancement of computational simulation of CHD that uses multiscale and multiphysics modelling to ensure a complete representation of the heart and circulation. We provide a brief future direction of computational modelling of CHD such as to include growth and remodelling, detailed conduction system, and occurrence of myocardial infarction. We also proposed validation technique using advanced three-dimensional (3D) printing and particle image velocimetry (PIV) technologies to improve the model accuracy.

Preclinical Models of Cardiac Disease: A Comprehensive Overview for Clinical Scientists

For recent decades, cardiac diseases have been the leading cause of death and morbidity worldwide. Despite significant achievements in their management, profound understanding of disease progression is limited. The lack of biologically relevant and robust preclinical disease models that truly grasp the molecular underpinnings of cardiac disease and its pathophysiology attributes to this stagnation, as well as the insufficiency of platforms that effectively explore novel therapeutic avenues. The area of fundamental and translational cardiac research has therefore gained wide interest of scientists in the clinical field, while the landscape has rapidly evolved towards an elaborate array of research modalities, characterized by diverse and distinctive traits. As a consequence, current literature lacks an intelligible and complete overview aimed at clinical scientists that focuses on selecting the optimal platform for translational research questions. In this review, we present an elaborate overview of current in vitro, ex vivo, in vivo and in silico platforms that model cardiac health and disease, delineating their main benefits and drawbacks, innovative prospects, and foremost fields of application in the scope of clinical research incentives.

Assessment of the elastic stiffness of human cardiac fibres after an apical infarction using finite element simulation

Several research works in the literature have focused on understanding the post-infarction ventricular remodelling phenomenon, but few works have considered the evaluation of the elastic behaviour of the cardiac tissue after a myocardial infarction. This paper presents an investigation focused on predicting the elastic performance of the human heart after a left ventricular apical infarction. The aim is to understand the elastic alterations of the cardiac fibres at different periods after an apical infarct. For this purpose, a hybrid method based on pressure and volume measurements of the left ventricle (LV) at different periods of ventricular remodelling, and the Finite Element Method (FEM), is developed. In addition, several performance indexes are defined to evaluate the heart performance during the ventricular remodelling process. The results show that during the first 2 weeks after a heart infarction, the cardiac fibres must support a much higher structural overload than during normal conditions. This structural overload is proportional to the aneurysm size but diminishes with the time, together with a significant reduction of the ventricular pumping capacity.

Biaxial Estimation of Biomechanical Constitutive Parameters of Passive Porcine Sclera Soft Tissue

This study assesses the modelling capabilities of four constitutive hyperelastic material models to fit the experimental data of the porcine sclera soft tissue. It further estimates the material parameters and discusses their applicability to a finite element model by examining the statistical dispersion measured through the standard deviation. Fifteen sclera tissues were harvested from porcine' slaughtered at an abattoir and were subjected to equi-biaxial testing. The results show that all the four material models yielded very good correlations at correlations above 96%. The polynomial (anisotropic) model gave the best correlation of 98%. However, the estimated material parameters varied widely from one test to another such that there would be need to normalise the test data to avoid long optimisation processes after applying the average material parameters to finite element models. However, for application of the estimated material parameters to finite element models, there would be need to consider normalising the test data to reduce the search region for the optimisation algorithms. Although the polynomial (anisotropic) model yielded the best correlation, it was found that the Choi-Vito had the least variation in the estimated material parameters, thereby making it an easier option for application of its material parameters to a finite element model and requiring minimum effort in the optimisation procedure. For the porcine sclera tissue, it was found that the anisotropy was more influenced by the fiber-related properties than the background material matrix-related properties.

Using models to advance medicine: mathematical modeling of post-myocardial infarction left ventricular remodeling

The heart is an organ with limited capacity for regeneration and repair. The irreversible cell death and corresponding diminished ability of the heart to repair after myocardial infarction (MI), is a leading cause of morbidity and mortality worldwide. In this paper, a new mathematical model is presented to study the left ventricular (LV) remodeling and associated events after MI. The model accurately describes and predicts the interactions among heart cells and the immune system post-MI in the absence of medical interventions. The resulting system of nonlinear ordinary differential equations is studied both analytically and numerically in order to demonstrate the functionality and performance of the new model. To the best of our knowledge, this model is the only one of its kind to consider and correctly apply all of the known factors in diseased heart LV modeling. This model has the potential to provide researchers with a predictive computational tool to better understand the MI pathology and develop various cell-based treatment options, with benefits of lowering the cost and reducing the development time.

Precision medicine in human heart modeling : Perspectives, challenges, and opportunities

Precision medicine is a new frontier in healthcare that uses scientific methods to customize medical treatment to the individual genes, anatomy, physiology, and lifestyle of each person. In cardiovascular health, precision medicine has emerged as a promising paradigm to enable cost-effective solutions that improve quality of life and reduce mortality rates. However, the exact role in precision medicine for human heart modeling has not yet been fully explored. Here, we discuss the challenges and opportunities for personalized human heart simulations, from diagnosis to device design, treatment planning, and prognosis. With a view toward personalization, we map out the history of anatomic, physical, and constitutive human heart models throughout the past three decades. We illustrate recent human heart modeling in electrophysiology, cardiac mechanics, and fluid dynamics and highlight clinically relevant applications of these models for drug development, pacing lead failure, heart failure, ventricular assist devices, edge-to-edge repair, and annuloplasty. With a view toward translational medicine, we provide a clinical perspective on virtual imaging trials and a regulatory perspective on medical device innovation. We show that precision medicine in human heart modeling does not necessarily require a fully personalized, high-resolution whole heart model with an entire personalized medical history. Instead, we advocate for creating personalized models out of population-based libraries with geometric, biological, physical, and clinical information by morphing between clinical data and medical histories from cohorts of patients using machine learning. We anticipate that this perspective will shape the path toward introducing human heart simulations into precision medicine with the ultimate goals to facilitate clinical decision making, guide treatment planning, and accelerate device design.

Towards the simulation of active cardiac mechanics using a smoothed finite element method

In the last decades, various computational models have been developed to simulate cardiac electromechanics. The most common numerical tool is the finite element method (FEM). However, this method crucially depends on the mesh quality. For complex geometries such as cardiac structures, it is convenient to use tetrahedral discretisations which can be generated automatically. On the other hand, such automatic meshing with tetrahedrons together with large deformations often lead to elements distortion and volumetric locking. To overcome these difficulties, different smoothed finite element methods (S-FEMs) have been proposed in the recent years. They are known to be volumetric locking free, less sensitive to mesh distortion and so far have been used e.g. in simulation of passive cardiac mechanics. In this work, we extend for the first time node-based S-FEM (NS-FEM) towards active cardiac mechanics. Firstly, the sensitivity to mesh distortion is tested and compared to that of FEM. Secondly, an active contraction in circumferentially aligned fibre direction is modelled in the healthy and the infarcted case. We show, that the proposed method is more robust with respect to mesh distortion and computationally more efficient than standard FEM. Being furthermore free of volumetric locking problems makes S-FEM a promising alternative in modelling of active cardiac mechanics, respectively electromechanics.

The study of border zone formation in ischemic heart using electro-chemical coupled computational model

Myocardial infarction (MI) is the most common cause of a heart failure, which occurs due to myocardial ischemia leading to left ventricular (LV) remodeling. LV remodeling particularly occurs at the ischemic area and the region surrounds it, known as the border zone. The role of the border zone in initiating LV remodeling process urges the investigation on the correlation between early border zone changes and remodeling outcome. Thus, this study aims to simulate a preliminary conceptual work of the border zone formation and evolution during onset of MI and its effect towards early LV remodeling processes by incorporating the oxygen concentration effect on the electrophysiology of an idealized three-dimensional LV through electro-chemical coupled mathematical model. The simulation result shows that the region of border zone, represented by the distribution of electrical conductivities, keeps expanding over time. Based on this result, the border zone is also proposed to consist of three sub-regions, namely mildly, moderately, and seriously impaired conductivity regions, which each region categorized depending on its electrical conductivities. This division could be used as a biomarker for classification of reversible and irreversible myocardial injury and will help to identify the different risks for the survival of patient. Larger ischemic size and complete occlusion of the coronary artery can be associated with an increased risk of developing irreversible injury, in particular if the reperfusion treatment is delayed. Increased irreversible injury area can be related with cardiovascular events and will further deteriorate the LV function over time.

The study of myocardial ischemia-reperfusion treatment through computational modelling

Reperfusion of the blood flow to ischemic myocardium is the standard treatment for patients suffering myocardial infarction. However, the reperfusion itself can also induce myocardial injury, in which the actual mechanism and its risk factors remain unclear. This work aims to study the mechanism of ischemia-reperfusion treatment using a three-dimensional (3D) oxygen diffusion model. An electrical model is then coupled to an oxygen model to identify the possible region of myocardial damage. Our findings show that the value of oxygen exceeds its optimum (>1.0) at the ischemic area during early reperfusion period. This complication was exacerbated in a longer ischemic period. While a longer reperfusion time causes a continuous excessive oxygen supply to the ischemic area throughout the reperfusion time. This work also suggests the use of less than 0.8 of initial oxygen concentration in the reperfusion treatment to prevent undesired upsurge at the early reperfusion period and further myocardial injury. We also found the region at risk for myocardial injury is confined in the ischemic vicinity revealed by its electrical conductivity impairment. Although there is a risk that reperfusion leads to myocardial injury for excessive oxygen accumulation, the reperfusion treatment is helpful in reducing the infarct size.

Biomechanics of infarcted left ventricle: a review of modelling

Mathematical modelling in biomechanics of infarcted left ventricle (LV) serves as an indispensable tool for remodelling mechanism exploration, LV biomechanical property estimation and therapy assessment after myocardial infarction (MI). However, a review of mathematical modelling after MI has not been seen in the literature so far. In the paper, a systematic review of mathematical models in biomechanics of infarcted LV was established. The models include comprehensive cardiovascular system model, essential LV pressure-volume and stress-stretch models, constitutive laws for passive myocardium and scars, tension models for active myocardium, collagen fibre orientation optimization models, fibroblast and collagen fibre growth/degradation models and integrated growth-electro-mechanical model after MI. The primary idea, unique characteristics and key equations of each model were identified and extracted. Discussions on the models were provided and followed research issues on them were addressed. Considerable improvements in the cardiovascular system model, LV aneurysm model, coupled agent-based models and integrated electro-mechanical-growth LV model are encouraged. Substantial attention should be paid to new constitutive laws with respect to stress-stretch curve and strain energy function for infarcted passive myocardium, collagen fibre orientation optimization in scar, cardiac rupture and tissue damage and viscoelastic effect post-MI in the future.

A framework for biomechanics simulations using four-chamber cardiac models

Computational cardiac models have been extensively used to study different cardiac biomechanics; specifically, finite-element analysis has been one of the tools used to study the internal stresses and strains in the cardiac wall during the cardiac cycle. Cubic-Hermite finite element meshes have been used for simulating cardiac biomechanics due to their convergence characteristics and their ability to capture smooth geometries compactly-fewer elements are needed to build the cardiac geometry-compared to linear tetrahedral meshes. Such meshes have previously been used only with simple ventricular geometries with non-physiological boundary conditions due to challenges associated with creating cubic-Hermite meshes of the complex heart geometry. However, it is critical to accurately capture the different geometric characteristics of the heart and apply physiologically equivalent boundary conditions to replicate the in vivo heart motion. In this work, we created a four-chamber cardiac model utilizing cubic-Hermite elements and simulated a full cardiac cycle by coupling the 3D finite element model with a lumped circulation model. The myocardial fiber-orientations were interpolated within the mesh using the Log-Euclidean method to overcome the singularity associated with interpolation of orthogonal matrices. Physiologically equivalent rigid body constraints were applied to the nodes along the valve plane and the accuracy of the resulting simulations were validated using open source clinical data. We then simulated a complete cardiac cycle of a healthy heart and a heart with acute myocardial infarction. We compared the pumping functionality of the heart for both cases by calculating the ventricular work. We observed a 20% reduction in acute work done by the heart immediately after myocardial infarction. The myocardial wall displacements obtained from the four-chamber model are comparable to actual patient data, without requiring complicated non-physiological boundary conditions usually required in truncated ventricular heart models.

Therapeutic effects of a mesenchymal stem cell‑based insulin‑like growth factor‑1/enhanced green fluorescent protein dual gene sorting system in a myocardial infarction rat model

The present study was conducted in order to improve gene expression efficiency of insulin‑like growth factor‑1 (IGF‑1)‑transfected mesenchymal stem cells (MSCs) using a non‑viral carrier and a simplified method of dual gene selection. The therapeutic efficacy of this MSC‑based IGF‑1/enhanced green fluorescent protein (EGFP) dual gene sorting system was evaluated in a rat myocardial infarction (MI) model. IGF‑1 and EGFP genes were expressed in MSCs in vitro. The purity of dual gene‑expressing MSCs was 95.1% by fluorescence‑activated cell sorting. Transfected MSCs injected into rats were identified based on green fluorescence, with an increased signal intensity observed in rats injected with sorted cells, compared with unsorted cells. IGF‑1 expression levels were additionally increased in the sorted group, and decreases in infarct size, fibrotic area and fraction of apoptotic cells were observed. These results demonstrated that IGF‑1 overexpression protects against fibrosis and apoptosis in the myocardium and reduces infarct size following MI. Additionally, the present vector sorting system may potentially be applied to other types of stem cell‑based gene therapy.

Specific Cell (Re-)Programming: Approaches and Perspectives

Many disorders are manifested by dysfunction of key cell types or their disturbed integration in complex organs. Thereby, adult organ systems often bear restricted self-renewal potential and are incapable of achieving functional regeneration. This underlies the need for novel strategies in the field of cell (re-)programming-based regenerative medicine as well as for drug development in vitro. The regenerative field has been hampered by restricted availability of adult stem cells and the potentially hazardous features of pluripotent embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). Moreover, ethical concerns and legal restrictions regarding the generation and use of ESCs still exist. The establishment of direct reprogramming protocols for various therapeutically valuable somatic cell types has overcome some of these limitations. Meanwhile, new perspectives for safe and efficient generation of different specified somatic cell types have emerged from numerous approaches relying on exogenous expression of lineage-specific transcription factors, coding and noncoding RNAs, and chemical compounds.It should be of highest priority to develop protocols for the production of mature and physiologically functional cells with properties ideally matching those of their endogenous counterparts. Their availability can bring together basic research, drug screening, safety testing, and ultimately clinical trials. Here, we highlight the remarkable successes in cellular (re-)programming, which have greatly advanced the field of regenerative medicine in recent years. In particular, we review recent progress on the generation of cardiomyocyte subtypes, with a focus on cardiac pacemaker cells. Graphical Abstract.

GSK-3β inhibition confers cardioprotection associated with the restoration of mitochondrial function and suppression of endoplasmic reticulum stress in sevoflurane preconditioned rats following ischemia/reperfusion injury

Background:

Sevoflurane has been shown to protect against myocardial ischemia/reperfusion (I/R) injury in animals, while its cardioprotection is lost if the ischemic insult is too long. In this study, we proposed a prevailing hypothesis that GSK-3β inhibitor-mediated activation of GSK-3β/β-catenin signaling pathway provides additional cardioprotection in sevoflurane preconditioned rats following I/R injury.

Methods:

Rats were subjected to treatment with TDZD-8, a GSK-3β inhibitor, 5 minutes prior to sevoflurane preconditioning and 30-minute ischemia and 120-minute reperfusion. Furthermore, in order to find out whether this cardioprotection is linked with mitochondrial function and endoplasmic reticulum stress (ERS), we isolated mitochondria from rat hearts perfused with TDZD-8 and determined the alternations of ERS markers.

Results:

Sevoflurane preconditioning or GSK-3β inhibitor treatment prevented cardiomyocyte apoptosis, phosphorylated GSK-3β and accelerated total β-catenin expression levels, reduced mitochondrial permeability transition pore (MPTP) activity, promoted the recovery of mitochondrial membrane potential and decreased the expression levels of GRP78, caspase-12 and C/EBP homology protein (CHOP) in rats under I/R condition, suggesting sevoflurane preconditioning or TDZD-8 activate the GSK-3β/β-catenin signaling pathway, improve mitochondria function and suppress ERS occurrence.

Conclusions:

Taken together, the findings obtained from the study support the concept that sevoflurane preconditioning confers cardioprotection against myocardial I/R injury and GSK-3β/β-catenin signaling activation mediated by TDZD-8 as a novel target to prolong cardioprotection by sevoflurane anaesthesia.

Nonlinear diffusion and thermo-electric coupling in a two-variable model of cardiac action potential

This work reports the results of the theoretical investigation of nonlinear dynamics and spiral wave breakup in a generalized two-variable model of cardiac action potential accounting for thermo-electric coupling and diffusion nonlinearities. As customary in excitable media, the common Q₁₀ and Moore factors are used to describe thermo-electric feedback in a 10° range. Motivated by the porous nature of the cardiac tissue, in this study we also propose a nonlinear Fickian flux formulated by Taylor expanding the voltage dependent diffusion coefficient up to quadratic terms. A fine tuning of the diffusive parameters is performed a priori to match the conduction velocity of the equivalent cable model. The resulting combined effects are then studied by numerically simulating different stimulation protocols on a one-dimensional cable. Model features are compared in terms of action potential morphology, restitution curves, frequency spectra, and spatio-temporal phase differences. Two-dimensional long-run simulations are finally performed to characterize spiral breakup during sustained fibrillation at different thermal states. Temperature and nonlinear diffusion effects are found to impact the repolarization phase of the action potential wave with non-monotone patterns and to increase the propensity of arrhythmogenesis.