Cardiac organoid technology and computational processing of cardiac physiology for advanced drug screening applications

Stem cell technology has gained considerable recognition since its inception to advance disease modeling and drug screening. This is especially true for tissues that are difficult to study due to tissue sensitivity and limited regenerative capacity, such as the heart. Previous work in stem cell-derived cardiac tissue has exploited how we can engineer biologically functional heart tissue by providing the appropriate external stimuli to facilitate tissue development. The goal of this dissertation is to explore the potentials of stem cell cardiac organoid models to recapitulate heart development and implement analytical computational tools to study cardiac physiology. These new tools were implemented as potential advancements in drug screening applications for better predictions of drug-related cardiotoxicity. Cardiac organoids, generated via micropatterning techniques, were explored to determine how controlling engineering parameters, specifically the geometry, direct tissue fate and organoid function. The advantage of cardiac organoid models is the ability to recapitulate and study human tissue morphogenesis and development, which has currently been restricted through animal models. The cardiac organoids demonstrated responsiveness manifested as impairments to tissue formation and contractile functions as a result of developmental drug toxicity. Single-cell genomic characterization of cardiac organoids unveiled a co-emergence of cardiac and endoderm tissue, which is seen in vivo through paracrine signaling between the liver and heart. We then implemented computational tools based on nonlinear mathematical analysis to evaluate the cardiac physiological drug response of stem cell-derived cardiomyocytes. This dissertation discusses in vitro tissue platforms as well as computational tools to study drug-induced cardiotoxicity. Using these tools, we can extend current toolboxes of understanding cardiac physiology for advanced investigations of stem-cell based cardiac tissue engineering

Complexity analysis of experimental cardiac arrhythmia

International audienceTo study the cardiac arrhythmia, an in vitro experimental model and Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through it the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as cell of human's heart. In order to discriminate the cardiac arrhythmia, complexity analysis methods (Approximate Entropy, ApEn and Sample Entropy, SampEn) are used especially taking into account noise. The results showed that, in case of arrhythmia, the ApEn and SampEn are reduced to about 50\% of the original entropies. Both parameters could be used as factors to discriminate arrhythmia. Moreover, from a point of view of biophysics this decrease 50\% of Entropy coincides with the bifurcation (periods, attractors etc.) in case of arrhythmia which have been reported previously. It supports once more the hypothesis that in case of cardiac arrhythmia, the heart entered into chaos which helps to better understand the mechanism of atrial fibrillation

Feasibility of improving risk stratification in the inherited cardiac conditions

Fatal ventricular arrhythmias can occur in patients with Hypertrophic Cardiomyopathy, Brugada Syndrome and rarely in patients with normal cardiac investigations. Despite very different pathogeneses, we hypothesised that a common electrophysiological substrate precipitates these arrhythmias and could be used as a marker for risk stratification. In Chapter 3 of this thesis, we found that fewer than half the cardiac arrest survivors with Brugada Syndrome would have been offered prophylactic defibrillators based on current risk scoring, highlighting the need for better risk stratification. Our group previously used a commercially available 252-electrode vest which constructs ventricular electrograms onto a CT image of the heart to show exercise related differences in high-risk patients. In Chapter 4, we applied this method to Brugada patients, but could not reproduce prior results. Further investigation revealed periodic changes in activation patterns after exercise that could explain this discrepancy. An alternative matrix approach was developed to overcome this problem. Exercise induced conduction heterogeneity differentiated Brugada patients from unaffected controls, but not those surviving cardiac arrest. However, if considered alongside spontaneous type 1 ECG and syncope, inducible conduction heterogeneity markedly improved identification of Brugada cardiac arrest survivors. In Chapter 5 the method was shown to differentiate idiopathic ventricular fibrillation patients from those fully recovered from acute ischaemic cardiac arrest, implying a permanent electrophysiological abnormality. In Chapter 8, we showed prolonged mean local activation times and activation-recovery intervals in hypertrophic cardiomyopathy cardiac arrest survivors compared to those without previous ventricular arrhythmia. These metrics were combined into both logistic regression and support vector machine models to strongly differentiate the groups. We concluded that electrophysiological changes could identify cardiac arrest survivors in various cardiac conditions, but a single factor common pathway was not established. Prospective studies are required to determine if using these parameters could enhance current risk stratification for sudden death.Open Acces

Clinical Application of Electrocardiographic Imaging in Patients with Ischemic Cardiomyopathy, Early Repolarization Syndrome and Brugada Syndrome

Electrocardiographic Imaging (ECGI) is a noninvasive modality for human application in both research and clinical settings. It is an important tool for investigation of abnormal electrophysiological (EP) substrates and arrhythmias in patients. Multi-channel body surface potential recordings and the patient-specific heart-torso geometry from ECG gated computed tomography are processed by ECGI algorithms to reconstruct epicardial potentials, electrograms and patterns of activation and repolarization. ECGI is able to continuously generate high-resolution, panoramic EP maps of the entire heart on a beat-by-beat basis, which cannot be achieved with invasive catheter mapping. ECGI was applied in ischemic cardiomyopathy patients to characterize the abnormal EP substrate associated with myocardial infarction. In patients who developed ventricular tachycardia during the study, the arrhythmia activation pattern and site of origin were correlated with the EP substrate to identify components of the reentry circuit. The study subjects included patients with and without a history of clinical ventricular arrhythmias. The properties of scar EP substrate were compared between the two groups to determine whether substantial differences exist. This differentiating capability of ECGI was examined as a potential tool for arrhythmic risk stratification in this population. In a separate clinical study, ECGI was applied in a group of patients with early repolarization syndrome, which has been recently shown to be associated with an increased risk of ventricular fibrillation. The ventricular activation and repolarization patterns during sinus rhythm were characterized and compared with data from normal controls. This study aimed to provide insights into the mechanisms of the early repolarization ECG pattern and the related arrhythmogenesis. ECGI was also applied in patients with Brugada syndrome to image the EP substrate and to study the underlying mechanisms of the Brugada ECG pattern and abnormal epicardial electrograms. Heart rate change protocol in selected patients helped unmask the coexistence of abnormal conduction and abnormal repolarization in the EP substrate. Brugada syndrome patients were also compared with patients with right bundle branch block (generally considered benign) to determine whether the substrate was specific to Brugada syndrome, and whether ECGI can differentiate between these two pathologies with similar ECG patterns. The above studies demonstrated the feasibility and clinical importance of ECGI for noninvasive diagnosis, pre-procedural guidance and arrhythmic risk stratification in human subjects

Modeling Action Potential Propagation During Hypertrophic Cardiomyopathy Through a Three-Dimensional Computational Model

Hypertrophic cardiomyopathy (HCM) is the most common monogenic disorder and the leading cause of sudden arrhythmic death in children and young adults. It is typically asymptomatic and first manifests itself during cardiac arrest, making it a challenge to diagnose in advance. Computational models can explore and reveal underlying molecular mechanisms in cardiac electrophysiology by allowing researchers to alter various parameters such as tissue size or ionic current amplitudes. The goal of this thesis is to develop a computational model in MATLAB and to determine if this model can accurately indicate cases of hypertrophic cardiomyopathy. This goal is achieved by combining a three-dimensional network of the bidomain model with the Beeler-Reuter model and then by manually varying the thickness of that tissue and recording the resulting membrane potential with respect to time. The results of this analysis demonstrated that the developed model is able to depict variations in tissue thickness through the difference in membrane potential recordings. A one-way ANOVA analysis confirmed that the membrane potential recordings of the different thicknesses were significantly different from one another. This study assumed continuum behavior, which may not be indicative of diseased tissue. In the future, such a model might be validated through in vitro experiments that measure electrical activity in hypertrophied cardiac tissue. This model may be useful in future applications to study the ionic mechanisms related to hypertrophic cardiomyopathy or other related cardiac diseases

Load-Independent And Regional Measures Of Cardiac Function Via Real-Time Mri

LOAD-INDEPENDENT AND REGIONAL MEASURES OF CARDIAC FUNCTION VIA REAL-TIME MRI Francisco Jose Contijoch Robert C Gorman, MD Expansion of infarcted tissue during left ventricular (LV) remodeling after a myocardial infarction is associated with poor long-term prognosis. Several interventions have been developed to limit infarct expansion by modifying the material properties of the infarcted or surrounding borderzone tissue. Measures of myocardial function and material properties can be obtained non-invasively via imaging. However, these measures are sensitive to variations in loading conditions and acquisition of load-independent measures have been limited by surgically invasive procedures and limited spatial resolution. In this dissertation, a real-time magnetic resonance imaging (MRI) technique was validated in clinical patients and instrumented animals, several technical improvements in MRI acquisition and reconstruction were presented for improved imaging resolution, load-independent measures were obtained in animal studies via non-invasive imaging, and regional variations in function were measured in both na�ve and post-infarction animals. Specifically, a golden-angle radial MRI acquisition with non-Cartesian SENSE-based reconstruction with an exposure time less than 95 ms and a frame rate above 89 fps allows for accurate estimation of LV slice volume in clinical patients and instrumented animals. Two technical developments were pursued to improve image quality and spatial resolution. First, the slice volume obtained can be used as a self-navigator signal to generate retrospectively-gated, high-resolution datasets of multiple beat morphologies. Second, cross-correlation of the ECG with previously observed values resulted in accurate interpretation of cardiac phase in patients with arrhythmias and allowed for multi-shot imaging of dynamic scenarios. Synchronizing the measured LV slice volume with an LV pressure signal allowed for pressure-volume loops and corresponding load-independent measures of function to be obtained in instrumented animals. Acquiring LV slice volume at multiple slice locations revealed regional differences in contractile function. Motion-tracking of the myocardium during real-time imaging allowed for differences in contractile function between normal, borderzone, and infarcted myocardium to be measured. Lastly, application of real-time imaging to patients with arrhythmias revealed the variable impact of ectopic beats on global hemodynamic function, depending on frequency and ectopic pattern. This work established the feasibility of obtaining load-independent measures of function via real-time MRI and illustrated regional variations in cardiac function