Integrated Cardiac Electromechanics: Modeling and Personalization

Cardiac disease remains the leading cause of morbidity and mortality in the world. A variety of heart diagnosis techniques have been developed during the last century, and generally fall into two groups. The first group evaluates the electrical function of the heart using electrophysiological data such as electrocardiogram (ECG), while the second group aims to assess the mechanical function of the heart through medical imaging data. Nevertheless, the heart is an integrated electromechanical organ, where its cyclic pumping arises from the synergy of its electrical and mechanical function which requires first to be electrically excited in order to contract. At the same time, cardiac electrical function experiences feedback from mechanical contraction. This inter-dependent relationship determines that neither electrical function nor mechanical function alone can completely reflect the pathophysiological conditions of the heart. The aim of this thesis is working towards building an integrated framework for heart diagnosis through evaluation of electrical and mechanical functions simultaneously. The basic rational is to obtain quantitative interpretation of a subject-specific heart system by combining an electromechanical heart model and individual clinical measurements of the heart. To this end, we first develop a biologically-inspired mathematical model of the heart that provides a general, macroscopic description of cardiac electromechanics. The intrinsic electromechanical coupling arises from both excitation-induced contraction and deformation-induced mechano-electrical feedback. Then, as a first step towards a fully electromechanically integrated framework, we develop a model-based approach for investigating the effect of cardiac motion on noninvasive transmural imaging of cardiac electrophysiology. Specifically, we utilize the proposed heart model to obtain updated heart geometry through simulation, and further recover the electrical activities of the heart from body surface potential maps (BSPMs) by solving an optimization problem. Various simulations of the heart have been performed under healthy and abnormal conditions, which demonstrate the physiological plausibility of the proposed integrated electromechanical heart model. What\u27s more, this work presents the effect of cardiac motion to the solution of noninvasive estimation of cardiac electrophysiology and shows the importance of integrating cardiac electrical and mechanical functions for heart diagnosis. This thesis also paves the road for noninvasive evaluation of cardiac electromechanics

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 128, May 1974

This special bibliography lists 282 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1974

From medical images to individualized cardiac mechanics: A Physiome approach

Cardiac mechanics is a branch of science that deals with forces, kinematics, and material properties of the heart, which is valuable for clinical applications and physiological studies. Although anatomical and biomechanical experiments are necessary to provide the fundamental knowledge of cardiac mechanics, the invasive nature of the procedures limits their further applicability. In consequence, noninvasive alternatives are required, and cardiac images provide an excellent source of subject-specific and in vivo information. Noninvasive and individualized cardiac mechanical studies can be achieved through coupling general physiological models derived from invasive experiments with subject-specific information extracted from medical images. Nevertheless, as data extracted from images are gross, sparse, or noisy, and do not directly provide the information of interest in general, the couplings between models and measurements are complicated inverse problems with numerous issues need to be carefully considered. The goal of this research is to develop a noninvasive framework for studying individualized cardiac mechanics through systematic coupling between cardiac physiological models and medical images according to their respective merits. More specifically, nonlinear state-space filtering frameworks for recovering individualized cardiac deformation and local material parameters of realistic nonlinear constitutive laws have been proposed. To ensure the physiological meaningfulness, clinical relevance, and computational feasibility of the frameworks, five key issues have to be properly addressed, including the cardiac physiological model, the heart representation in the computational environment, the information extraction from cardiac images, the coupling between models and image information, and also the computational complexity. For the cardiac physiological model, a cardiac physiome model tailored for cardiac image analysis has been proposed to provide a macroscopic physiological foundation for the study. For the heart representation, a meshfree method has been adopted to facilitate implementations and spatial accuracy refinements. For the information extraction from cardiac images, a registration method based on free-form deformation has been adopted for robust motion tracking. For the coupling between models and images, state-space filtering has been applied to systematically couple the models with the measurements. For the computational complexity, a mode superposition approach has been adopted to project the system into an equivalent mathematical space with much fewer dimensions for computationally feasible filtering. Experiments were performed on both synthetic and clinical data to verify the proposed frameworks

Diffusion tensor magnetic resonance imaging-derived myocardial fiber disarray in hypertensive left ventricular hypertrophy: visualization, quantification and the effect on mechanical function

Left ventricular hypertrophy induced by systemic hypertension is generally regarded a morphological precursor of unfortunate cardiovascular events. Myocardial fiber disarray has been long recognized as a prevalent hallmark of this pathology. In this chapter, ex vivo diffusion tensor magnetic resonance imaging is employed to delineate the regional loss of myocardial organization that is present in the excised heart of a spontaneously hypertensive rat, as opposed to a control. Fiber tracking results are provided that illustrate in great detail the alterations in the integrity of cardiac muscle microstructure due to the disease. A quantitative analysis is also performed. Another contribution of this chapter is the model-based assessment of the role of the myofiber disarray in modulating the mechanical properties of the myocardium. The results of this study improve our understanding of the structural remodeling mechanisms that are associated with hypetensive left ventricular hypertrophy and their role

Real-time Observation of Dynamic Sarcomeric Addition in an In Vivo-like Cardiomyocyte Culture Model

Cardiac hypertrophy is the enlargement of individual cardiac muscle cell (cardiomyocyte) in both size and mass, which is achieved by addition of sarcomeres, the basic contractile unit. Cardiomyocytes elongate by adding sarcomeres in series and thicken by adding sarcomeres in parallel. Though it is generally accepted that sarcomeric addition can be initiated by increased mechanical loading, the sarcomeric addition process under various mechanical overloads on molecular level remains largely unknown. Previous research on sarcomeric addition largely rely on animal models of induced cardiac hypertrophy; those experiments provide little direct evidence for sarcomeric addition process as a response to increased mechanical loading, aside from the start and end point conditions. Studies showing the dynamic addition process of sarcomeric addition are rare, due to lack of in vivo-like cardiomyocyte culture models for mechanical assays and limited choice of live imaging techniques. In this project, a 3D cardiomyocyte culture model that recapitulates the in vivo-like mechanical loading environment, was established in vitro on a 2D PDMS substrate. With this culture model, we, for the first time, revealed the dynamic sarcomeric addition process at intercalated discs and Z discs with custom-built passive pulse splitter-based TPEF-SHG microscope, which confirmed the long-standing hypothesis of sarcomeric addition at intercalated discs and Z discs. These findings may advance the comprehension of cardiomyocyte remodeling process on sarcomeric level during development of cardiac hypertrophy

Investigating the protective role of the natural hormone Melatonin, in reducing drug-induced cardiotoxicity in the therapy of chronic diseases

Heart failure (HF) is a highly complex disorder and a major end-point of cardiovascular diseases (CVD). The pathogenesis of HF is mostly unresolved but involves interplay between cardiac structural and electrical remodelling, metabolic alterations, cell death and altered gene expression. Mitochondrial dysfunction and HF are common complications of chronic treatment from diverse groups of drugs, in particular anticancer drugs such as doxorubicin (DOX). Treatment of animals and cardiomyocytes with cardiotoxic chemicals such as β-adrenergic receptor agonists (such as isoproterenol) induces cardiac dysfunction and HF. Previous work done by the group have identified the pineal hormone melatonin was protective against stress-induced cardiac arrhythmias and simulated heart failure in cardiomyocytes in vitro. Melatonin synthesis is also dramatically decreased with age and in patients with CVD. The aim of the present project was to better understand the pathogenesis of druginduced cardiac dysfunction and delineate the role of melatonin in cardioprotection in H9c2, a model rat cell line in vitro. Using the Seahorse XF analyser method, it was demonstrated that commonly used medication for chronic diseases such as amiodarone, amitriptyline, and statins all caused altered mitochondrial dysfunction. In addition, cardiotoxic chemicals (isoproterenol, hydrogen peroxide, DOX) altered oxidative phosphorylation and glycolysis in living cardiomyocyte-derived H9c2 cells; these deleterious metabolic changes were ameliorated by melatonin. Flowcytometry and Alamar Blue staining methods demonstrated that DOX robustly induced apoptosis in H9c2 cells (~30%) which was reversed by melatonin. Doxorubicin-induced stress in H9c2 cells dramatically altered gene expression in several key signalling pathways integral in cardiac function and disease. These included mitochondrial metabolism (UCP2, PPARɣ, Drp1, Mfn1, Parp 1, Parp2, Sirt3 and Cav3), apoptosis (Bcl2 and Bcl-xL), cardiac electrophysiology and arrhythmia (Scn5a, SERCA2a), calcium handling (SERCA2a) and cardiac remodelling (Myh7, ms1). Melatonin pre-treatment attenuated or completely blocked this DOX-induced alteration in gene expression in cardiomyocytes. In conclusion, the present result demonstrated for the first time that melatonin is cardioprotective against drug-induced cardiotoxicity and apoptosis via modifying diverse heart failure-related signalling pathways. This provides novel insight on the possible use of melatonin as an adjunct intervention in several therapies including anti-cancer