Mathematical models of Abnormal automaticiy in cardiac tissue

心脏组织异常自律的数学模型

• 批准号: RGPIN-2014-05558
• 负责人: Vinet, Alain
• 金额: $ 1.89万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=630187
• 关键词: Mathematical; models; Abnormal; automaticiy; cardiac

Ventricular arrhythmia during the acute phase of ischemia and atrial fibrillation (AF) are widespread arrhythmias. Their most common mechanism is reentry, whereby one or multiple self sustained electrical activation fronts travel in the tissue. The resulting high frequency activation supersedes the normal pacemaker of the heart and may lead to life threatening complications. In both cases, the trigger may come from abnormal automaticity of some part of the tissue. Our goal is to study the mechanisms leading to abnormal automaticity in mathematical models of cells and tissues.In previous work, we have established the conditions to get sustained automaticity in a realistic ionic model of the human ventricular myocyte considering parameters that are known to change during ischemia. Similar analyses were performed on a model of atrial myocyte with respect to parameters modified by adrenergic neuronal activation, which is known to favor abnormal automaticity and AF. However, these analyses were incomplete and model dependent. Our first objective is to complete these analyses and reach an understanding of the general conditions by which sustained automaticity may occur that would be applicable to a wide class of cardiac ionic models. We want to identify the subsystem involved and their basic generic properties to reach simplified formulations that would still reproduce the main characteristics of the dynamics. Analysis will be extended to transient automaticity, whereby the system may produce isolated burst of activation. However the real and most significant challenge is to find the conditions needed for automaticity in tissue, in which the cells are interconnected by gap junctions acting as intracellular resistance. We propose a new approach to this problem by which the results of the cell analyses are used to get conditions of automaticity in the tissue. Upon spatial distribution of the parameters associated to either ischemia or adrenergic stimulation, cells have different resting potentials, ending in spatially inhomogeneous stationary voltage profile modulated by the coupling. Automaticity occurs when this stationary solution loses its stability. The problem is to find spatial distributions of parameters that can produce this loss of stability. Our second aim is to develop a method to build these distributions using the stationary solutions of the cells as function of the parameters obtained in the first part of the project.The final and third problem is to examine whether the distribution of parameters producing automaticity obtained in the second part of the project can be physiologically realistic. Consider as an example the extracellular distribution of potassium Ko which is known to vary during ischemia and was shown in our preliminary analysis to be able to induce automaticity. Ko is treated as a parameter in the first two part of the proposal. We propose to develop a model of the spatial dynamics of Ko in the extracellular medium that will be used to assess whether such a profile could indeed occur. The same type of approach will be used for other parameters, such as the spatial distribution of noradrenalin during adrenergic stimulations. In summary, we propose to use mathematical model to reach robust and generic less model dependent conclusion over the distribution of parameters needed to reach abnormal automaticity in condition ischemia and adrenergic stimulation.

缺血急性期的室性心律失常和房颤(房颤)是常见的心律失常。它们最常见的机制是再入，即一个或多个自我维持的电激活前沿在组织中移动。由此产生的高频激活取代了正常的心脏起搏器，并可能导致危及生命的并发症。在这两种情况下，触发因素都可能来自组织某些部分的异常自律性。我们的目标是研究细胞和组织数学模型中导致异常自律性的机制。在以前的工作中，我们已经在一个现实的人体心肌细胞离子模型中建立了获得持续自律性的条件，考虑了在缺血过程中已知的参数变化。在一个心房肌细胞模型上也进行了类似的分析，研究了肾上腺素能神经元激活对参数的修改，已知肾上腺素能神经元激活有利于异常自律性和房颤。然而，这些分析是不完整的，而且依赖于模型。我们的第一个目标是完成这些分析，并理解持续的自律性可能发生的一般条件，这些条件将适用于一大类心脏离子模型。我们想要确定所涉及的子系统及其基本的类属性质，以达到简化的公式，仍然可以再现动力学的主要特征。分析将扩展到瞬时自动机，从而系统可能产生孤立的激活猝发。然而，真正和最重要的挑战是找到组织中实现自律性所需的条件，在组织中，细胞通过充当细胞内阻力的缝隙连接相互连接。我们提出了一种新的方法来解决这个问题，通过这种方法，细胞分析的结果被用来获得组织中的自动条件。根据与缺血或肾上腺素能刺激相关的参数的空间分布，细胞具有不同的静息电位，最终导致受耦合调制的空间不均匀的静态电压分布。当这种固定溶液失去其稳定性时，就会发生自律性。问题是找到可能导致这种稳定性损失的参数的空间分布。我们的第二个目标是开发一种方法，使用细胞的稳定解作为项目第一部分中获得的参数的函数来构建这些分布。最后和第三个问题是检查在项目第二部分中获得的产生自动机的参数的分布是否在生理上是真实的。以Ko的胞外分布为例，我们的初步分析表明，Ko在缺血过程中会发生变化，并能够诱导自律性。在提案的前两部分中，Ko被视为一个参数。我们建议开发一个细胞外介质中KO的空间动力学模型，该模型将被用来评估是否确实可能发生这样的分布。同样类型的方法将用于其他参数，如肾上腺素能刺激期间去甲肾上腺素的空间分布。综上所述，我们建议使用数学模型来得出在条件缺血和肾上腺素能刺激下达到异常自律性所需的参数分布的健壮和一般的较少模型依赖性的结论。