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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=667824
• 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.

急性期室性心律失常和房颤（AF）是广泛存在的心律失常。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体在组织中传播。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，触发可能来自组织的某些部分的异常自动性。我们的目标是研究导致细胞和组织数学模型中异常自动性的机制。**在之前的工作中，我们已经建立了在现实的人类心室肌细胞离子模型中获得持续自动性的条件，考虑到已知在缺血期间变化的参数。在心房肌细胞模型上进行了类似的分析，关于肾上腺素能神经元激活改变的参数，这有利于异常自动性和房颤。然而，这些分析是不完整的，并且依赖于模型。我们的第一个目标是完成这些分析，并了解持续自动性可能发生的一般条件，这将适用于广泛的心脏离子模型。我们想要确定所涉及的子系统和它们的基本一般属性，以达到简化的公式，仍然可以再现动力学的主要特征。分析将扩展到瞬态自动性，即系统可能产生孤立的激活突发。**然而，真正的和最重要的挑战是找到组织中自动性所需的条件，其中细胞通过间隙连接作为细胞内阻力相互连接。我们提出了一种新的方法来解决这个问题，通过细胞分析的结果来获得组织中自动性的条件。在缺血或肾上腺素能刺激相关参数的空间分布上，细胞有不同的静息电位，最终在空间上不均匀的由耦合调制的平稳电压分布。当这个固定解失去稳定性时，就会发生自动性。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，使用单元的固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。**最后也是第三个问题是检验项目第二部分中获得的产生自动性的参数分布在生理上是否真实。以钾钾的细胞外分布为例，已知钾钾在缺血期间会发生变化，并在我们的初步分析中显示能够诱导自动性。在提案的前两部分中，Ko被视为参数。我们建议建立一个细胞外介质中Ko的空间动力学模型，该模型将用于评估这种情况是否确实可能发生。同样的方法将用于其他参数，如肾上腺素能刺激时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对缺血和肾上腺素能刺激条件下达到异常自动性所需的参数分布得出鲁棒性和通用的不依赖模型的结论。