Age Dependent Mechanical Ventilator-Induced Inflammation: Modeling & Experiments

年龄依赖性机械呼吸机引起的炎症：建模

基本信息

批准号：
8399980
负责人：
Rebecca Long Heise
金额：
$ 29.7万
依托单位：
VIRGINIA COMMONWEALTH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-08-01 至 2016-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8399980
关键词：
Accounting Acute Acute Lung Injury Adult Adult Respiratory Distress Syndrome Age Algorithms Alveolar Alveolus Animal Experiments Animals Asthma Blood Breathing Carbon Dioxide Cell model Cells Clinical Trials Clinical Trials Design Computer Simulation Coupled Couples Data Dependence Diffusion Disease Elderly Elements Endothelial Cells Environment Environmental air flow Equation Exhalation Finite Element Analysis Future Gases Human Hybrids In Vitro Incidence Individual Inflammation Inflammation Mediators Inflammatory Inflammatory Response Link Liquid substance Literature Lung Lung Inflammation Mechanical Ventilators Mechanical ventilation Mechanics Mediating Methods Modeling Movement Multiple Organ Failure Organ Output Oxygen Partial Pressure Patients Physics Play Production Property Protocols documentation Respiratory Failure Respiratory System Respiratory physiology Rodent Signal Transduction Solid Stress Stretching Structure of parenchyma of lung Testing Tidal Volume Tissues Translating Treatment Protocols Validation Ventilator Ventilator-induced lung injury age related aged base cytokine in vivo lung injury macrophage model development mortality multi-scale modeling normal aging preclinical study pressure research study response

项目摘要

DESCRIPTION (provided by applicant): Incidences of respiratory failure in US are about 137-253 per 100,000 US residents with mortality rates of these patients at about 36%-44%. Mechanical ventilation is a method that partially or fully assists patients whose respiratory systems fails to achieve adequate gas exchange function due to acute lung injury (ALI) and various lung and airway disease, such as acute respiratory distress syndrome and asthma. The majority of patients receiving mechanical ventilation are elderly. The mortality rate for patients on mechanical ventilation increases with both the patient's age and the duration of the ventilation. Despite its necessity, mechanical ventilation can itself cause lung injury or ventilatr-associated lung injury (VALI). As individuals age, there are changes in their lung function, e.g. alveolar volumes increase and diffusion rates decrease, which play a key role in their response to mechanical ventilation. These responses may result in harmful inflammation. In order to understand the mechanisms behind ventilator-induced inflammation in an aged lung and to develop age-dependent treatment protocols that minimize the inflammatory response, we will develop a multi- scale hybrid computational model of ventilator-induced inflammation in the lung. This multi-scale hybrid model will be created by linking models at the cellular, tissue and organ level that will be used to determine the levels of inflammation in the lung, with a model for gas exchange. The hybrid model couples finite element modeling of mechanical lung mechanical properties with agent based modeling of inflammation and differential equation modeling of gas exchange. We will experimentally validate the cellular level model by recording macrophage and several pro-inflammatory cytokine levels in stretched non-aged and aged adult lung rodent cells. Organ and tissue level models will be validated with existing data from literature. The cellular level model (discrete method) takes the inputs of the strain environment generated within the tissue by mechanical ventilation and determines the levels of overall inflammation. The organ and tissue level models (continuum methods) will determine these stresses and strains using ventilator parameters. We will use a model of gas exchange (partial differential equations) to quantify changes in the partial pressure of oxygen and carbon dioxide in circulating blood due to mechanical ventilator-induced inflammation. After validation, these models will be combined to create our multi-scale hybrid model for ventilator-induced inflammation. We will validate this model using whole animal experiments, in which aged rodents are mechanically ventilated and the resulting inflammation will be characterized and quantified. After validating the integrated model, the proposed project can be used to investigate several age dependent ventilator protocols that may be developed to minimize inflammation and reducing the likelihood of ventilator induced lung injury. PUBLIC HEALTH RELEVANCE: Mechanical ventilation is needed in aged patients whose respiratory system fails to achieve adequate gas exchange function. Despite its necessity mechanical ventilation itself gives rise to lung inflammation. In order to decrease ventilator-induced inflammation, we will develop and experimentally validate an age dependent multi-scale computational model and will analyze the mechanisms of ventilator-induced inflammation and develop age-dependent ventilation protocols that minimize the resulting lung inflammation.

描述（申请人提供）：美国呼吸衰竭发病率约为每10万美国居民137-253例，这些患者的死亡率约为36%-44%。机械通气是部分或全部帮助因急性肺损伤（ALI）和各种肺部和气道疾病（例如急性呼吸窘迫综合征和哮喘）导致呼吸系统无法实现足够气体交换功能的患者的方法。大多数接受机械通气的患者是老年人。机械通气患者的死亡率随着患者年龄和通气持续时间的增加而增加。尽管有必要，机械通气本身也可能导致肺损伤或呼吸机相关肺损伤 (VALI)。随着个体年龄的增长，肺功能会发生变化，例如肺功能。肺泡容积增加和扩散率降低，这在他们对机械通气的反应中起着关键作用。这些反应可能会导致有害的炎症。为了了解老年肺部由呼吸机引起的炎症背后的机制，并制定最大限度地减少炎症反应的年龄依赖性治疗方案，我们将开发一种由呼吸机引起的肺部炎症的多尺度混合计算模型。这种多尺度混合模型将通过将细胞、组织和器官水平的模型与用于确定肺部炎症水平的模型联系起来来创建气体交换。该混合模型将肺机械特性的有限元建模与基于代理的炎症建模和气体交换的微分方程建模相结合。我们将通过记录拉伸的非老化和老化成年啮齿动物肺细胞中的巨噬细胞和几种促炎细胞因子水平来实验验证细胞水平模型。器官和组织水平模型将利用文献中的现有数据进行验证。细胞水平模型（离散方法）采用机械通气在组织内产生的应变环境的输入，并确定总体炎症水平。器官和组织水平模型（连续方法）将使用呼吸机参数确定这些应力和应变。我们将使用气体交换模型（偏微分方程）来量化由于机械呼吸机引起的炎症导致循环血液中氧气和二氧化碳分压的变化。验证后，这些模型将被组合起来创建我们的呼吸机引起的炎症的多尺度混合模型。我们将使用整体动物实验来验证该模型，其中对老年啮齿动物进行机械通气，并对由此产生的炎症进行表征和量化。验证集成模型后，拟议的项目可用于研究几种与年龄相关的呼吸机方案，这些方案可用于最大限度地减少炎症并降低呼吸机引起的肺损伤的可能性。公共卫生相关性：呼吸系统无法实现足够气体交换功能的老年患者需要机械通气。尽管有必要，机械通气本身也会引起肺部炎症。为了减少呼吸机引起的炎症，我们将开发并通过实验验证年龄依赖性多尺度计算模型，并将分析呼吸机引起的炎症的机制并开发年龄依赖性通气方案，以最大限度地减少由此产生的肺部炎症。