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.
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.