Optimizing Ventilation Distribution in Injured Lung Using Computational Modeling

Beth Israel Deaconess Medical Center, Boston MA

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Abstract

DESCRIPTION (provided by applicant): Ventilated patients with acute lung injury (ALI) are predisposed to parenchymal overdistension and derecruitment, which may worsen existing injury. An optimal ventilatory strategy may improve the gas exchange and also minimize parenchymal overdistension and derecruitment. Through the current proposed research study, we will develop a 3D model of a canine lung, based on CT-images from our lab. Airway dimensions are dependent on local transmural pressures. We will also incorporate viscoelastic acini capable of pressure-dependent overdistention and recruitment. Recruitment and derecruitment of the lung is simulated using pressure-dependent stochastic distribution of opening and closing pressure. The identified location of injury in the lung may be translated from CT-images to spatial coordinates on 3D model of the lung. The model is validated by comparison of its predicted alterations in global lung mechanics (i.e. resistance, elastance, peak airway pressure) measured at the trachea with measurements already obtained in dogs from our lab with induced lung injury. We will select varying conditions of positive end expiratory pressure (PEEP), tidal volume (VT), and respiratory rate while determining acinar flow and pressure distributions through the lung. We will also quantify the amount of intratidal recruitment / derecruitment and overdistension as well as determine how these processes impact global lung mechanics. In summary, this model will allow us to determine an optimal, protective ventilatory strategy based on global lung mechanics, acinar-level mechanics, and ventilation distribution.