Optimizing Ventilation Distribution and Gas Exchange in Combat-Related Lung Injury Using Multifrequency Oscillation
Abstract
Respiratory failure from acute lung injury, now termed the acute respiratory distress syndrome (ARDS), accounts for 4 million days annually in the intensive care units throughout the United States, and is associated with a high death rate in military personnel (i.e., up to 40% patients diagnosed with ARDS will die within a 28-day period). Moreover, survivors of ARDS may have substantial long-term problems due to physical and mental health impairments. Military personnel in combat environments are at particular risk for developing ARDS due to trauma, inhalation injury, and exposure to chemical, biological, or nuclear weapons. ARDS thus imposes significant burdens on military and public health resources worldwide, and only minimal improvements in patient survival have occurred over recent decades. A key feature of the lung in ARDS is that different regions of an injured lung can have different mechanical properties, such as how easily it expands or collapses during breathing or ventilation. Thus, many patients with ARDS must be supported on breathing machines, or ventilators, that provide assistance by using positive airway pressure. Lung protective ventilation strategies use high average airway pressures but small breathing volumes, in order to keep the lung inflated while minimizing the amount that it may be stretched. Such strategies have significantly improved survival in patients with ARDS, although the death rate remains high. This is because the best ventilator settings for one lung region may not necessarily be the same for another, even within the same patient: some areas become overinflated and damaged, while other areas may be underinflated and collapse. This detrimental process is referred to as "ventilator-associated lung injury" (VALI), and may cause to lung to release different inflammatory mediators that not only worsen existing lung injury, but may also lead to additional organ failure and death. Thus, the goal of this research project is to develop a novel method for mechanical ventilation, called "Multi-Frequency Oscillatory Ventilation" (MFOV), that optimizes the delivery of oxygen and removal of carbon dioxide from the lung (gas exchange) while simultaneously preserving lung protective ventilation. We hypothesize that lung function and gas exchange will be significantly improved if volume oscillations are applied at multiple frequencies (or breathing rates) simultaneously, rather than at a single frequency. MFOV allows each part of the lung to act as a unique mechanical filter and use whatever component of the multifrequency waveform it is best suited for. In Specific Aim 1 of this project, we will design MFOV waveforms for the injured lung using computer models of the respiratory system. These models will incorporate simulated mechanical properties similar to that observed in actual combat-related ARDS, allowing for realistic simulations that predict how the MFOV waveform should be fine-tuned to provide the optimal delivery of gas to all parts of an injured lung. In Specific Aim 2, computed tomographic (CT) imaging will be used to assess and quantify how MFOV improves the movement of gas throughout the lung in an animal model of combat-relevant ARDS, using inhaled Xenon gas as a radiographic tracer. This will establish a mechanistic basis for how lung function and gas exchange may be improved when MFOV is applied to an actual lung that has been injured. Ultimately, this innovative combination of computational modeling, physiologic experiments, and CT imaging will yield MFOV waveforms that are specifically optimized and "tuned" to the heterogeneous mechanics of the lung with ARDS. Results obtained from these comprehensive studies have a high likelihood of yielding a new, viable mode of ventilation in both military and civilian settings. MFOV thus has potential to change the current treatment strategies and protocols for critically ill ventilated patients and may significantly improve survi
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 31, 2017
- Source ID
- W81XWH1610434
Entities
People
- David W. Kaczka
Organizations
- United States Army
- University of Iowa