Interstitial lung disease (ILD) represents a collection of lung disorders with a lethal trajectory with few therapeutic options with the exception of lung transplantation. Various extracorporeal membrane oxygenation (ECMO) configurations have been used for bridge to transplant (BTT), yet no optimal configuration has been clearly demonstrated. Using a cardiopulmonary simulation, we assessed different ECMO configurations for patients with end-stage ILD to assess the physiologic deficits and help guide the development of new long-term pulmonary support devices. A cardiopulmonary ECMO simulation was created, and changes in hemodynamics and blood gases were compared for different inflow and outflow anatomic locations and for different sweep gas and blood pump flow rates. The system simulated the physiologic response of patients with severe ILD at rest and during exercise with central ECMO, peripheral ECMO, and with no ECMO. The output parameters were total cardiac output (CO), mixed venous oxygen (O2) saturation, arterial pH, and O2 delivery (DO2)/O2 utilization (VO2) at different levels of exercise. The model described the physiologic state of progressive ILD and showed the relative effects of using various ECMO configurations to support them. It elucidated the optimal device configurations and required physiologic pump performance and provided insight into the physiologic demands of exercise in ILD patients. The simulation program was able to model the pathophysiologic state of progressive ILD with PH and demonstrate how mechanical support devices can be implemented to improve cardiopulmonary function at rest and during exercise. The information generated from simulation can be used to optimize ECMO configuration selection for BTT patients and provide design guidance for new devices to better meet the physiologic demands of exercise associated with normal activities of daily living.
Extracorporeal Membrane Oxygenation for End-Stage Interstitial Lung Disease With Secondary Pulmonary Hypertension at Rest and Exercise: Insights From Simulation Modeling
S Chicotka, D Burkhoff, ML Dickstein and M Bacchetta
ASAIO J 2017