Lung Research Poster Session

Farhad Rikhtegar Nezami, PhD

Lead investigator and Member of Faculty
Thoracic Surgery
Hamed Moradi, Elazer R. Edelman, Steven P. Keller, Farhad R. Nezami*
Risk of cardiac ischemia in respiratory failure patients using upper body venoarterial extracorporeal membrane oxygenation: a computational study

Extracorporeal membrane oxygenation (ECMO) can provide timely, comprehensive hemodynamic support for patients with cardiac and/or pulmonary failure. Though nowadays use of ECMO as a bridge to recovery or a pathway to a more durable therapy has been increased significantly, its interactions with the failing lung and/or heart as well as resulted perfusion patterns are still understudied. There is particular uncertainty about the optimal approach to bridge patients with end-stage lung disease complicated by pulmonary hypertension or right ventricular failure to lung transplant. Use of upper body venoarterial (VA) ECMO is recently suggested and clinically practiced for this patient group shunting blood around the cardiopulmonary circulation to offload and improve the function of the right ventricle while providing oxygenated blood to the aortic arch. Herein, we leverage our recent computational toolkit to explore the effects of upper body VA ECMO modulation on aorta hemodynamics, vital organs perfusion, and quantified oxygen distribution. With varying ECMO-derived perfusion between 0 to 5 Lit/min and imposing different levels of lung failure, we modeled oxygen transport and distribution in the aortic tree of a patient-specific model. Clinical flow waveforms and dynamic boundary conditions, i.e. lumped parameter models, were applied to maximize the outcome accuracy. Results revealed direct relation between ECMO cardiac flow share, geometrical morphology, and oxygen distribution of different vital organs and highlighted ischemia risk due to coronary perfusion with low-oxygenated blood. Such comprehensive computational modeling offers indispensable platforms with the potential of providing invaluable clinical insights to enhance therapy planning and improve patient outcomes.