In Vitro and In Silico Engineering of Cardiopulmonary Bypass Models

Pediatric patients undergoing open-heart surgery are supported by cardiopulmonary bypass (CPB), in which the artificial heart-lung machine pumps and oxygenates blood. CPB exposes blood to non-physiological stimuli, including high shear stress, which can cause acute postoperative systemic inflammation. We hypothesize that pro-inflammatory shear stresses can be mitigated by a data-driven optimization of CPB operation parameters and by introducing crystalloid fluid hemodilution.

To test our hypothesis, we developed 3D in silico models of the CPB pump head to calculate the dependence of flow shear stress on CPB parameters like roller occlusion, rotational speed, and hematocrit. Our models employ finite element analysis to reproduce the dynamics of tubing deformation in the raceway and computational fluid dynamics to resolve blood flow inside the tubing. Comparison studies with these models show the nonlinear relationships between CPB parameters and shear stress outcomes. In parallel, we built in vitro models to study circulating blood cells phenotypic changes, hemolysis, and monocyte inflammation after shearing.

These models offer a comprehensive platform to optimize CPB operational conditions and screen for mechanistic targets to ameliorate post-CPB systemic inflammation.