| Autor: |
Nguyen T; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA., Argueta-Morales IR; b The Heart Center, Cardiothoracic Surgery , Arnold Palmer Hospital for Children , Orlando , FL , USA., Guimond S; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA., Clark W; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA., Ceballos A; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA., Osorio R; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA., Divo EA; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA.; c Department of Mechanical Engineering , Embry-Riddle Aeronautical University , Daytona Beach , FL , USA., De Campli WM; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA.; b The Heart Center, Cardiothoracic Surgery , Arnold Palmer Hospital for Children , Orlando , FL , USA.; d College of Medicine , University of Central Florida , Orlando , FL , USA., Kassab AJ; a Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, University of Central Florida , Orlando , FL , USA. |
| Abstrakt: |
Stroke is the most devastating complication after ventricular assist device (VAD) implantation with a 19% incidence and 65% mortality in the pediatric population. Current pediatric VAD technology and anticoagulation strategies alone are suboptimal. VAD implantation assisted by computational methods (CFD) may contribute reducing the risk of cerebral embolization. Representative three-dimensional aortic arch models of an infant and a child were generated. An 8 mm VAD outflow-graft (VAD-OG) anastomosed to the aorta was rendered and CFD was applied to study blood flow patterns. Particle tracks, originating in the VAD, were computed with a Lagrangian phase model and the percentage of particles entering the cerebral vessels was calculated. Eight implantation configurations (infant = 5 and child = 3) and 5 particle sizes (0.5, 1, 2, 3, and 4 mm) were considered. For the infant model, percentage of particles entering the cerebral vessels ranged from 15% for a VAD-OG anastomosed at 90° to the aorta, to 31% for 30° VAD-OG anastomosis (overall percentages: X(2) = 10,852, p < 0.0001). For the child model, cerebral embolization ranged from 9% for the 30° VAD-OG anastomosis to 15% for the 60° anastomosis (overall percentages: χ(2) = 10,323, p < 0.0001). Using detailed CFD calculations, we demonstrate that the risk of stroke depends significantly on the VAD implantation geometry. In turn, the risk probably depends on patient-specific anatomy. CFD can be used to optimize VAD implantation geometry to minimize stroke risk. |
