Fig 1.
A) Diagram of platelet activation and deposition in the thrombosis model of Wu et al. [20]. krpdB and kapdB are the rates at which resting and activated platelets deposit to the surface. Resting platelets can be activated by mechanical shear or the combination of agonists: ADP, TxA2 and thrombin. Once deposited, APd can be detached by flow shearing forces. B) Platelet deposition on deposited platelets including cleaning by large shear stresses.
Table 1.
Biochemical species involved in platelet activity.
Table 2.
If units are not specified, parameters are non-dimensional. For more details on how krpd and kapd are computed please refer to the original paper of Wu et al. [20].
Fig 2.
A) Schematic depiction of fibrin production due to thrombin (Tb) cleavage and deposition of fibrinogen and fibrin at kFgB and kFnB kinetic rates, respectively. Deposited fibrin and fibrinogen (Fnd, Fgd) detach from the boundary or thrombus due to the flow shear stress. B) Fibrin deposition to existing thrombus.
Fig 3.
Partial model of the coagulation cascade.
Table 3.
Coagulation factors involved in the thrombosis model definition and reaction terms.
Table 4.
Kinetic constants used in the partial coagulation model.
Fig 4.
Dimensions were taken from experimental setup of Taylor et al. [38]. The magenta lines denote biomaterial walls where factor XII activation boundary conditions were applied.
Table 5.
Baseline inlet concentration values.
Table 6.
S = 1 − phi is used to quantified available binding sites.
Table 7.
Model parameters used in the bovine BFS simulation.
Table 8.
Grids used in the mesh convergence study for the BFS case.
The meshes are composed of uniform quadrilateral elements. The relative error is based on the predicted recirculation length.
Fig 5.
A) Microfluidic chamber geometry, upper part is hidden to visualize fibers. B) Experimental setup for hollow fiber bundle chamber experiment.
Fig 6.
A) Simulation domain comprised a quarter of the full geometry, taking advantage of device symmetries. Boundaries colored blue were set as symmetry planes, and boundaries colored red correspond to reactive boundary conditions. B) Mesh boundary layers at hollow fibers in the microfluidic chamber.
Table 9.
Inlet concentration for biochemical species for the microfluidic chamber case.
The platelet count was taken from Lai [49].
Table 10.
Mesh sizes used in mesh convergence analysis for the microfluidic chamber case.
Element dimension size corresponds to the smaller elements located at the fiber boundary layers. The meshes are composed of hexahedral, prism and polyhedral elements. The relative error was computed using the pressure drop across the chamber.
Fig 7.
Time course of scalar fields of thrombus and platelet volume fractions.
In the middle row shows the log10 scaled velocity magnitude scalar field and the influence of the growing thrombus in the flow.
Fig 8.
Quantitative comparison of simulation results and experimental data for BFS thrombus height normalized by step height and thrombus length normalized by the initial flow recirculation length.
Fig 9.
Comparison of thrombus formation at 10 min for the baseline model of Wu et al. [20] in terms of platelet volume fraction (pltVF) and the current thrombosis model as the sum of fibrin volume fraction and platelet volume fraction, THVF.
Fig 10.
Time course of thrombus formation in the hollow fiber bundle oxygenator, depicted by thrombus volume fraction threshold (THVF > 0.1) colored red.
The wall shear rate field (s−1) is shown prior to any thrombus growth, i.e., t = 0 min.
Fig 11.
Simulated and experimental thrombus formation patterns in the microfluidic hollow fiber bundle chamber at 15 min.
Thrombus height was used as a surrogate for thrombus density to compare against experimental deposition maps computed from multiple μCT averaged scans from Lai to create a clot probability map [49].
Fig 12.
Fibrin concentration field on the middle plane at 15 min.
Insets: local fibrin structure around individual hollow fibers compared against experimental images from Lai [49].