Structural Features of Microvascular Networks Trigger Blood Flow Oscillations

We analyse mathematical models in order to understand how microstructural features of vascular networks may affect blood flow dynamics, and to identify particular characteristics that promote the onset of self-sustained oscillations. By focusing on a simple three-node motif, we predict that network redundancy, in the form of a redundant vessel connecting two main flow-branches, together with differences in haemodynamic resistance in the branches, can promote the emergence of oscillatory dynamics. We use existing mathematical descriptions for blood rheology and haematocrit splitting at vessel branch-points to construct our flow model; we combine numerical simulations and stability analysis to study the dynamics of the three-node network and its relation to the system's multiple steady-state solutions. While, for the case of equal inlet-pressure conditions, a trivial equilibrium solution with no flow in the redundant vessel always exists, we find that it is not stable when other, stable, steady-state attractors exist. In turn, these nontrivial steady-state solutions may undergo a Hopf bifurcation into an oscillatory state. We use the branch diameter ratio, together with the inlet haematocrit rate, to construct a two-parameter stability diagram that delineates regimes in which such oscillatory dynamics exist. We show that flow oscillations in this network geometry are only possible when the branch diameters are sufficiently different to allow for a sufficiently large flow in the redundant vessel, which acts as the driving force of the oscillations. These microstructural properties, which were found to promote oscillatory dynamics, could be used to explore sources of flow instability in biological microvascular networks.

Automated summary

By analyzing mathematical models, we found that the microstructural features of vascular networks, such as redundancy and differences in flow resistance, can promote the emergence of oscillatory dynamics. We used numerical simulations and stability analysis to study the dynamics of a three-node network and its multiple steady-state solutions. We constructed a stability diagram using the branch diameter ratio and inlet haematocrit rate, which delineates the regimes where flow oscillations exist.