Temporal-spatial heterogeneity of hematocrit in microvascular networks

Hematocrit, defined as the volume percentage of red blood cells in blood, is an important indicator of human health status, which demonstrates the capability of blood to deliver oxygen. It has been studied over many decades using in vivo, in vitro, and in silico experiments, and recent studies have shown that its major feature in microvascular networks is the temporal-spatial heterogeneity. The present work is a numerical study of such temporal-spatial heterogeneity, based on direct simulations of cellular-scale blood flow in complex microvascular networks. The simulations take into account the cell deformation and aggregation and thus are able to capture both the three-dimensional dynamics of each individual cell and the temporal-spatial distribution of cell population. The results showed that the temporal-spatial heterogeneity is more pronounced in the network that has the vessels with smaller diameters or with more complex geometry. Such heterogeneity is largely attributed to the existence of bifurcations, where the positively correlated hypotactic (feeding-branch) and paratactic (branch-branch) relations are generally observed in both the time-averaged hematocrit and temporal hematocrit ranges. This suggests that the successive bifurcations have a substantial impact on the temporal-spatial heterogeneity of hematocrit. However, these positive correlations may be broken up if the diameter of the feeding vessel is small enough or the bifurcation is asymmetric extremely, due to the vessel blockage. The present study is of great clinical significance to help doctors make more accurate diagnosis and treatment, by providing more information about the temporal-spatial distribution of the hematocrit in microvascular networks.

Automated summary

Hematocrit, as an important indicator of human health, shows the capability of blood to deliver oxygen. Recent studies have found that temporal-spatial heterogeneity is a major feature of hematocrit in microvascular networks. This study uses numerical simulations to investigate the temporal-spatial heterogeneity, and the results show that it is more pronounced in networks with smaller vessel diameters or more complex geometry. This research has significant clinical implications for more accurate diagnosis and treatment.