Vascular adaptation and network efficiency

The formation of stable vascular networks is a complex process, and the exact mechanisms involved are not known. In addition to shear‐driven adaptation, tissue‐derived growth factors are thought to be important for maintaining a stable vasculature. Thus, the minimization of the energy necessary to drive flow can be balanced against the metabolic demands of the surrounding tissue. Using the principle of parsimony, we seek the simplest mathematical model of structural adaption that leads to a stable, physiologically plausible equilibrium. To simulate vascular remodeling, we employ a lattice Boltzmann framework (LBM) optimized for graphics processing units (GPUs) and incorporate numerical techniques derived from image processing to track the evolution of the computational domain over time. Some novel aspects of our model include: i) spatially‐resolved mesoscale permeabilities for both fluid and solute species; ii) particle erythrocyte advection with real oxygen release dynamics; iii) diffusive and conductive signaling; iv) automatic handling of changes in vascular topology. In addition to simulating structural adaption in silico, we combine our modeling framework with in vivo imaging to analyze the structure and function of vessels in living tissues.