The central role of metabolism in vascular morphogenesis

TL;DR

This paper presents an optimization-based model explaining how vascular networks self-organize to achieve uniform perfusion, balancing efficiency, energy, and material costs, with implications validated by experimental data.

Contribution

It introduces a simple adaptation rule for vessel radii that accounts for metabolic demand, explaining the transition between different vascular architectures.

Findings

Optimal absorption rate matches in vivo measurements.

Model reproduces diverse vascular morphologies.

Metabolic demand controls network structure transition.

Abstract

As nutrients travel through microcirculation and are absorbed, their availability continuously decreases. However, a uniform nutrient distribution is critical, as it prevents tissue death in poorly supplied areas. How, then, do vascular networks achieve equi-perfusion? Given the extensive number of vessels in animal vascular systems, the structure of smaller vessels cannot be fully genetically predetermined and thus relies on a self-organizing developmental mechanism. We propose a simple, optimization-based adaptation rule to control vessel radii, aiming to equalize perfusion while minimizing flow resistance and material cost. This adaptation balances three competing factors: perfusion efficiency, energy dissipation, and material expenditure, which together drive complex network morphologies. These morphologies range from hierarchical architectures optimized for minimal resistance and material cost to dense networks that achieve efficient perfusion. Notably, metabolic demand is the primary factor modulating the transition between these contrasting structures. By applying our adaptation rule to networks in the rat mesentery and comparing the resulting optimal perfusion architectures with the experimental data, we can estimate the biologically relevant parameters, such as the oxygen absorption rate, for which the optimization and experimental networks align the most. Surprisingly, the optimal absorption rate we derive matches independent in vivo measurements. This suggests that reduced-order models like ours can provide valuable insights into the development and function of real vascular networks.