Parallel generation of extensive vascular networks with application to an archetypal human kidney model

Given the relevance of the inextricable coupling between microcirculation
and physiology, and the relation to organ function and disease
progression, the construction of synthetic vascular networks for
mathematical modelling and computer simulation is becoming an increasingly
broad field of research. Building vascular networks that mimic in-vivo
morphometry is feasible through algorithms such as constrained
constructive optimisation (CCO) and variations. Nevertheless, these
methods are limited by the maximum number of vessels to be generated due
to the whole network update required at each vessel addition. In this
work, we propose a CCO-based approach endowed with a domain decomposition
strategy to concurrently create vascular networks. The performance of this
approach is evaluated by analysing the agreement with the sequentially
generated networks and studying the scalability when building vascular
networks up to 200,000 vascular segments. Finally, we apply our
method to vascularise a highly complex geometry corresponding to the
cortex of a prototypical human kidney. The technique presented in this
work enables the automatic generation of extensive vascular networks,
removing the limitation from previous works. Thus, we can extent vascular
networks (e.g., obtained from medical images) to pre-arteriolar level,
yielding patient-specific whole-organ vascular models with an
unprecedented level of detail.