Arterio-venous-fistulae (AVF) are surgically-formed connections between an artery and a vein and are regarded as the “gold standard” method of vascular access, for
haemodialysis. Nonetheless, up to 60% fail within three months of creation. Their principal failure mechanism is intimal hyperplasia (IH), an adverse inflammatory
process causing AVF to block and fail. Evidence suggests that IH is a multifactorial process, attributable to an altered vascular environment, including increased metabolic stress, flow disturbances, mechanical stress, and wall hypoxia (low oxygen levels). The present work focuses on studying wall hypoxia in idealised AVF.
Vascular walls are oxygenated by transport from both luminal oxygenated blood and adventitial vasa vasorum (VV), the microvascular network supplying large vessels. Luminal oxygen supply is affected by the altered AVF haemodynamics, while altered wall-mechanics can prevent adequate VV perfusion. The aim of this thesis is to ascertain what is most important in determining wall-oxygen levels: (i) modified luminal flow field; (ii) mechanically-modified VV perfusion. Hence, a model of oxygen transport, capable of accounting for VV damage/hypoperfusion, was developed. Geometries and VV perfusion fields obtained from mechanical simulations were used to provide the oxygen transport model with a VV oxygen source. Results suggest that for a given set of wall parameters, the local wall-oxygen levels are governed by the flow field, while spatial distributions of mechanically-modified VV perfusion are shown to have negligible effects on the local wall-oxygen levels. However, overall wall-oxygen levels are highly sensitive to changes in bulk wall parameters, particularly oxygen consumption rates.
Finally, these results were used to develop a simplified oxygen transport model, that is combined with a mesh-adaptive-direct-search approach to identify an optimal AVF configuration with reduced hypoxia levels. The configuration features a non-planar anastomosis and a helical shaped vein.Open Acces