Patient-specific computational haemodynamics associated with surgical creation of an arteriovenous fistula
Abstract Despite arteriovenous fistulae (AVF) being the preferred vascular access for haemodialysis, high primary failure rates (30-70%) and low one-year patency rates (40-70%) hamper their use. The haemodynamics within the vessels of the fistula change significantly following surgical creation of the anastomosis and can be a surrogate of AVF success or failure. Computational fluid dynamics (CFD) can crucially predict AVF outcomes through robust analysis of a fistula’s haemodynamic patterns, which is impractical in-vivo. We present a proof-of-concept CFD framework for characterising the AVF blood flow prior and following surgical creation of a successful left radiocephalic AVF in a 20-year-old end-stage kidney disease patient. The reconstructed vasculature was generated utilising multiple contrast-enhanced magnetic resonance imaging (MRI) datasets. Large eddy simulations were conducted for establishing the extent of arterial and venous remodelling. Following anastomosis creation, a significant 2-3-fold increase in blood flow rate was induced downstream of the left subclavian artery. This was validated through comparison with post-AVF patient-specific phase-contrast data. The increased flow rate yielded an increase in time-averaged wall shear stress (TAWSS), a key marker of adaptive vascular remodelling. We have demonstrated TAWSS and oscillatory shear distributions of the transitional-flow in the venous anastomosis are predictive of AVF remodelling.