Computational Model for Anatomical and Flow Characteristic Analysis for Arteriovenous Fistulae

Abstract

Currently, arteriovenous fistulas (typically the attachment of the radial artery to the cephalic vein and termed AVF) are the most common form of vascular access for patients enduring end-stage renal failure undergoing hemodialysis. Plagued with high failure rates, the root causes of the primary failure mode, stenosis, are still unknown. The purpose of this thesis is to (i) investigate and potentially identify hemodynamic parameters that may contribute to the onset and progression of stenosis and (ii) determine surgical configurations to promote fistula maturation in patients.Here, a numerical method has been developed to noninvasively analyze the geometric fistula and flow parameters and, in turn, to improve the understanding of the underlying mechanisms behind fistula stenosis. This approach involves the use of non-contrast magnetic resonance (MR) imaging to generate 3D fistula models and perform computational fluid dynamic (CFD) analyses to analyze fistula hemodynamic parameters 3 days post-operation and the subsequent impact on Cross-Sectional Area (CSA) at 28 days post-operation. This study was performed on 3 fistulas created in 2 Yorkshire cross domestic swine. The vein CSA was divided into four subregions to examine how hemodynamic flow parameters vary across the same cross section. Based on our findings, high levels of oscillatory shear index (OSI) at day 3 suggests a great risk of CSA reduction. The hemodynamic profiles vary based on the angle of attachment of the fistulas and the curvature of the vein. The angle of attachment of the AVF and the curvature impact the uniformity of the low, Flow profiles that reduce blood recirculation in the vein and create a uniform velocity promote factors that lead to maturation, though more fistulas need to be analyzed to establish direct relationships. Characterizing the hemodynamic profiles of a several fistulas configurations could aid in the determination of factors that drive stenosis and allow for the creation of risk categories. This approach could eventually lead to higher fistula maturation rates and allow for early stratification of patient risk to enhance patient treatment.