Computational model for simulation of vascular adaptation following vascular access surgery in haemodialysis patients

Abstract

An important number of surgical procedures for creation of vascular access (VA) in haemodialysis patients still results in non-adequate increase in blood flow (non-maturation). The rise in blood flow in arteriovenous shunts depends on vascular remodelling. Computational tools to predict the outcome of VA surgery would be important in this clinical context. The aim of our investigation was then to develop a 0D/1D computational model of arm vasculature able to simulate vessel wall remodelling and related changes in blood flow. We assumed that blood vessel remodelling is driven by peak wall shear stress. The model was calibrated with previously reported values of radial artery diameter and blood flow after end-to-end distal fistula creation. Good agreement was obtained between predicted changes in VA flow and in arterial diameter after surgery and corresponding measured values. The use of this computational model may allow accurate vascular surgery planning and ameliorate VA surgery outcomes.

Validation of a patient-specific hemodynamic computational model for surgical planning of vascular access in hemodialysis patients

“…The results of our clinical and numerical investigations provide evidence that the patient-specific hemodynamic computational models that we used 16,21 are accurate …”

“…In addition, in order to reliably predict changes in BFV several weeks after surgery, the solver embeds a vascular adaptation algorithm 21 calibrated (by setting of model constants, as recently described) 21 using a data set obtained by a previous investigation 26 based on the assumption that changes in blood vessel diameter take place upon changes in BFV to maintain a physiological value of the peak wall shear stress acting on vascular endothelial cells. 21 Brachial and radial artery BFV and diameter of vessels involved in the anastomosis were predicted according to AVF configuration using patient-specific theoretical vascular network models based on preoperative data (demographic and clinical parameters, blood pressure measurements, cardiac output and frequency, blood analysis, and preoperative brachial, radial, and ulnar artery BFV and major arm vessel diameters, as assessed during preoperative US examination). These theoretical models are based on a previously defined 28 network model of artery and vein segments connected on anatomical basis.…”

“…19,20 As these models enable to estimate changes in BFV only immediately after surgery, we extended this modeling approach to include a simulation of vessel wall remodeling and consequent hemodynamic changes that are responsible for the so-called access maturation. 21 Despite promising results, the potential clinical use of these computational tools needs assessment of their reliability and of the accuracy of model prediction in terms of BFV redistribution in arm vasculature. To this aim, a multicenter longitudinal clinical prospective study was conducted in patients with end-stage renal disease awaiting VA creation for HD treatment in the context of the EU-FP7 research project ARCH.…”

Haemodialysis access: clinical and epidemiological profile of patients and their vascular access in interior of Brazil

“…A significant proportion of patients with unknown etiology are reported in the literature, 16.2% of the elderly Indian Affairs, [12] 5.9% in the United States, 18% in the United Kingdom [13] and, similarly, 14, 8% in Iran. [14] Our finding of 31.7% of cases of unknown etiology may reflect the lack of awareness of the disease, deficiency in early diagnosis and delay in referral before you get to the specialist.…”

“…[3,9] They should be made 6 months prior to initiating haemodialysis. [10] If an AVF cannot be created, an AVF graft or venous catheter may be needed [11,12] but they should be avoided [6,13]. The studies showed that the native access presents the best patency (4 to 5 years) and lower rate of reoperation when compared with other accesses [14,15].…”