ASN's Mission

To create a world without kidney diseases, the ASN Alliance for Kidney Health elevates care by educating and informing, driving breakthroughs and innovation, and advocating for policies that create transformative changes in kidney medicine throughout the world.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on X

Kidney Week

Abstract: PUB053

Identification of Native Arteriovenous Fistula Maturation Failure Markers Through Patient-Specific Computational Models Based on Fluid Dynamics

Session Information

Category: Artificial Intelligence, Digital Health, and Data Science

  • 300 Artificial Intelligence, Digital Health, and Data Science

Authors

  • Ibeas, Jose, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Martínez-Dalmau, Lídia, Universitat Pompeu Fabra Escola d'Enginyeria, Barcelona, Spain
  • Aguado, Joaquin Vallespin, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Caravaca, Miriam, Institut d'Investigacio i Innovacio Parc Tauli, Sabadell, Barcelona, Spain
  • Camara, Oscar, Universitat Pompeu Fabra Escola d'Enginyeria, Barcelona, Spain
  • González de la Huebra, Teresa, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Correa Soto, Roberto, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Navazo, Diego, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Raldúa, Jana Merino, Hospital de Sabadell, Sabadell, Barcelona, Spain
  • Soto, Andres, Institut d'Investigacio i Innovacio Parc Tauli, Sabadell, Barcelona, Spain
  • Olivares, Andy, Universitat Pompeu Fabra Escola d'Enginyeria, Barcelona, Spain
Background

Native arteriovenous fistula (nAVF) has a high risk of failure. The aim is to identify markers associated with failure by constructing a computational fluid dynamics (CFD) model during maturation and developing a patient-specific modelling time pipeline, incorporating the haemodynamics of the blood flow to the anatomy.

Methods

Analysis of 3 patients at 1, 4 and 24 weeks post-surgery. 3D geometry was obtained via magnetic resonance imaging, flow data from ultrasound and pressure estimates from the 3-element Windkessel model were integrated using Ansys Fluent. CFD simulations provided key markers such as velocity, pressure, and Wall Shear Stress (WSS) to identify regions prone to complications.

Results

Results in Figs 1 and 2, illustrate the evolution over time. The geometrical characteristics were found to significantly impact flow dynamics. The most affected area by flow was the juxta-anastomotic, with a higher magnitude of WSS and velocity for all time-points.

A perpendicular junction between vein and artery potentially resulted in less damage. At the maturation stage (1 month), the analysis shows WSS distribution mainly located in the juxta-anastomosis and decreased in magnitude over one week; therefore, this can be marked as the stabilisation point for maturation.

Conclusion

- CFD simulation can contribute to an understanding of maturation pathophysiology
- This is the first model with follow-up and blood pressure in real conditions
- This method has the potential to personalised approach

Digital Object Identifier (DOI)