Patient-specific hemodynamic markers co-localise with regions of neointimal hyperplasia in an arteriovenous graft

Abstract

Purpose. Most computational fluid dynamics (CFD) studies on arteriovenous grafts (AVGs) adopt idealised geometries and simplified boundary conditions (BCs), potentially resulting in misleading conclusions when attempting to predict neointimal hyperplasia (NIH) development. Moreover, they often analyse a limited range of hemodynamic indices, lack validation, and fail to link the graft-altered hemodynamics with follow-up data. This study develops a novel patient-specific CFD workflow for AVGs using pathophysiological BCs. It validates the CFD results with patient medical data and assesses the co-localisation between CFD results and NIH regions at follow-up. Methods. Contrast-enhanced computed tomography angiography images were used to segment the patient-specific AVG geometry. A uniform Doppler ultrasound (DUS)-derived velocity profile was imposed at the inlet, and three-element Windkessel models were applied at the arterial outlets of the domain. Transient, rigid-wall simulations were performed using the k-omega SST turbulence model. The CFD-derived flow waveform was compared with the DUS image of the patient to ensure validation. Turbulent kinetic energy (TKE), helicity and near-wall hemodynamic descriptors were calculated and linked with regions presenting NIH from a 4-month follow-up fistulogram. Results. In the analysed patient, areas presenting high TKE and balanced helical flow structures at baseline exhibit NIH growth at follow-up. Transverse wall shear stress index is a stronger predictor of NIH than other commonly analysed near-wall hemodynamic indices, since luminal areas subjected to high values greatly co-localise with observed areas of remodelling. Conclusion. This patient-specific computational workflow for AVGs could be applied to a larger cohort to unravel the link between altered hemodynamics and NIH progression in vascular access.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work was funded by the University College London EPSRC Centre for Doctoral Training i4health [EP/S021930/1] and the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) [203145Z/16/Z]. We also acknowledge the BBRC International Institutional Awards University College London (IIA Tranche 1 UCL).

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study received ethical approval from the Yale Institutional Review Board (approval number 2000032101).

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Data Availability

All data produced in the present study are available upon reasonable request to the authors.

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