Computational Fluid Dynamics for the Prediction of Endograft Thrombosis in the Superficial Femoral Artery

Abstract

Purpose: Contemporary diagnostic modalities, including contrast-enhanced computed tomography (CTA) and duplex ultrasound, have been insufficiently able to predict endograft thrombosis. This study introduces an implementation of image-based computational fluid dynamics (CFD), by exemplification with 4 patients treated with an endograft for occlusive disease of the superficial femoral artery (SFA). The potential of personalized CFD for predicting endograft thrombosis is investigated. Materials and Methods: Four patients treated with endografts for an occluded SFA were retrospectively included. CFD simulations, based on CTA and duplex ultrasound, were compared for patients with and without endograft thrombosis to investigate potential flow-related causes of endograft thrombosis. Time-averaged wall shear stress (TAWSS) was computed, which highlights areas of prolonged residence times of coagulation factors in the graft. Results: CFD simulations demonstrated normal TAWSS (>0.4 Pa) in the SFA for cases 1 and 2, but low levels of TAWSS (<0.4 Pa) in cases 3 and 4, respectively. Primary patency was achieved in cases 1 and 2 for over 2 year follow-up. Cases 3 and 4 were complicated by recurrent endograft thrombosis. Conclusion: The presence of a low TAWSS was associated with recurrent endograft thrombosis in subjects with otherwise normal anatomic and ultrasound assessment and a good distal run-off.

Lesion Eccentricity Plays a Key Role in Determining the Pressure Gradient of Serial Stenotic Lesions: Results from a Computational Hemodynamics Study

“…For assessing flow mechanics in the variety of stenotic shapes in patients, image-based computational fluid dynamic simulations are an attractive and validated method for coronary lesions [ 26 ]. For peripheral arteries, computational fluid dynamic simulations of a patient’s geometry can furthermore be informed with a patient’s temporal flow profile obtained from duplex ultrasound [ 27 ]. Calcified plaques are difficult to quantify accurately using non-invasive imaging and may require intra-vascular ultrasonic or optical imaging [ 28 ] for accurate simulations.…”

Validation of ultrasound velocimetry and computational fluid dynamics for flow assessment in femoral artery stenotic disease

“…In addition, vector derived parameters, such as VC and WSS, could be used to quantify complex flow phenomena and identify locations potentially at risk for plaque formation, in-stent restenosis 47 or stentgraft thrombosis. 48 An extra potential benefit of CFD models is the ability to predict the effect of different treatment strategies on local hemodynamics to select a treatment that creates an optimal hemodynamic environment, with the aim to reduce reintervention rates. 49,50 The feasibility of ePIV and CFD in patients with atherosclerosis has already been shown in small patient populations.…”

“…49,50 The feasibility of ePIV and CFD in patients with atherosclerosis has already been shown in small patient populations. 16,47,48,51,52 However, longitudinal studies with larger cohorts are necessary to show the potential benefit of these novel modalities in clinical practice and to study the relation between vector derived parameters and clinical outcome.…”

Computational fluid dynamics for peripheral artery disease

“…97 For peripheral arteries, computational fluid dynamic simulations of a patient's geometry can furthermore be informed with a patient's temporal flow profile obtained from Duplex ultrasound. 183 Calcified plaques are difficult to quantify accurately using non-invasive imaging and may require intravascular ultrasonic or optical imaging for accurate simulations. It would be of interest to investigate whether the observed adverse effect of eccentricity also holds for other stenotic degrees and whether a correlation between eccentricity index 176 and pressure gradient is present in patients.…”

“…Further constants for the simulation were a blood density of 1059 kg/m3, a rigid wall, and a constant viscosity model with the dynamic viscosity set to µ blood = µ plasma (1+ 2.5ϵ + 6.2ϵ 2 ), 183 with µ plasma equal to 1.2 mPa s and the volumetric cell fraction of blood, considered equal to the hematocrit value of the patient prior to the procedure. A three-element prismatic boundary layer was applied for the meshing of the geometries, 1000 timesteps of 0.1 ms were simulated and the meshes were considered converged if the inlet pressure averaged at three timepoints (0.06, 0.08 and 0.1 s) did not change > 1% for a doubling of the mesh size.…”