Numerical analysis of the pressure drop across highly-eccentric coronary stenoses: application to the calculation of the fractional flow reserve

Abstract

BackgroundFractional flow reverse (FFR) is the gold standard assessment of the hemodynamic significance of coronary stenoses. However, it requires the catheterization of the coronary artery to determine the pressure waveforms proximal and distal to the stenosis. On the contrary, computational fluid dynamics enables the calculation of the FFR value from relatively non-invasive computed tomography angiography (CTA).MethodsWe analyze the flow across idealized highly-eccentric coronary stenoses by solving the Navier–Stokes equations. We examine the influence of several aspects (approximations) of the simulation method on the calculation of the FFR value. We study the effects on the FFR value of errors made in the segmentation of clinical images. For this purpose, we compare the FFR value for the nominal geometry with that calculated for other shapes that slightly deviate from that geometry. This analysis is conducted for a range of stenosis severities and different inlet velocity and pressure waveforms.Results and conclusionsThe errors made in assuming a uniform velocity profile in front of the stenosis, as well as those due to the Newtonian and laminar approximations, are negligible for stenosis severities leading to FFR values around the threshold 0.8. The limited resolution of the stenosis geometry reconstruction is the major source of error when predicting the FFR value. Both systematic errors in the contour detection of just 1-pixel size in the CTA images and a low-quality representation of the stenosis surface (coarse faceted geometry) may yield wrong outcomes of the FFR assessment for an important set of eccentric stenoses. On the contrary, the spatial resolution of images acquired with optical coherence tomography may be sufficient to ensure accurate predictions for the FFR value.

A Hemodynamic-Based Evaluation of Applying Different Types of Coronary Artery Bypass Grafts to Coronary Artery Aneurysms

“…However, obtaining coronary artery physiological parameters is not easy due to its small size, numerous branches, and distribution on the heart's surface. erefore, in order to obtain life-like boundary conditions, we selected the lumped-parameter model (LPM), which is a circuit model that can simulate the blood flow and pressure through current and voltage, to provide boundary conditions for the CFD simulation [25][26][27]. One reason for choosing LPM is its simplicity.…”

Influence of the position of the distal pressure measurement point on the Fractional Flow Reserve using in-silico simulations

“…Since in this case the most relevant variable is aortic pressure instead of time, a uniform step will be used in the dependent variable aortic pressure rather than a uniform step in the independent variable time. This procedure [8,46,47] uses a constant pressure increase, being determined the corresponding time increase. An algorithm, that is incorporated into the program by means of an UDF, determines the appropriate constant aortic pressure variation and calculates the corresponding variable time steps.…”

“…This procedure is a catheterization to measure the pressure in two points distal and proximal to the stenosis. Then, FFR is de ned as the minimum value of the ratio P d /P a in several cardiac cycles, being P d and P a the mean values over a cardiac cycle as de ned in [8]. The FAME (Fractional Flow Reserve vs Angiography for Multivessel Evaluation) [9] and FAME II [10] trials have proved that, in critical lesions (FFR < 0.80), a substantial reduction in urgent revascularizations is achieved performing FFR-guided PCI plus the best medical therapy in contrast to applying only the best medical therapy.…”

Image‐based computational fluid dynamics for estimating pressure drop and fractional flow reserve across iliac artery stenosis: A comparison with in‐vivo measurements

“…The study showed that in two out of three of vessels the minimum lumen diameter variation resulted in the highest variation of FFR CT , followed closely by the resistance value, while in the third vessel the opposite was true with resistance responsible for the highest variation in FFR CT followed by the minimum lumen diameter [19]. This was later confirmed by Agujetas et al who investigated the effects of single pixel variation in the geometry of an idealised coronary artery with a highly eccentric stenosis and showed significant errors in the calculated FFR [20]. While both geometry and boundary conditions seem to impact the final results in coronary FFR and warrant further investigation for the broader applications in other vessels, solely the investigation of boundary condition variations is the intended purpose of this study.…”

“…The accurate prediction of blood flow via CFD simulations is dependent on many factors such as accurate representation of the geometry, mesh quality, the numerical methods that have been used, and appropriate boundary conditions. Out of these the geometry reconstruction and mesh quality have some of the highest impact when it comes to coronary artery FFR, closely followed by the choice of boundary conditions [19,20]. Sankaran et al investigated errors in calculating CFD derived coronary FFR on CT‐derived geometries (FFR CT ) using inlet velocity profiles estimated from cardiac output and resistance boundary conditions.…”