Affiliations: [a] Institute for Information Technologies, University of Kragujevac, Kragujevac, Serbia | [b] Bioengineering Research and Development Center, Kragujevac, Serbia | [c] Faculty of Engineering, University of Kragujevac, Kragujevac, Serbia
Correspondence:
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Corresponding author: Aleksandar Milovanovic, Institute for Information Technologies, University of Kragujevac, 34000 Kragujevac, Serbia. E-mail: acakg85@hotmail.com.
Abstract: BACKGROUND: The fractional flow reserve (FFR) index has been widely accepted as a standard diagnostic method for identifying functional relevance of coronary stenosis. Since the invasive techniques used for its determination are associated with a certain risk of vascular injury, as well as with an increased cost, several non-invasive procedures have been developed. OBJECTIVE: The aim of this study was to compare FFR values for the coronary artery obtained by computational fluid dynamics (CFD) and coronary computed tomography angiography (CCTA). METHODS: Computation of FFR has been performed using both numerical and the analytical method. The numerical method employs CFD to solve the governing equations which relate to mass and momentum conservation (the continuity equation and the Navier-Stokes equations) as well as CCTA to generate the three-dimensional computational domain. After imposing the appropriate boundary conditions, the values of the pressure change are calculated and the FFR index is determined. Based on Bernoulli’s law, the analytical method calculates the overall pressure drop across the stenosis in the coronary artery, enabling FFR determination. RESULTS: The clinical data for twenty patients who underwent invasive coronary angiography are used to validate the results obtained by using CFD (together with CCTA) simulation and analytical solution. The medically measured FFR compared to the analytical one differs by about 4%, while, the difference is about 2.6% when compared to the numerical FFR. For FFR values below 0.8 (which are considered to be associated with myocardial ischemia) the standard error has a value of 0.01201, while the standard deviation is 0.02081. For FFR values above 0.80, these values are slightly higher. Bland-Altman analysis showed that medical measurement and numerical FFR were in good agreement (SD = 0.0292, p< 0.0001). CONCLUSIONS: The analytically calculated FFR has a slightly lower coefficient of determination than the numerically computed FFR when compared with experimental one. However, it can still give a reliable answer to the question of whether patients need a stent, bypass surgery or only drug treatment and it requires a significantly lower computation time.
Keywords: Coronary artery stenosis, fractional flow reserve, CFD, Bernoulli’s law
