A fast algebraic approach for noninvasive prediction of fractional flow reserve in coronary arteries
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Taylor and Francis Ltd.
Abstract
The fractional flow reserve (FFR) index is an important clinical indicator for characterizing coronary artery disease (CAD) functional significance, allowing cardiologists to decide whether intervention is required or not. Noninvasive techniques for calculating FFR are still incompletely resolved and rely heavily on time consuming numerical methods, which may hinder their clinical translation. This paper reports on the development of two fast and noninvasive methods for predicting FFR in diseased coronary arteries. The new methods are derived from physical principles and account for patient-specific physiological parameters that can be noninvasively measured. The developed algebraic equations calculate FFR without performing any tedious numerical simulations, making them attractive for clinical applications. The performance of the methods is assessed by comparing their predictions with measurements and with results obtained by full three-dimensional numerical simulations on healthy and diseased idealized coronary arteries and actual anatomical branches. Results generated by the new methodology are within 5% of measurements and in very good agreement with values obtained numerically. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
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Computational fluid dynamics, Coronary arteries, Finite volume method, Fractional flow reserve, Reduced order model, Coronary angiography, Coronary artery disease, Coronary stenosis, Coronary vessels, Fractional flow reserve, myocardial, Humans, Predictive value of tests, Algebra, Diseases, Forecasting, Heart, Noninvasive medical procedures, Numerical models, Physiological models, Algebraic approaches, Clinical application, Fractional flow reserves, Full three-dimensional, Non-invasive prediction, Noninvasive technique, Physiological parameters, Article, Coronary artery pressure, Doppler flowmetry, Finite element analysis, Heart rate, Hemodynamics, Mathematical model, Mathematics, Non invasive procedure, Right coronary artery, Stenosis, Validation process, Coronary artery obstruction, Coronary blood vessel, Diagnostic imaging, Human, Predictive value, Numerical methods