A fast algebraic approach for noninvasive prediction of fractional flow reserve in coronary arteries

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.