Quantification of effects of mean blood pressure and left ventricular mass on noninvasive fast fractional flow reserve

Proper inlet boundary conditions arc essential for accurate computational fluid dynamics (CFD) modeling. We developed methodology to derive noninvasive FFR B using CFD and computed tomography coronary angiography (CTCA) images. This study aims to assess the influence of brachial mean blood pressure (MBP) and total coronary inflow on FFRB computation. Twenty-two patients underwent both CTCA and FFR measurements. Total coronary flow was computed from left ventricular mass (LVM) measured from CTCA. A total of 286 CFD simulations were run by varying MBP and LVM at 70, 80, 90, 100, 110, 120, and 130% of the measured values. FFRB increased with incrementally higher input values of MBP: 0.78 +/- 0.12, 0.80 +/- 0.11, 0.82 +/- 0.10, 0.84 +/- 0.09, 0.85 +/- 0.08, 0.86 +/- 0.08, and 0.87 +/- 0.07. respectively. Conversely. FFRB decreased with incrementally higher inputs value of LVM: 0.86 +/- 0.08, 0.85 +/- 0.08, 0.84 +/- 0.09. 0.84 +/- 0.09, 0.83 +/- 0.10, 0.83 +/- 0.10, and 0.82 +/- 0.10, respectively. Noninvasive FFRB calculated using measured MBP and LVM on a total of 30 vessels was 0.84 +/- 0.09 and correlated well with invasive FFR (0.83 +/- 0.09) (r = 0.92. P < 0.001). Positive association was observed between FFRB and MBP input values (mmHg) and negative association between FFRB and LVM values (g). Respective slopes were 0.0016 and -0.005. respectively, suggesting potential application of FFRB in a clinical setting. Inaccurate MBP and LVM inputs differing from patient-specific values could result in misclassification of borderline ischemic lesions. NEW & NOTEWORTHY While brachial mean blood pressure (MBP) and left ventricular mass (LVM) measured from CTCA are the two CFI) simulation input parameters, their effects on noninvasive fractional flow reserve (FFRB) have not been systematically investigated. We demonstrate that inaccurate MBP and LVM inputs differing from patient-specific values could result in misclassification of borderline ischemic lesions. This is important in the clinical application of noninvasive FFR in coronary artery disease diagnosis.