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The key role of a coronary artery is supplying sufficient blood flow that contains vital materials such as oxygen or glucose required by the myocardium. Therefore quantification of coronary blood flow (CBF) has paramount importance in the coronary physiology. However, absolute quantitation of vessel-specific CBF requires invasive cardiac catheterization and use of intracoronary wires with Doppler, pressure, or temperature probes. Non-invasive measurement of vessel-specific CBF from widely available modality would be very useful in clinical risk stratification and decision-making.
Computational flow dynamics modeling investigated the rheological background of vessel-specific CBF-derived from transluminal attenuation flow encoding (TAFE), which consisted of arterial input function of contrast, vascular dimension to be filled by contrast, and transluminal attenuation gradient (TAG) reflecting intracoronary kinetics of contrast. TAFE formula was calibrated and validated with myocardial blood flow (MBF) by perfusion CT. TAFE-derived vessel-specific CBF of normal and obstructive vessels were compared in separated single-beat CCTA study. In both studies, the vessel-specific myocardial mass was calculated by %fractional myocardial mass (%FMM).
In the simulated model, TAFE-derived CBF matched well with computational CBF and decreased proportionally to the stenosis severity. In perfusion CT study (134 vessels, 30 patients), TAFE formula showed good correlation with absolute vessel-specific MBF (r=0.87). In single-beat CCTA study (287 vessels, 98 patient), TAFE-derived CBF decreased consistently according to the diameter stenosis (DS) of 0% to 70% (0.98 ml g-1 min-1 to 0.67 ml g-1 min-1, test for trend, p<0.01)
The optimal cutoff of TAFE-derived CBF for DS≥50% was ≤0.89 ml g-1 min-1 and showed diagnostic performance with sensitivity 89%, specificity 66%, positive predictive value 46%, negative predictive value 95%, accuracy 71%.
TAFE enables easy-to-use non-invasive quantitative measurement of vessel-specific CBF from conventional CCTA. And shows good diagnostic performance for obstructive coronary artery disease compared to TAG. If we added TAFE to computational FFR, the performance of computational FFR would be improved.