Fluid dynamics-informed CCTA-derived geometric parameters in right coronary artery anomalies predict abnormal invasive Adenosine-FFR and Dobutamine-FFR.
Abstract
Background Traditional anatomical assessment of stenosis in right anomalous aortic origin of coronary arteries (R-AAOCA) may not capture the complex, eccentrically shaped lumen and its perimeter-dependent resistance, and may therefore underestimate flow limitation. R-AAOCA involves both fixed stenosis, similar to atherosclerotic plaques (assessable with invasive adenosine-derived fractional flow reserve, FFRAdenosine), and additional stress-induced dynamic stenosis; both components can be captured with dobutamine-derived FFR (FFRDobutamine). We hypothesized that fluid dynamics-informed geometric parameters provide a physiologically grounded description with enhanced discriminative value compared with conventional geometric parameters for predicting FFRAdenosine and FFRDobutamine.Methods We performed a retrospective analysis of prospectively enrolled participants from the National Registry of Coronary Anomalies (NARCO) who underwent invasive FFRAdenosine and FFRDobutamine assessment. We calculated multiple CCTA-derived geometric parameters organized into two categories: (1) conventional geometric parameters including cross-sectional area (A), perimeter (P), minor and major axes at the ostium and intramural lumen area (ILA; i.e., the point of maximal stenosis), and effective diameter (Deff = (4A/π)); and conventional stenosis ratios including the area stenosis ratio (ASR) and effective diameter stenosis ratio (EDSR); (2) fluid dynamics-informed parameters comprising shape descriptors: including hydraulic diameter (Dh = 4A/P), elliptic ratio (ER = major/minor axis), circularity (C = 4πA/P2), and hydraulic diameter stenosis ratio (HDSR); and resistance-based indices including resistance index (RI = L × P4/A4), ostial angulation penalty (OAP = Aostial/Aref × [1 + tan(θ)]), and comprehensive stenosis score (CSS = RI × ER × [1 + sin(θ)]) integrating resistance, shape-dependent losses, and take-off angle (θ) effects. The invasive reference was hemodynamic relevance (i.e. FFR≤0.80) in FFRAdenosine and FFRDobutamine. We assessed Pearson correlation with FFR, univariable linear regression (R2), logistic regression with odds ratios (OR), and ROC AUC for classification (FFR≤0.80).Results A total of 81 R-AAOCA patients were included with a mean age of 52.3 ± 12.0 years and a mean body mass index of 27.0 ± 5.1 kg/m2; 27 patients (33.3%) were female. FFRAdenosine≤0.80 was observed in 5 (6.2%) patients and FFRDobutamine≤0.80 in 16 (19.8%) patients. The highest discriminatory power to predict abnormal FFRAdenosine was observed for the RI (AUC = 0.97, 95% CI 0.92-1.00), followed by the OAP (AUC = 0.97, 95% CI 0.92-1.00), ostial area (AUC = 0.96, 95% CI 0.90-1.00), CSS (AUC = 0.95, 95% CI 0.89-0.99), and ostial minor diameter (AUC = 0.95, 95% CI 0.90-0.99). The highest discriminatory power to predict abnormal FFRDobutamine was observed for ostial minor diameter (AUC = 0.85, 95% CI 0.74-0.94), followed by RI (AUC = 0.83, 95% CI 0.68-0.95) and ILA minor diameter (AUC = 0.81, 95% CI 0.69-0.92). RI explained 45% of the variance in FFRAdenosine and 43% of the variance in FFRDobutamine. At optimal thresholds, RI achieved 100% sensitivity and 95% specificity for predicting abnormal FFRAdenosine, whereas ostial minor diameter achieved 100% sensitivity and 57% specificity for predicting abnormal FFRDobutamine.Conclusions In patients with R-AAOCA, CCTA-derived fluid dynamics-informed metrics showed high diagnostic performance for identifying hemodynamically relevant fixed stenosis (i.e., defined by abnormal FFRAdenosine), with discriminatory ability comparable to conventional geometric parameters. For combined fixed and stress-induced dynamic stenosis (i.e., defined by abnormal FFRDobutamine), both approaches performed similarly but with lower accuracy, underscoring the need for more advanced noninvasive modeling approaches that explicitly capture the stress-induced dynamic component.
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Authors: Ali Mokhtari, Anselm W. Stark, Dominik Obrist, Marius Reto Bigler, Stefano F. de Marchi, Lorenz Räber, Isaac Shiri, Christoph Gräni
Institutions: University Clinic of Traumatology, Centre for Biomedical Engineering and Physics