Why the study?
Does a virtual functional assessment index (vFAI) derived from routine angiographic data accurately predict invasive fractional flow reserve in patients with intermediate coronary lesions?
Does a virtual functional assessment index (vFAI) derived from routine angiographic data accurately predict invasive fractional flow reserve in patients with intermediate coronary lesions?
A fast, CFD-powered virtual haemodynamic assessment model using routine angiography showed high diagnostic performance for predicting invasive wire-FFR in intermediate coronary lesions without requiring hyperaemia.
Supports angiography-based virtual assessment of intermediate lesions; hypothesis-generating and requires prospective validation before clinical adoption.
AIMS: To develop a simplified approach of virtual functional assessment of coronary stenosis from routine angiographic data and test it against fractional flow reserve using a pressure wire (wire-FFR). METHODS AND RESULTS: Three-dimensional quantitative coronary angiography (3D-QCA) was performed in 139 vessels (120 patients) with intermediate lesions assessed by wire-FFR (reference standard: ≤0.80). The 3D-QCA models were processed with computational fluid dynamics (CFD) to calculate the lesion-specific pressure gradient (ΔP) and construct the ΔP-flow curve, from which the virtual functional assessment index (vFAI) was derived. The discriminatory power of vFAI for ischaemia- producing lesions was high (area under the receiver operator characteristic curve [AUC]: 92% [95% CI: 86-96%]). Diagnostic accuracy, sensitivity and specificity for the optimal vFAI cut-point (≤0.82) were 88%, 90% and 86%, respectively. Virtual-FAI demonstrated superior discrimination against 3D-QCA-derived % area stenosis (AUC: 78% [95% CI: 70- 84%]; p<0.0001 compared to vFAI). There was a close correlation (r=0.78, p<0.0001) and agreement of vFAI compared to wire-FFR (mean difference: -0.0039±0.085, p=0.59). CONCLUSIONS: We developed a fast and simple CFD-powered virtual haemodynamic assessment model using only routine angiography and without requiring any invasive physiology measurements/hyperaemia induction. Virtual-FAI showed a high diagnostic performance and incremental value to QCA for predicting wire-FFR; this "less invasive" approach could have important implications for patient management and cost.
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Papafaklis et al. (2014) studied this question.
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