Background Percutaneous coronary intervention (PCI) guided by fractional flow reserve (FFR) measurement is superior to visual angiographic assessment alone. We have developed a workflow that takes a single rotational angiogram (RoCA), reconstructs the 3-dimensional arterial tree and applies computational fluid dynamics (CFD) to calculate the FFR without the need to induce hyperaemia or perform invasive pressure measurements.
Methods 20 patients, scheduled for elective PCI underwent RoCA. The FFR was measured with a Combowire (Volcano), under resting and hyperaemic conditions. Physiologically significant lesions were stented and the measurements repeated. The arterial anatomy was reconstructed on a Philips 3DCA workstation. Generic boundary conditions for CFD were derived from the measured data. The calculated (“virtual”) and measured FFR values were then compared.
Results There were 11 right coronary artery (RCA) cases (6 stented) and 12 left coronary artery (LCA) cases (8 stented). The anatomy was reconstructed, and the FFR computed in each case (pre- and post-stenting). The CFD model accurately predicted which lesions were physiologically significant (FFR <0.8) and which were not (FFR >0.8) in all cases. The virtual FFR values deviated from the measured by ±6% (SD=6%) for both RCA and LCA cases.
Conclusion We have developed a novel, user-friendly workflow, which has the potential to predict FFR without the need for invasive measurements or inducing hyperaemic conditions. Our model identified lesions requiring intervention in all cases. Further work will optimise and refine the model by better characterising the downstream generic boundary conditions. We aim to improve the accuracy of the optimised model with more complex patients and lesions.
- Coronary artery disease
- fractional flow reserve
- percutaneous coronary intervention