Virtual Coronary Intervention: A Treatment Planning Tool Based Upon the Angiogram

Area of Science:

• Cardiovascular imaging and intervention
• Computational fluid dynamics in cardiology
• Medical device technology

Background:

• Fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) improves outcomes over angiography alone.
• Virtual FFR (vFFR) uses 3D coronary anatomy reconstruction and computational fluid dynamics (CFD) for non-invasive FFR calculation.
• Virtual stenting (VCI) predicts post-PCI FFR, enabling optimized treatment planning.

Purpose of the Study:

• To assess a novel virtual coronary intervention (VCI) tool's ability to predict physiological response to stenting.
• To evaluate the accuracy of VCI in predicting post-stenting outcomes compared to measured FFR.

Main Methods:

• Patients undergoing elective PCI had pre- and post-PCI pressure-wire FFR measurements.
• A 3D coronary artery model was reconstructed from angiograms for VCI simulation.
• Virtual stenting (VCI) was performed using CFD, calculating pre- and post-VCI vFFR, and compared with measured FFR (mFFR).

Main Results:

• Pre-PCI vFFR showed minimal deviation from mFFR (mean Δ = -0.02, SD = 0.07).
• Post-VCI vFFR closely matched post-PCI mFFR (mean Δ = -0.01, SD = 0.03).
• Mean CFD processing time for VCI was 95 seconds per case.

Conclusions:

• A novel VCI tool, utilizing angiographic data, accurately predicts the physiological response to coronary stenting.
• This VCI technology demonstrates high accuracy in predicting post-PCI FFR.
• The VCI tool shows promise for optimizing PCI treatment planning.