Virtual Coronary Artery Bypass Grafting.

Area of Science:

• Cardiovascular Surgery
• Medical Imaging
• Computational Fluid Dynamics

Background:

• Coronary artery bypass grafting (CABG) is superior to percutaneous coronary intervention (PCI) for complex coronary artery disease (CAD).
• Accurate prediction of post-operative hemodynamics is crucial for CABG success.
• Current methods for assessing graft performance often require invasive procedures.

Purpose of the Study:

• To develop and validate a non-invasive computational platform integrating coronary computed tomographic angiography (CCTA) and computational fluid dynamics (CFD).
• To predict post-CABG hemodynamics, including virtual grafting and fractional flow reserve (FFR) estimation.
• To assess the accuracy of virtual FFR compared to invasive measurements.

Main Methods:

• Prospective proof-of-concept study involving four patients with multi-vessel CAD undergoing CABG.
• 3D reconstruction of coronary anatomy from pre-CABG CCTA.
• Virtual bypass grafting simulations using patient-specific and mixed-specificity graft sizes.
• CFD simulations to estimate post-CABG FFR, validated against invasive FFR.

Main Results:

• Computational FFR demonstrated strong correlation with invasive FFR (r² = 0.92 for patient-specific, r² = 0.88 for mixed-specificity).
• Bland-Altman analysis showed minimal bias for both graft types.
• High agreement with invasive FFR was observed (90% for patient-specific, 80% for mixed-specificity).

Conclusions:

• The virtual CABG model accurately predicts post-operative hemodynamics and FFR.
• This non-invasive platform offers potential to optimize graft strategies and reduce reliance on invasive FFR.
• Further clinical integration and large-scale validation are warranted to enhance surgical planning and patient outcomes.