Computer-Aided Patient-Specific Coronary Artery Graft Design Improvements Using CFD Coupled Shape Optimizer.

Area of Science:

• Biomedical Engineering
• Cardiovascular Surgery
• Computational Fluid Dynamics

Background:

• Coronary artery bypass grafting (CABG) is crucial for treating complex cardiovascular disease.
• Optimizing graft design is essential to improve surgical outcomes and minimize re-stenosis.
• Patient-specific anatomical variations necessitate advanced planning tools.

Purpose of the Study:

• To demonstrate a novel surgical planning framework for cardiovascular reconstructions.
• To develop a CFD-coupled shape optimization method for patient-specific CABG design.
• To compare the hemodynamic efficiency of sequential CABG versus standard techniques.

Main Methods:

• Utilized multivariate 2D constraint optimization for Left Internal Mammary Artery (LIMA) graft design.
• Employed a sketch-based interactive tool for 3D graft translation.
• Evaluated graft performance using a validated non-Newtonian CFD solver.

Main Results:

• Restored coronary perfusion to healthy baseline levels across all revascularization techniques.
• Achieved significant Wall Shear Stress Gradient (WSSG) relief (~34%) with the optimized LIMA graft.
• Sequential grafts reduced WSSG by 15% proximal to the LAD and diagonal bifurcation.

Conclusions:

• The proposed framework effectively optimizes CABG design for improved hemodynamic efficiency.
• The methodology aids surgical decision-making in complex, patient-specific coronary bypass operations.
• This approach offers a rational basis for pre-operative surgical planning and evaluation.