Leveraging Computational Fluid Dynamics for Next-Generation Preoperative Planning in Vascular Surgery

Chronic limb-threatening ischemia (CLTI) is one of the leading causes of permanent disability and death in the United States and around the world. Surgical revascularization is the mainstay of treatment for CLTI, but patients still suffer high rates of limb loss and early death, even compared to other cardiovascular diseases. One significant reason for this is the difficulty of accurately predicting whether a planned intervention will, in fact, improve distal blood flow as hoped. Given this need, we have introduced an angiography-based computational tool to enable surgeons to preoperatively assess a given revascularization strategy, before selecting the option that maximizes distal perfusion. We describe this computational model and demonstrate how it can accurately predict distal arterial flow in a pilot study of patients undergoing femoral artery angioplasty for CLTI.