Multi-scale Computational Models of Pro-angiogenic Treatments in Peripheral Arterial Disease

Abstract

The induction of angiogenesis is a promising therapeutic strategy for the amelioration of peripheral arterial disease (PAD). This occlusive disease results in muscle ischemia, and neovascularization is a route to increasing the perfusion in the tissue. The vascular endothelial growth factor (VEGF) family of potent pro-angiogenic cytokines is a potential therapeutic agent, increasing VEGF-receptor signaling on tissue vasculature. To investigate the effects of possible therapies on the VEGF concentrations and gradients within the tissue, we consider three such strategies: VEGF gene therapy (e.g. by adeno-associated virus); VEGF cell-based therapy (injected myoblasts that overexpress VEGF); and chronic exercise (which upregulates VEGF receptor expression). The multi-scale computational model used to investigate these strategies is an integration of several components: an anatomical description of the muscle geometry and cell types; microvascular blood flow; tissue oxygen distribution; VEGF secretion from muscle fibers; VEGF transport through interstitial space; and VEGF-receptor binding on microvascular endothelial cells. Exercise training, which results in increased VEGF secretion in hypoxic tissue and increased VEGF receptor expression, exhibits increases in both VEGF concentration and VEGF gradients, and is predicted to be more effective than the other, VEGF-only treatments.