CAREER: A Unified Multiscale Computational Approach to Model Vein Graft Failure

Coronary artery disease is the leading cause of death in the United States. One common treatment is the coronary bypass surgery, which is performed on about 350,000 patients in the United States each year. This surgery is considered the gold standard treatment for patients with disease in multiple coronary arteries. Vein grafts are used as bypass conduits in majority of these surgeries and have unacceptably high failure rates leading to reoperation and increased risk of complications. The underlying mechanisms of vein graft failure remain poorly understood. This Faculty Early Career Development Program (CAREER) project will use computer models of blood flow and blood vessels to understand these mechanisms of adaptations at different biological length scales. The computer models will also provide a framework for virtually testing biotechnologies and therapies for improving vein graft performance. In addition, the project includes educational programs to train students in these computer modeling tools, apply them to other blood vessel related diseases and strengthen biomedical engineering education through new educational modules and training opportunities. Coronary vein graft remodeling is a complex process influenced by multiple factors, including hemodynamic loads, inflammation and surgical trauma. Understanding how these factors interact across biological scales to determine the vein graft outcomes remains a major challenge. Recent advances in multiscale computational models of vascular adaptation can help gain insights into these adaptations; multiscale computational models allow for precise and controlled manipulation of individual contributing factors (either independently or in combination) while physics-based multiscale models can provide mechanistic insights across spatial and temporal scales. This project integrates several complementary modeling approaches to capture vein graft remodeling across biological levels. Specifically, it combines a vascular finite element model (at tissue scale) with continuum mechanics-based growth and remodeling (tissue/cellular scale), and systems cell level models. Formal data science methods will be used to inform and calibrate these models against existing experimental data. Advances in artificial intelligence will be leveraged to estimate unknown parameters, infer constitutive functions, and identify key mechanisms that govern vein graft remodeling. The resulting in silico model will be used to probe the central roles of mechanics and inflammation in vein graft remodeling and identify mechanisms that strongly influence vein graft outcomes. The multiscale model provides a powerful tool to accelerate hypothesis generation, guide experimental design, and support translational efforts. Insights will improve vein graft performance and cardiovascular health. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2543650 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Abhay Bangalore Ramachandra | Institution: Iowa State University, AMES, IA | Award Amount: $500,000 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2543650 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2543650.html