Coronary artery bypass graft (CABG) surgery is a gold standard treatment for patients with advanced coronary artery disease, with over 400,000 cases performed each year in the US. While arterial grafts have greater long- term patency compared to vein grafts, their use is limited by availability, and saphenous vein grafts (SVGs) are used in the majority of patients. Following CABG surgery, SVG failure occurs at alarmingly high rates, with 5- 10% of SVGs occluding within the first month after surgery, and 40-50% of SVGs failing within 10 years. The risk of SVG disease and the complex mechanobiology of graft failure are known to be associated with mechanical stimuli, including hemodynamics and vessel wall mechanics. However, standard computed tomography (CT) imaging provides no direct means to characterize these stimuli. Recent advances in multiscale modeling now permit physiologic closed-loop simulations with realistic material properties, avoiding prior limitations of idealized anatomy, rigid walls, and incomplete coronary models. We propose a novel coronary simulation framework that can comprehensively characterize bypass graft hemodynamics and wall mechanics using only non-invasive clinical data. We propose that validated simulations with realistic hemodynamics and wall motion, in concert with modern imaging techniques will enable post-CABG risk stratification and early identification of patients at high risk for saphenous graft failure. To accomplish these goals, we propose three specific aims: 1) design and validate a novel closed-loop multiscale CABG simulation framework that can predict local hemodynamics and wall mechanics using only non-invasive clinical data, 2) quantify and compare the mechanical stimuli acting on arterial and vein grafts in patient- specific models, and 3) develop a pilot risk stratification scoring system for post-CABG patients by correlating mechanical stimuli with clinical outcomes in vessels with and without SVG disease. The proposed work is significant and innovative because it will (1) use patient-specific simulations to virtually reverse SVG disease thus using patients as their own control (2) enable early identification of patients at increased risk of SVG obstruction whose outcomes may be improved by more intensive treatment and monitoring, (3) enable future vessel wall growth and remodeling simulations which rely on mechanical stimuli data, (4) combine high resolution imaging with sophisticated multiscale modeling of the complete coronary circulation, and (5) directly validate model predictions against clinical data and report confidence intervals on simulation results. This project assembles a unique team including an adult cardiologist and imaging specialist with a background in physics, and an engineering team with established expertise in cardiovascular biomechanics. We will build upon our extensive experience with patient-specific blood flow simulations, and a successful track record of clinical translation and multi-disciplinary collaboration. Our translational goal is to provide clinicians with new tools to improve management decisions for CABG patients at risk for graft failure and improve outcomes.

Public Health Relevance

Coronary artery bypass grafting (CABG) is a gold standard for treatment of patients with advanced coronary artery disease, with nearly half a million CABG surgeries performed annually in the US. Despite improvements in surgical technique and post-surgical medical management, failure rates of saphenous vein grafts remain as high as 40-50% in the 10 years following surgery. This proposal applies novel multiscale simulation methods with deformable vessel walls using data from high-resolution computed tomography angiography to assess coronary artery hemodynamics and develop a pilot risk-scoring system to predict SVG failure.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL123689-01
Application #
8751621
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Lee, Albert
Project Start
2014-07-22
Project End
2019-06-30
Budget Start
2014-07-22
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of California San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Liu, Ju; Marsden, Alison L (2018) A unified continuum and variational multiscale formulation for fluids, solids, and fluid-structure interaction. Comput Methods Appl Mech Eng 337:549-597
Schiavazzi, D E; Doostan, A; Iaccarino, G et al. (2017) A generalized multi-resolution expansion for uncertainty propagation with application to cardiovascular modeling. Comput Methods Appl Mech Eng 314:196-221
Tran, Justin S; Schiavazzi, Daniele E; Ramachandra, Abhay B et al. (2017) Automated Tuning for Parameter Identification and Uncertainty Quantification in Multi-scale Coronary Simulations. Comput Fluids 142:128-138
Ramachandra, Abhay B; Humphrey, Jay D; Marsden, Alison L (2017) Gradual loading ameliorates maladaptation in computational simulations of vein graft growth and remodelling. J R Soc Interface 14:
Schiavazzi, D E; Hsia, T Y; Marsden, A L (2016) On a sparse pressure-flow rate condensation of rigid circulation models. J Biomech 49:2174-2186
Ramachandra, Abhay B; Kahn, Andrew M; Marsden, Alison L (2016) Patient-Specific Simulations Reveal Significant Differences in Mechanical Stimuli in Venous and Arterial Coronary Grafts. J Cardiovasc Transl Res 9:279-90
Ramachandra, Abhay B; Sankaran, Sethuraman; Humphrey, Jay D et al. (2015) Computational simulation of the adaptive capacity of vein grafts in response to increased pressure. J Biomech Eng 137:
Sankaran, Sethuraman; Humphrey, Jay D; Marsden, Alison L (2013) An efficient framework for optimization and parameter sensitivity analysis in arterial growth and remodeling computations. Comput Methods Appl Mech Eng 256:200-210