Computational modeling of tissue-engineered vascular grafts
Abstract/Contents
- Abstract
- Tissue-engineered vascular grafts (TEVGs) have the potential to improve patient outcomes in the field of pediatric cardiology given their ability to grow and remodel over time. However, the widespread clinical use of TEVGs has historically been limited by complications such as stenosis and occlusion, as well as variability in outcomes. This thesis focuses on leveraging computational models to enhance our understanding of TEVGs and aid their translation to clinical use. In this work, we analyzed outcomes from the first U.S. clinical trial of TEVGs in single-ventricle patients with completed Fontan circulation. The study identified two distinct phases of graft remodeling, characterized by rapid geometry changes followed by sustained growth and reduced stiffness. Clinically-informed and patient-specific computational fluid dynamics (CFD) simulations were employed to examine the impact of TEVG geometry. Using virtual surgery, we evaluated the outcomes under mild and severe stenosis. Particular focus was placed on evaluating exercise tolerance in these patients, and, to this end, we developed a model of the cardiovascular behavior of Fontan patients during both rest and exercise. We determined that the Fontan circulation is robust to a wide variety of TEVG geometries and that TEVGs demonstrate favorable hemodynamics compared to the standard-of-care synthetic grafts. These insights support ongoing clinical evaluation of TEVGs. We extend the capabilities of growth and remodeling frameworks to predict TEVG behavior by incorporating constrained mixture theory into a full, three-dimensional fluid-structure interaction solver using a novel coupling framework. We validate this framework's behavior against past work and demonstrate its robustness across a variety of vascular settings, timescales, and pathologies. This "fluid-solid-growth" solver enables long-term, predictions of changing hemodynamics, vessel wall morphology, tissue composition, and material properties and provides one of the first patient-specific growth and remodeling frameworks that accounts for complex hemodynamics. Using these computational tools, we next evaluated treatment options for single-ventricle physiology, specifically examining the design of flow restrictors for hybrid palliation. We used patient-specific CFD simulations to compare the performance of internal flow restrictors with traditional external pulmonary bands. Our findings demonstrate that the geometric resistance of flow restrictors, crucial for regulating systemic-to-pulmonary flow ratios, is influenced by patient-specific geometry. Additionally, we note that device design does not disrupt the load balance in the distal pulmonary vasculature compared to the preoperative or externally banded geometry. By leveraging and expanding computational models, we show how computational tools can aid the path from it in-silico experiments to it in-vivo applications. Together, this work has the potential to significantly improve the diagnosis, classification, and treatment of pediatric CHD patients.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Schwarz, Erica Leigh |
|---|---|
| Degree supervisor | Marsden, Alison (Alison Leslie), 1976- |
| Thesis advisor | Marsden, Alison (Alison Leslie), 1976- |
| Thesis advisor | Ennis, Daniel B |
| Thesis advisor | Kuhl, Ellen, 1971- |
| Degree committee member | Ennis, Daniel B |
| Degree committee member | Kuhl, Ellen, 1971- |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Bioengineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Erica Leigh Schwarz. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/wk572qc9200 |
Access conditions
- Copyright
- © 2023 by Erica Leigh Schwarz
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