Date of Award

2024

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Biomedical Engineering (PhD)

Administrative Home Department

Department of Biomedical Engineering

Advisor 1

Jingfeng Jiang

Committee Member 1

Sean J. Kirkpatrick

Committee Member 2

Hoda Hatoum

Committee Member 3

Weihua Zhou

Abstract

Vascular aneurysms, such as intracranial aneurysms (IAs) and abdominal aortic aneurysms (AAAs), pose significant health risks, particularly upon rupture. Disturbed hemodynamics, characterized by swirling flow patterns, can lead to cellular and structural changes that disrupt normal physiological processes and contribute to destructive vascular remodeling. Integrating hemodynamic analysis into clinical assessments of aneurysms has become crucial, especially through patient-specific computational fluid dynamics (CFD) simulations based on medical imaging. However, the complexity of CFD tools presents challenges in model creation and post-simulation analysis, limiting their accessibility to clinicians.
This project aimed to advance aneurysm management by exploring the role of intraluminal thrombus (ILT) in aneurysm progression and optimizing the workflow for running CFD simulations in clinical settings. Additionally, it sought to develop a new approach for measuring blood flow characteristics. Key contributions included a comprehensive analysis of ILT’s impact on AAA progression, focusing on its dimensions and texture. Novel metrics were also developed to assess spatial and temporal hemodynamic characteristics, enhancing predictive accuracy. A streamlined CFD pipeline, integrating deep learning and open-source technologies, was introduced to improve usability and clinical applicability. By enhancing diagnostic precision and predictive capabilities, this study aimed to refine clinical strategies for managing vascular aneurysms and ultimately improve patient outcomes.

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