Hemodynamic based thrombotic risk stratification in Kawasaki disease patients with coronary artery aneurysms

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Thrombosis is a major adverse outcome associated with coronary artery aneurysms resulting from Kawasaki disease, the leading cause of acquired heart disease among children in developed countries. Clinical guidelines recommend initiation of anticoagulation therapy based solely on anatomical measurements. Here, we investigate the role of aneurysm hemodynamics as a superior method for thrombotic risk stratification in Kawasaki disease patients and the use of patient-specific computational modeling to understand the mechanisms underlying coronary artery aneurysm thrombosis. First, we will discuss novel image processing methods that use transluminal attenuation gradient (TAG) to extract functional information from Computer Tomography Angiography. We demonstrate significantly abnormal TAG values in aneurysms caused by Kawasaki disease compared to normal coronary arteries. Second, we will present an image-based computational framework combining a deep understanding of coronary physiology with advanced numerical methods and high performance computing, to obtain fully resolved patient-specific hemodynamic data relevant to thrombotic risk stratification. Simulations are performed with finite element methods incorporating fluid structure interaction and closed loop lumped parameter models to represent vascular boundary conditions. The primary translational goal is to support clinical decisions about when and if a patient needs to start systemic anti-coagulation therapy. Our results demonstrate that hemodynamic variables such as wall shear stress and residence time are significantly more predictive of thrombotic risk than the anatomical measurements currently used in clinical practice. Finally, we focus on the biochemical aspects of thrombus initiation and how these processes can be modeled using a continuum approach. Here we present a model based on scalar transport and incorporating velocity fields from patient-specific simulations to track activation and accumulation of platelets and other blood components, critical to the coagulation cascade. This model provides a new approach to investigate thrombus initiation from a patient-specific perspective, which could help identify regions at higher risk of thrombosis as well as strategies for thrombosis prevention.


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 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English


Author Grande Gutierrez, Noelia
Degree supervisor Kuhl, Ellen, 1971-
Degree supervisor Marsden, Alison
Thesis advisor Kuhl, Ellen, 1971-
Thesis advisor Marsden, Alison
Thesis advisor Eaton, John K
Degree committee member Eaton, John K
Associated with Stanford University, Department of Mechanical Engineering.


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Noelia Grande Gutierrez.
Note Submitted to the Department of Mechanical Engineering.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

© 2019 by Noelia Grande Gutierrez
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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