Date of Graduation

12-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Biomedical Engineering

Advisor/Mentor

Morten Jensen

Committee Member

Balachandran, Kartik

Second Committee Member

Leylek, Jim

Third Committee Member

Jensen, Hanna

Keywords

cardiovascular device peformance, cardiovascular device evaluation

Abstract

Cardiovascular disease (CVD) is the leading cause of death worldwide and its treatment continues to improve due to the advancement of innovative cardiovascular medical devices. In vitro and in silico models serve to replicate the in vivo environment for the development and testing of these devices prior to using animals for testing, and eventually humans in clinical trials. However, limitations related to these models exist in multiple areas including general, cardiac, and venous applications. Specifically, current gaps have been identified with customizable, tissue-mimicking phantoms (general), 2D Blood Speckle Imaging (BSI) (cardiac) and a bioprosthetic venous valve (venous). This dissertation focuses on establishing a framework of flow models for use in the development and testing of cardiovascular devices related to the three areas identified. First, a method of fabricating customizable flow phantoms from a tissue-mimicking gel was developed, its mechanical properties characterized, and flow visualization through the phantom demonstrated using ultrasound-based imaging modalities. Next, pressure drop across two geometries of tissue-mimicking phantoms was determined using direct pressure measurements, 2D BSI, and 3D Computational Fluid Dynamics (CFD) to establish a relationship between the three sources for use in understanding the use of BSI for intracardiac flow analysis. Finally, the effects of glutaraldehyde fixation on the in vitro performance and mechanical/functional properties of venous tissue were evaluated for comparison to alternative xenograft fixation methods for a bioprosthetic venous valve. This work serves as a foundation to further improve and develop these models for additional, more complex applications and establish their use beyond some of the preliminary indications presented here.

Available for download on Wednesday, February 05, 2025

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